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Air Quality Impact Assessment of the Proposed Enviroserv Chloorkop Landfill Expansion, Ekurhuleni Metropolitan

Municipality

Project done on behalf of the SLR Consulting (South Africa) (Pty) Ltd

Project Compiled by: L W Burger

Project Manager L W Burger

Project Assistants R Bornman

Report No: 18SLR25 | Date: May 2018

Air Quality Impact Assessment of the Proposed Enviroserv Chloorkop Landfill Expansion, Ekurhuleni Metropolitan Municipality

Report No.: 18SLR25 Rev 0.1 i

Report Details

Reference No. 18SLR25

Status Rev 0.0

Report Title Air Quality Impact Assessment of the Proposed Enviroserv Chloorkop Landfill Expansion, Ekurhuleni Metropolitan Municipality

Date May 2018

Client SLR Consulting (South Africa) (Pty) Ltd

Prepared by Lucian Burger, PhD (Univ of Natal) MSc Eng (Chem), BSc Eng (Chem)

Assistance Rochelle Bornman, MPhil (GIS & Remote Sensing), B.Land Surveying

Reviewed by Hanlie Liebenberg-Enslin, PhD (Univ of Johannesburg) MSc (Geography) BSc Hons

Notice

Airshed Planning Professionals (Pty) Ltd is a consulting company located in Midrand, South Africa, specialising in all aspects of air quality, ranging from nearby neighbourhood concerns to regional air pollution impacts as well as noise impact assessments. The company originated in 1990 as Environmental Management Services, which amalgamated with its sister company, Matrix Environmental Consultants, in 2003.

Declaration Airshed is an independent consulting firm with no interest in the project other than to fulfil the contract between the client and the consultant for delivery of specialised services as stipulated in the terms of reference.

Copyright Warning

Unless otherwise noted, the copyright in all text and other matter (including the manner of presentation) is the exclusive property of Airshed Planning Professionals (Pty) Ltd. It is a criminal offence to reproduce and/or use, without written consent, any matter, technical procedure and/or technique contained in this document.

Revision Record

Revision Number Date Reason for Revision

Rev 0.0 18 April 2019 Initial Release

Rev 0.1 14 May 2019 Minor Editorial Changes


Report No.: 18SLR25 Rev 0.1 ii

Specialist Report Requirements

A specialist report prepared in terms of the Environmental Impact Regulations of 2014 must contain:

Section in report

a details of-

(i) the specialist who prepared the report; and

(ii) the expertise of that specialist to compile a specialist report including a curriculum vitae;

Report details (page i)

Section 1.5

Appendix C

b a declaration that the specialist is independent in a form as may be specified by the competent authority;

Report details (page i)

c an indication of the scope of, and the purpose for which, the report was prepared; Section 1.1 & 1.2

d the date and season of the site investigation and the relevance of the season to the outcome of the assessment;

Section 3

e a description of the methodology adopted in preparing the report or carrying out the specialised process;

Section 1.3

f the specific identified sensitivity of the site related to the activity and its associated structures and infrastructure;

Section 3

g an identification of any areas to be avoided, including buffers; Section 5 and Section 6

h a map superimposing the activity including the associated structures and infrastructure on the environmental sensitivities of the site including areas to be avoided, including buffers;

Figure 1-2, Figure 1-3, Figure 4-2,

Figure 5-1, Figure 5-2, Figure 5-3,

Figure 5-4, Figure 5-5, Figure 6-1

i a description of any assumptions made and any uncertainties or gaps in knowledge; Section 1.4

j a description of the findings and potential implications of such findings on the impact of the proposed activity, including identified alternatives on the environment;

Section 5 and 6

k any mitigation measures for inclusion in the EMPr; Section 6

l any conditions for inclusion in the environmental authorisation; Section 6

m any monitoring requirements for inclusion in the EMPr or environmental authorisation; Section 6

n a reasoned opinion- (I) as to whether the proposed activity or portions thereof should be authorised; and

(ii) if the opinion is that the proposed activity or portions thereof should be authorised, any avoidance, management and mitigation measures that should be included in the EMPr, and where applicable, the closure plan;

Section 6

Section 6

o a description of any consultation process that was undertaken during the course of preparing the specialist report;

N/A

p a summary and copies of any comments received during any consultation process and where applicable all responses thereto; and

N/A

q any other information requested by the competent authority. N/A



Abbreviations °C Degree Celsius

µg/m3 Micro grams per cubic meter (concentration)

AEL Atmospheric Emission License

AERMIC American Meteorological Society/EPA Regulatory Model Improvement Committee

Airshed Airshed Planning Professionals (Pty) Ltd

AMSL Above Mean Sea Level

AST Anemometer Starting Threshold

ATSDR US Federal Agency for Toxic Substances and Disease Registry

CALEPA California Environmental Protection Agency

CAMx Comprehensive Air Quality Model with Extensions

CARB California Air Resources Board

CLS Chloorkop Landfill Site

CO Carbon monoxide

CoJ City of Johannesburg

DEA Department of Environmental Affairs

DOE U.S. Department of Energy

DWAF Department of Water Affairs and Forestry

EC European Community

EIA Environmental Impact Assessment

FDA US Food and Drug Administration

GDARD Gauteng Department: Agriculture and Rural Development

GHG Greenhouse Gas

GWIS Gauteng Waste Information System

g/s Grams per second

HEAST U.S. EPA Health Effects Assessment Summary Tables

HP High-Pressure

IRIS US EPA Integrated Risk Information System

K Kelvin

LFG Landfill Gas

MES Listed Activities and Minimum National Emission Standards

mg/Nm3 Milligram per normal cubic meter

N/A Not applicable

NAAQS National Ambient Air Quality Standards

NAERR Atmospheric Emissions Reporting Regulations

NAEIS Atmospheric Emissions Inventory System

NEM:AQA National Environmental Management: Air Quality Act of 2004



NDCR National Dust Control Regulations

NERGs National Greenhouse Gas Emission Reporting Regulations

NMBM Nelson Mandela Bay Municipality

NPi Australian National Pollutant Inventory

NSW EPA New South Wales Environment Protection Authority

NO Nitrogen oxide

NO2 Nitrogen dioxide

NOx Nitrogen oxides

O3 Ozone

OEHHA Californian Office of Environmental Health Hazard Assessment

ORTIA OR Tambo International Airport

OU Odour Unit

Pb Lead

PM10 Thoracic particulate matter with a diameter of less than 10 µm

PM2.5 Respirable particulate matter with a diameter of less than 2.5 µm

ppb Parts per billion (concentrations)

ppm Parts per million

PPRTV US EPA Provisional Peer Reviewed Toxicity Values

RAIS US EPA’s Risk Assessment Information System

REL Reference exposure levels

RfC Reference Concentrations

SA South Africa

SAAQIS South African Air Quality Information System

SAWS South African Weather Services

SEA Strategic Environmental Assessment

SO2 Sulfur dioxide

t/a Tonnes per annum

TSP Total suspended particulates, also PM (particulate matter)

UK EA United Kingdom Environmental Agency

UNFCCC United Nations Framework Convention on Climate Change

URF Unit risk factors

US EPA United Stated Environmental Protection Agency

VOC Volatile organic compound

WBG World Bank Group

WHO World Health Organization


Report No.: 18SLR25 Rev 0.1 3

Executive Summary

Airshed Planning Professionals was appointed by SLR Consulting (South Africa) (Pty) Ltd (‘SLR’) to undertake an air quality

impact evaluation of the proposed expansion of the Chloorkop Landfill Site (CLS), which is in the Chloorkop Industrial area on

Portion 63 of Klipfontein 12-IR in the Ekurhuleni Metropolitan Municipality. The closest residential area is Phomolong to the

east and Klipfontein View to the west (approximately 0.5 km). The site is surrounded by industrial areas to the north, south

and east.

The CLS has been operating since 1997 and was originally proposed to operate until 2017 (21 years). The site was classified

by the Department of Water Affairs and Forestry (DWAF as a GLB- site, which according the Minimum Requirements for the

Handling, Classification and Disposal of Hazardous Waste (MRHW); 2nd Ed.1998 classification system allows the disposal of

‘moderate risk waste’. The design capacity required was originally expected to be approximately 4.5 million m³. The CLS has

been developed over the past two decades with six engineered waste disposal cells that form the waste body. As the landfilling

progressed, progressive capping of the landfill took place as follows:

o 2007 - Cells 1 to 3 filled and capped;

o 2010 - Cell 4 filled and capped;

o 2013 - Cell 5 filled and capped; and

o 2017 - Cell 6 filled and capped.

In 2007, Cells 1 to 3 were the first to be fitted with a landfill gas (LFG) pipe collection system for the purpose of flaring. Gas

collection were later also fitted to Cells 4 to 6. Two flare systems were installed with typical extraction rates per flare varying

from 400 m³/hr to a maximum design capacity of 2000 m³/hr.

The waste body at the CLS has finite airspace, defined by the permitted footprint, height and design parameters. In 2016, the

Gauteng Department: Agriculture and Rural Development (GDARD) granted approval for the permitted height of the waste

body to be increased from 10 m to a maximum of 25 m above ground level. This provided additional airspace on the original

footprint and thereby could accommodate a further two years (2018 and 2019) waste disposal.

Given the current and future waste generation potential of the Midrand region, EnviroServ is proposing to expand the CLS

onto adjacent properties to the north of the site. The targeted properties include Erf 334 and 335 of Chloorkop Extension 6,

which are approximately 14 ha in extent. The proposed expansion of the CLS involve the establishment of three engineered

waste disposal cells on the target properties (Phase 1A, Phase 1B Cell1 and Phase 1B Cell 2), as well as an additional cell

(Cell 7) on the original CLS footprint, which is currently accommodating the leachate dam. These additional waste disposal

cells would join with the current CLS waste body. The proposed expansion would be Class B, as per the revised DWAF

classification scheme). It is also proposed that the facility would include a small Material Recovery Facility (MRF) for the

separation of clean recyclables from the waste. Supporting infrastructure would be integrated with the CLS and/or redeveloped

as appropriate.



Objective and Scope

The objective of the study is to quantify the potential change in the air quality due to the proposed expansion of the CLS and

thereby provide the significance of this impact for the purposes of submitting a Basic Assessment (BA) to the Department of

Environmental Affairs (DEA)

The requested scope of work is as follows:

1. Description of baseline conditions, based on existing air quality observations made by Geozone Environmental and

meteorological measurements;

2. Model the air quality impact of the facility for the current landfill operations and extrapolate for the years after capping;

3. Model the air quality impact considering several waste disposal and recycling options (to be supplied); and

4. Assess and identify the need for any changes in the existing Management Plan.

At the time of the assessment no detailed waste disposal and recycling options were supplied for analysis and it was therefore

not included in the report.

Approach

The air quality impact assessment included the current impacts (Baseline), the proposal to develop Cell 7 over the current

leachate dam, and the proposed expansions of the operation to the north of the current site (Phase 1A and Phase 1B). The

assessment aimed at assessing odour, nuisance dust and health impacts associated with the air emissions emanating from

the landfill disposal areas, leachate dams/tanks and the flares. These air emissions include several potential gaseous

compounds as well as airborne particulate matter. The latter pollutants are mainly due to operations that produce fugitive dust

such as vehicle movement and material transport. Although the flares also produce particulate matter emissions, these are

insignificant when compared to the fugitive dust.

Air emissions from waste disposal sites are known to be difficult to quantify due to the complex and varying nature of the

waste, the landfill design and inhomogeneity of the waste body. Emissions also depend on meteorological parameters

including rainfall, atmospheric pressure and wind speed. The UK developed GasSim landfill emission model was selected to

estimate air emissions from the disposal area and the flares. In order to account for the variability in waste character and

trace gases contained in the LFG, the calculation methodology followed a probabilistic technique rather than a deterministic

technique. Trace gas composition is provided as probability density functions which assume a minimum, a maximum and a

mean concentration value. Where information was available from onsite measurement of the CLS LFG, these were used to

replace the default means included in the GasSim database. Whereas a deterministic technique would be based on a single

result obtained from inputting single concentration values into the model, such as the US EPA Landgem model, the GasSim

model calculates emissions based on random sampling of the various probability density functions and produce emissions

based on percentiles less than a specific emission rate. The 95th percentiles were used for further analyses in the atmospheric

dispersion modelling. Emissions from the flares were similarly calculated in GasSim and contained combustion products,

such as carbon dioxide, carbon monoxide, sulfur dioxide, oxides of nitrogen and particulates, as well as trace gases (assuming

99% destruction of organic compounds). Air emissions from the leachate pond and tanks were also estimated using a



dissociation model coupled to a mass transfer model that considers the gas transfer through the liquid/air interface and effects

of wind speed.

Although many trace gas emissions were calculated to originate from the CLS, not all were deemed necessary for inclusion

in the detailed analyses. Screening of pollutants took place in two steps. The first step was done using the GasSim Tier 1

screening methodology using health risk endpoints. According to the GasSim screening, only arsenic, ethylene dichloride and

hydrogen sulfide (H2S) were identified for inclusion in further analyses. However, based on onsite monitoring campaigns by

Geozone Environmental and comparisons with relevant internationally published health and odour risk criteria, it was further

decided to also include limonene, ammonia (NH3), acetaldehyde, benzene and formaldehyde. Since the flares produce

insignificant particulate matter (PM2.5 and PM10)1, only emissions from landfill fugitive dust sources were assumed for further

analyses. To be conservative, the emission rates corresponding to the end of each scenario (Baseline, Phase 1A & Cell7 and

Phase 1B) were used in the atmospheric dispersion simulations.

The US EPA AERMOD model was used to simulate the atmospheric dispersion of the selected pollutants. Three years of

hourly average meteorological data which were measured at OR Tambo International Airport by the South African Weather

Services (SAWS), were used in these simulations. This weather station is approximately 13km from the CLS and since the

terrain including the CLS and OR Tambo International Airport is relatively flat, these meteorological observations were

considered adequate for use in the dispersion model representing the CLS.

In the second screening exercise of the selected (first screened) pollutants, the predicted maximum ground level air

concentration (using AERMOD) was used to determine the health and nuisance risks associated with each compound. Key-

pollutants were selected with each representing carcinogenic and non-carcinogenic (irritational) impacts, as well as nuisance

impacts (odour and dustfall). This screening resulted in the selection of benzene for carcinogenic impacts, PM10 for irritational

impacts, H2S for odour impacts and total suspended particulates (TSP)2 for fallout dust. The odour impact from the CLS was

based on the New South Wales Environmental Protection Agency (NSW EPA) odour assessment policy which accepts that

existing facilities with an odour performance criterion of approximately 7-fold the odour threshold concentration (or 7OU) is

likely to represent the level below which “offensive” odours should not occur for an individual with a “standard sensitivity” to

odours. However, the NSW EPA also recognises that this criterion does not adequately address the nuisance value with

denser populations. Accordingly, they recommended a sliding scale, starting with 7OU (sparsely populated) down to 2OU for

urban areas, where more than 2000 people could be affected by the odour. The latter criterion was used in the assessment.

Assumptions and Limitations

• For practical reasons only key odiferous and toxic components and indicator species of the LFG were included in

the detailed investigation. The following criteria were for the selection or exclusion of compounds:

o Compounds typically recorded at various other landfills were included for consideration, (82 compounds).

1 PM2.5 and PM10 refer to inhalable particulate matter can be breathed into the nose or mouth. PM10, it consists of particles with a mean

aerodynamic diameter of 10 μm or smaller and deposit efficiently along the airways. This fraction is known as thoracic particulate matter and it is that fraction of inhalable coarse particulate matter that can penetrate the head airways and enter the airways of the lung. Respirable particulate fraction is that fraction of inhaled airborne particles that can penetrate beyond the terminal bronchioles into the gas-exchange region of the lungs. Also known as fine particulate matter, it consists of particles with a mean aerodynamic diameter equal or less than 2.5 µm (PM2.5) that can be inhaled deeply into the lungs. 2 Total suspended particulates (TSP) refer to all airborne particles and may have particle sizes as large as 150 µm, depending on the ability of the air to carry such large particles.



o Compounds for which sub-surface gaseous probe measurements are available for local, general landfill

sites.

o From these compounds ‘indicator’ or ‘marker’ species were identified for further analysis based on toxicity

and/or odour nuisance. Compounds frequently included due to their potential impacts on human health

include carcinogens (e.g. benzene, formaldehyde, carbon tetrachloride, methylene chloride) and several

non-carcinogenic toxins (e.g. chlorobenzene, toluene and tetrachloroethylene).

• The following GasSim model assumptions also apply:

o GasSim can only be used to assess the risk of exposure from LFG and cannot be used to assess exposure

from soils or ground waters;

o Migration of gas is not modelled in the saturation zone;

o The model does not determine the pressure generated by the landfill and to simplify the model, pressure

has been excluded from all modules;

o LFG is only abstracted from the capped area of the landfill and gas generated from the operational area

is emitted directly to atmosphere;

o Lateral migration is determined using a conservative one-dimensional advection and diffusion equation.

The diffusivity is determined for the diffusivity of the gas in air, which is corrected for the porosity and

moisture content of the medium. Methane is not included in this module.

o The biological methane oxidation module assumes that all fissures/discrete features emit the same

quantity of gas and that these emissions are not reduced by methane oxidation.

o Since subsurface measurements of H2S were available from several monitoring, the H2S module included

in the GasSim model was not used to estimate the production rate of H2S.

o The predicted air quality impact of the LFG from the existing CLS was based on estimates of the

subsurface concentrations of the various compounds included in the GasSim model. These

concentrations were assumed to represent the mean value, whilst the minimum and maximum

concentrations assumed in the probability densities adopted the default range provided in GasSim.

o The order in which the subsurface concentrations were adopted was as follows: Contra Odour sampling

campaign (latest sampling) was used in preference, or if they did not include a specific compound or if the

observation was below the respective detection limit, then the Levago concentration result was used

unless their observation was below detection limit or not included in the campaign, in which case the

Bogner and Saner results were used. If none of the campaigns included a specific compound, then the

GasSim defaults were used.

o The H2S emission rate from the flares were based on a mass balance, assuming the Lavego sampling

results (17.35 µg/m³, 60.09 µg/m³, 212.6 µg/m³) and an air to fuel ratio of 11.

o The NO2 emission rates from the flares were based on the default flare exhaust gas concentrations

assumed in the GasSim model for enclosed flares, i.e. a triangular distribution with 43 µg/m³ (minimum),

85 µg/m³ (mean) and 149 µg/m³ (maximum).

• A progressive installation of horizontal gas collection trenches is assumed to be installed after the start of waste

filling within each of the proposed landfill cells.

• An interim cap is assumed to be progressively constructed after the completion of waste filling in each cell and a

final cap is to be constructed in the year after finalizing waste filling.

• It was assumed that the vertical LFG wells would be installed and commissioned 3 months after installing the final

cap. Gas collection reduces emission by between 25-30% (no final cover) to 80-95% (final cover).

• Combustion of LFG is the most common method used to reduce the volatility, global warming potential and hazards

associated with LFG. Combustion methods include flares, electricity generation units and energy recovery



technologies (e.g. boilers). The current assessment assumed gas collection and flaring at the end of the cell’s

operational life. Of the combustion methods, flaring is the most commonly used. Two different types of flares

available, i.e. open and enclosed flares. The current flare system at the CLS employs enclosed flares. The same

method was assumed in for the proposed expansion project. Destruction efficiencies of about 99% for gases such

as H2S in the flare are possible and therefore has the potential to reduce odour nuisance significantly.

• Oxides of nitrogen (NOx) is predominantly released as nitric oxide (NO) with lower fractions as nitrogen dioxide

(NO2. The conversion of NO to NO2 was conservatively assumed to be instantaneous. Typically, NO2 would be

less than 20% of the NOx concentration nearby the source where the concentrations are higher than further

downwind where the NO2 fraction could be up to 80%;

• Upset conditions were not included in the dispersion simulations due to the difficulty in estimating the emission rates

of air pollutants during such an event.

• The quantification of sources of emission was restricted to the existing CLS and the proposed expansion. Although

other existing sources of emission within the study area were identified, such sources were not quantified as part of

the emissions inventory and simulations.

• Use was made of data provided by the SAWS for the weather station located at OR Tambo International Airport

approximately 13 km from the CLS. It was assumed that the data is representative of the project area. The

Regulations Regarding Air Dispersion Modelling prescribes the use of a minimum of one year’s on-site data or at

least three years of appropriate off-site data for use in Level 2 assessments. It also states that the meteorological

data must be for a period no older than five years to the year of assessment. The data set includes a three-year

period from January 2016 to December 2018, which complies with the requirements of these regulations.

• Ambient air quality criteria apply to areas where the Occupational Health and Safety regulations do not apply, thus

outside the property or lease area. Ambient air quality criteria are therefore not occupational health indicators but

applicable to areas where the general public has access i.e. off-site.

• There will always be some error in any geophysical model, but it is desirable to structure the model in such a way

to minimise the total error. A model represents the most likely outcome of an ensemble of experimental results. The

total uncertainty can be thought of as the sum of three components: the uncertainty due to errors in the model

physics; the uncertainty due to data errors; and the uncertainty due to stochastic processes (turbulence) in the

atmosphere. Typically, complex topography with a high incidence of calm wind conditions, produce predictions

within a factor of 2 to 10 of the observed concentrations. When applied in flat or gently rolling terrain, the USA

Environmental Protection Agency (US EPA) considers the range of uncertainty to be -50% to 200%. The accuracy

improves with strong wind speeds and during neutral atmospheric conditions.

Main Assessment Results

The baseline predictions represent the LFG emissions just prior to the proposed development of Cell 7, i.e. including gas

collection and flaring for Cells 1 to 6. The results for Phase 1A and Phase 1B, represent the maximum emissions prior to final

capping and flaring of these cells, respectively. In other words, the combined emissions at the end of Phase 1A would include

the emissions from Cells 1 to 7 assuming gas collection and flaring, but no flaring yet for Phase 1A. Similarly, the emissions

at the end of Phase 1B include all emissions from Cells 1 to 7 and Phase 1A (gas collection and flaring), but not yet any

collection and flaring from Phase 1B.

The results from the dispersion simulations are summarised in Table A for the predicted health risks, and Table B for predicted

nuisance impacts, i.e. odour and fallout dust. Apart from odour impacts that could potentially extend far beyond the CLS, all

other impacts were predicted to occur in the near vicinity of the CLS. This includes both carcinogens and irritants.



Table 1-1: Assessment of health risk impacts

Measure of Assessment Scenario Calculation Result

The exceedance of the daily average PM10 NAAQS,

showing both unmitigated and 75% mitigated scenarios

Baseline Mitigated – PM10 daily average concertation exceedances is limited to four exceedances just offsite of the CLS,

i.e. by about 50m to the east and 30m to the south of the landfill boundary

No mitigation, PM10 daily average concentration exceedances extends to about 150m east and 100m south. The

predicted isopleth depicting this NAAQS with no mitigation is marginally offsite for Phase 1A, and about 20m (east)

and 15 m (west) of the extended portion of the CLS for Phase 1B. With 75% mitigation, the NAAQS is predicted

not to be exceeded

Phase 1A Mitigated – no exceedances of the PM10 daily average concertation beyond the landfill boundary

No mitigation – PM10 daily average concentration exceedances marginally offsite towards the east

Phase 1B Mitigated – no exceedances of the PM10 daily average concertation beyond the landfill boundary

No mitigation – PM10 daily average concertation exceedances extends about 20m (east) and 15 m (west) of the

extended portion of the CLS

The incremental cancer risk based on the predicted annual

average benzene concentrations

Baseline The predicted annual average benzene concentration is predicted to be below the NAAQS limit value of 5 µg/m³

The incremental cancer risk is predicted to be trivial (1-in-10 million increased risk)

Phase 1A With gas collection and flaring, the predicted annual average benzene concentration is predicted to be below the

NAAQS limit value of 5 µg/m³

The 1-in-a-million incremental risk (generally accepted as a Low Risk) isopleth extends about 20m (east) and 10m

(west) of the CLS boundary for Phase 1A (& Cell 7)

Phase 1B With gas collection and flaring, the predicted annual average benzene concentration is predicted to be below the


The 1-in-a-million incremental risk isopleth extends about 100m (east), and about 50m (north) for the CLS boundary

for Phase 1B



Table 1-2: Assessment of nuisance impacts


Odour Impact

The NSW EPA applies the odour recognition concentration

to the short-term concentrations (1- to 3-minute averages).

The AERMOD model is restricted to providing hourly

average concentrations (or longer), and shorter averaging

times were therefore extrapolated

Baseline The hourly average 2OU is predicted to marginally extend by about 20m towards the east of the CLS leachate dam

The 3-minute average 2OU is predicted to extend by about 300m towards the east of the CLS leachate dam

Phase 1A The hourly average 2OU is predicted to extend by about 400m towards the east of the CLS leachate dam

The 3-minute average 2OU is predicted to include a large portion of Commercia to the northeast (about 800m from

the CLS expansion)

The impact towards the east (200m) and west (50m) are less significant for the 3-minute average prediction

The odour impact to the south is confined to the CLS

Phase 1B The hourly average 2OU is predicted to extend by about 500m towards the east of the CLS leachate dam


the CLS expansion)



Fallout dust Baseline The unmitigated fallout zone is enclosed by about 200m south and 100m to the east

The mitigated fallout zone stretches about 50m to the east and south

Phase 1A With mitigation, the fallout is predicted to be within the landfill boundaries

With no mitigation, the predicted fallout zones for Phases 1A are limited to about 30m east and west of the CLS

expansion

Phase 1B With mitigation, the fallout is predicted to be within the landfill boundaries


expansion



The health risk results are also summarised in Figure A. The figure combines the zones predicted by the incremental cancer

risk of 1-in-a-million and PM10 exceedances of the. For the Base Case, only the unmitigated PM10 impact is shown since the

mitigated impacts are confined to the CLS. The zone of impact for Phase 1A and Phase 1B are mainly due to the predicted

incremental cancer risk. The cancer risk is based on the 95th percentile benzene emission rates at the end of each of the two

expansion phases (Phase 1A and Phase 1B), and therefore reflect an upper, worst case estimate. A more realistic emission

rate would have been the 50th percentile, which for the Base Case (1997-2019) is a factor of 2.2 lower, and for Phase 1A+Cell 7

(2019-2024) and Phase 1B (2019-2028), a both factor of 5.5 lower. Given this level of conservatism, it is more likely that the

1-in-a-million isopleth is within the proposed CLS expansion. Given that regular watering of the access roads would be taking

place, as per current practice, the predicted unmitigated impact zones in Figure A would most likely not be realistic. A more

realistic prediction would more likely be closer to the mitigated predictions. Therefore, it is predicted that the National Ambient

Air Quality Standards for PM10 daily average concentrations may be exceeded only immediately beyond the eastern boundary

of the expansion, i.e. east of Phase 1B Cell 2.

Figure A: Predicted health risks including benzene incremental cancer risk (isopleth represents 1-in-a-

million incremental cancer risk) and PM10 (unmitigated and mitigated isopleths represents NAAQS)



The odour impact from the CLS is based on the quantification of H2S emissions from the landfill, leachate dams/tanks and the

flares. The NSW EPA applies the odour recognition concentration to the short-term, 1- to 3-minute averaged concentrations.

The AERMOD model is restricted to providing hourly average concentrations (or longer), and therefore for shorter averaging

times these results had to be extrapolated. Hourly and 3-minute average predictions, assuming are provided in Figure B and

Figure C respectively. The predicted baseline represents emissions prior to the operation of Cell 7. The conditions for

Phase 1A and Phase 1B assume maximum emissions just prior to final capping. Whereas the hourly average 2OU is predicted

to extend by about 500m towards the northeast of the CLS expansion, the 3-minute average 2OU is predicted to include a

large portion of Commercia to the northeast (about 950m from the CLS expansion). The impact zones towards the east and

west are less significant, i.e. approximately 300m for the 3-minute average prediction. The odour impact to the south is

confined to the CLS.

Figure B: Potential zone of odour nuisance based the 98th percentile hourly average H2S concentrations

(Isopleths represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria. The

baseline predictions represent the emissions just prior to the proposed development of Cell 7. The results for Phase

1A and Phase 1B, represent the maximum emissions prior to capping and flaring.)


Report No.: 18SLR25 Rev 0.1 iii

Figure C: Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations (Isopleths

represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria. The baseline

predictions represent the emissions just prior to the proposed development of Cell 7. The results for Phase 1A and

Phase 1B, represent the maximum emissions prior to capping and flaring)

Conclusions

The results depicted in Figure A and Figure C may be used to define a health and management buffer zone, respectively.

Given the assumption of gas collection and flaring at the end of each cell’s operation, the calculations showed that the health

risk due to emissions from the landfill is governed by particulate air emissions. Additional mitigation for LFG emissions were

therefore not included in the calculations.

The significance of the health risk is based on the following classifications as defined in the SLR Significance Rating Criteria

provide in Appendix C:


Report No.: 18SLR25 Rev 0.1 iv

Phase 1A & Cell 7 – Health Risk

Unmitigated – No dust suppression Mitigated – Dust suppression

Intensity of Impacts M: Moderate change, disturbance or discomfort. Associated with real but not substantial consequences. Targets, limits and thresholds of concern may occasionally be exceeded. Likely to require some intervention. Occasional complaints can be expected.

L: Minor (Slight) change, disturbance or nuisance. Associated with minor consequences or deterioration. Targets, limits and thresholds of concern rarely exceeded. Require only minor interventions or clean-up actions. Sporadic complaints could be expected.

Duration of Impacts H:

Long term, between 10 and 20 years. (Likely to cease at the end of the operational life of the activity)

H:


Extent of Impacts L:

Whole site

L:

Whole site

Consequences MEDIUM LOW

Probability H:

Probable

M:

Possible/frequent

Significance MEDIUM LOW

Phase 1B Cell 1 and Cell 2 – Health Risk

Unmitigated – No dust suppression Mitigated– Dust suppression





H:


Extent of Impacts M:

Beyond the site boundary, affecting immediate

neighbours

L:

Whole site


Probability H:

Probable

M:

Possible/Frequent


The predicted nuisance impact zone is mainly determined by the potential odour impacts from the CLS. Whereas the worse-

case predictions for the Base Case was predicted to impact mainly over the industrial activities to the east of the CLS, a

significant portion of Commercia, to the northeast of the CLS could experience odours from facility during Phases 1A and 1B.

The worse-case prediction is based on the highest 95th percentile emission rates calculated in GasSim for each phase.

Furthermore, it represents any short-term exposure of a few minutes in duration. With the hourly average odour estimates,

which provide the odour levels for durations from 15 minutes to one hour, the impacts were predicted to be limited to the

aggregate works, east and north-east of the CLS. The significance of the odour risk is as follows:


Report No.: 18SLR25 Rev 0.1 v

Phase 1A & Cell 7 – Odour Risk

Unmitigated – Flares not Operating Mitigated – Flares Operating

Intensity of Impacts H: Prominent change, disturbance or degradation. Associated with real and substantial consequences. May result in illness or injury. Targets, limits and thresholds of concern regularly exceeded. Will require intervention. Threats of community action. Regular complaints can be expected when the impact takes place.

M: Moderate change, disturbance or discomfort. Associated with real but not substantial consequences. Targets, limits and thresholds of concern may occasionally be exceeded. Likely to require some intervention. Occasional complaints can be expected.



H:


Extent of Impacts H:

Local area, extending far beyond site boundary

H:


Consequences HIGH HIGH

Probability H:

Probable

M:

Possible/Frequent

Significance HIGH MEDIUM

Phase 1B Cell 1 and Cell 2 – Odour Risk


Intensity of Impacts H: Prominent change, disturbance or degradation. Associated with real and substantial consequences. May result in illness or injury. Targets, limits and thresholds of concern regularly exceeded. Will definitely require intervention. Threats of community action. Regular complaints can be expected when the impact takes place.




H:




H:



Probability H:

Probable

M:

Possible/Frequent


Recommendations

Background concentrations of airborne particulates are already high and the CLS operator should therefore control on-site

fugitive dust emissions by effective management and mitigation. At least a 70% dust control efficiency is required on unpaved

roads to ensure dustfall rates are reduced to the levels predicted.


Report No.: 18SLR25 Rev 0.1 vi

It is recommended to continue gas collection and flaring, as with the current operation of the CLS. Flares should be maintained

in accordance with the manufacturer’s recommendations. Full records should be available for inspection.

Management measures should be put in place to ensure

• that upsets in the landfill gas collection system are avoided, which would result in the flares not operating effectively;

• that upsets such as the emission of concentrated, un-combusted organic compounds during flare downtime do not

occur. If the flare is not operational no gas extraction and venting through the stack should be permitted.

• minimal downtime of flares since the odour impact could otherwise be significant

Measures should be put in place to reduce the potential for subsurface gas liberation during waste disturbance and gas

extraction network installation activities.


Report No.: 18SLR25 Rev 0.1 vii

Table of Contents

Specialist Report Requirements ................................................................................................................................................ ii

Abbreviations .............................................................................................................................................................................. i

Executive Summary ................................................................................................................................................................... 3

1 Introduction..................................................................................................................................................................... 13

1.1 Objective ............................................................................................................................................................... 17

1.2 Scope of Work ...................................................................................................................................................... 17

1.3 Methodology ......................................................................................................................................................... 18

1.3.1 Air Emissions Inventory ................................................................................................................................... 18

1.3.2 Study Area ....................................................................................................................................................... 19

1.3.3 Atmospheric Dispersion Simulations ............................................................................................................... 20

1.3.4 Health Risk Assessment .................................................................................................................................. 20

1.3.5 Odour Impact Assessment .............................................................................................................................. 21

1.4 Assumptions and Limitations ................................................................................................................................ 21

1.5 Competency Profile: L W Burger (PhD(Natal) MScEng (Chem) BScEng (Chem), FSACheE, FIChemE) ........... 24

2 Regulatory Requirements and Assessment Criteria ...................................................................................................... 26

2.1 Regulatory Requirements ..................................................................................................................................... 26

2.1.1 Listed Activities and Minimum National Emission Standards (MES) ............................................................... 26

2.1.2 Atmospheric Emissions Reporting Regulations (NAERR) ............................................................................... 26

2.1.3 National Greenhouse Gas Emission Reporting Regulations (NGERs)............................................................ 27

2.1.4 National Ambient Air Quality Standards (NAAQS) .......................................................................................... 28

2.1.5 National Dust Control Regulations (NDCR)) .................................................................................................... 29

2.1.6 Atmospheric Dispersion Modelling Regulations .............................................................................................. 30

2.1.7 Air Quality Management Plans (AQMP) – the Highveld Priority Area (HPA) ................................................... 31

2.1.8 Gauteng Waste Information System (GWIS) ................................................................................................... 32

2.1.9 Gauteng Pollution Buffer Zones Guideline ...................................................................................................... 33

2.2 Ambient Air Quality Guidelines ............................................................................................................................. 33

2.2.1 Irritational Health Risk Factors ......................................................................................................................... 33

2.2.2 Cancer Health Risk Factors ............................................................................................................................. 36

2.2.3 Odour Impact Evaluation ................................................................................................................................. 37

3 Environmental Baseline.................................................................................................................................................. 42

3.1 Topography .......................................................................................................................................................... 42


Report No.: 18SLR25 Rev 0.1 viii

3.1 Atmospheric Dispersion Potential ......................................................................................................................... 42

3.1.1 Surface Wind Field .......................................................................................................................................... 42

3.1.2 Precipitation ..................................................................................................................................................... 46

3.1.3 Atmospheric Stability ....................................................................................................................................... 47

3.2 Air Pollution Measurements .................................................................................................................................. 48

3.2.1 Air Pollution Measurements ............................................................................................................................. 48

3.2.2 Onsite Ambient Air Monitoring ......................................................................................................................... 52

4 Landfill Gas Emissions ................................................................................................................................................... 57

4.1 Landfill Gas Generation ........................................................................................................................................ 57

4.2 Gaseous Emissions from Leachate Dams ........................................................................................................... 62

4.3 Flare Emissions .................................................................................................................................................... 64

4.4 Fugitive Particulate Emission ............................................................................................................................... 64

4.5 Litter ...................................................................................................................................................................... 65

4.6 Pathogens ............................................................................................................................................................ 65

4.7 Quantification of Air Pollutant Emissions .............................................................................................................. 65

4.7.1 Landfill Gas Emissions .................................................................................................................................... 65

4.7.2 Flare Emissions ............................................................................................................................................... 75

4.7.3 Leachate Pond Gas Emissions ........................................................................................................................ 76

4.7.4 Fugitive Particulate Emissions ......................................................................................................................... 77

4.8 Greenhouse Gas Emissions ................................................................................................................................. 78

5 Dispersion Simulations ................................................................................................................................................... 85

6 Conclusions and Recommendations .............................................................................................................................. 94

6.1 Conclusions .......................................................................................................................................................... 98

6.2 Recommendations ................................................................................................................................................ 99

7 References ................................................................................................................................................................... 101

8 APPENDIX A: GasSim Model Input Parameters .......................................................................................................... 105

9 APPENDIX B: SLR Significance Rating Criteria .......................................................................................................... 139

10 APPENDIX C: CURRICULUM VITAE OF SPECIALIST .............................................................................................. 142

11 APPENDIX D: Dispersion Model Results ..................................................................................................................... 143

11.1 Dispersion Model Results for Phase 1A (including Cell 7) ................................................................................. 143

11.2 Dispersion Model Results for Phase 1B ............................................................................................................. 150


Report No.: 18SLR25 Rev 0.1 ix

List of Tables

Table 1-1: Assessment of health risk impacts .................................................................................................................... 8

Table 1-2: Assessment of nuisance impacts ...................................................................................................................... 9

Table 1-1: List of potential compounds in LFG ................................................................................................................. 22

Table 2-1: National Ambient Air Quality Standards ......................................................................................................... 29

Table 2-2: Acceptable dust fall rates ................................................................................................................................. 29

Table 2-3: International health risk criteria for pollutants not included in the NAAQS ...................................................... 34

Table 2-4: Unit risk factors ................................................................................................................................................ 36

Table 2-5: Excess Lifetime Cancer Risk (as applied by New York Department of Health) .............................................. 37

Table 2-6: Odour threshold values for common odorants ................................................................................................. 38

Table 2-7: NSW EPA odour performance criteria defined based on population density (NSW EPA, 2017) .................... 40

Table 2-8: Odour performance criteria used in various jurisdictions in the US and Australia (after NSW EPA, 2001b) ... 40

Table 3-1: Monthly temperature summary (2016 - 2018) ................................................................................................. 44

Table 3-2: Long-term monthly rainfall total compared observations for the period 2016 to 2018 at ORTIA SAWS weather

station 46

Table 3-3: Maximum and average air pollution concentrations recorded at the AECI Ester Park monitoring station during

the 2002-3 period (values given in bold print represent exceedances of air quality limits) ...................................................... 52

Table 3-4: Summary of diffusive passive sampler results for the period June 2014 to January 2019 (source: Geozone

Environmental) ......................................................................................................................................................................... 54

Table 3-5: Extrapolated short-term concentration from June 2014 to January 2019 air quality monitoring data (source:

Geozone Environmental) ......................................................................................................................................................... 55

Table 3-6: Extrapolated short-term concentration from January 2017 to January 2019 air quality monitoring data (source:

Geozone Environmental) ......................................................................................................................................................... 56

Table 4-1: Historical waste amounts received at the CLS from 1997, i.e. the start of operations .................................... 58

Table 4-2: Percentage split of different waste streams to assist the classification of waste received at the CLS ............ 59

Table 4-3: Summary of subsurface gas concentrations measurements campaigns at CLS............................................. 60

Table 4-4: Inorganic chemical analyses (17 August 2018) of Leachate dam at the CLS ................................................. 63

Table 4-5: Leachate dam VOC chemical analyses (4 April 2019) at the CLS .................................................................. 63

Table 4-6: Annual waste disposal rates for the CLS (shaded cells are projected rates assumed in the assessment based

on estimated schedules in Table 4-8) ...................................................................................................................................... 67

Table 4-7: Details of the cells proposed in the northern expansion of the CLS ................................................................ 69

Table 4-8: Assumed periods of operating cells proposed for the northern expansion ...................................................... 69

Table 4-9: GasSim default Environmental Quality Standards (EQS) and Environmental Assessment Levels (EAL) values

for use in Tier 1 screening evaluation ...................................................................................................................................... 70

Table 4-10: GasSim calculated emission rates for baseline and two proposed phases ..................................................... 75

Table 4-11: Calculated (GasSim) flare air pollutant emission rates (two flares combined emission rates) ........................ 75

Table 4-12: Calculated H2S emission rates from the current leachate dam and proposed tanks ....................................... 77

Table 4-13: Emission rate equations used to quantify fugitive dust emissions ................................................................... 80

Table 4-14: Fugitive particulate emission rates for baseline conditions .............................................................................. 82

Table 4-15: Fugitive particulate emission rates for Phase 1A ............................................................................................. 82

Table 4-16: Fugitive particulate emission rates for Phase 1B ............................................................................................. 83

Table 4-17: Calculated GHG inventory for the Baseline, Phase 1A (+Cell 7) and Phase 1B ............................................. 84


Report No.: 18SLR25 Rev 0.1 x

Table 5-1: Comparison with NAAQS ................................................................................................................................ 86

Table 5-2: Incremental cancer risk estimates ................................................................................................................... 87

Table 5-3: Hazard index .................................................................................................................................................... 87

Table 6-1: Assessment of health risk impacts .................................................................................................................. 96

Table 6-2: Assessment of nuisance impacts .................................................................................................................... 97


Report No.: 18SLR25 Rev 0.1 xi

List of Figures

Figure 1-1: Location of the Chloorkop Landfill Site ............................................................................................................ 14

Figure 1-2: Satellite imagery showing Chloorkop landfill site and adjacent landuse including the residential areas of

Phomolong and Klipfontein View. ............................................................................................................................................ 15

Figure 1-3: Satellite imagery showing the CLS (existing and proposed expansion) and adjacent land-use including

Phomolong and Klipfontein View residential areas .................................................................................................................. 16

Figure 1-4: Layout of the original CLS (1997 to 2017) ....................................................................................................... 17

Figure 1-5: The different scales of the impacts of gas from landfills (after Kjeldsen, 1996) ............................................... 20

Figure 2-1: Modelled frequency of exceedance of the 24-hour ambient PM10 standard in the HPA, indicating the modelled air

quality Hot Spot areas .............................................................................................................................................................. 32

Figure 3-1: Period average, day-time and night-time wind roses (measured data; 2016 to 2018) .................................... 43

Figure 3-2: Seasonal wind roses (measured data; 2016 to 2018) ..................................................................................... 44

Figure 3-3: Monthly average temperature profile (measured data; 2016 to 2018; ORTIA SAWS station) ........................ 45

Figure 3-4: Comparison of monthly mean temperatures at ORTIA for 1951-1984 (Schultz 1986) and 2016-2018 ........... 45

Figure 3-5: Monthly rainfall figures (measured data; 2016 to 2018; ORTIA SAWS station) .............................................. 47

Figure 3-6: Diurnal atmospheric stability (AERMET processed SAWS data, 2016 to 2018) ............................................. 47

Figure 3-7: CLS in relationship with the air quality monitoring stations in and near CoJ from City of Tshwane (CoT),

Ekurhuleni (EKHL), West Rand (WRDM) and Vaal Triangle Airshed Priority Area (VTAPA) networks (City of Johannesburg

Air Quality Management Plan, 2017) ....................................................................................................................................... 49

Figure 3-8: Simulated PM10 air concentrations for 2014 (99th percentile, daily average) ................................................. 50

Figure 3-9: Simulated SO2 air concentrations for 2014 (99th percentile, daily average) .................................................... 51

Figure 3-10: Locations of passive sampling at the CLS .................................................................................................. 53

Figure 4-1: Fractions of sulphide species (H2S, HS-, S2-) present in aqueous solution as function of pH at 25°C [Source:

Snoeyink and Jenkins (1980)] .................................................................................................................................................. 62

Figure 4-2: Proposed expansion of the CLS (Cell 7, Phase 1A Cell 1 and Phase 1B Cell2) ............................................. 66

Figure 4-3: GasSim simulated LFG generation rate .......................................................................................................... 72

Figure 4-4: GasSim simulated 95th percentile H2S landfill generation rate ........................................................................ 73

Figure 4-5: GasSim simulated 95th percentile benzene landfill generation rate ................................................................. 74

Figure 4-6: Calculated H2S air emissions from leachate dam for a 2016 to 2018 .............................................................. 77

Figure 4-7: Calculated GWP for the CLS and proposed expansion ................................................................................... 79

Figure 5-1: Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4 daily exceedances per

calendar year) 89

Figure 5-2: The predicted incremental cancer risk based on exposure to benzene emissions from the CLS (an incremental

cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see Table 2-5) ................................... 90

Figure 5-3: Potential zone of odour nuisance based the 98th percentile hourly average H2S concentrations (isopleths

represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria Table 2-7) ................. 91

Figure 5-4: Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations (isopleths represent

the equivalent of 2OU – assessment follows New South Wales odour performance criteria Table 2-7) ................................. 92

Figure 5-5: Predicted highest monthly average fallout dust (residential areas should not exceed more than 600 mg/m²-day)

93


Report No.: 18SLR25 Rev 0.1 xii

Figure 6-1: Prediction results for combined health risks, including the PM10 (unmitigated and mitigated) and benzene

incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth represents the 1-in-a-million

incremental cancer risk) ........................................................................................................................................................... 95

Figure 11-1: Phase 1A - Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4 daily

exceedances per calendar year) ............................................................................................................................................ 143

Figure 11-2: Phase 1A - The predicted incremental cancer risk based on exposure to benzene emissions from the CLS

(an incremental cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see Table 2-5) ....... 144

Figure 11-3: Phase 1A - Potential zone of odour nuisance based the 98th percentile hourly average H2S concentrations

(isopleths represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria Table 2-7)

145

Figure 11-4: Phase 1A - Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations


146

Figure 11-5: Phase 1A - Predicted highest monthly average fallout dust (residential areas should not exceed more than

600 mg/m²-day) 147

Figure 11-6: Potential zone of odour nuisance over lifetime of landfill up to and including Cell 7 and Phase 1A ......... 148

Figure 11-7: Phase 1A - Prediction results for combined health risks, including the PM10 (unmitigated and mitigated)

and benzene incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth represents the 1-in-a-

million incremental cancer risk) .............................................................................................................................................. 149

Figure 11-8: Phase 1B - Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4 daily

exceedances per calendar year) ............................................................................................................................................ 150

Figure 11-9: Phase 1B - The predicted incremental cancer risk based on exposure to benzene emissions from the CLS

(an incremental cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see Table 2-5) ....... 151

Figure 11-10: Phase 1B - Potential zone of odour nuisance based the 98th percentile hourly average H2S concentrations


152

Figure 11-11: Phase 1B - Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations


153

Figure 11-12: Phase 1B - Predicted highest monthly average fallout dust (residential areas should not exceed more than

600 mg/m²-day) 154

Figure 11-13: Potential zone of odour nuisance over lifetime of landfill up to and including Phase 1B .......................... 155

Figure 11-14: Phase 1B - Prediction results for combined health risks, including the PM10 (unmitigated and mitigated)

and benzene incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth represents the 1-in-a-

million incremental cancer risk) .............................................................................................................................................. 156



1 INTRODUCTION

Airshed Planning Professionals was appointed by SLR Consulting (South Africa) (Pty) Ltd (‘SLR’) to undertake an air quality

impact evaluation of the proposed expansion of the Chloorkop Landfill Site (CLS), which is in the Chloorkop Industrial area on

Portion 63 of Klipfontein 12-IR in the Ekurhuleni Metropolitan Municipality. EnviroServ Waste Management (Pty) Ltd

(‘Énviroserv’) owns the CLS and operates it in terms of a waste management licence (Ref: 16/2/7/A230/D17/Z1). Municipal

solid waste is received from the Midrand area, including the City of Johannesburg and the Ekurhuleni Metropolitan Municipality,

and is accessed from Marsala Road. The CLS is situated in the Northern Service Delivery Area of the Ekurhuleni Metropolitan

Municipality. It is approximately 13 km from the OR Tambo International Airport, 7 km from the Buccleuch Interchange and 7

km from the Allandale off-ramp from the N1 (Figure 1-1). The closest residential area is Phomolong to the east and Klipfontein

View to the west (approximately 0.5 km). The site is surrounded by industrial areas to the north, south and east (Figure 1-2

and Figure 1-3).

The CLS has been operating since 1997 and was originally proposed to operate until 2017 (21 years). The site was classified

by the Department of Water Affairs and Forestry (DWAF as a GLB- site, which according the Minimum Requirements for the

Handling, Classification and Disposal of Hazardous Waste (MRHW); 2nd Ed.1998 classification system allows the disposal of

‘moderate risk waste’. The design capacity required was originally expected to be approximately 4.5 million m³. The CLS has

been developed over the past two decades with six engineered waste disposal cells that form the waste body, as illustrated

in Figure 1-4. The waste body covers an area of approximately 23.2 ha. As the landfilling progressed, progressive capping of

the landfill took place as follows:

o 2007 - Cells 1 to 3 filled and capped;

o 2010 - Cell 4 filled and capped;

o 2013 - Cell 5 filled and capped; and

o 2017 - Cell 6 filled and capped.

In 2007, Cells 1 to 3 were the first to be fitted with a landfill gas (LFG) pipe collection system for the purpose of flaring, thereby

disposing of flammable constituents safely, particularly methane, and to control odour nuisance, health risks and adverse

environmental impacts. Gas collection were later also fitted to Cells 4 to 6. Two flare systems were installed with typical

extraction rates per flare varying from 400 m³/hr to a maximum design capacity of 2000 m³/hr.

The waste body at the CLS has finite airspace, defined by the permitted footprint, height and design parameters. In 2016, the

Gauteng Department: Agriculture and Rural Development (GDARD) granted approval for the permitted height of the waste

body to be increased from 10 m to a maximum of 25 m above ground level. This provided additional airspace on the original

footprint and thereby could accommodate a further two years (2018 and 2019) waste disposal. Given the current and future

waste generation potential of the Midrand region, there is an ongoing need for waste disposal services, even with growing

levels of waste diversion. EnviroServ is therefore proposing to expand the CLS onto adjacent properties to the north of the

site. The targeted properties include Erf 334 and 335 of Chloorkop Extension 6, which are approximately 14 ha in extent. The

proposed expansion of the CLS involve the establishment of three engineered waste disposal cells on the target properties

(Phase 1A, Phase 1B Cell1 and Phase 1B Cell 2), as well as an additional cell (Cell 7) on the original CLS footprint, which is

currently accommodating the leachate dam. These additional waste disposal cells would join with the current CLS waste

body. The proposed expansion would be Class B, as per the Norms and Standards for Disposal of Waste to Landfill

(Government Gazette R636 of 2013). A small Material Recovery Facility (MRF) is also proposed for the separation of clean

recyclables from the waste. Supporting infrastructure would be integrated with the CLS and/or redeveloped as appropriate.



Figure 1-1: Location of the Chloorkop Landfill Site



Figure 1-2: Satellite imagery showing Chloorkop landfill site and adjacent landuse including the residential areas of Phomolong and Klipfontein View.



Figure 1-3: Satellite imagery showing the CLS (existing and proposed expansion) and adjacent land-use including Phomolong and Klipfontein View residential areas



Figure 1-4: Layout of the original CLS (1997 to 2017)

1.1 Objective

The objective of the study is to quantify the potential change in the air quality due to the proposed expansion of the CLS and

thereby provide the significance of this impact for the purposes of submitting a Basic Assessment (BA).

1.2 Scope of Work

The requested scope of work was as follows:

• Description of baseline conditions, based on existing air quality observations made by Geozone and meteorological

measurements;



• Model the air quality impact of the facility for the current landfill operations and extrapolate for the years after capping;

• Model the air quality impact considering several waste disposal and recycling options (to be supplied); and

• Assess and identify the need for any changes in the existing Management Plan.

1.3 Methodology

1.3.1 Air Emissions Inventory

The establishment of an air emission inventory for the current and proposed expansion of the CLS forms the basis for the

assessment of the impact of these emissions on the receiving environment. The establishment of an emissions inventory

comprises the identification of sources of emission, and the quantification of each significant source’s contribution to ambient

air pollution concentrations, including the following:

• Gaseous emissions from the working surface and covered portions of the landfill and vehicles on the access road;

• Gaseous emissions from open leachate dam and storage areas; and

• Fugitive particulate emissions as a result of vehicles travelling on unpaved road surfaces, materials handling,

construction and covering operations etc.

In the quantification of fugitive dust (including vehicle entrainment, materials handling, wind erosion, etc.) and vehicle

emissions use is made of emission factors which associate the quantity of a pollutant to the activity associated with the release

of that pollutant. In the absence of locally generated emission factors, use is made of international factors such as those

published by the United States Environmental Protection Agency (US-EPA) and Australian National Pollutant Inventory (NPI).

The US-EPA AP-42 emission factors are of the most widely used in the field of air pollution. Empirically derived predictive

emission factor equations are available for vehicle-entrained dust from roadways, aeolian erosion from open areas, and for

materials handling operations. Predictive equations explain much of the observed variance in measured emission by relating

emissions to parameters, which characterise the source (US EPA 1995). Such parameters may be grouped into three classes:

• Measures of source activity or energy expended (e.g. the speed and weight of a vehicle on an unpaved road);

• Properties of the material being disturbed (e.g. the content of suspendble fines in the surface material on an unpaved

road); and

• Climatic parameters (e.g. wind speed and number of precipitation free days per year, when a maximum of emissions

occur).

Airborne particulate matter has conveniently been divided into the following classes based on their size:

• Total suspended particulates (TSP) refer to all airborne particles and may have particle sizes as large as 150 µm,

depending on the ability of the air to carry such large particles. Generally, however, suspended particles larger than

75 to 100 µm do not travel far and deposits close to the source of emission.

• Inhalable coarse particulate matter is that fraction of a dust cloud that can be breathed into the nose or mouth.

o Thoracic particulate matter is that fraction of inhalable coarse particulate matter that can penetrate the

head airways and enter the airways of the lung. Also referred to as PM10, it consists of particles with a

mean aerodynamic diameter of 10 μm or smaller and deposit efficiently along the airways. Particles larger



than a mean size of 10 µm are generally not inhalable into the lungs. These particles are typically found

near roadways and dusty industries.

o Respirable particulate fraction is that fraction of inhaled airborne particles that can penetrate beyond the

terminal bronchioles into the gas-exchange region of the lungs. Also known as fine particulate matter, it

consists of particles with a mean aerodynamic diameter equal or less than 2.5 µm (PM2.5) that can be

inhaled deeply into the lungs. These particles can be directly emitted from sources such as forest fires, or

they can form when gases emitted from power plants, industries and automobiles react in the air.

o Ultrafine particles (PM0.1), are the smallest, and consist of particles with a mean aerodynamic diameter

equal or smaller than 0.1 µm and have widespread deposition within the respiratory tract. These particles

are typically as a result of secondary chemical reactions in the atmosphere.

Gaseous emissions from the landfill emanate from the work face, trenches (if any) and covered portions. In the estimation of

gaseous emissions from the working faces and covered portions of the landfill, the United Kingdom Environmental Agency’s

(UK EA) GasSim model was employed. This model was developed to provide a standard risk assessment methodology for

the UK EA, landfill operators and consultants. GasSim is designed to aid LFG risk assessment, by enabling LFG generation,

emissions, migration/dispersion and impact/exposure to be assessed in a reproducible manner by those familiar with the

subject, but without the need to build multiple models. In order to quantitatively evaluate the risks of landfill processes and the

magnitude of the impacts, GasSim considers the uncertainty in input parameters using a Monte Carlo Simulation. The model

allows the calculation of bulk LFG gas emissions (methane, carbon dioxide and hydrogen) as well as trace LFG gases such

as hydrogen sulfide (H2S). The generation of LFG for an individual site is based on the mass of waste deposited and the

composition of the waste streams. The waste is degraded following the first order decay model that calculates the LFG

generation for up to 200 years. The emission model of GasSim takes this output and uses it to calculate LFG emissions, of

bulk and trace gases, to the environment after allowing for LFG collection, flaring, utilisation (energy recovery) and biological

methane oxidation. This is undertaken by using information on the site gas collection system, flare, engine and engineered

barriers (cap and liner), if present. The model assumes that LFG generated and not collected is in equilibrium and will be

emitted from the landfill cap or liner at a steady state, i.e. the model does not consider transient storage of LFG. Additionally,

the model calculates the concentrations of other major and trace gasses emitted from flare and engines following combustion.

Emission inventories were compiled for base case (i.e. landfilling and LFG recovery up to and including January 2019) and

for the proposed expansion phases, i.e. Phase 1A (and Cell 7) and Phase 1B (Cells 1 and 2), comprising on-going waste

disposal activities together with landfill gas recovery and flaring. Although the combined landfill gas emissions were expected

to vary as the landfill is developed due to biological activities, particulate releases due to fugitive dust emissions were

anticipated to remain unchanged. (The majority of dust emissions are from waste hauling and soil handling operations which

remain the same for both scenarios.)

Emissions from the leachate dam were based on the dissociation of compounds such as hydrogen sulfide and ammonia in

the liquid and the subsequent evaporation from the surface of the dam or tanks. The dissociation depends strongly on the pH

of the liquid, as well as liquid temperature. The evaporation is a function mainly of the liquid surface area, ambient air

temperature and wind speed.

1.3.2 Study Area

These potential airborne releases from the waste disposal activities have various impacts on their surroundings and act on

different scales, as illustrated by Figure 1-5. Odours could potentially be detected at downwind distances of kilometres, whilst



dust fallout would occur less than 500 metres from the facility, and the consequences of explosions and fires from tens to a

few hundred metres from the incident. Whilst methane constitutes (CH4) both a very short term and acute explosion hazard

it also has a much more far-reaching and long-term effect on global warming. Based on these impact zones and experience

from previously completed LFG impact assessments, a study area of 5 km by 5 km was selected in the current modelling.

Figure 1-5: The different scales of the impacts of gas from landfills (after Kjeldsen, 1996)

1.3.3 Atmospheric Dispersion Simulations

Regulations Regarding Air Dispersion Modelling were promulgated in Government Gazette No. 37804 vol. 589; 11 July 2014

and recommend a suite of dispersion models to be applied for regulatory practices as well as guidance on modelling input

requirements, protocols and procedures to be followed. Chapter 2 of the Regulations present the typical levels of

assessments, technical summaries of the prescribed models (SCREEN3, AERSCREEN, AERMOD, SCIPUFF, and

CALPUFF) and good practice steps to be taken for modelling applications. Based on a review of the levels, it was decided to

employ the US EPAs AERMET/AEROMD modelling suite. This model is recommended when the assessment of air quality

impacts is part of license application or amendment processes, and where the impacts are the greatest within a few kilometres

downwind (less than 50km).

In the absence of an onsite weather station, hourly average meteorological data from the South African Weather Services

(SAWS) weather station located at OR Tambo International Airport (Approximately 13 km southeast of the CLS) were used in

the dispersion model. Hourly average meteorology for the period 2016 to 2018 was included in the analysis.

1.3.4 Health Risk Assessment

The dispersion simulations undertaken for particulate and gaseous emissions facilitate a preliminary assessment of the health

implications of the CLS emissions, through the comparison of simulated concentrations with local and international ambient



air quality guidelines and standards. For pollutants for which no ambient guidelines are available, use is made of health and

odour thresholds from the general literature with preference being given to refereed sources, e.g. US-EPA Integrated Risk

Information System (IRIS) data base. In instances where predicted ambient concentrations and/or deposition levels exceed

permissible levels, frequencies of exceedance are estimated and recommendations made as to alternative and/or additional

measures which may be adopted to curb emissions.

1.3.5 Odour Impact Assessment

Due to the absence of detailed local guidance, reference was made to the international literature in identifying a suitable

method to use in assessing the potential acceptability of odour impacts associated with the CLS. Reference was primarily

made to approaches adopted in the US and in the Australia, e.g. California Air Resources Board (CARB) method of assessing

H2S related odours and the policy developed for the New South Wales Environment Protection Authority (NSW EPA) on the

assessment and management of odours from stationary sources.

It was recommended that the NSW EPA approach be adopted for use in the current study given that it is comprehensively

documented (NSW EPA 2017). Reference was, however, made to the CARB method of selecting detection limits for use in

the odour unit calculation. The approach adopted may be summarised as follows:

• 3-Minute average air pollutant concentrations were calculated based on predicted 1-hourly average concentrations

(most dispersion models, including the Australian regulatory model Ausplume and the US-EPA AERMOD model

used in this study, do not allow for the prediction of averages over a shorter time interval than 1 hour);

• The detection range for substances of interest were identified and the geometric mean detection limit calculated;

• Odour units were calculated by calculating ratios between the 99th percentile, 3-minute average air pollutant

concentrations and the respective geometric mean detection limits; and

• The odour performance criteria set out by the NSW EPA was applied.

1.4 Assumptions and Limitations

• For practical reasons only key odiferous and toxic components and indicator species of the LFG could be included

in the current investigation. The following criteria were adopted during the current investigation for the selection or

exclusion of compounds:

o Compounds typically recorded at various other landfills were included for consideration (see Table 1-1).

o From these compounds ‘indicator’ or ‘marker’ species were identified for further analysis based on toxicity

and/or odour nuisance. Compounds frequently included due to their potential impacts on human health

include carcinogens (e.g. benzene, carbon tetrachloride, methylene chloride) and several non-

carcinogenic toxins (e.g. chlorobenzene, toluene and tetrachloroethylene).

o Compounds for which sub-surface gaseous probe measurements are available for local, general landfill

sites.

• The GasSim model furthermore makes the following assumptions:

o GasSim can only be used to assess the risk of exposure from LFG and cannot be used to assess exposure

from soils or ground waters;

o Migration of gas is not modelled in the saturation zone;

o The model does not determine the pressure generated by the landfill and to simplify the model, pressure

has been excluded from all modules;



Table 1-1: List of potential compounds in LFG

1,1,1,2-Tetrafluorochloroethane Ethyl toluene (all isomers)

1,1,1-Trichlorotrifluoroethane Ethylbenzene

1,1,2-Trichloroethane Ethylene

1,1-Dichloroethane Ethylene dichloride

1,1-Dichloroethene Fluorotrichloromethane

1,1-Dichlorotetrafluoroethane Formaldehyde (methanal)

1,2-Dichloropropane Freon 113

1,2-Dichlorotetrafluoroethane Hexane

1-Chloro-1,1-difluoroethane Hydrochlorofluorocarbons (HCHCs) (Total)

2-butoxy ethanol Hydrogen sulfide

2-Chloro-1,1,1-trifluoroethane Limonene

2-Propanol Methanethiol (methyl mercaptan)

Acetaldehyde (ethanal) Methyl chloride (chloromethane)

Acetone Methyl chloroform (1,1,1-Trichloroethane)

Acrylonitrile Methyl ethyl ketone (2-butanone)

Ammonia Methyl isobutyl ketone

Benzene n-Butyl acetate

Benzo(a)pyrene Odour Units (Predicted)

Butadiene (modeled as 1,3-Butadiene) PAH (reported as Naphthalene)

Butane para-Dichlorobenzene

Butene isomers Pentane

Carbon disulphide Pentene (all isomers)

Carbon monoxide Propane

Carbon tetrachloride (tetrachloromethane) Propanethiol

Carbonyl sulphide Sulphide, total simulations with H2S

Chlorobenzene Sulphide, total simulations without H2S

Chlorodifluoromethane Sulphur reduced (reported as SO2)

Chloroethane t-1,2-Dichloroethene

Chlorofluorocarbons (CFCs) (Total) Tetrachloroethane

Chlorofluoromethane Tetrachloroethylene (Tetrachloroethene)

Chloroform (trichloromethane) Toluene

Chlorotrifluoromethane Total chloride (reported as HCL)

Dichlorodifluoromethane Total fluoride (reported as HF)

Dichlorofluoromethane Total non-methane volatile organic compounds (NMVOCs)

Dichloromethane (methylene chloride) Trichlorobenzene (all isomers)

Diethyl disulphide Trichloroethylene (trichloroethene)

Dimethyl disulphide Trichlorofluoromethane

Dimethyl sulphide Trichlorotrifluoroethane

Ethane Trimethylbenzene (all isomers)

Ethanethiol (ethyl mercaptan) Vinyl chloride (chloroethene, chloroethylene)

Ethanol Xylene (all isomers)



o LFG is only abstracted from the capped area of the landfill and gas generated from the operational area

is emitted directly to atmosphere;

o Lateral migration is determined using a conservative one-dimensional advection and diffusion equation.

The diffusivity is determined for the diffusivity of the gas in air, which is corrected for the porosity and

moisture content of the medium. Methane is not included in this module.

o The biological methane oxidation module assumes that all fissures/discrete features emit the same

quantity of gas and that these emissions are not reduced by methane oxidation.

• Since subsurface measurements of H2S were available from several monitoring campaigns (Saner 2004 & 2005,

Bogner, Lavego 2009, and Contra Odour 2015), the H2S module included in the GasSim model was not used to

estimate the production rate of H2S. H2S emissions are controlled by the quantity of degraded organic material and

available calcium sulphate and iron in the waste; all of which are required by GasSim if the H2S module is to be

used.

• The predicted air quality impact of the LFG from the existing CLS was based on estimates of the subsurface

concentrations of the various compounds included in the GasSim model. These concentrations were assumed to

represent the mean value, whilst the minimum and maximum concentrations assumed in the probability densities

adopted the default range provided in GasSim.

• The order in which the subsurface concentrations were adopted was as follows: Contra Odour sampling campaign

(latest sampling) was used in preference, or if they did not include a specific compound or if the observation was

below the respective detection limit, then the Levago concentration result was used unless their observation was

below detection limit or not included in the campaign, in which case the Bogner and Saner results were used. If

none of the campaigns included a specific compound, then the GasSim defaults were used.

• A progressive installation of horizontal gas collection trenches is assumed to be installed after the start of waste

filling within each of the proposed landfill cells.

• An interim cap is assumed to be progressively constructed after the completion of waste filling in each cell and a

final cap is to be constructed in the year after finalizing waste filling. Gas collection reduces emission by between

25-30% (no final cover) to 80-95% (final cover).

• It was assumed that the vertical LFG wells would be installed and commissioned 3 months after installing the final

cap.

• Combustion of LFG is the most common method used to reduce the volatility, global warming potential and hazards

associated with LFG. Combustion methods include flares, electricity generation units and energy recovery

technologies (e.g. boilers). The current assessment assumed gas collection and flaring at the end of the cell’s

operational life. Of the combustion methods, flaring is the most commonly used. Two different types of flares

available, i.e. open and enclosed flares. The current flare system at the CLS employs enclosed flares. The same

method was assumed in for the proposed expansion project. Destruction efficiencies of about 99% for gases such

as H2S in the flare are possible and therefore has the potential to reduce odour nuisance significantly.

• The H2S emission rate from the flares were based on a mass balance, assuming the Lavego sampling results

(17.35 µg/m³, 60.09 µg/m³, 212.6 µg/m³) and an air to fuel ratio of 11.

• The NO2 emission rates from the flares were based on the default flare exhaust gas concentrations assumed in the

GasSim model for enclosed flares, i.e. a triangular distribution with 43 µg/m³ (minimum), 85 µg/m³ (mean) and

149 µg/m³ (maximum).

• Oxides of nitrogen (NOx) is predominantly released as nitric oxide (NO) with lower fractions as nitrogen dioxide

(NO2. The conversion of NO to NO2 was conservatively assumed to be instantaneous. Typically, NO2 would be

less than 20% of the NOx concentration nearby the source where the concentrations are higher than further

downwind where the NO2 fraction could be up to 80%;



• Upset conditions were not included in the dispersion simulations due to the difficulty in estimating the emission rates

of air pollutants during such an event.

• The quantification of sources of emission was restricted to the existing CLS and the proposed expansion. Although

other existing sources of emission within the study area were identified, such sources were not quantified as part of

the emissions inventory and simulations.

• Use was made of data provided by the SAWS for the weather station located at OR Tambo International Airport

approximately 13 km from the CLS. It was assumed that the data is representative of the project area. The

Regulations Regarding Air Dispersion Modelling prescribes the use of a minimum of one-year on-site data or at least

three years of appropriate off-site data for use in Level 2 assessments. It also states that the meteorological data

must be for a period no older than five years to the year of assessment. The data set includes a three-year period

from January 2016 to December 2018, which complies with the requirements of these regulations.

• Ambient air quality criteria apply to areas where the Occupational Health and Safety regulations do not apply, thus

outside the property or lease area. Ambient air quality criteria are therefore not occupational health indicators but

applicable to areas where the general public has access i.e. off-site;

• There will always be some error in any geophysical model, but it is desirable to structure the model in such a way

to minimise the total error. A model represents the most likely outcome of an ensemble of experimental results. The

total uncertainty can be thought of as the sum of three components: the uncertainty due to errors in the model

physics; the uncertainty due to data errors; and the uncertainty due to stochastic processes (turbulence) in the

atmosphere. Typically, complex topography with a high incidence of calm wind conditions, produce predictions

within a factor of 2 to 10 of the observed concentrations. When applied in flat or gently rolling terrain, the USA-EPA

(EPA 1986) considers the range of uncertainty to be -50% to 200%. The accuracy improves with strong wind speeds

and during neutral atmospheric conditions.

1.5 Competency Profile: L W Burger (PhD(Natal) MScEng (Chem) BScEng (Chem), FSACheE, FIChemE)

Dr Burger is a Fellow of the South African Institute of Chemical Engineers (Fellow: No. 4533) and an Associate Fellow of the

Institute of Chemical Engineers (IChemE) (Fellow: No. 99963108). Dr Burger holds an MSc and PhD in chemical engineering

from the University of Natal. Following the completion of his bachelor’s degree (cum laude) in chemical engineering in 1982,

his experience in air pollution started in 1983 with the development and implementation of a real-time atmospheric dispersion

model for processing industries (as partial fulfilment of his MSc Eng). This model was further developed for execution on

different computer platforms as an off-the-shelf software package known as “HAWK” and was marketed by the Atomic Energy

Commission (later known as NECSA).

During the period 1984 to 1986, a more complex atmospheric dispersion model was developed, which contributed towards

his PhD and later formed part of an international contract on the evaluation and validation of transport models as applied to

the Chernobyl accident of April 1986 (International Atomic Energy Agency).

Lucian Burger currently serves on the board of directors of Airshed Planning Professionals (Pty) Ltd and of Riscom (Pty) Ltd.

Airshed Planning Professionals is a technical and scientific consultancy providing scientific, engineering and strategic air

pollution impact assessment and management services and policy support to assist clients in addressing a wide variety of air

pollution related risks and air quality management challenges. Riscom specialises in quantitative process risk assessments,

including hazan, hazop, what-if analyses, detailed risk assessments, Major Hazard Installation and incident investigations,

and other risk related studies.



He has been involved in several Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA)

projects and has conducted specialist studies for both quantified process risk assessments and air pollution impact

components of these. Over the past three decades Dr Burger has been actively involved in the development of atmospheric

dispersion modelling and its applications, air pollution compliance assessments, health risk assessments, mitigation

measures, development of air quality management plans, meteorological and air quality monitoring programmes, strategy and

policy development, training and expert witnessing.

Whilst most of his working experience has been in South Africa, a number of investigations were made in countries elsewhere,

including Angola, Botswana, Central African Republic, Congo, Democratic Republic of Congo, England, Ethiopia, Equatorial

Guinea, Ghana, Iran, Ireland, Lesotho, Liberia, Madagascar, Mozambique, Namibia, Suriname, Togo, Ukraine, Zimbabwe and

Zambia.



2 REGULATORY REQUIREMENTS AND ASSESSMENT CRITERIA

2.1 Regulatory Requirements

Prior to assessing the impact of proposed activities on human health and the environment, reference needs to be made to the

environmental regulations governing the impact of such operations i.e. air emission standards, greenhouse gas reporting,

ambient air quality standards and dust control regulations:

• Air emission standards are generally provided for point sources and specify the amount of the pollutant acceptable

in an emission stream and are often based on proven efficiencies of air pollution control equipment. The DEA

published a list of activities (Listed Activities and Minimum National Emission Standards), identifying those activities

that are regulated by the DEA and which require the application for an Atmospheric Emission License (AEL).

• As a requirement under the Paris Climate Agreement, which South Africa ratified in November 2016, the National

Greenhouse Gas Emission Reporting Regulations were published in 2017 to allow the DEA to gather information

from businesses to assist South Africa to update and maintain a National Greenhouse Gas Inventory.

• Air quality guidelines and standards are fundamental to effective air quality management, providing the link between

the source of atmospheric emissions and the user of that air at the downstream receptor site. The ambient air

pollution concentration standards included in the National Ambient Air Quality Standards (NAAQS) indicate safe

daily exposure levels for most of the population, including the very young and the elderly, throughout an individual’s

lifetime. These air quality standards are normally given for specific averaging or exposure periods.

• Dust controls are regulated under the National Dust Control Regulations (NDCR) and provide dustfall rate standards

for residential and non-residential areas.

This section summarises legislation for criteria pollutants and dustfall, as well as screening criteria for non-regulated pollutants,

including carcinogens other than benzene. Regulations regarding the Highveld Priority Area (HPA) air quality management,

dispersion modelling and emissions reporting are also provided.

2.1.1 Listed Activities and Minimum National Emission Standards (MES)

The Minister, in terms of Section 21 of the National Environmental Management: Air Quality Act of 2004 (NEM:AQA)

(Government Gazette No. 27318), published a list of activities which result in atmospheric emissions and which are believed

to have significant detrimental effects on the environment, human health and social welfare. All scheduled processes as

previously stipulated under Air Pollution Prevention Act 45 of 1965 (APPA) were included as listed activities with additional

activities being added to the list. The Minimum Emission Standards (MES) were first published on 31 March 2010 (Government

Gazette No. 33064) with a revision of the schedule on the 22 November 2013 (Government Gazette No. 37054).

The current and proposed expansion of the CLS include landfilling activities, flaring and waste recycling options (not requiring

heat or chemical reactions). According to Section 21 of the NEM:AQA none of these activities fall under the Act and therefore

does not require an AEL to operate.

2.1.2 Atmospheric Emissions Reporting Regulations (NAERR)

The National Atmospheric Emission Reporting Regulations (Government Gazette No. 38633) came into effect on 2 April 2015.

The purpose of the regulations is to regulate the reporting of data and information from an identified point, non-point and



mobile sources of atmospheric emissions to an internet-based National Atmospheric Emissions Inventory System (NAEIS).

The NAEIS is a component of the South African Air Quality Information System (SAAQIS). Its objective is to provide all

stakeholders with relevant, up to date and accurate information on South Africa's emissions profile for informed decision

making. All activities requiring an Atmospheric Emissions Licence (AEL) must report their annual atmospheric emissions on

the system by 31 March of each year.

Although the CLS is excluded from an AEL, by virtue of not falling under any of listed activities in the MES, the requirement to

report emissions on the NAEIS may still be required under the NEM:AQA National Greenhouse Gas Emission Reporting

Regulations, discussed in the next section.

2.1.3 National Greenhouse Gas Emission Reporting Regulations (NGERs)

The NEM:AQA National Greenhouse Gas Emission Reporting Regulations (NGERs) came into effect on 3 April 2017

(Government Gazette No. 40762). Each company’s Greenhouse Gas (GHG) Emissions Report will be used as the basis for

their carbon tax calculations. Companies, in control of certain GHG emitting activities and which exceed a predetermined

threshold, will be required to submit GHG emission data calculated in line with technical guidelines and in a format prescribed

by the NGERs. Listed activities and associated capacity thresholds that require a GHG Emissions Report are provided in

Annexure 1: List of Activities for which GHG Emissions must be Reported to the Competent Authority of the NGERs. The DEA

separately published the Technical Guidelines for Monitoring, Reporting and Verification of Greenhouse Gas Emissions by

Industry (‘Technical Guideline‘) as a companion to the NGERs that provides details of the reporting methodology as specified

in the NGERs. According to the NGERs, a data provider is defined as any person in control of or conducting an activity listed

in Table 5.2 of the Technical guideline and shall include:

• its holding company or corporation or legal entity, registered in South Africa in accordance with the Legislation of

South Africa;

• all its subsidiaries and legally held operations, including joint ventures and partnerships where it has a controlling

interest, or is nominated as the responsible entity for the purpose of reporting under these Regulations (i.e. NGER);

and

• all facilities generally over which it has operational control, which are not part of another data provider as provided

for in these Regulations (i.e. NGER).

An IPCC emission source is defined in the NGERs as “any process or activity which releases a greenhouse gas, an aerosol

or a precursor of a greenhouse gas into the atmosphere which is identified by the Intergovernmental Panel on Climate Change

(IPCC) code in Annexure 1 of the NGERs”. These emission sources are divided into the following main groups:

1. Energy

2. Industrial Processes and Product Use

3. Agricultural, Forestry and Other Land Use

4. Waste

Each of these groups are further subdivided into subcategories, each of which is covered in Technical Guideline companion

to the NGERs. The scope of activities listed for mandatory reporting as per Table 5.2 of the Technical Guideline does not

include land-based emissions covered by the United Nations Framework Convention on Climate Change (UNFCCC)



categories ‘Agriculture and Land Use, Land Use Change and Forestry. However, emissions from fuel combustion or any other

listed emission source, and which originate from a facility operating within a land-based industry are, nonetheless, covered.

The fourth category 4 Waste Emissions is of relevance to the current project, which deals with emissions mainly released from

the decomposition of organic material in landfills or wastewater handling facilities and waste incineration. More specifically,

subcategory 4A Solid Waste Disposal 4A1 Managed Waste Disposal Sites applies. The requirement in Annexure 1 of the

NGERs (Table 5.2 of the Technical Guidelines) states that a data provider shall report when their total installed waste capacity

is 25000 tonnes (or more) or if the facility receives 5 tonnes per day (or more). The method of determining GHG emissions

shall be Tier 1 or Tier 2, i.e. Tier 1 methodologies allow for the use of default emission factors readily available in the 2006

IPCC Guidelines. Tier 2 methodologies require more appropriate emission factors such as country-specific emission factors.

(Tier 3 methodologies require facility or technology specific parameters that describe carbon inputs and process conditions.)

The greenhouse gases covered by the NGERs include:

• carbon dioxide (CO2)

• methane (CH4)

• nitrous oxide (N2O)

• hydrofluorocarbons (HFCs)

• perfluorocarbons (PFCs)

• sullur hexafluoride (SF6)

The IPCC methodology for estimating CH4 emissions from solid waste disposal sites (SWDS) is based on the First Order

Decay (FOD) method. This method assumes that the degradable organic component (degradable organic carbon, DOC) in

waste decays slowly throughout a few decades, during which CH4 and CO2 are formed. If conditions are constant, the rate of

CH4 production depends solely on the amount of carbon remaining in the waste. As a result, emissions of CH4 from waste

deposited in a disposal site are highest in the first few years after deposition, then gradually decline as the degradable carbon

in the waste is consumed by the bacteria responsible for the decay. (2006 IPCC Guidelines Chapter 3)

According to the 2006 IPCC Guidelines, emissions from flaring are not significant, as the CO2 emissions are of biogenic origin

and the CH4 and N2O emissions are very small, so good practice in the waste sector does not require their estimation.

Emissions from flaring are hence not treated at Tier 1. (2006 IPCC Guidelines Chapter 3)

2.1.4 National Ambient Air Quality Standards (NAAQS)

The initial NAAQS were published for comment in the Government Gazette on 9 June 2007. The revised NAAQS were

subsequently published for comment in the Government Gazette on the 13th of March 2009. The final NAAQS was published

in the Government Gazette on the 24th of December 2009 (Government Gazette 32816) and additional standards for

particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) was published on the 29th June 2012. The standards

were developed for those pollutants that are most commonly found in the atmosphere, that have proven detrimental health

effects when inhaled and are regulated by ambient air quality criteria. These generally include CO, NO2, SO2, benzene, lead

(Pb), PM10, PM2.5, and ground level ozone (O3), as listed in Table 2-1.



Table 2-1: National Ambient Air Quality Standards

Pollutant Averaging Period Concentration

(µg/m³)

Permitted Frequency

of Exceedance Compliance Date

Sulphur Dioxide

(SO2)

10 minutes 500 526 Immediate

1 hour 350 88 Immediate

24 hours 125 4 Immediate

1 year 50 0 Immediate

Benzene 1 year 5 0 1 January 2015

Carbon

Monoxide (CO)


8 hour(a) 10000 11 Immediate

Lead (Pb) 1 year 0.5 0 Immediate

Nitrogen Dioxide

(NO2)


1 year 40 0 Immediate

Ozone (O3) 8 hour(b) 120 11 Immediate

PM2.5

24 hours 40 4 1 January 2016 till 31 December 2029

24 hours 25 4 1 January 2030

1 year 20 0 1 January 2016 till 31 December 2029

1 year 15 0 1 January 2030

PM10 24 hours 75 4 1 January 2015

1 year 40 0 1 January 2015

Notes: (a) Calculated on 1-hour averages. (b) Running average.

2.1.5 National Dust Control Regulations (NDCR))

The NDCR were published on 1 November 2013, with the purpose of prescribe general measures for the control of dust in all

areas including residential and non-residential areas. The standard for acceptable dustfall rates is set out in Table 2-2 for

residential and non-residential areas. According to these regulations the dustfall rates at the boundary or beyond the boundary

of the premises where it originates cannot exceed 600 mg/m²/day in residential and light commercial areas; or

1 200 mg/m²/day in areas other than residential and light commercial areas.

Table 2-2: Acceptable dust fall rates

Restriction Area Dust-fall rate (D) (mg/m²/day, 30-

day average) Permitted frequency of exceeding dust fall rate

Residential D < 600 Two within a year, not sequential months.

Non-residential 600 < D < 1 200 Two within a year, not sequential months

Note: The method to be used for measuring dustfall rate and the guideline for locating sampling points shall be ASTM D1739: 1970, or

equivalent method approved by any internationally recognized body

In addition to the dust fall limits, the NDCR prescribe monitoring procedures and reporting requirements. This will be based

on the measuring reference method ASTM 01739:1970 (or an equivalent method approved by any internationally recognised

body) averaged over 30 days.



2.1.6 Atmospheric Dispersion Modelling Regulations

Air dispersion modelling provides a cost-effective means for assessing the impact of air emission sources, the major focus of

which is to determine compliance with the relevant ambient air quality standards. Dispersion modelling provides a versatile

means of assessing various emission options for the management of emissions from existing or proposed installations. The

Regulations Regarding Air Dispersion Modelling recommend a suite of dispersion models to be applied for regulatory practices

as well as guidance on modelling input requirements, protocols and procedures to be followed. These Regulations are

applicable –

• in the development of an air quality management plan, as contemplated in Chapter 3 of the NEM:AQA;

• in the development of a Priority Area Air Quality Management Plan, as contemplated in Section 19 of the NEM:AQA;

• in the development of an Atmospheric Impact Report (AIR), as contemplated in Section 30 of the NEM:AQA; and,

• in the development of a specialist air quality impact assessment study, as contemplated in Chapter 5 of the

NEM:AQA.

Three Levels of Assessment are defined in the Regulations. The three levels are:

• Level 1: where worst-case air quality impacts are assessed using simpler screening models

• Level 2: for assessment of air quality impacts as part of license application or amendment processes, where impacts

are the greatest within a few kilometres downwind (less than 50km)

• Level 3: require more sophisticated dispersion models (and corresponding input data, resources and model operator

expertise) in the following situations:

o where a detailed understanding of air quality impacts, in time and space, is required;

o where it is important to account for causality effects, calms, non-linear plume trajectories, spatial variations

in turbulent mixing, multiple source types & chemical transformations;

o when conducting permitting and/or environmental assessment process for large industrial developments

that have considerable social, economic and environmental consequences;

o when evaluating air quality management approaches involving multi-source, multi-sector contributions

from permitted and non-permitted sources in an air-shed; or,

o when assessing contaminants resulting from non-linear processes (e.g. deposition, ground-level O3,

particulate formation, visibility).

Chapter 3 of the Regulation prescribes the source data input to be used in the model. Dispersion models are particularly useful

under circumstances where the maximum ambient concentration approaches the ambient air quality limit value and provide a

means for establishing the preferred combination of mitigation measures that may be required.

Chapter 4 of the Regulations prescribes meteorological data input from onsite observations to simulated meteorological data.

The chapter also gives information on how missing data and calm conditions are to be treated in modelling applications.

Meteorology is fundamental for the dispersion of pollutants because it is the primary factor determining the diluting effect of

the atmosphere.

Topography may also be an important geophysical parameter. The presence of significant terrain differences can lead to

significantly higher ambient concentrations than would occur in the absence of the terrain feature. Where there is a significant

relative difference in elevation between the source and off-site receptors large ground level concentrations can result.



The modelling domain would normally be decided on the expected zone of influence; the extent being defined by simulated

ground level concentrations from initial model runs. The modelling domain must include all areas where the ground level

concentration is significant when compared to the air quality limit value (or other guideline). Air dispersion models require a

receptor grid at which ground-level concentrations can be calculated. The receptor grid size should include the entire modelling

domain to ensure that the maximum ground-level concentration is captured and the grid resolution (distance between grid

points) sufficiently small to ensure that areas of maximum impact adequately covered. No receptors should however be

located within the property line as health and safety legislation (rather than ambient air quality standards) is applicable within

the site.

Chapter 5 provides general guidance on geophysical data, model domain and coordinates system requirements, whereas

Chapter 6 elaborates more on these parameters as well as the inclusion of background air pollutant concentration data.

Chapter 6 also provides guidance on the treatment of NO2 formation from NOx emissions, chemical transformation of SO2

into sulfates and deposition processes.

Chapter 7 of the Regulation outlines how the plan of study and modelling assessment reports are to be presented to

authorities.

The first step in the dispersion modelling exercise requires a clear objective of the modelling exercise and thereby gives clear

direction to the choice of the dispersion model most suited for the purpose. Accordingly, Level 2 was deemed the most

appropriate due to the relatively uncomplicated nature of the study area as well as the anticipated impacts to be confined

within 50 km of the project location.

2.1.7 Air Quality Management Plans (AQMP) – the Highveld Priority Area (HPA)

The Highveld Airshed Priority Area (HPA) was declared the second national air quality priority area (after the Vaal Triangle

Airshed Priority Area) by the Minister of Environmental Affairs at the end of 2007 (HPA 2011). This required that an AQMP

for the area be developed. The plan includes the establishment of emissions reduction strategies and intervention programmes

based on the findings of a baseline characterisation of the area. The implication of this is that all contributing sources in the

area will be assessed to determine the emission reduction targets to be achieved over the following few years. Most of the

HPA experiences relatively good air quality, but there are nine extensive areas where ambient air quality standards for SO2,

NO2, PM10 and O3 are exceeded. These “hot spots” are illustrated in Figure 2-1 by the number of modelled exceedances of

the 24-hour PM10 limit. The air quality hot spots result from a combination of emissions from the different industrial sectors

and residential fuel burning, with motor vehicle emissions, mining and cross-boundary transport of pollutants into the HPA

adding to the base loading. The CLS is in the Ekurhuleni Hot Spot (HPA 2011) and the current particulate emissions from the

CLS is likely to also contribute to the existing compromised air quality of the HPA.

The DEA published the AQMP for the Highveld Priority Area on the 2nd of March 2012 (Government Gazette No. 35072).

Included in this management plan are seven goals, each of which has a further list of objectives that must be met. The seven

goals for the Highveld Priority area are as follows:

• Goal 1: By 2015, organizational capacity in government is optimized to efficiently and effectively maintain,

monitor and enforce compliance with ambient air quality standards.



• Goal 2: By 2020, industrial emissions are equitably reduced to achieve compliance with ambient air quality

standards and dust fall-out limit values.

• Goal 3: By 2020, air quality in all low-income settlements is in full compliance with ambient air quality standards.

• Goal 4: By 2020, all vehicles comply with the requirements of the National Vehicle Emission Strategy.

• Goal 5: By 2020, a measurable increase in awareness and knowledge of air quality exists.

• Goal 6: By 2020, biomass burning, and agricultural emissions will be 30% less than current.

• Goal 7: By 2020, emissions from waste management are 40% less than current.

Since the CLS is in the HPA, any means of mitigating air pollution emissions from the plant, such as improved fugitive

particulate emission control measures, would be beneficial to the air quality in the HPA.

Figure 2-1: Modelled frequency of exceedance of the 24-hour ambient PM10 standard in the HPA, indicating the

modelled air quality Hot Spot areas

2.1.8 Gauteng Waste Information System (GWIS)

Regulated under Provincial Regulations (Gauteng Waste Information Regulations, 2004. Gazette No: 372, Notice No: 3035b),

the GWIS was developed and implemented within the Province in 2004. The GWIS was instituted in order to make data and

information of waste available to the public and organs of state. A further objective of the system was to make available waste

information for education, research and development, public health and disaster management. The information required for



input into the GWIS includes the quantity of waste disposed, recycled or treated, the type of waste and the source of the

waste. The CLS is registered with GWIS with number GPF-00-038.

2.1.9 Gauteng Pollution Buffer Zones Guideline

The GDARDs Gauteng Pollution Buffer Zones Guideline (initially developed in 2002 and reviewed in 2017) was developed to

ensure that pollution buffer areas are created between the pollution sources and the nearest human settlements. A buffer

zone in terms of the guideline refers to an area of land required to filter out the deleterious effects of the pollution source that

is buffered (based on current understanding of the pollution type and mode of dispersal). The purpose of the guideline is to

ensure that residents are protected from air emissions from pollution generators and thereby establish buffers around them to

ensure that only the compatible land uses are allowed in the buffer areas.

This Guideline classified industry into eight categories based on the GDARDs brief and the release or potential for the release

of harmful effluent or emissions and associated nuisance factors like noise. The classification was made based on the nature

and level of pollution or potential release of effluents or emissions associated with specific industrial areas. Industrial areas

with pollution risks that can have potentially serious health effects on a large scale have been placed in Category 1 Industries.

Industrial areas with pollution risks that may cause minor health effects or with activities that result in nuisance rather than

actual health impacts were placed in Category 2 Industries. Industrial areas that pose little or no health impacts and that may

result in a nuisance on a localised scale have been placed in Category 3 Industries. The other categories include Sewage

Treatment Works; Landfill Sites/Waste Disposal Facilities; Mine Dumps; Mine Slimes Dams and Ash Dumps; and Nuclear

Complexes. Landfill sites are further subcategorised into the type of waste that the site can receive, i.e. Type 0 to Type 4.

The CFS can receive Type 2 Waste, hence Class B landfill. Accordingly, the Guideline provides a generic maximum buffer

of 1000 m for Class B landfill. The buffer zones around hazardous landfill sites in the Guideline were based on expert opinion

and the potential toxicity of waste accepted at the site. As stated in the Guideline, an additional safety factor was built into the

buffers for landfill sites, thus the buffers prescribed are generally larger than the buffers prescribed by the landfill licensing

conditions.

2.2 Ambient Air Quality Guidelines

2.2.1 Irritational Health Risk Factors

Air quality criteria for non-criteria pollutants are published by various sources. Such criteria include:

• World Health Organization (WHO) guideline values,

• Chronic and sub-chronic inhalation reference concentrations and cancer unit risk factors published by the US EPA

in its Integrated Risk Information System (IRIS),

• U.S. EPA Health Effects Assessment Summary Tables (HEAST)

• Reference exposure levels (RELs) published by the Californian Office of Environmental Health Hazard Assessment

(OEHHA), and

• Minimal risk levels issued by the US Federal Agency for Toxic Substances and Disease Registry (ATSDR).



Table 2-3: International health risk criteria for pollutants not included in the NAAQS

ANALYSIS CAS #

Chronic Reference Concentration

Subchronic Reference Concentration Short-Term Reference

Concentration Acute Reference Concentration

Concentration [µg/m³]

Reference Concentration

[µg/m³] Reference



[µg/m³] Reference

Acetaldehyde 75-07-0 9 IRIS 470 CALEPA

Acetonitrile 75-05-8 60 IRIS 500 HEAST Current

Acrolein 107-02-8 0.02 IRIS 0.092 ATSDR Final 0.092 ATSDR Final 6.88 ATSDR Final

Ammonia 7664-41-7 500 IRIS 100 PPRTV Current 1184.1 ATSDR Final

Arsenic 7440-38-2 0.015 CALEPA 70 PPRTV Current 0.2 CALEPA

Benzaldehyde 100-52-7

Benzene 71-43-2 30 IRIS 80 PPRTV Current 19.17 ATSDR Final 28.75 ATSDR Final

Butylacetate 123-86-4

Carbon Tetrachloride 56-23-5 100 IRIS 188.7 ATSDR Final 188.7 ATSDR Final 1900 CALEPA

Chloroform 67-66-3 97.7 ATSDR Final 244.1 ATSDR Final 244.1 ATSDR Final 488.3 ATSDR Final

Cresol, m- 108-39-4 600 CALEPA

Cresol, o- 95-48-7 600 CALEPA

Cresol, p- 106-44-5 600 CALEPA

Ethyl Acetate 141-78-6 70 PPRTV Current 700 PPRTV Current

Ethylene Dichloride 107-06-2 7 PPRTV Current 70 PPRTV Current

Formaldehyde 50-00-0 9.8 ATSDR Final 36.8 ATSDR Final 36.85 ATSDR Final 49.13 ATSDR Final

Hexane, N- 110-54-3 700 IRIS 2000 PPRTV Current

Hydrogen Sulfide 7783-06-4 2 IRIS 27.9 ATSDR Final 27.88 ATSDR Final 97.57 ATSDR Final

Methyl Ethyl Ketone 78-93-3 5000 IRIS 1000 HEAST Current 13000 CALEPA

Methyl Isobutyl Ketone 108-10-1 3000 IRIS 800 HEAST Current

Pentane, n- 109-66-0 1000 PPRTV Current 10000 PPRTV Current

Phenol 108-95-2 200 CALEPA 5800 CALEPA

Propionaldehyde 123-38-6 8 IRIS

Tetrachloroethylene 127-18-4 40 IRIS 40.69 ATSDR Draft 40.69 ATSDR Draft 40.69 ATSDR Draft

Toluene 108-88-3 5000 IRIS 5000 PPRTV Current 7600 ATSDR Final



ANALYSIS CAS #

Chronic Reference Concentration

Subchronic Reference Concentration Short-Term Reference

Concentration Acute Reference Concentration



[µg/m³] Reference



[µg/m³] Reference

Trichloroethylene 79-01-6 2 IRIS 2.15 ATSDR Draft 2.15 ATSDR Draft

Trimethylbenzene, 1,2,3- 526-73-8 60 IRIS 200 IRIS



Vinyl Chloride 75-01-4 100 IRIS 76.7 ATSDR Final 76.7 ATSDR Final 1.28 ATSDR Final

Xylenes 1330-20-7 100 IRIS 400 PPRTV Current 2605.4 ATSDR Final 8684.662577 ATSDR Final

Notes: IRIS – IRIS U.S. EPA Integrated Risk Information System

PPRTV – U.S. EPA Provisional Peer Reviewed Toxicity Values

ATSDR – Agency for Toxic Substances and Disease Registry minimal risk levels (MRLs)

CALEPA – California Environmental Protection Agency (CalEPA) Office of Environmental Health Hazard Assessment (OEHHA) Chronic Reference Exposure Levels (RELs)

HEAST – U.S. EPA Health Effects Assessment Summary Tables



Various non-carcinogenic exposure thresholds for pollutants of interest in the current study are given in Table 2-3. These

Reference Concentrations (RfC) were obtained from the US EPA’s Risk Assessment Information System (RAIS). RAIS has

been sponsored by the U.S. Department of Energy (DOE), Office of Environmental Management, Oak Ridge Operations

(ORO) Office through a contract between URS | CH2M Oak Ridge LLC (UCOR) and the University of Tennessee. The

database is subject to quality assurance review before being published.

2.2.2 Cancer Health Risk Factors

Unit risk factors (URFs) are applied in the calculation of carcinogenic risks. These factors are defined as the estimated

probability of a person (60-70 kg) contracting cancer as a result of constant exposure to an ambient concentration of 1 µg/m³

over a 70-year lifetime. Unit risk factors were obtained from the sources described in the previous section and summarised

in Table 2-4.

Table 2-4: Unit risk factors

Chemical Inhalation Unit Risk (µg/m3)-

1 Inhalation Unit Risk Source

1,1,2,2-Tetrachloroethane 3.0E-06 WHO

1,1,2-Trichloroehane 1.6E-05 IRIS

1,1-Dichloroethane 1.6E-06 CALEPA

1,2-Dichloroethane (Ethylene dichloride) 2.8E-06 WHO

1,3-Butadiene 3.0E-05 WHO

Acetaldehyde 9.0E-07 WHO

Acrylonitrile 2.0-05 WHO

Arsenic 1.5E-03 WHO

Benzene 7.5E-06 WHO

Benzo(a)pyrene 8.7E-02 WHO

Bromodichloromethane 3.7E-05 CALEPA

Cadmium 1.8E-03 IRIS

Carbon tetrachloride 6.0E-06 IRIS

Chloroform 4.2E-07 WHO

Chromium (hexavalent) 8.4E-02 IRIS

Formaldehyde 1.3E-05 IRIS

Lead 1.2E-05 CALEPA

Methylene chloride 4.7E-07 IRIS

Nickel 2.4E-04 WHO

PCDD/PCDF (i-TEQ) 33 IRIS

Tetrachloroethylene 5.9E-06 CALEPA

Trichloroethylene 4.3E-07 WHO

Vinyl chloride 1.0E-06 WHO

Notes: IRIS – IRIS U.S. EPA Integrated Risk Information System

CALEPA – California Environmental Protection Agency Office of Environmental Health Hazard Assessment

WHO – World Health Organization (WHO) guideline values



The identification of an acceptable cancer risk level has been debated for many years and it possibly will continue as societal

norms and values change. Some people would easily accept higher risks than others, even if it were not within their own

control; others prefer to take very low risks. An acceptable risk is a question of societal acceptance and will therefore vary

from society to society. Despite the difficulty to provide a definitive “acceptable risk level”, the estimation of a risk associated

with an activity provides the means for a comparison of the activity to other everyday hazards, and therefore allowing risk-

management policy decisions. During the middle 1970s, the US EPA and US Food and Drug Administration (FDA) issued

guidance for estimating risks associated with small exposures to potentially carcinogenic chemicals. Their guidance made

estimated risks of one extra cancer over the lifetime of 100 000 people (US EPA) or 1 million people (FDA) action levels for

regulatory attention. Estimated risks below those levels are considered negligible because they add individually so little to the

background rate of about 250 000 cancer deaths out of every 1 million people who die every year in the United States, i.e.

25%. Accepting 1 in 100 000 or 1 in a million risk translates to 0.004% or 0.0004% increase in the existing cancer risk level,

respectively. Similarly, the European Parliament and the European Council, when considering the proposal for a Directive on

Drinking Water, agreed that an excess lifetime risk of 1-in-a-million should be taken as the starting point for developing limit

values. Whilst it is perhaps inappropriate to make a judgment about how much risk should be acceptable, through reviewing

acceptable risk levels selected by other well-known organizations, the US EPA’s application is the most suitable, i.e.

“If the risk to the maximally exposed individual (MEI) is no more than 1x10-6, then no further action is required. If not, the

MEI risk must be reduced to no more than 1x10-4, regardless of feasibility and cost, while protecting as many individuals as

possible in the general population against risks exceeding 1x10-6”

Some authorities tend to avoid the specification of a single acceptable risk level. Instead a “risk-ranking system” is preferred.

For example, the New York Department of Health produced a qualitative ranking of cancer risk estimates, from very low to

very high (Table 2-5). Therefore, if the qualitative descriptor was "low", then the excess lifetime cancer risk from that exposure

is in the range of greater than one per million to less than one per ten thousand.

Table 2-5: Excess Lifetime Cancer Risk (as applied by New York Department of Health)

Risk Ratio Qualitative Descriptor

Equal to or less than one in a million Very low

Greater than one in a million to less than one in ten thousand Low

One in ten thousand to less than one in a thousand Moderate

One in a thousand to less than one in ten High

Equal to or greater than one in ten Very high

2.2.3 Odour Impact Evaluation

Odour thresholds are defined in several ways including absolute perception thresholds, recognition thresholds and

objectionability thresholds. At the perception threshold one is barely certain that an odour is detected but it is too faint to

identify further. Recognition thresholds are normally given for 50% and 100% recognition by an odour panel. Various odour

thresholds published in the literature for odorous compounds are given in Table 2-6. Reported odour threshold data varies

considerably, as much as four orders of magnitude for certain chemicals, as is evident from the thresholds included in Table

2-6. Reasons for this variability include differences in experimental methodologies and in human olfactory responses.



Table 2-6: Odour threshold values for common odorants

Pollutant

Detection Thresholds Odour Recognition Thresholds

Concentration Reference


µg/m³ µg/m³

1-Pentane 3800 Nagata 2003 350 000 Laffort and Dravnieks 1973

1-Pentene 6.2 Verschueren, 1996

1,1-Dichloroethane 200000 Rylova 1953 493200 Verschueren, 1996

1,1-Dichloroethene 23000 Verschueren, 1996

1,2-Dichloropropane 490 Verschueren, 1996

1,1,2,2-

Tetrachloroethane 1600 Dravnieks & Laffort 1972 20000

Lehmann & Schmidt-Kehl

1936

1,3 Butadiene 3540 Verschueren, 1996

Acetaldehyde 1000 Naus 1982 10000 Naus 1982

Acetone 1000 Naus 1982 20000 Naus 1982

Acrylonitrile 22000 Nagata 2003

Ammonia 1100 Nagata 2003 35000 Naus 1982

a-pinene 64 Verschueren, 1996

Benzene 1500 Naus 1982 16000 Naus 1982

Butane 2880000 Nagata 2003 6160000 Mullins 1955

Butyl mercaptan 0.01 Nagata 2003 3 Wilby 1969

Carbon disulphide 100 Naus 1982 1000 Naus 1982

Carbon tetrachloride 29 Nagata 2003 135000 Leonardos et al 1969

Chlorobenzene 1000 Don 1986 3000 Smith and Hochstettler 1969

Chloroform 500 Naus 1982 20000 Naus 1982

Cresol (all isomers) 0.24 Nagata 2003 4.4 Leonardos et al 1969

Cumene 41 Nagata 2003 230 Hellman and Small 1974

Cyclohexane 8500 Nagata 2003 120000 Schley 1934

Cyclohexanone 480 Hellman and Small 1974 480 Hellman and Small 1974

Dimethyl disulphide 6.6 Nagy 1991 29 Wilby 1969

Dimethyl sulphide 1 Glindemann et al 2006 49 Moschandreas & Jones 1983

Ethyl benzene 730 Nagata 2003 1900 Nagy 1991

Ethyl butyrate 280 Verschueren, 1996

Ethyl chloride 10000 Backman 1917

Ethyl mercaptan 1 Wilby 1969 2.5 Leonardos et al 1969

Formaldehyde 600 Nagata 2003 12000 Leonardos et al 1969

Hydrogen sulphide 0.57 Nagata 2003 7 WHO

Limonene 10 Apell 1969 58 Fuller et al 1964

Methylene chloride 560000 Nagata 2003 730000 Leonardos et al 1969

Methyl ethyl ketone 1300 Nagata 2003 29000 Leonardos et al 1969

Methyl mercaptan 0.14 Nagata 2003 2 Wilby 1969

n-Butyl Acetate 77 Nagata 2003 180 Hellman and Small 1974

Phenyl mercaptan 0.14 Stuiver 1958 1.2 Katz & Talbert 1930

Naphthalene 450 Nagy 1991 3370 Morimura 1934

Phenol 21 Nagata 2003 180 Leonardos et al 1969

Propionic acid 17 Nagata 2003 100 Hellman and Small 1974

Tetrachloroethylene 8000 WHO 2000



Pollutant

Detection Thresholds Odour Recognition Thresholds



µg/m³ µg/m³

Trichloroethylene 1500 Verschueren, 1996 20000 Naus 1982

Toluene 1300 Nagata 2003 20000 Naus 1982

Vinyl chloride 520000 Hori et al 1972 910000 Hori et al 1972

Xylene (all isomers) 180 Nagata 2003 2000 Leonardos et al 1969

Due to the absence of detailed South African guidance, reference was made to the international literature in identifying a

suitable method to use in assessing the potential acceptability of odour impacts associated with the proposed landfill.

Reference was primarily made to approaches adopted in the US and in the Australia due to the availability of literature on the

approaches adopted in these countries. There are two main steps in odour assessment, viz.: (i) calculation of odour units

based on predicted or measured ground level air pollution concentrations, and (ii) evaluation of odour unit acceptability based

on defined odour performance criteria. The manner with which these steps are carried out are discussed in subsequent

subsections and a method recommended for adoption in the current study.

The detectability of an odour is a sensory property that refers to the theoretical minimum concentration that produces an

olfactory response or sensation. This point is called the odour thresholds and defines one odour unit per cubic metre (OU/m³).

The odour unit is the concentration of a substance divided by the number of dilutions required for the sample to reach the

threshold as observed by a testing panel in a laboratory. This odour threshold is typically the numerical value equivalent to

when 50% of the testing panel correctly detect an odour. Alternative, and applicable to the assessment of modelled

concentrations, the odour unit is the predicted concentration of a substance divided by the odour threshold for that substance.

Therefore, an odour criterion of less than 1 OU would theoretically result in no odour impact being experienced. Based on the

literature available, the level at which an odour is perceived to be of nuisance can range from 2 OU to 10 OU, depending on

a combination of several factors, including:

o Odour quality – i.e. whether the odour results from a pure compound or from a mixture of compounds. (Pure

compounds tend to have a higher threshold – lower offensiveness – than a mixture of compounds

o Population sensitivity – any given population contains individuals with a range of sensitivities to odour. The

larger the population, generally the greater the number of sensitive individuals contained.

o Background level – refers to the likelihood of cumulative odour impacts due to the co-location of sources

emitting odours

o Public expectation – whether a given community is tolerant of a specific odour and does not find it offensive.

Background agricultural odours may, for example, not be considered offensive until a higher threshold is

reached whereas odours from a waste disposal site or chemical facility may be considered offensive at lower

thresholds.

o Source characteristics – emissions from point sources are more easily controlled that are diffuse sources,

e.g. waste disposal sites

o Health effects – whether an odour is likely to be associated with adverse health effects. In general, odour

from an agricultural operation is less likely to present a health risk than emissions from a waste disposal or

chemical facility.



Experience gained in NSW through odour assessments for proposed and existing facilities has indicated that an odour

performance criterion of 7 OU/m³ is likely to represent the level below which “offensive” odours should not occur for an

individual with a “standard sensitivity”3 to odours. The NSW EPA (NSW 2017) policy therefore recommends that, as a design

criterion, no individual be exposed to ambient odour levels of greater than 7 OU/m3. Where several the factors listed above

simultaneously contribute to making an odour ‘offensive’, an odour criterion of 2 OU/m3 at the nearest sensitive receptor

(existing or any likely future receptor) is appropriate. This is given as generally occurring for affected populations equal to or

above 2000 people. A summary of the NSW EPA’s odour performance criteria for various population densities is shown in

Table 2-7.

Table 2-7: NSW EPA odour performance criteria defined based on population density (NSW EPA, 2017)

Population of Affected Community Odour performance criteria (odour units/m³)

Urban area (>2000) 2.0 500 – 2000 3.0

125 – 500 4.0

30 – 125 5.0

10 – 30 6.0

Single residences (2) 7.0

The odour performance criteria specified by the NSW EPA is compared to that used in other jurisdictions in Table 2-8. It is

evident that the odour performance criteria range specified by the NSW EPA includes the criteria stipulated in various other

jurisdictions. The exception being the South Coast Air Quality Management District in the US which permits odour units of up

to 10 OU in certain instances.

Table 2-8: Odour performance criteria used in various jurisdictions in the US and Australia (after NSW EPA,

2001b)

Jurisdiction

Odour Performance

Criteria (given for application to

odour units) (OU)

New South Wales EPA (NSW EPA, 2001a, 2001b) 2 to 7 California Air Resources Board (Amoore, 1999) 5

South Coast Air Quality Management District (SCAQMD) (CEQA, 1993) 5 to 10

Massachusetts (Leonardos, 1995) 5

Connecticut (Warren Spring Laboratory, 1990) 7

Queensland (Queensland Department of Environment and Heritage, 1994) 5

It is recommended that the NSW EPA approach (NSW EPA 2017) be adopted for use in the current study. The approach

may be summarised as follows:

(i) It is recognised that the predicted model results from dispersion models such as AERMOD need to be extrapolated

to shorter intervals from the typical hourly average concentration results to more accurately simulate atmospheric

dispersion of odours. This is because the instantaneous perception of odours by the human nose typically occurs

3 “Standard Sensitivity” is defined by the Australian and European CEN Standards, which require that the geometric mean of individual odour thresholds estimates must fall between 20 ppb and 80 ppb for n-butanol (the reference compound).



over a time scale of a few seconds, whereas dispersion model predictions are typically valid for time scales

equivalent to ten minutes to one hour averaging periods. To estimate the effects of plume meandering and

concentration fluctuations perceived by the human nose, it is more appropriate to multiply dispersion model

predictions by a correction factor. The prediction of peak concentrations from estimates of ensemble means can be

obtained from a ratio between extreme short-term concentration and longer-term averages. Properly defined peak-

to-mean ratios depend upon the type of source, atmospheric stability and distance downwind. The NSW EPA (NSW

EPA 2017) recommend different factors for estimating peak concentrations depending on different source types,

stabilities and distances. The peak to mean ratio for area sources in the near-field4 is 2.3 (stable atmospheric

conditions and 2.5 (unstable and neutral atmospheric conditions), and in the far field the ratio is 1.9 (stable

atmospheric conditions and 2.3 (unstable and neutral atmospheric conditions), respectively. For the purposes of the

current assessment, a value of 2.3 was adopted for all atmospheric stabilities and downwind distances. This ratio is

similar to the recommendation provided in the DEA Regulations Regarding Air Dispersion Modelling (Section 6.4.1)

for an approximation of the 1-minute average concentration. The extrapolation is performed with the following

equation:

𝐶1

𝐶2

= (𝑇2

𝑇1

)𝑝

where

𝐶1 and 𝐶2 are concentrations for averaging times 𝑇1 and 𝑇2, respectively;

𝑇1 and 𝑇2 are any two averaging times – in this instance 𝑇1 = 1 and 𝑇2 = 60 minutes

p is a parameter ranging from 0.16 to 0.68, depending on the atmospheric stability.

Most widely used values range between 0.16 and 0.25. The DEA Regulations

Regarding Air Dispersion Modelling (Section 6.4.1) recommend using 0.2, which if

applied to the equation provides a ratio of 2.3

(ii) recognition of the detection range for a substance and calculation of the geometric mean detection limit within the

range;

(iii) calculation of odour units by calculating ratios between the 99.9th percentile 3-minute average air pollutant

concentrations and the respective geometric mean detection limits; and

(iv) application of the odour performance criteria set out by the NSW EPA in Table 2-8.

4 The near field is typically 10 times the largest source dimension, either height or width (NSW EPA 2016).



3 ENVIRONMENTAL BASELINE

3.1 Topography

There are no significant topographical features in the study area. The topography rises gradually from the CFS towards the

southeast and northeast. From the southern boundary at an elevation of about 1620 m above mean sea level (AMSL), the

topography rises to about 1674 m AMSL at about 1 km southeast from the CFS. From the eastern boundary at an elevation

of about 1600 m AMSL, the topography rises to about 1632 m AMSL at about 1 km southeast from the CFS. The topography

rises slightly from about 1585 m AMSL at the northern boundary of the CFS to approximately 1597 m AMSL at about 390 m

northwest from the boundary. From here it falls to approximately 1560 m AMSL at about 1.4km from the CFS. There is a

similar fall towards the west of the CFS, i.e. dropping from approximately 1602m AMSL to approximately 1552 m AMSL at

about 1 km from the western boundary of the CFS. The topography increases again to approximately 1578 m AMSL at about

1.6 km. The average slope varies from +5% to the southeast, +3% to the northeast, -4% to the northwest and -5% to the west

for the CFS. These are not significant, and it is therefore reasonable not having to include detailed topography data into the

dispersion model.

3.1 Atmospheric Dispersion Potential

Physical and meteorological mechanisms govern the dispersion, transformation, and eventual removal of pollutants from the

atmosphere. The analysis of hourly average meteorological data is necessary to facilitate a comprehensive understanding of

the dispersion potential of the site. The primary meteorological parameters for air pollutant dispersion include wind speed,

wind direction and ambient temperature. Other meteorological parameters that influence the air concentration levels include

rainfall (washout) and a measure of atmospheric stability. Atmospheric stability is not normally measured but rather derived

from other parameters such as the vertical height temperature difference or the standard deviation of wind direction. The depth

of the atmosphere in which the pollutants can mix is similarly derived from other meteorological parameters by means of

mathematical parameterizations. The meteorological data used for the assessment was from the SAWS OR Tambo

International Airport (ORTIA) meteorological station for the three-year period 2016 to 2018. The weather station is

approximately 13 km southeast of the CLS. The parameters of interest are discussed below.

3.1.1 Surface Wind Field

The wind regime recorded at the weather station largely reflects the synoptic scale circulation. Situated in the subtropical

high-pressure (HP) belt, southern Africa is influenced by several HP cells, in addition to various circulation systems prevailing

in the adjacent tropical and temperature latitudes. The mean circulation of the atmosphere over southern Africa is anticyclonic

throughout the year (except near the surface) due to the dominance of three HP cells, viz. the South Atlantic HP off the west

coast, the South Indian HP off the east coast, and the continental HP over the interior. Seasonal variations in the position and

intensity of the HP cells determine the extent to which the tropical easterlies and the circumpolar westerlies impact on the

atmosphere over the subcontinent. The tropical easterlies, and the occurrence of easterly waves and lows, affect most of

southern Africa throughout the year. In winter, the HP belt intensifies and moves northward, the upper level circumpolar

westerlies expand and displace the upper tropical easterlies equatorward. The winter weather of South Africa is, therefore,

largely dominated by perturbations in the westerly circulation. Such perturbations take the form of a succession of cyclones

or anticyclones moving eastwards around the coast or across the country. During summer months, the anticyclonic belt

weakens and shifts southwards, allowing the tropical easterly flow to resume its influence over South Africa. A weak heat low

characterises the near surface summer circulation over the interior, replacing the strongly anticyclonic winter-time circulation



(Schulze, 1986; Preston-Whyte and Tyson, 1988). The wind field for the study area is described with the use of wind roses.

Wind roses comprise 16 spokes, which represent the directions from which winds blew during a specific period. The colours

used in the wind roses below, reflect the different categories of wind speeds; the yellow area, for example, representing winds

in between 4 and 5 m/s. The dotted circles provide information regarding the frequency of occurrence of wind speed and

direction categories. Calm conditions are periods when the wind speed was below 1 m/s. These low values can be due to

“meteorological” calm conditions when there is no air movement; or, when there may be wind, but it is below the anemometer

starting threshold (AST).

The period, day-time and night-time wind roses are shown in Figure 3-1 for the ORTIA SAWS station, and seasonal wind

roses are shown in Figure 3-2. The ORTIA station wind field was dominated by winds from the north and north-west, with

winds of increased speeds more frequently originating to the north. Winds were infrequently from the south-west. Calm

conditions occurred approximately 1.5% of the time, most frequently at night (2.4%). During the day, winds at higher wind

speeds occurred more frequently from the north and north-west. Night-time airflow had was also dominated by north and

north-westerly winds but at lower wind speeds.

Calm conditions were most frequently recorded in autumn and most infrequently in spring (Figure 3-2). Although the seasonal

wind fields were similar than the period average, slight variations were observed. The autumn and winter wind fields showed

more frequent winds from the south, with a predominance of north-westerly winds. Winds in the higher wind speed categories

are most common in spring, with the fewest calm conditions. The wind field in summer shows a predominance of northerly

winds.

Figure 3-1: Period average, day-time and night-time wind roses (measured data; 2016 to 2018)



Figure 3-2: Seasonal wind roses (measured data; 2016 to 2018)

3.1.1.1 Temperature

Air temperature is important, both for determining the effect of plume buoyancy and determining the development of the mixing

and inversion layers. The monthly temperature trends are presented in Table 3-1 and Figure 3-3. The warmest temperatures

experienced from October to February, while the coolest temperature occur in June and July. Figure 3-4 is a comparison of

the monthly mean temperatures recorded at ORTIA for the two periods 1951 to 1984 (Schultz 1986) and the more recent 2016

to 2018. The latter three years’ averages were significantly higher than the long-term averages by approximately 8% (a

minimum of 2% for February and a maximum of 22% for June).

Table 3-1: Monthly temperature summary (2016 - 2018)

Hourly Minimum, Hourly Maximum and Monthly Average Temperatures (°C)

ORTIA SAWS Weather Station (2016 - 2018)

Statistic Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Minimum 8.3 10.7 7.3 5.7 2.3 -1.1 -2.3 0.0 -0.6 2.8 3.9 10.7

Average 20.3 19.9 19.3 17.3 13.9 12.2 11.4 14.2 18.1 18.4 19.1 20.5



Maximum 35.0 31.1 29.4 28.3 22.8 21.8 21.8 26.8 30.7 32.8 31.8 32.8

Figure 3-3: Monthly average temperature profile (measured data; 2016 to 2018; ORTIA SAWS station)

Figure 3-4: Comparison of monthly mean temperatures at ORTIA for 1951-1984 (Schultz 1986) and 2016-2018



3.1.2 Precipitation

Precipitation is important to air pollution studies since it represents an effective removal mechanism for atmospheric pollutants

and inhibits dust generation potentials. According to the rainfall data from the ORTIA station, the mean annual precipitation is

650 mm (for the three-year period 2016 to 2018 - Figure 3-5). Precipitation occurs as showers and thunderstorms and falls

mainly from October to May (approximately 90 days of measurable rain per year. The winter months are dry with the combined

rainfall in June, July and August making up only 1 % of the annual total.

The average of the three years’ monthly totals are compared to the long-term average monthly totals (1951-1984) in Table

3-2.Table 3-2: Long-term monthly rainfall total compared observations for the period 2016 to 2018 The most significant

differences are noted for the months of April and May; and August and September. Lower rainfall was received during April,

August and September for the 2016-2018 period, whereas nearly double the rainfall where received for May when compared

to the long-term statistics. The annual rainfall for 2016 was slightly higher (797 mm), whereas the rainfall for 2017 (641 mm)

and 2018 (510 mm) were significantly lower than the long-term average of 718 mm (Schultz 1986).

Table 3-2: Long-term monthly rainfall total compared observations for the period 2016 to 2018 at ORTIA

SAWS weather station

Comparison of Monthly Rainfall for the periods 1951-1984 and 2016-2018

Period Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2016-2018 101 92 93 34 39 4 6 0 6 61 112 102

1951-1984 131 95 81 55 19 7 6 6 26 72 114 106

Jan Feb Mar Apr May June Jul Aug Sep Oct Nov Dec

2016 123 65 137 14 49 11 15 0 3 50 210 120

2017 116 118 26 64 46 0 2 0 4 81 76 109

2018 63 93 115 23 24 0 1 0 11 52 50 78

0

50

100

150

200

250

Rai

nfal

l (m

m)



Figure 3-5: Monthly rainfall figures (measured data; 2016 to 2018; ORTIA SAWS station)

3.1.3 Atmospheric Stability

The new-generation air dispersion models describe atmospheric stability as a continuum rather than discrete classes used in

older models. The atmospheric boundary layer properties are therefore described by two parameters; the boundary layer

depth and the Obukhov length. The Obukhov length (LMo) provides a measure of the importance of buoyancy generated by

the heating of the ground and mechanical mixing generated by the frictional effect of the earth’s surface. Physically, it can be

thought of as representing the depth of the boundary layer within which mechanical mixing is the dominant form of turbulence

generation (CERC 2004). The atmospheric boundary layer constitutes the first few hundred metres of the atmosphere. During

daytime, the atmospheric boundary layer is characterised by thermal turbulence due to the heating of the earth’s surface.

Night-times are characterised by weak vertical mixing and the predominance of a stable layer. These conditions are normally

associated with low wind speeds and lower dilution potential.

Diurnal variation in atmospheric stability, as calculated from modelled data, and described by the inverse Obukhov length and

the boundary layer depth is provided in Figure 3-6. The highest concentrations for ground level, or near-ground level releases

from non-wind dependent sources would occur during weak wind speeds and stable (night-time) atmospheric conditions. For

elevated releases, unstable conditions can result in very high concentrations of poorly diluted emissions close to the stack.

This is called looping and occurs mostly during daytime hours. Neutral conditions disperse the plume equally in both the

vertical and horizontal planes and the plume shape is referred to as coning. Stable conditions prevent the plume from mixing

vertically, although it can still spread horizontally and is called fanning. For ground level releases, the highest ground level

concentrations will occur during stable night-time conditions.

Figure 3-6: Diurnal atmospheric stability (AERMET processed SAWS data, 2016 to 2018)



Together with topography, atmospheric stability accounts for occurrence of low-level inversion layers where pollutants may

not disperse effectively. The upper air profile, generated by the AERMET pre-processor, accounts for periods when inversion

layers develop in the upper air.

3.2 Air Pollution Measurements

Reference is made to ambient air quality monitoring information from onsite measurements, fence line samplers and air quality

monitoring stations located in the greater region for the purpose of assessing existing air pollution levels and determining the

potential which exists for cumulative concentrations and hence impacts.

3.2.1 Air Pollution Measurements

The City of Johannesburg (CoJ) currently operates three stations nearest to the CLS. These include a station located at the

Buccleuch Interchange, and a station located within Alexandra at the East Bank Clinic, both of which were commissioned in

2004; and later, in 2009, a monitoring station was commissioned in Ivory Park (see Figure 3-7). The former monitoring location

was specific to the purpose of monitoring vehicular exhaust emissions whereas the latter two are in low income communities

with a strong reliance on domestic combustion. The Buccleuch station has only recently been operational again, after an

extended period of experiencing power connection problems. The station is equipped to monitor meteorological parameters,

SO2, NOx, ozone, PM2.5 and PM10. Similarly, the stations in Ivory Park and Alexandra is equipped to monitor meteorological

parameters, SO2, and PM10. Unfortunately, these two stations also experienced problems and only Alexandra has very

recently been collecting data again. Long term availability of air quality data from these stations is limited and relatively old –

Buccleuch up to and including 2011, Alexandra up to and including 2008 (availability for 2006 to 2008 below 80%) and Ivory

Park for the years 2008 to 2012 but availability less than 10% for the entire period (City of Johannesburg Air Quality

Management Plan, 2017).

Ekurhuleni District Municipality operates two air quality monitoring stations which are located further east from the Ivory Park

station, as shown in Figure 3-7. The station in Olifantsfontein records measurement of meteorological parameters, SO2, NOx

CO, PM10, PM2.5, benzene, toluene, and ethyl benzene. This station has reportedly good data recovery; however, these

observations, just like the other monitoring stations are not relevant to describe the air quality in the vicinity of the CLS. Apart

from the relatively large separation distances between the various monitoring stations and the CLS (order of 10 km) these

observations reflect the concentrations of air pollutants which are due primarily from very local air emission sources. Instead,

it may be more relevant to derive the baseline air quality at the CLS from air quality simulation studies such as the results

published in the draft City of Johannesburg Air Quality Management Plan (2017). The primary aim of the air quality modelling

was to identify air pollutant hotspots. This was achieved by simulating the transport and transformation of pollutant emissions

on an hourly basis within the CoJ boundary and applying various analyses to the output. The air quality model employed to

achieve this was the Comprehensive Air Quality Model with Extensions (CAMx) developed by Ramboll-ENVIRON. The authors

pointed out that only a limited comparison with model output and measurements were performed due to the sparse

measurement data available for this purpose. It was therefore difficult to ascertain the actual performance of the model.

Nonetheless, the simulations clearly identified areas near communities with heavy residential fuel burning and mine tailings

storage facilities as hotspots for PM10 (Figure 3-8). The Tembisa and Ivory Park area was identified as a hotspot, and the

predicted PM10 concentration over the CLS is in the range 75 to 120 µg/m³ towards the east and north, and below 75 µg/m³



towards the southwest. The study area may therefore be prone to occasional exceedances of the daily average NAAQS for

PM10 of 75 µg/m³.

Figure 3-7: CLS in relationship with the air quality monitoring stations in and near CoJ from City of Tshwane

(CoT), Ekurhuleni (EKHL), West Rand (WRDM) and Vaal Triangle Airshed Priority Area (VTAPA) networks (City of

Johannesburg Air Quality Management Plan, 2017)



Figure 3-8: Simulated PM10 air concentrations for 2014 (99th percentile, daily average)

The hotspot analysis identified a large area impacted by SO2 emissions in the current study area (Figure 3-9). The SO2 99th

percentile daily average concentrations predicted at the CLS is in the range of 48 ppb to 354 ppb (125 µg/m³ to 927 µg/m³),



which is above the NAAQS limit value of 125 µg/m³. The authors pointed out that this hotspot simulation was dominated by

the SO2 emissions from Kelvin power station (south of the CLS), but further cautioned that an analysis of the monitoring data

did not support the many exceedances of the SO2 limit, as predicted by the model.

Figure 3-9: Simulated SO2 air concentrations for 2014 (99th percentile, daily average)



Privately owned monitoring stations in the study area include the Chlorchem and AECI networks. Chlorchem, however, only

monitors chlorine air concentrations and therefore not relevant to the study. AECI operates an air quality monitoring station

located south-south east of the CLS in Ester Park, as shown in Figure 3-7. The AECI station can monitors meteorological

parameters as well as SO2, NOx, PM10 and ammonia (NH3). Unfortunately, at the time of the current study, information from

this station was not available for analysis.

Highest hourly, highest daily and annual average pollutant concentrations recorded at the AECI Ester Park monitoring station

during the 2002-2003 are given in Table 3-3. NAAQS limit exceedances are indicated in the table in bold print. Exceedances

of the limit values were noted to occur for PM10, NO2 and SO2. Frequencies of exceedance of the stringent air quality limits

were calculated to be 1.06% for NO2, 0.1% for SO2 and 31.3% for PM10. Although the NAAQS limit values were exceeded

for NO2 and SO2, these were within the 1% allowable frequency of exceedance and hence within their respective NAAQS

standards.

Table 3-3: Maximum and average air pollution concentrations recorded at the AECI Ester Park monitoring

station during the 2002-3 period (values given in bold print represent exceedances of air quality limits)

Pollutants Air Pollutant Concentrations (µg/m³)

Highest Hourly Average Highest Daily Average Annual Average (2003)

PM10 498.7 146.0(a) 54.0(b)

NO2 960.0(c) 302.2 87.5(d)

SO2 574.1(e) 129.4(f) 32.2

NH3 510.0 252.3 27.7

(a) Exceeds the NAAQS daily average limit (75 µg/m³) (d) Exceeds the NAAQS annual average standard (40 µg/m³)

(b) Exceeds the NAAQS annual average standard (40 µg/m³) (e) Exceeds the NAAQS hourly average limit (350 µg/m³)

(c) Exceeds the NAAQS hourly average limit (200 µg/m³) (f) Exceeds the NAAQS daily average limit (125 µg/m³)

3.2.2 Onsite Ambient Air Monitoring

Enviroserv commissioned Geozone Environmental to perform regular measurement of the air quality at the CFS. These

measurements have been made at two fence line locations at the CLS, as shown in Figure 3-10. The sampling method used

passive diffusive samplers which were exposed for monthly (approximate) periods at a time. The samplers were used to

measure H2S, NH3 and volatile organic compounds. Measurement data consisting of 26 monthly samples from July 2014 to

January 2019 were made available for analysis. A summary of the results is provided in Table 3-4. Of the 31 different

compounds listed in the Geozone Environmental results, 6 were found to be below detection, including 2-butoxyethanol,

carbon tetrachloride, cresol, phenol, tetrachloroethylene and trichloroethylene

The results in the table are ranked from highest mean concentration for the period June 2014 to January 2019. The compound

with the highest mean air concentration was observed to be NH3, with a mean value of 37.6 µg/m³ and a maximum of 195.1

µg/m³ (measured for a month during May 2017 and June 2017). Although this was the compound with the highest

concentration, it was still below the chronic and sub-chronic RfCs provided in Table 2-3. The only compounds that exceeded

their respective chronic RfCs include H2S (chronic RfC = 2 µg/m³) and acrolein (chronic RfC = 0.02 µg/m³). Only acrolein

exceeded its sub-chronic RfC of 0.09 µg/m³ when compared to the observed maximum concentration. However, according to

the Geozone data, acrolein was below the detection limit from 2015 onwards.



Figure 3-10: Locations of passive sampling at the CLS



Table 3-4: Summary of diffusive passive sampler results for the period June 2014 to January 2019 (source: Geozone Environmental)

Compound

Sampling Location 1 Sampling Location 2

June 2014 - January 2019 2016-2018 2018 June 2014 - January 2019 2016-2019 2018

Mean Maximum Mean Maximum Mean Maximum Mean Maximum Mean Maximum Mean Maximum

Ammonia 37.6 195.1 53.4 195.1 38.9 54.25 10.4 73.2 12.4 50.3 7.4 9.26

White spirits 19.5 90.9 26.6 90.9 22.1 29.66 33.6 76.0 26.2 54.0 31.2 43.12

Xylenes (all isomers) 9.2 17.1 10.8 17.1 10.6 17.13 15.3 38.3 11.7 16.2 11.0 16.16

Toluene 7.5 13.5 8.6 13.5 9.3 13.54 13.3 50.0 9.5 13.5 9.8 13.54

Limonene 7.4 57.1 1.6 5.5 3.2 5.46 11.3 81.6 1.8 6.1 3.7 6.13

Pentane 4.8 9.8 5.7 9.8 5.6 9.32 6.5 14.1 5.8 11.0 5.8 9.08

Hydrogen Sulphide 4.0 27.5 11.6 27.5 12.8 27.52 2.8 18.4 6.9 18.4 6.9 11.95

Formaldehyde 3.6 16.0 0.8 2.0 1.1 1.95 3.9 18.1 1.1 2.7 1.2 2.11

Benzene 3.3 15.6 4.5 15.6 2.3 3.11 3.3 15.7 4.3 15.7 2.5 3.08

Trimethylbenzenes 3.2 7.8 2.6 5.5 3.9 5.52 5.0 13.7 3.1 6.3 4.4 5.76

Ethyl acetate 2.9 7.7 4.4 7.7 4.9 7.69 3.7 14.2 3.6 5.4 3.9 5.38

Ethylbenzene 2.6 6.3 2.8 4.8 2.9 4.77 3.6 9.3 3.4 5.6 3.5 5.55

Isohexane 2.3 4.3 2.7 4.3 2.4 3.95 2.9 5.6 2.9 5.3 2.6 3.96

Butyraldehyde 2.2 13.8 2.2 6.7 3.9 6.66 3.0 16.2 2.3 7.0 2.3 6.97

Acetaldehyde 2.0 11.5 0.8 2.1 1.1 2.09 2.4 13.5 1.2 3.4 1.3 2.6

n-Hexane 1.7 2.7 1.8 2.7 1.8 2.65 2.6 15.7 1.9 2.7 2.0 2.65

Acrolein 1.5 19.9 0.0 0.0 0.0 0 0.8 8.1 0.0 0.0 0.0 0

Acetonitrile 1.0 26.4 3.8 26.4 8.8 26.41 0.1 1.5 0.2 1.5 0.5 1.49

Propionaldehyde 0.4 2.3 0.2 0.8 0.3 0.82 1.1 16.3 0.3 1.6 0.5 1.56

Benzaldehyde 0.4 3.2 0.0 0.0 0.0 0 0.5 5.7 0.0 0.0 0.0 0

n-Butyl acetate 0.3 1.8 0.5 1.8 1.0 1.77 0.8 3.7 0.7 1.2 1.1 1.16

Methyl ethyl ketone 0.3 2.5 1.0 2.5 1.5 2.5 0.4 5.1 0.7 5.1 0.0 0

Methyl isobutyl ketone 0.3 1.0 0.2 0.8 0.2 0.53 0.2 0.8 0.1 0.4 0.1 0.34

Chloroform 0.1 2.2 0.3 2.2 0.0 0 0.2 5.2 0.7 5.2 0.0 0

Naphthalene 0.0 0.9 0.0 0.0 0.0 0 0.8 19.6 0.0 0.0 0.0 0



The incremental cancer risk for the carcinogenic compounds found in the samples was calculated using the unit risk factors

from Table 2-5. Of the potential carcinogens included in the analysis, only acetaldehyde and benzene were detected.

Carbon tetrachloride, chloroform, tetrachloroethylene and trichloroethylene were below detection limits. The incremental

cancer risks on the site (i.e. conservatively assuming lifetime exposure to the average passive diffusive sampler results)

are:

• Acetaldehyde : 1 in a million

• Benzene : 18 in a million

Testing the for the most significant odours were done using the odour recognition concentrations in Table 2-6. In order to

compare the observed passive sampler concentrations, the monthly mean values need to be extrapolated to short-term

concentrations (1-minute or 1-hour averages). The methodology to extrapolate from hourly to minute average

concentrations were discussed in Section 2.2.3. However, since the observations represent monthly means, a slightly

different exponent for the equation is used. The observed monthly means is first extrapolated to a daily mean value using

the formula as discussed in Section 2.2.3, i.e.

𝐶1

𝐶2

= (𝑇2

𝑇1

)𝑝

where

𝐶1 and 𝐶2 are concentrations for averaging times 𝑇1 = 1 and 𝑇2 = 30 days

p 0.53 (Beychok 2005)

The calculated conversion ratio is approximately 6.06. The next extrapolation is from a daily mean to an hourly mean.

Applying the above formula with 𝑇1 = 60 and 𝑇2 = 24𝑥60 = 1440 minutes and p = 0.2, the calculate conversion ratio

is approximately 1.89. The overall conversion ratio is then obtained as the product, i.e. 11.45.

Through comparison of the compounds contained in Table 3-4, with their respective odour recognition concentrations

(Table 2-6), H2S, NH3, limonene and formaldehyde were initially identified as potential nuisance odorants. However, when

applying the above extrapolation to estimate short-term concentrations of the pollutants, only H2S and limonene flagged

as significant odorants, i.e. exceeding the odour recognition concentrations, as shown in Table 3-5.

Table 3-5: Extrapolated short-term concentration from June 2014 to January 2019 air quality monitoring

data (source: Geozone Environmental)

Compound

Odour Recognition

Concentration

[µg/m³]

Extrapolated Observations

98th Percentile 99th Percentile Peak

Location 1 Location 2 Location 1 Location 2 Location 1 Location 2

H2S 7 263 176 289 193 315 211

Limonene 58 623 882 639 908 654 882

Formaldehyde 12000 182 201 182 204 182 201

NH3 35000 1569 713 1902 776 2234 839

Although other reduced sulphurs other than H2S (e.g. methyl mercaptan, ethyl mercaptan, dimethyl sulphide, etc.) were

not included in the Geozone Environmental data, it is suspected that H2S adequately represents this group of compounds



for its odour significance. Furthermore, although both H2S and limonene were identified as significant odorants, the

observed H2S concentrations are much higher relative to its odour recognition concentration than limonene, and hence

assuming no synergistic effects, the H2S odour would dominate the impact from the landfill.

It is noticeable that monitoring Location #1 recorded higher H2S values than at Location #2 (50% higher). On the other

hand, lower concentrations of limonene were recorded at Location #1 than Location #2 (30% lower). This difference may

be due to different emission locations, and it is suspected the higher H2S concentrations were possibly due to the proximity

of the leachate dam to Location #1. Limonene is more likely to only be released from the landfill whereas H2S would be

from both the landfill and the leachate dam. This is further illustrated when the results in Table 3-5 are compared with the

observations for January 2017 to January 2019 (Table 3-6). The limonene and formaldehyde concentrations have reduced

significantly during the past two years (i.e. lower LFG production), whilst the H2S and NH3 concentrations have remained

relatively similar than the long-term statistics. The latter may be due to a reduction of the limonene and formaldehyde

emissions from the landfill, whereas the leachate dam still emits H2S and NH3 (see Section 4.6.2 for discussion on leachate

dam).

Table 3-6: Extrapolated short-term concentration from January 2017 to January 2019 air quality

monitoring data (source: Geozone Environmental)

Compound

Odour Recognition

Concentration

[µg/m³]

Extrapolated Observations

98th Percentile 99th Percentile Peak

Location 1 Location 2 Location 1 Location 2 Location 1 Location 2

H2S 7 299 201 307 206 315 211

Limonene 58 61 68 62 69 63 70

Formaldehyde 12000 28 30 28 31 29 31

NH3 35000 2040 511 2137 544 2234 544



4 LANDFILL GAS EMISSIONS

Under standard operating practices, a landfill site is characterised by two main sources of gaseous emissions, namely the

working surface and covered portions of the landfill. Although gaseous emissions can also originate from the leachate dam

(or tanks), this is often less significant – once the leachate has been collected and removed from the landfill, it must undergo

some type of treatment and disposal which also reduces air emissions, particularly volatile organic compounds (VOCs). If the

LFG is captured and flared, emissions from the flare would represent a further source of gaseous and particulate emissions.

Sources of fugitive dust emissions include vehicle-entrained dust from paved and unpaved roads, materials handling

operations (e.g. waste movement, compaction and tipping operations), wind erosion of open areas and soil cover, and vehicle

activity on the landfill site, including general vehicle traffic (tractors, trucks, etc.) and earthmoving activities.

This chapter describes the methods employed for the quantification of routine landfill gas and fugitive dust emissions, and

emission rates estimated for each of the pollutants selected for inclusion in the investigation. The following three operational

scenarios were considered during the current study:

• Base Case: current (2019) landfill operations with capping employed on the closed portions of the fill (cells 1 to 6),

and gas collection or flaring in place. This scenario includes surcharge over the previously capped landfill cells.

• Phase 1A: Proposed landfill operations with the gas recovery project in place for Cells 1 to 7 and Phase 1A (i.e. with

capping employed on the closed portions of the fill, collection of gaseous emissions conducted with flaring of these

emissions to atmosphere).

• Phase 1B: Proposed landfill operations with the gas recovery project in place for Cells 1 to 7, Phase 1A and Phase

1B (Cell1 and Cell 2) (i.e. with capping employed on the closed portions of the fill, collection of gaseous emissions

conducted with flaring of these emissions to atmosphere).

4.1 Landfill Gas Generation

Organic waste in a landfill decomposes to form gaseous products and manifests itself as LFG. The waste decomposition

process involves several stages during which different groups of bacteria break down complex organic substances such as

carbohydrates, proteins and lipids into successively simpler compounds. When the degradation process slowly moves from

aerobic condition (presence of free oxygen) to anaerobic condition (absence of free oxygen), carbon dioxide levels continue

to be high, gradually falling as the methane concentration builds up. Upon commencement of the degradation process, bacteria

consume any oxygen contained within the waste and release mainly carbon dioxide, water and heat. In the presence of

atmospheric air, that is near the surface of the landfill, the natural organic compounds are oxidised aerobically, which is a

reaction that is like combustion because the products are carbon dioxide and water vapour. Methane production

(methanogenesis) only starts after anaerobic conditions have been established in the waste, typically 3-6 months after waste

placement (IE EPA 2012). Anaerobic digestion takes place in three stages. In the first stage, fermentative bacteria hydrolyse

the complex organic matter into soluble molecules. In the second stage, these molecules are converted by acid forming

bacteria to simple organic acids, carbon dioxide and hydrogen; the principal acids produced are acetic acid, propionic acid,

butyric acid and ethanol. Finally, in the third stage, methane is formed by methanogenic bacteria, either by breaking down

the acids to methane and carbon dioxide, or by reducing carbon dioxide with hydrogen (Themelis and Ulloa 2007). During

peak gas production the bulk gas consists typically of 50 to 60% methane and 40 to 50% carbon dioxide (IE EPA 2012). Once

all biodegradable substrate in the waste has been consumed, gas production slows and the gas composition in the waste

returns to atmospheric conditions.



Apart from methane and carbon dioxide there are more than 500 substances contained in LFG (IE EPA 2012). The list of

compounds included in the assessment were provided in Table 1-1. Many of these trace gases are toxic, odorous, or both.

Their combined total concentration is typically in the order of a few per cent. Their release to atmosphere occurs mainly

because bulk landfill gas, which is produced in much larger volumes, acts as a carrier gas and flushes the trace gases out of

the body of waste and into the surrounding environment. Certain compounds of both bulk and trace landfill gas can be defined

as VOCs. These include the chemical groups known as alcohols, aldehydes, alkanes, aromatics, halocarbons, ketones and

halogenated derivatives of these substances. VOCs are often grouped into methane and other non-methane VOCs

(NMVOCs). While many VOCs have no odour (such as methane), several VOCs are highly odorous, for example the sulphur

containing mercaptans and dimethyl sulphides.

The quantity of LFG generation would vary with time. An analysis of several anaerobic digestion operations by Verma and

Themelis (2004) showed that the reported rate of generation of biogas ranged from 100 to 200 Nm³ of biogas (54 to108 Nm³

methane) per tonne of wastes digested (using an estimated 60% biomass content). For a landfill containing about 70% of

biomass materials, Themelis and Ulloa (2007) showed that the theoretical generation rate is 208 Nm³ per one tonne of

municipal waste of biogas or 0.149 tonnes of methane per of one tonne of municipal waste, assuming complete reaction.

Table 4-1 summarises the waste disposal rates per year since the start of operation at the CLS. Using the Verma and Themelis

(2004) emission factor range, the estimated average LFG generation over the lifetime of the CLS is calculated to vary between

about 2500 m³/hr and 5000 m³/hr.

Table 4-1: Historical waste amounts received at the CLS from 1997, i.e. the start of operations

Year Waste Receival Rate [tonne]

Waste Only Cover Material Waste and Cover Material

1997 14067 2345 16412

1998 117536 19589 137125

1999 169919 28320 198239

2000 268172 44695 312867

2001 290343 48390 338733

2002 281077 46846 327923

2003 271812 45302 317114

2004 321101 53517 374618

2005 321329 53671 375000

2006 (July-Dec) 180312 59321 239633

2007 344116 114023 458138

2008 291784 70755 362540

2009 322074 65890 387963

2010 308410 64631 373042

2011 310255 46251 356506

2012 310680 14745 325425

2013 10990 51680 62669

2014 66351 49997 116347

2015 120052 34849 154900

2016 146357 5793 152150

2017 144206 25597 169803



Year Waste Receival Rate [tonne]

Waste Only Cover Material Waste and Cover Material

2018 256719 1918 258637

2019 (Jan-Feb) 81509 536 82045

Although the exact composition of the waste received at the site was not available, an estimate of the composition for the

purposes of input into the GasSim model is based on the original study by Jarrod Ball (Ball J & Ass, 2001). This waste

composition is compared with a detailed analysis completed for the Nelson Mandela Bay Municipality (NMBM) (2005) and a

more recent analysis for the City of Johannesburg Municipality by Aurecon (2015). The table also includes the waste

composition which was determined for the Robinson Deep Landfill. Although some variations exist between the analyses,

these are relatively small and the original analysis of Jarrod and Ball (2001) is still determined adequate for the current study.

Table 4-2: Percentage split of different waste streams to assist the classification of waste received at the CLS

Waste Classification NMBM (2005)

Robinson Deep

Aurecon (2015)

IPCC (2006)

Jarrod Ball (2001)

Do

mes

tic

Was

te

Food/Putrescible

73.0%

34% 24.8% 34% 38% 23% 36%

Garden 3% 2.2%

Paper/Card 14% 10.2% 12% 18% 25% 17%

Wood 10% 7.3% 15%

Textiles 2% 1.5% 3%

Plastics (other inert) 19% 9% 10%

Non-Degradable 37% 27.0% 14% 8% 8%

Miscellaneous 18% 27% 37% 30%

Co

mm

erci

al W

aste

Food/Putrescible

4.0%

34% 1.4% 14%

Garden 3% 0.1%

Paper/Card 14% 0.6% 17%

Wood 10% 0.4%

Textiles 2% 0.1% 8%

Plastics (other inert) 0.0% 34%

Non-Degradable 37% 1.5% 17%

Miscellaneous 10%

Industrial Waste 1.20% 100% 1.2%

Inert Waste 14.0% 100% 14.0%

Liquid Waste 3.50% 100% 3.5%

Unknown 4.30% 100% 4.3%

The GasSim model requires various input parameters based on the characterisation of the waste type and the way the waste

is to be stored and managed. The details regarding the waste input, breakdown and composition are discussed in the next

chapter. In addition to these parameters, the GasSim model makes provision for the input of site-specific gaseous

concentrations within the waste (i.e. subsurface gas concentrations) despite comprising default values based on information

from UK landfill sites. Several subsurface concentration campaigns have been completed at the CLS since its inception.

Table 4-3 summarises these campaigns and includes both pre-2006 and more recent 2009 and 2013 measurement

campaigns. The older (pre-2006) campaigns were discussed and summarised in the Air Quality Impact Assessment for The



Enviroserv Chloorkop Landfill Gas Recovery Project (Scorgie et al, 2006). These include the sampling campaigns conducted

by Margot Saner & Associates (Pty) Ltd and Jean Bogner from Landfills Plus. Levego was contracted by Enviroserv to carry

out the measurement of the LFG in 2009 to quantify specific pollutant concentrations entering the CLS gas collection system.

The sampling position was located on the duct downstream of the blower leading to the flare. The Levago campaign also

determined that methane and carbon dioxide were present in the fractions of 41.5% and 36.4%, respectively. More recently,

in 2013, Contra Odour were requested by EnviroServ to undertake an analysis of the collected LFG to determine the quantity

of contaminants found in the gas at a representative sample point before the blower entering the current high temperature

combustion flare.

The analyses from all the surveys are summarised in Table 4-3. Compounds that could potentially be in the LFG that were

below the limit of detection (LOD) are displayed in italics. Various imputation methods for values below the LOD have been

proposed, including: replacement by zero, LOD, LOD/2, LOD/√2 and the truncation and use of the observed values and

bootstrap methods. For the purposes of the current assessment, the relatively simple LOD/√2 was adopted to represent the

concentration for the applicable compounds. This is a reasonable trade-off between replacing it with zero or the LOD, and

slightly more conservative than assuming LOD/2.

Table 4-3: Summary of subsurface gas concentrations measurements campaigns at CLS

Compound Concentration [mg/Nm³]

Scorgie et al (2006) Levago (2009) Contra Odour (2013)

1,1,1-trichloroethane 0.7 0.07

1,1,2-Trichloroethane 0.546 0.7

1,1-Dichloroethane 0.405 0.7 0.07

1,1-Dichloroethene 0.405 0.7 0.07

1,2-Dichloroethane 0.7 0.07

1,2-Dichloropropane 0.7

1,2,3-Trimethyl benzene 19.5

1,2,4-Trimethyl benzene 18.3

1,3,5-Trimethyl benzene 6

Ammonia 74.4

a-Pinene 63.7

Benzene 0.957 2.2

Bromochloromethane 0.7

cis-1,2-Dichloroethene 5.4

Carbon Disulphide 0.592 3.5

Chlorobenzene 0.462 0.7

Chloroethane 0.264 0.7

cis-1,2-Dichloroethylene 28.0

cis-1,3-Dichloropropene 0.7

Dibromochloromethane 0.7

Dichlorobenzene 0.7

Dichloromethane 1.355 2.6 0.07

Diethyl Sulfide 0.7

Diethyldisulphide 0.254 0.7

Dimethyldisulphide 0.193 1.7

Dimethylsulphide 0.368 7.1



Compound Concentration [mg/Nm³]

Scorgie et al (2006) Levago (2009) Contra Odour (2013)

Ethane Thiol 0.127 0.7

Ethylmethylsulphide 0.7

Freon 114 0.7

Freon 142b (semi-quantitative) 0.7

Freon 21 0.7

Freon 22 0.7

Hydrogen Sulfide 2.793 - 174.519 96.7

Methane Thiol 0.669 3.0

d-3-Carene 8.7

Decamethylcyclopentasiloxane (D5) 5.6

Decamethyltetrasiloxane (L4) 0.07

Dichlorodifluoromethane (F12) 12.859 4.3 0.1

Ethyl Benzene 1.275 45.9

Hexamethylcyclotrisiloxane (D3) 0.3

Hexamethyldisiloxane (L2) 1.5

i-Propylbenzene 2.8

i-Propyltoluene 178

Limonene 1.352 - 50.703 203

m- & p-Ethyltoluene 0.492 20.4

m-Xylene p-Xylene 17.487 87.6

n-Propylbenzene 2.8

Octamethylcyclotetrasiloxane (D4) 11

Octamethyltrisiloxane (L3) 0.1

o-Ethyltoluene 0.492 7.4

o-Xylene 17.487 30.5

ß-Pinene 6.8

Styrene 3.7

Tetrachloroethene 3.234 19.1 2.2

Tetrachloromethane (carbon tetrachloride) 0.629 0.7 0.07

Tetramethylsilane 0.07

Toluene 15.099 51.5

trans-1,2-Dichloroethene 1.0 0.07

Trichloroethene 1.856 4.9 0.9

Trichlorofluoromethane (F11) 0.7 0.07

Trichloromethane (chloroform) 0.488 0.7 0.07

Trichlorotrifluoroethane (F113) 0.766 0.7 0.07

Trimethylsilanol 1.4

Vinyl Chloride 0.256 1.7 0.9

Total Volatile Organic Compounds 4340

Total Chlorinated Compounds 57.2

Total Fluorinated Compounds 4.3

Total Organo-Sulphur Compounds 15.2

Total Chlorinated Compounds as Cl 47.1



4.2 Gaseous Emissions from Leachate Dams

Leachate and evaporation dam emissions can occur through diffusive and/or convective mechanisms. Diffusion occurs when

constituent concentrations on the surface of the dam are much higher than the ambient air concentrations. This leads to the

volatilization of these constituents to reach equilibrium between the liquid and vapour phases. Convection occurs when air

flows over the storage dam surface vapours are “swept” from the surface to the air. The rate of volatilisation is directly related

to the wind speed over the leachate dam surface (NPI, 1999).

Typical evaporating emissions from leachate dam surfaces include sulphides, especially in the form of H2S which could result

in significant odour impacts. Other gases may include NH3 and potentially organic vapours. The latter would typically only

when there are evaporating ponds containing waste oils and solvents.

Sulphates in the leachate have the potential to react with organic media in the waste to form aqueous H2S. This formation is

dependent on the presence of anaerobic bacteria, and the amount of sulphur available. Organic acids such as lactic acid,

propionic acid, and acetic acid produced in the anaerobic decomposition process of organic matter are utilised together with

sulphate ions to produce H2S. Depending on the pH of the liquid, aqueous H2S exists in equilibrium with the bisulphide anion

(HS-) and the sulphide anion (S2-) as shown in Figure 4-1. H2S and HS- are in equilibrium at a pH of 7, whereas HS- and S2-

are in equilibrium at a pH of 12.9. The dissociation of molecular H2S in water increases at pH values above 7 and, as pH

shifts from alkaline to acidic (pH <7), the potential for H2S emissions increases. For example, at a pH of 6, the H2S fraction

(i.e. available to the atmosphere) is around 91%, at a pH=7.0, the fraction is about 60%, and at a pH = 9.0, the fraction would

only be about 1%.

Figure 4-1: Fractions of sulphide species (H2S, HS-, S2-) present in aqueous solution as function of pH at 25°C

[Source: Snoeyink and Jenkins (1980)]



A chemical analysis of the current CFS leachate pond was completed by Enviroserv to quantify the concentrations of both

organic and inorganic compounds in the liquid. The results of the August 2018 inorganic analysis is provided in Table 4-4 and

the organic analysis, which were done in April 2019, is provided in Table 4-5. The parameters required to estimate the H2S

emissions include the pH, which was observed to be 8.12 and the sulphates concentration (35 mg/L). The only other

compound that is relevant include NH3, since the metals would not become airborne from the pond. All the VOCs include in

the organic analysis where below their respective detection limits, which apart from Hexachlorobutadiene, are all less than

1 µg/L. It is therefore reasonable to assume that the VOCs originating from the leachate pond is insignificant compared to

the LFG.

Table 4-4: Inorganic chemical analyses (17 August 2018) of Leachate dam at the CLS

Determinant Detection Limit Result

pH 1 8.12

Ammonia 0.01 612 mg/L

Sulphates, as SO4 35 35 mg/L

Chloride 0.5 1703 mg/L

Fluoride 0.1 0.16 mg/L

Arsenic 0.01 Below Detection Limit (BDL)

Barium 0.01 0.72 mg/L

Boron 0.03 3.2 mg/L

Cadmium 0.002 BDL

Calcium 0.01 101 mg/L

Chromium (total) 0.01 0.38 mg/L

Chromium (Hexavalent) 1 BDL

Copper 0.01 BDL

Iron 0.1 BDL

Lead 0.01 0.03 mg/L

Magnesium 0.03 94 mg/L

Manganese 0.01 0.78 mg/L

Potassium 0.01 826 mg/L

Sodium 0.01 1399 mg/L

Table 4-5: Leachate dam VOC chemical analyses (4 April 2019) at the CLS

Determinant Detection Limit [µg/L] Result

Benzene 0.02 Below Detection Limit (BDL)

Chlorobenzene 0.02 BDL

Chloroform 0.05 BDL

1,2-Dichlorobenzene 0.12 BDL

1,4-Dichlorobenzene 0.07 BDL

1,2-Dichloroethane 0.01 BDL

1,1-Dichloroethene 0.34 BDL

1,2-0ichloroethene 0.08 BDL

Ethylbenzene 0.09 BDL

Hexachlorobutadiene 1.63 BDL

Styrene 0.21 BDL

1,1,1,2-Tetrachloroethane 0.19 BDL



4.3 Flare Emissions

The current CLS utilises two enclosed flares, at locations shown in Figure 1-4. It is also proposed to continue with these flares

for the proposed expansions to the CLS. The exact locations of the proposed flares were not available at the time of the

assessment; however, it was indicated that it would be located in the top, northern corner of the expansion, as indicated in

Figure 4-2. The purpose of flaring is to dispose of the flammable constituents safely, particularly methane, and to control

odour nuisance, health risks and adverse environmental impacts. The quantity of LFG extraction from a landfill will vary with

time and between cells for the same reasons that account for compositional differences. As indicated in Section 4.1, the

theoretical LFG generation rates for the CLS is calculated to vary between about 2500 m³/hr and 5000 m³/hr. The ultimate

amount available for the flare also depend on the efficiency of the extraction and collection system. Enviroserv indicated that

the current LFG feed varies between 400 Nm³/hr and 2000 Nm³/hr, and they have estimated the collection efficiency to be

80% to 90%. The theoretical rate estimated using the LFG generation factor in Section 4.1 therefore appears to be too high.

The quality of the capping material significantly influences the degree to which landfill gas escapes through the surface of the

site to atmosphere and the quantities of water that may enter the body of the waste. As a landfill ages further and the intensity

of anaerobic activity subsides, so the rate of gas generated will decline. It is expected that the rate of gas extraction will

decrease proportionately, though relatively greater quantities of air might be drawn in. Landfill gas production may continue

for several hundred years (UK Environment Agency, 2002).

4.4 Fugitive Particulate Emission

Vehicle-entrained dust emissions have been found to account for the greatest portion of fugitive dust emissions from many

local waste disposal operations. The force of the wheels of vehicles travelling on unpaved roadways causes the pulverisation

of surface material. Particles are lifted and dropped from the rotating wheels, and the road surface is exposed to strong air

currents in turbulent shear with the surface. The turbulent wake behind the vehicle continues to act on the road surface after

the vehicle has passed. The quantity of dust emissions from unpaved roads varies linearly with the volume of traffic. The silt

content given by the US-EPA as being typical for disposal routes at municipal solid waste landfills ranges between 2.2% to

21% (US EPA 2006a).

The fugitive dust generated from handling of the waste (tipping, compacting, and covering) is dependent on climatic

parameters, such as wind speed and precipitation, as well as parameters such as the nature and volume of the material

handled. The crushing of building rubble on-site, for use in road stabilisation and as daily cover material, may also occur.

.

1,1,2,2-Tetrachloroethane 0.19 BDL

Tetrachloroethylene 0.36 BDL

Toluene 0.04 BDL

Trichlorobenzene 0.57 BDL

1,1,2-Trichloroethane 0.11 BDL

1,1,1-Trichloroethane 0.04 BDL

Trichloroethylene 0.09 BDL

m/p-Xylene 0.05 BDL

a-Xylene 0.04 BDL

Carbon Tetrachloride 0.06 BDL

Vinyl chloride 0.04 BDL



4.5 Litter

A significant fraction of litter items are plastic bags, which are particularly prone to becoming litter due to their low weight and

ability to become airborne and travel in wind. Litter at landfill sites is largely associated with delivery and unloading of waste,

as well as during picking and sorting for recycling purposes. This is rather than with compaction and burial operations since

the compaction and burial process generally punctures the plastic bags and covers the waste material making bags less likely

to become windblown.

4.6 Pathogens

Pathogens are mainly associated with discarded carcasses if these are disposed of on a landfill site. The distribution of

pathogens and the predicted risk associated with pathogens at landfills are not easily quantifiable. The limitations in

quantifying these impacts are generally the lack of knowledge as to concentration of a pathogen that may be attached to

windblown dust or simply blown from the landfill, as pathogens may not be evenly distributed in the waste. Using best

management practice, when carcasses arrive on the site, they should be disposed of immediately and covered. Furthermore,

carcasses should always be disposed of in a dedicated section of the landfill, where trenching is not carried out. The addition

of lime inhibits pathogens by controlling the environment required for bacterial growth. The high alklinity also provides a vector

attraction barrier (i.e. prevents flies and other insects from infecting the treated biological waste).

4.7 Quantification of Air Pollutant Emissions

4.7.1 Landfill Gas Emissions

Numerous factors affect the ultimate rate with which gases may be released from the covered portions of the landfill. Such

factors include advection, diffusion, accumulation, generation, adsorption, biodegradation, leaching, capillary action and

evaporation. Due to the complexity of predicting emissions from the CLS, use was made of the GasSim Model. This model

was used to quantify the emissions emitted by the landfill during different operating scenarios. The emissions were quantified

considering working faces, covered cells, gas extraction and flaring at site as well as the release of gaseous emissions from

fissures in the capped portions of the fill. The CLS has been operating since 1997, with the original closure scheduled for

2017 (21 years). However, GDARD subsequently issued a permit allowing Enviroserv to increase the operating height of the

landfill, thereby providing the opportunity to place additional waste on the previously closed operating Cells 1 to 6 (Chapter 1,

Figure 1-4). The proposed expansion includes the development of Cell 7, Phase 1A, Phase 1B Cell 1 and Phase 1B Cell 2,

as shown in Figure 4-2.

The annual waste acceptance rate for the period 1997 to 2019 was summarised in Table 4-1. The projected rates for the

expansion is assumed to be 420 000 tonnes per annum (35 000 per month), which would be allocated as projected for the

different developments of the cells in the northern expansion, as summarised in Table 4-7. Proposed Cell 7 has approximately

11 months of life, whilst Phase 1A has approximately 44 months (3.66 years), Phase 1B Cell 1 (1.46 years) and Phase 1B

Cell 2 (4.18 years). This would extend the operating life of the CLS from 2019 to 2028 (Table 4-8) with the assumed waste

disposal rates as summarised in Table 4-6. The following assumptions were made regarding the capping of the landfill:

• 2005 – Cells 1 and 2 filled and partially capped;

• 2007 – Cells 1 to 3 filled and capped;



Figure 4-2: Proposed expansion of the CLS (Cell 7, Phase 1A Cell 1 and Phase 1B Cell2)



Table 4-6: Annual waste disposal rates for the CLS (shaded cells are projected rates assumed in the assessment based on estimated schedules in Table 4-8)

Year Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 Cell 6 Surcharge Cell 7 Phase 1A Phase 1B Cell1 Phase 1B Cell 2

1997 14067

1998 117536

1999 84960 84960

2000 134086 134086

2001 145172 145172

2002 140539 140539

2003 135906 135906

2004 107034 107034 107034

2005 107110 107110 107110

2006 119816 119816

2007 152713 152713 152713

2008 362540

2009 387963

2010 186521 186521

2011 356506

2012 325425

2013 31335 31335

2014 116347

2015 154900

2016 152150

2017 169803

2018 258637

2019 315000 105000

2020 280000 140000

2021 420000

2022 420000

2023 420000

2024 140000 280000

2025 350000 70000



Year Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 Cell 6 Surcharge Cell 7 Phase 1A Phase 1B Cell1 Phase 1B Cell 2

2026 420000

2027 420000

2028 245000



• 2010 – Cell 4 filled and capped;



• 2020 – Surcharge area capped

• 2021 – Cell 7 filled and capped

• 2025 – Phase 1A filled and capped

• 2026 – Phase 1B Cell 1 filled and capped

• 2029 – Phase 1B Cell 2 filled and capped

The detailed input file used in the GasSim model can be found in Appendix A. The file includes the assumed pollutant

distributions used as initial concentrations in the LFG based on the analytical results contained in Table 4-3. The procedure

assumed the concentrations from the latest subsurface analytical results first, i.e. Contra Odour (2013); and if not included or

BDL, then those obtained in the Levago (2009) survey were used. The Scorgie et al (2006) summaries were only used when

neither the Contra Odour nor Levago had results to use. Where measurements of compounds in GasSim were not part of the

two surveys, default GasSim values were assumed. These concentrations replaced the mean values in the Gassim default

probability distribution functions (pdfs) unless none of the datasets could be used. The Gassim pdfs, as well as the default

minimum and maximum concentrations were used in the calculations.

Table 4-7: Details of the cells proposed in the northern expansion of the CLS

Waste Cell Area [m²] Volume [m³]

Disposal Duration Construction Duration

[months] [months] [years]

Phase 1A (Incl. Cell 7) 46 500.00 1 538 530.00 43.96 3.66 6.64

Phase 1B Cell 1 40 200.00 613 510.00 17.53 1.46

Phase 1B Cell 2 22 900.00 1 140 806.00 32.59 2.72

Phase 1B Total 63 100.00 1 754 316.00 50.12 4.18 9.01

Table 4-8: Assumed periods of operating cells proposed for the northern expansion

Cell Projected Disposal Period

Start End

Cell 7 Oct-19 Aug-20

Phase 1A Aug-20 Apr-24

Phase 1B1 Apr-24 Oct-25

Phase 1B2 Oct-25 Jul-28

The hours of operation at the site were given as 07h00 to 17h00 Monday to Friday, 07h00 to 15h00 on Saturday and 07h00

to 12h00 on Sunday. Work faces are covered at the end of each day. Dust suppression includes watering with odour controls

being implemented on leachate areas “as required”. The emission rates calculated by the GasSim model were estimated

using the subsurface gas concentrations specified in Table 4-3 and 95th percentiles calculated across the 200 iterations

simulated. The assumed probability density functions and statistical values (minimum, mean and maximum) used in the

respective functions’ emissions are given in the GasSim input file which is provided in Appendix A. The historical and projected

annual waste amounts provided in Table 4-1 as well as the waste composition from Table 4-2 were assumed in the GasSim

model.



Anker Street separates part of the expansion area from the CLS and thus a phased approach is likely. The figure includes the

current emissions (Baseline), the development of Cell 7, Phase 1A, and Phase 1B Cell 1 and Cell 2 (Phase 1B). Phase 1A

would entail the development and use of waste disposal cells between the CLS and Anker Street. Phase 1B would involve the

development and use of waste disposal cells on the northerly portion of the site, connecting with the CLS and Phase 1A. The

second phase would only proceed if Anker Street had been relocated or closed (subject to municipal engagement and

approvals).

Emission rates for all compounds contained in Table 4-3, as well as several compounds included in the GasSim default

database were calculated. Based on the GasSim Tier 1 screening methodology as well as the observed Geozone

Environmental results (Section 3.2.2), the following emissions were the highest ranked with respect to the respective rate of

release, and its toxicity and/or odour concerns. GasSim uses as the basis for Tier 1 screening the data from the Environment

Agency guidance “Screening method for emissions to air from landfill sites” (Environment Agency, 2004b). This provides

several tables that can be used to calculate a ground-level concentration of a gaseous emission at a receptor, based on the

95th percentile emission rate from the process, its height, and the distance to the receptor. Separate tables are provided for

short-term and long-term concentrations.

The GasSim Tier 1 screening methodology is based on health risk endpoints provided as default Environmental Quality

Standards (EQS) and Environmental Assessment Levels (EAL) values, as given in Table 4-9. Gases without an EAL/EQS is

not screened by the model. The first pair of rules determines whether the impact is insignificant or not, over the short-term (1

hour) or long-term (annual) assessment period. The second pair of rules determines whether the impact requires detailed

modelling or if GasSim is sufficient. The look-up tables have been developed to be conservative:

• The tables are not directional, so you do not need meteorological data;

• The tables are essentially based on the 100th percentile emissions;

• The tables are derived from a representative and not extreme wind rose; and

• The tables evaluate the Environment Agency’s H1 assessment equations.

Ground level air concentrations are taken from the lookup tables for locations along the landfill boundary and at the nearest

defined receptor locations. Based on a comparison with the EQS or EAL, recommendations would be provided whether

further, more detailed dispersion modelling is required.

According the Tier 1 screening results, short-term simulations are recommended for arsenic, ethylene dichloride and hydrogen

sulfide, whereas no long-term screening levels were exceeded. For the proposed expansions, the screening also included

vinyl chloride in the list. Nonetheless, since limonene, ammonia, benzene and formaldehyde were identified in the Geozone

monitoring results as potentially significant, it was decided to include these in addition to ethylene dichloride in the next

simulations.

Table 4-9: GasSim default Environmental Quality Standards (EQS) and Environmental Assessment Levels

(EAL) values for use in Tier 1 screening evaluation

Pollutant Short Term EQS or

EAL [μg/m³] Long Term EQS or EAL

[μg/m³]

Acetalehyde (ethanal) 9200 370

Acetone 362000 18100

Acrylonitrile 264 8.8

Arsenic 0.003 0

Benzene 0 5



Pollutant Short Term EQS or

EAL [μg/m³] Long Term EQS or EAL

[μg/m³]

Benzo(a)pyrene -flare emissions 0 0.00025

Butadiene (modelled as 1,3-Butadiene) 0 2.25

Butane 181000 14500

Carbon disulphide 100 64

Carbon monoxide -flare emissions 10000 0

Carbon monoxide 10000 0

Carbon tetrachloride (tetrachloromethane) 3900 130

Chloroform (trichloromethane) 2970 99

Dichloromethane (methylene chloride) 3000 700

Ethylbenzene 55200 4410

Ethylene dichloride 700 42

Formaldehyde (methanal) 100 5

Hexane 21600 720

Hydrogen chloride, or (Total chloride (reported as HCl)) -flare emissions 750 0

Hydrogen fluoride, or (Total fluoride (reported as HF)) -flare emissions 160 16

Hydrogen sulphide 150 140

Mercury 7.5 0.25

Methyl chloride (chloromethane) 21000 1050

Methyl chloroform (1,1,1-Trichloroethane) 222000 11100

Methyl ethyl ketone (2-butanone) 89900 6000

Nitric acid 1000 52

Nitrogen oxides (NOx) -flare emissions 200 40

PAH (reported as Naphthalene) 8000 530

para-Dichlorobenzene (modelled as 1,4-Dichlorobenzene) 30600 1530

Phenol 3900 200

PM10s -flare emissions 0 40

PM10s 24 hour -flare emissions 50

Sulphur dioxide -flare emissions 350 0

Sulphur dioxide 15 min -flare emissions 266

Sulphur dioxide 24 hour -flare emissions 125

Tetrachloroethylene (Tetrachloroethene) 8000 3450

Toluene 8000 1910

Trichlorobenzene (all isomers) 2280 76

Trichloroethylene (trichloroethene) 1000 1100

Trimethylbenzene (all isomers) 37500 1250

Vinyl chloride (chloroethene, chloroethylene) 1851 159

Xylene (all isomers) 66200 4410

The temporal variation of LFG emissions throughout the landfill’s lifetime is illustrated in Figure 4-3. These emission rate

calculations included gas extraction for flare operation throughout the proposed phases and 7 years beyond the final waste

acceptance i.e. 2028.

Similarly, emission rates for H2S, limonene, NH3, acetaldehyde, benzene, formaldehyde, ethylene dichloride, vinyl chloride

and arsenic were calculated. As shown in the examples included Figure 4-4 for H2S and Figure 4-5 for benzene, the emission

rate closely follow the bulk LFG generation curve in Figure 4-3. The landfill gas emission rates for the selected key pollutants

are provided in Table 4-10.



Figure 4-3: GasSim simulated LFG generation rate



Figure 4-4: GasSim simulated 95th percentile H2S landfill generation rate



Figure 4-5: GasSim simulated 95th percentile benzene landfill generation rate



Table 4-10: GasSim calculated emission rates for baseline and two proposed phases

Key-Pollutant

Landfill Emission Rate (g/h)

Baseline Phase 1A Phase 1B

2018 2024 2029

Arsenic 0.02 0.11 0.09

Acetadehyde 1.15 1.43 1.38

Benzene 4.1 32.0 40.2

Ethylene dichloride 75.2 201.1 219.2

H2S 245.6 1854.7 1278.8

Formaldehyde 0.05 0.11 0.12

Vinyl chloride 122.7 278.5 274.7

Limonene 54.7 115.5 142.7

NH3 61.5 140.3 158.5

4.7.2 Flare Emissions

During the current assessment a landfill gas throughput of maximum 2 000 m³/hr (per flare; 1-2 flares in operation) at a

combustion temperature of 1000 °C was assumed, emitted from a 7.85 m high stack with a diameter of 1.8 m. Each flare was

also assumed to be enclosed. The projected emission rates for the flare operations, as projected using the GasSim model,

are given in Figure 4-3. The flare destruction efficiency was assumed to be in excess of 99%. Each flare was assumed to

operate for a period of 7 years after closure of Phase 1B, i.e. 2036. The GasSim generated flare emission rates for the given

the calculated LFG and assumed compositions, as discussed in the previous section, for the baseline, Phase 1A (& Cell 7),

and Phase 1B are provided in Table 4-11.

Table 4-11: Calculated (GasSim) flare air pollutant emission rates (two flares combined emission rates)

Air Pollutant

Baseline Phase 1A & Cell 7 Phase 1B

Concentration

[mg/m³]

Emission

[g/s]

Concentration

[mg/m³]

Emission

[g/s]

Concentration

[mg/m³]

Emission

[g/s]

NOx expressed as NO2 12.9 0.48 12.1 0.60 12.1 0.69

SO2 1.7 0.06 1.9 0.09 1.9 0.11

CO 110.9 4.16 110.0 5.47 110.0 6.26

NH3 0.0065 0.00024 0.0049 0.00024 0.0054 0.00031

H2S 0.05 0.0020 0.06 0.0030 0.05 0.0029

Benzene 0.0018 0.00007 0.0015 0.00007 0.0015 0.00009

Acetaldehyde 0.00016 0.000006 0.00012 0.000006 0.00011 0.000006

Formaldehyde 0.0018 0.00007 0.0015 0.00007 0.0015 0.00009

Ethylene Dichloride 0.0074 0.0003 0.0089 0.0004 0.0093 0.0053

Vinyl Chloride 0.036 0.0014 0.031 0.0015 0.029 0.0016

VOC 300.9 11.28 310.1 15.42 310.1 17.66

NMVOC 2.5 0.09 2.5 0.12 2.5 0.14

PM10 1.8 0.066 1.6 0.077 1.5 0.084

Exhaust Flow Rate [m³/hr] 135 000 179 000 205 000



4.7.3 Leachate Pond Gas Emissions

As indicated in Section 4.2, sulfates (and hence potentially the formation of H2S) and NH3 are the only compounds that flag

as potential air pollutants from the leachate dam. NH3 in solution (𝑁𝐻3(𝑎𝑞)) rapidly dissociates into NH3+ and OH-, as follows:

𝑁𝐻3(𝑎𝑞) ⇌ 𝑁𝐻4+ + 𝑂𝐻−

𝑁𝐻3(𝑔) ⇌ 𝑁𝐻3(𝑎𝑞)

This equilibrium depends strongly on the pH of the solution; shifting the equilibrium to the left when the pH is high (in other

words more 𝑂𝐻−) and hence more potential to release NH3 into the atmosphere. At lower pH, the equilibrium is shifted to the

right, and therefore lower concentration of 𝑁𝐻3(𝑎𝑞). This is equilibrium may be expressed as constant, defined as

𝐾𝑙 ⇌[𝑁𝐻4

+][𝑂𝐻−]

[𝑁𝐻3(𝑎𝑞)]

The equilibrium constant is a function of temperature. At 25°C it is approximately 1.75x10-5. At the pH of the lagoon (i.e.

pH=8.12, Table 4-4), the equilibrium is shifted well to the right with the result that only a very small fraction (<0.001%) of the

NH3 is available for atmospheric release and therefore not regarded significant enough to be included as a source in the

simulations.

H2S, on the other hand, could potentially be released in larger quantities from the leachate dam and proposed tanks. These

emissions were estimated using the model developed by Blunden, Aneja and Overton (2008). These authors developed a

model that simulates H2S emissions across the gas-liquid interface of an anaerobic swine waste treatment storage system.

Although the conditions within the landfill may not be the same as in a swine waste treatment plant, the speciation of the

sulphide ions obey the same chemical rules and the same theory is therefore assumed to be applicable to the leachate in the

landfill.

The Blunden et al (2008) simulation utilises a two-film model with three different modelling approaches: Coupled Mass Transfer

with Chemical Reactions Model with the assumption (a) pH remains constant in the liquid film and (b) pH may change

throughout the liquid film due to diffusion processes that occur within the film; and (c) a Mass Transfer Model which neglects

chemical reactions in the gas and liquid films. The model requires knowledge on the sulphide concentration in solution, the

pH of the leachate, leachate temperature and ambient temperature to estimate the available H2S that could be released from

the liquid surface. The mass transfer above the leachate liquid surface is determined by the atmospheric conditions such as

the wind speed and ambient air temperature. Wind speed has the effect of increasing evaporation rates from open liquid

surfaces. The model was subsequently used to calculate the H2S flux rate from the existing dam using the sulphate and pH

conditions in the leachate dam (Table 4-4) and the meteorological parameters for the period 1 January 2016 to 31 December

2018, as shown in Figure 4-6.



Figure 4-6: Calculated H2S air emissions from leachate dam for a 2016 to 2018

Assuming the same leachate conditions for the proposed tanks, representation H2S emission rates were estimated as

summarised in Table 4-12. It was conservatively assumed that the tank would be open to wind. Emissions from closed tank

vents can be controlled hence reducing any air emissions from the leachate.

Table 4-12: Calculated H2S emission rates from the current leachate dam and proposed tanks

Percentile H2S Flux Rate [mg/m²-min]

Emission Rate [g/hr]

Baseline Cell 7 New Leachate Tank Phase 1A & 1B Leachate Tanks

100 1.61 156.6 10.9 61.2

99 1.08 104.7 7.3 40.9

98 1.01 98.0 6.8 38.3

95 0.76 74.2 5.2 29.0

90 0.57 55.4 3.9 21.6

4.7.4 Fugitive Particulate Emissions

The emissions of fugitive dust occur at the working face (materials handling, and bulldozing and compaction), open areas

without permanent cover (wind erosion), and as a result of vehicle entrainment on unpaved and paved roads. Materials

handling operations include the transfer of material by means of tipping, loading and off-loading of trucks. The quantity of dust

generated from such loading and off-loading operations will depend on various climatic parameters, such as wind speed and

precipitation, in addition to non-climatic parameters such as the nature (moisture content) and volume of the material handled.

Fine particulates are most readily disaggregated and released to the atmosphere during the material transfer process, as a

result of exposure to strong winds. Increases in the moisture content of the material being transferred would decrease the



potential for dust emission, since moisture promotes the aggregation of fines to the surfaces of larger particles. Section 13.24

of the US EPA’s well-known emission factors handbook AP-42 (US EPA 2007) provides emission factors for these activities.

The relevant equation is provided in Table 4-13.

Emissions from bulldozing and compaction assumed on trash compactor and one front-end loader to be working

simultaneously at the active working face (during the working hours of the site). The equation used to determine the TSP

emission factor (in kg/hr) was taken from Table 11.9-2 in the US-EPA AP42 (Western Surface Coal Mining - for bulldozers on

material other than coal). The scaling factors for PM10 and PM2.5 were given as 0.75 and 0.105 respectively. The moisture

contents for landfill cover and waste (12% and 20% respectively) were taken from the US-EPA recommended moisture content

for municipal landfills.

Dust emissions due to wind erosion of exposed areas occur when the threshold wind speed is exceeded (Cowherd et al.,

1988; EPA, 1995). The threshold wind speed is dependent on the erosion potential of the exposed surface, which is expressed

in terms of the availability of erodible material per unit area (mass/area). Any factor that binds the erodible material, or

otherwise reduces the availability of erodible material on the surface, decreases the erosion potential of the fugitive source.

High moisture content, whether due to precipitation or deliberate wetting, promotes the aggregation and cementation of fines

to the surfaces of larger particles, thus decreasing the potential for dust emissions. Surface compaction and ground cover

similarly reduces the potential for dust generation. The default emission factor from the US-EPA AP42 (Western Surface Coal

Mining) (Table 11.9-4) was used to estimate particulate emissions due to wind erosion. The emission factor for TSP is given

as 0.85 tons per hectare per annum. The US-EPA recommends that in this situation, the PM10 fraction of the TSP is about

50% (EPA, 1992). An assumption was made that 30% of the active workface would be available to wind erosion per year.

Vehicle-entrained dust emissions have been found to account for a great portion of fugitive dust emissions from industrial

operations. The US-EPA paved, and unpaved road particle size-specific emission equations are provided in Table 4-13. The

particle size multiplier in the equation (k) varies with aerodynamic particle size range and is given as 1.5 for PM10, 0.15 for

PM2.5 and 4.9 for TSP. The mean vehicle weight for the delivery of waste was calculated as 13.06 tonne (Enviroserv provided

average empty weight of 10.83 tonne and a full weight of 15.28 tonne). The silt content value of the road surface material was

assumed to be 6.4%. A maximum control efficiency of 75% dust suppression was applied to emissions due to vehicle

entrainment of unpaved roadway dust. It should be noted however, that whilst 75% is achievable through water application,

efficiencies closer to 50% is more commonly achieved in practice. The current entrance to the CLS is from the southern

boundary, whereas the support services and infrastructure associated with the proposed expansion has not been finalised.

The assumption made for the assessment is that the site entrance, access controls and weigh bridge would be via Marsala

Road, off the M38. A summary of the particulate emissions are given in Table 4-14, Table 4-15 and Table 4-16 for the baseline,

Phase 1A and Phase 1 B, respectively. The tables show that the particulate emissions from unpaved and paved roads are

clearly the main contributors.

4.8 Greenhouse Gas Emissions

Landfills emit GHG which are associated with global warming and climate change. The risk to the global atmosphere from

LFG emissions is determined by estimating the detrimental effect using the Global Warming Potential (GWP), which compares

the effect of each compound to CO2, for a specified timeframe, i.e. CH4 been assessed to have 21 to 28 times the effect of

CO2 over a 100-year period. The annual GWP is displayed in Figure 4-7. The figure clearly illustrates the positive effect upon

the installation of the flares. It also illustrates that the flares could potentially operate for a period longer than the anticipated

7 years following final closure in 2028. Table 4-17 is a summary of the GHG inventory and GWP reductions for three scenarios.



Figure 4-7: Calculated GWP for the CLS and proposed expansion



Table 4-13: Emission rate equations used to quantify fugitive dust emissions

Activity Emission Equation Source Information assumed/provided

Materials handling

𝐸 = 0.0016(𝑈

2.2⁄ )1.3

(𝑀2⁄ )

1.4

Where,

E = Emission factor (kg dust / t transferred)

U = Mean wind speed (m/s)

M = Material moisture content (%)

The PM2.5, PM10 and TSP fraction of the emission factor is 5.3%, 35% and 74% respectively.

An average wind speed of 4.2 m/s was used based on data for ORT Airport for the period 2016 – 2018.

US-EPA AP42 Section 13.2.4

The moisture content of materials are as follows:

Waste: 35% (provided by client)

Throughputs were calculated from the number of vehicle trips per day and the capacity of the vehicles.

Hours of operation were given as:

7:00 – 17:00 (week days)

7:00 – 15:00 (Saturdays)

7:00 – 12:00 (Sundays)

Vehicle entrainment on unpaved surfaces 𝐸 = 𝑘 (

𝑠

12)

a

(𝑊

3)

b

∙ 281.9

Where,

E = particulate emission factor in grams per vehicle km travelled (g/VKT)

k = basic emission factor for particle size range and units of interest

s = road surface silt content (%)

W = average weight (tonnes) of the vehicles travelling the road = 10.55 t waste).

The particle size multiplier (k) is given as 0.15 for PM2.5 and 1.5 for PM10, and as 4.9 for TSP

The empirical constant (a) is given as 0.9 for PM2.5 and PM10, and 4.9 for TSP

The empirical constant (b) is given as 0.45 for PM2.5, PM10 and TSP

US-EPA AP42 Section 13.2.2

In the absence of site-specific silt data, use was made of US EPA default mean silt content of 6.4% (for industrial unpaved roads at municipal solid waste landfill).

Hours of operation as shown above.

The capacity of the haul trucks to be used was given as 4.45 tonnes.

The number of trips per day were given as follows:

260 – 400 (week days)

240 – 285 (Saturdays)

115 – 144 (Sundays)

The layout of the roads for the baseline was provided. The layouts of roads for Phase 1A and 1B were assumed. The width of the roads was assumed as 10 m.



Activity Emission Equation Source Information assumed/provided

Vehicle entrainment on paved surfaces

𝐸 = 𝑘(𝑠𝐿)0.91(𝑊)1.02

Where,

E = particulate emission factor in grams per vehicle km travelled (g/VKT)

k = basic emission factor for particle size range and units of interest

s = road surface silt loading (g/m²)

W = average weight (tonnes) of (all) the vehicles travelling the road

The particle size multiplier (k) is given as 0.15 for PM2.5, 0.62 for PM10, and 3.23 for TSP

US EPA AP42 Section 13.2.1

In the absence of site-specific silt data, use was made of US EPA default mean silt loading of 7.4 g/m² (for paved roads at municipal solid waste landfill).

Average weight of vehicles travelling on the paved road was assumed to be the same as the waste tankers, viz. 10.55 t.

The layout of the paved roads was assumed from Google Earth images (access road to the current landfill and access roads from Anker street for Phase 1A and 1B).

Bulldozing 𝐸 = 𝑘 ∙ (𝑠)a/(𝑀)b

Where,

E = Emission factor (kg dust / hr / vehicle)

s = Material silt content (%)

M = Material moisture content (%)

The particle size multiplier (k) is given as 2.6 for TSP, and 0.34 for PM10

The empirical constant (a) is given as 1.2 for TSP, and 1.5 for PM10

The empirical constant (b) is given as 1.3 for TSP, and 1.4 for PM10

Fraction of PM2.5 assumed to be 10% of PM10

NPI Section: Mining

The silt contents recommended by the US-EPA for landfill cover and miscellaneous fill materials (16% and 12% respectively) were used as input into the bulldozer equation.

The moisture contents for landfill cover and waste (12% and 20% respectively) were taken from the US-EPA recommended moisture content for municipal landfills and from previous landfill studies.

Compaction was assumed to take place over 7 hours on a week day, 5 hours on a Saturday and 3 hours on a Sunday.

Wind Erosion 𝐸 = 0.85 𝑡𝑜𝑛𝑠/ℎ𝑎/𝑎𝑛𝑛𝑢𝑚

Where,

E = particulate emission factor for TSP

The US-EPA recommends that in this situation, the PM10 fraction of the

TSP is about 50% (EPA, 1992). It was assumed that the PM2.5 fraction of

the TSP is about 10%.

US-EPA AP42 Table

11.9-4 Wind erosion was modelled for the active workface for each scenario.

An assumption was made that 30% of the active workface would be

available to wind erosion per year.



Table 4-14: Fugitive particulate emission rates for baseline conditions

Activity Unmitigated Emissions [tonne per annum] Mitigated Emissions [tonne per annum]

PM2.5 PM10 TSP PM2.5 PM10 TSP

Materials handling 0.002 0.01 0.03 0.002 0.01 0.03

Compaction 0.79 5.65 7.53 0.79 5.65 7.53

Wind erosion 0.53 2.63 5.25 0.53 2.63 5.25

Unpaved roads 5.27 51.31 190.07 1.28 12.83 47.52

Paved roads 1.81 8.23 42.86 0.50 2.06 10.72

Total 8.4 67.8 245.7 3.1 23.2 71.0

Table 4-15: Fugitive particulate emission rates for Phase 1A




Compaction 0.79 5.65 7.53 0.79 5.65 7.53

Wind erosion 0.11 0.57 1.13 0.11 0.57 1.13

Unpaved roads 1.96 9.03 33.47 0.49 2.26 8.37

Paved roads 3.79 16.40 85.45 0.99 4.10 21.36

Total 6.8 31.7 127.6 2.4 12.6 38.4



Table 4-16: Fugitive particulate emission rates for Phase 1B




Compaction 0.79 5.65 7.53 0.79 5.65 7.53

Wind erosion 0.11 0.53 1.06 0.11 0.53 1.06

Unpaved roads 3.62 36.20 134.08 0.90 9.05 33.52

Paved roads 3.97 16.40 85.45 0.99 4.10 21.36

Total 8.5 58.8 228.1 2.7 19.2 62.5



Table 4-17: Calculated GHG inventory for the Baseline, Phase 1A (+Cell 7) and Phase 1B

Species

Total for 1997 to 2019 Total for 2019 to 2024 Total for 2024 to 2029

Gas Release [t]

Global Warming Potential [t CO2]

Gas Release [t]


Gas Release [t]


CH4 Surface Emissions 44945.5 943711 9607 201700 56725.5 1191111

Flare Emissions 1003.9 21066 493.1 10350 1609.9 33806

CO2 Surface Emissions 134377.4 134377.4 28750 28750 169607.4 169607.4

Flare Emissions 515700 515700 253200 253200 827300 827300

Chloroform (trichloromethane) 0.04861821 1.458457 0.009 0.2701 0.06137821 1.841657

Dichloromethane (methylene chloride)

0.4738844 4.263896 0.1415 1.273 0.6390844 5.749896

Hydrofluorocarbons (HFCs) (Total) 0 0 0 0 0 0

Perfluorocarbons (PFCs) (Total) 0 0 0 0 0 0

Total CH4 45941.5 965011 10103 212100 58331.5 1225211

Total CO2 649787.4 649787.4 281800 281800 996487.4 996487.4

Trace Gases 0.722774 9.67946 0.1751 2.224 0.932774 12.10946

Total 695939.9 1614799 291900 494000 1055139.9 2220799

CH4 Burned [t] 100390 49310 160990

GWP Reduction [t CO2] 1829100 900000 2937100



5 DISPERSION SIMULATIONS

Dispersion modelling was undertaken to determine highest hourly, highest daily and annual average ground level

concentrations for each pollutant, with 3-minute average concentrations being calculated for H2S using the extrapolation

method discussed in Section 1.3.5. These averaging periods were selected to facilitate the comparison of predicted pollutant

concentrations with relevant air quality guidelines, odour thresholds, and health effect screening levels.

Gaussian-plume models are best used for near-field applications where the steady-state meteorology assumption is most

likely to apply. One of the most widely used Gaussian plume model is the US EPA AERMOD model, which was also used in

this study. AERMOD is a model developed with the support of the American Meteorological Society/Environmental Protection

Agency Regulatory Model Improvement Committee (AERMIC), whose objective has been to include state-of the-art science

in regulatory models (Hanna et al 1999). AERMOD is a dispersion modelling system with three components, namely:

AERMOD (AERMIC Dispersion Model), AERMAP (AERMOD terrain pre-processor), and AERMET (AERMOD meteorological

pre-processor).

AERMOD is an advanced new-generation model. It is designed to predict pollution concentrations from continuous point, flare,

area, line, and volume sources. AERMOD offers new and potentially improved algorithms for plume rise and buoyancy, and

the computation of vertical profiles of wind, turbulence and temperature however retains the single straight-line trajectory

limitation. AERMET is a meteorological pre-processor for AERMOD. Input data can come from hourly cloud cover

observations, surface meteorological observations and twice-a-day upper air soundings. Output includes surface

meteorological observations and parameters and vertical profiles of several atmospheric parameters. AERMAP is a terrain

pre-processor designed to simplify and standardise the input of terrain data for AERMOD. Input data includes receptor terrain

elevation data. The terrain data may be in the form of digital terrain data. The output includes, for each receptor, location and

height scale, which are elevations used for the computation of air flow around hills. A disadvantage of the model is that spatial

varying wind fields, due to topography or other factors cannot be included. Input data types required for the AERMOD model

include source data, meteorological data (pre-processed by the AERMET model), terrain data, information on the nature of

the receptor grid and pre-development or background pollutant concentrations or dustfall rates. Version 7.9 of AERMOD and

its pre-processors were used in the study.

All potential air pollutant emissions for the each of the baseline and proposed expansions from the CLS were quantified, as

discussed in the previous section. Most of the air pollutants were already screened out in the previous section using health

risk endpoints (EQS/EAL) which forms part of the GasSim Tier 1 screening methodology. According to the GasSim screening,

only arsenic, ethylene dichloride and H2S were identified for further analyses. However, based on the Geozone Environmental

passive diffusive sampling campaigns conducted at the CLS and comparisons with relevant health risk endpoints, it was

further decided to include limonene, NH3, acetaldehyde, benzene and formaldehyde in the simulations. In addition to these

gaseous pollutants, airborne particulates (PM2.5 and PM10) and fallout dust from fugitive landfill sources, as well as exhaust

gas from the flares were quantified and included further analysis using dispersion modelling. Flare emissions included criteria

pollutants such as SO2, NO2, CO and PM10/PM2.5.

The pollutants specific to health risks include arsenic, ethylene dichloride, PM10/PM2.5, NH3, H2S, SO2, NO2, benzene and

formaldehyde. Of these pollutants, arsenic, ethylene dichloride, benzene and formaldehyde are potential carcinogens,

whereas, SO2, NO2, CO, NH3, H2S and PM2.5/PM10 were analysed as potential irritants. Nuisance impacts include odour

and fallout dust. The key pollutants for the analysis of nuisance include H2S and limonene as odorants, and fugitive dust

fallout for its soiling potential.



Since several the key-pollutants may still be below their respective health criteria, a further screening was done based on the

maximum concentrations calculated with the AERMOD simulations. The three screening criteria used for this purpose

included:

(a) comparison with the NAAQS limit values (Table 2-1);

(b) calculating the incremental cancer risks using the unit risk factors contained in Table 2-4;

(c) calculating hazard indices using the reference concentrations from Table 2-3;

(d) estimating odour nuisance through comparisons with the odour thresholds established in Table 2-6; and

(e) estimating the significance fallout dust through comparisons with the NDCR provided in Table 2-2.

The simulations of the various emissions were completed for the three scenarios: Baseline, Phase 1A (& Cell7) and Phase

1B. Furthermore, the simulations included all sources of gaseous emissions, i.e. landfill operations, leachate dams and flares

as well as particulate emissions. The latter air emissions were mainly as a result of activities that generate fugitive dust. The

PM10PM2.5 emissions from the flares were low and contributed very little to the overall particulate emissions (Table 4-11).

A comparison of the relevant pollutants with the limit values contained in the NAAQS is summarised in Table 5-1. None of

the criteria gases were predicted to exceed their respective limit values; only PM2.5 and PM10 were. Furthermore, the

mitigated PM2.5 concentrations were all below the limit value of 40 µg/m³ (daily) and 20 µg/m³ (annual). However, the

unmitigated PM2.5 exceeded both limit values. Given that these concentrations were predicted at the boundary of the landfill,

exceedances of the limit values were predicted to mainly occur in the immediate vicinity of the CLS. Since the PM10

concentrations were predicted to exceed the limit values more significantly for all three scenarios, it was selected to serve as

a key-pollutant to establish the zone of impact based on health risks.

Table 5-1: Comparison with NAAQS

Pollutant NAAQS Limit Value

[µg/m³]

Factor of Limit Value


CO 30000 (hourly) <0.01 <0.01 <0.01

Benzene 5 (annual) 0.007 0.16 0..37

SO2

350 (hourly) <0.01 <0.01 <0.01

125 (daily) <0.01 <0.01 <0.01

50 (annual) <0.01 <0.01 <0.01

NO2 200 (hourly) <0.01 <0.01 <0.01

40 (annual) <0.01 <0.01 <0.01

PM2.5 (unmit) 40 (daily) 3.4 1.6 2.2

20 (annual) 2.5 1.2 1.4

PM2.5 (mit) 40 (daily) 0.9 0.5 0.7

20 (annual) 0.6 0.4 0.5

PM10 (unmit) 75 (daily) 11.6 8.1 11.5

40 (annual) 6.5 5.8 6.6

PM10 (mit) 75 (daily) 3.0 2.3 3.4

40 (annual) 1.7 1.8 2.2

The calculated incremental cancer risks for the screened carcinogens are summarised in Table 5-2. The incremental cancer

risk for benzene and vinyl chloride were calculated to be the most significant and very similar; with the maximum predicted

during Phase 1B for both compounds, viz. 13.9 per million and 12.7 per million for benzene and vinyl chloride, respectively.



Based on these results, benzene was selected as a key-pollutant, in addition to PM10 to establish the zone of impact based

on health risks.

Table 5-2: Incremental cancer risk estimates

Pollutant Unit Risk Factor

1/[µg/m³]

Cancer Risk per Million


Acetaldehyde 9.0E-7 0.002 0.03 0.06

Arsenic 1.5E-3 0.09 4.3 6.2

Benzene 7.5E-6 0.26 6.1 13.9

Ethylene Dichloride 2.8E-6 0.07 1.87 3.7

Formaldehyde 1.3E-5 0.01 0.12 0.3

Vinyl Chloride 1.0E-6 0.3 7.1 12.7

Non-carcinogenic impacts were evaluated based on the respective RfCs (Table 2-3) for the compounds of interest. As shown

in Table 5-3, only H2S flagged (i.e. maximum concentration calculated to be above the acute RCF of 97.57 µg/m³). H2S was

therefore also included as a key pollutant to determine the health risk impact. This pollutant as well as limonene also carries

a potential odour nuisance value. The predicted maximum hourly average concentration for limonene were 0.75 µg/m³

(Baseline), 14.97 µg/m³ (Phase 1A & Cell7) and 31.03 µg/m³ (Phase 1B), respectively. With a threshold odour concentration

of 58 µg/m³ (Table 2-6) for limonene, it was predicted that this odour would be detected marginally at the CLS boundary,

whereas a comparison of the predicted H2S concentrations shows a significant odour nuisance, i.e. with an odour threshold

of 7 µg/m³ (Table 2-6). H2S was therefore selected to determine the odour impact zone. The predicted nuisance impact zone

was determined using both the odour impact and fallout dust.

Table 5-3: Hazard index

Pollutant Acute RfC

[µg/m³]

Hazard Index


Acetaldehyde 470 0.00003 0.0004 0.0006

Benzene 28.72 0.01 0.14 0.30

Ethylene Dichloride 70 0.0002 0.003 0.059

Formaldehyde 49.13 0.0001 0.001 0.002

Vinyl Chloride 1.28 0.05 0.54 0.97

NH3 100 0.01 0.18 0.34

H2S 97.57 1.32 2.30 2.63

Having screened out the key-pollutants which should be used to estimate the air quality impacts from the CFS and the

proposed expansion phases, it remains to provide the spatial aspects of the predictions. These are provided as contours of

different impacts superimposed on a background map of the study area.

Results are presented in two groups, representing background to establish a health impact zone and a nuisance impact zone,

as follows:

• Health impact zone:

o Health risks represented by the exceedance of the daily average PM10 NAAQS (i.e. allowed four

exceedances of the daily average concentration limit value of 75 µg/m³)

o Incremental cancer risk applying the acceptable risk criteria listed in Table 2-5 and using the predicted

annual average benzene concentrations to represent 24-hour exposures over a 70-year lifetime. This is



a conservative assumption. According to the table, an incremental risk of 1-in-a-million and lower is Very

Low and 1-in-a-hundred thousand to 1-in-ten thousand, a Low risk.

• Nuisance impact zone:

o Simulated areas of exceedance of odour threshold concentrations associated with H2S. Both hourly

average predictions and 3-munte extrapolations were used in the estimation of this zone. The hourly

average was used to provide the zone within which more frequent exceedances of the odour threshold is

expected and the 3-minute peaks was used to indicate where short periods of exceedences may occur

o Simulated areas of exceedance of dust fallout levels as specified in the NDCR

The predicted zones have been provided for the Baseline, Phase 1A (including Cell7) and Phase 1B. The basis for determining

buffer zones, given predicted odour and health impact zones, has been a point of contention. However, it is proposed that

the above two definitions be considered to establish a Health Buffer Zone and a Management Zone, respectively. These zones

are defined as follows:

• Management zone - indicative of the odour and dust impact areas, with reductions in the extent of such impact areas

requiring the implementation of emission reduction measures at the landfill site; and,

• Health buffer zone - delineated exclusively based on health impact and of crucial importance in terms of determining

land use potentials.

From experience, depending on the type of landfill, particulate fallout (nuisance dust) and odorous emissions often determine

a “management” buffer zone, i.e. the impact zone that can be mitigated through water sprays, covering of waste, etc.

Furthermore, this buffer zone can extend a few hundred metres (but typically less than 1000m). This buffer zone can be used

for development, but would normally not include housing developments, but may include farming and industry. Other air

emissions emanating from the landfill, including PM10 and carcinogens such as benzene, chlorinated hydrocarbons,

formaldehyde, etc. normally define the “health” buffer zone where the land is more strictly controlled and may be considered

unsuitable for most developments, including industrial.

The simulation results for the various phases are provided in Appendix D with summaries provided in this section as follows:

• Health impact zone:

o Figure 5-1, the exceedance of the daily average PM10 NAAQS, showing both unmitigated and mitigated

scenarios.

o Figure 5-2, the incremental cancer risk based on the predicted annual average benzene concentrations

• Nuisance impact zone:

o Figure 5-3 and Figure 5-4 depicting 2 odour units (OU) based on the predicted hourly average and

3-minute peak H2S concentrations, respectively

o Figure 5-5, the area predicted to exceed the dust fallout rate specified for residential areas



Figure 5-1: Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4 daily

exceedances per calendar year)

As shown in Figure 5-1 for the Baseline scenario, when mitigated to reduce particulate air emissions by 75%, the impact

expressed as PM10 daily average concertation exceedances is limited to four exceedances just offsite of the CLS, i.e. by

about 50m to the east and 30m to the south of the landfill boundary. With no mitigation, the same line of exceedance would

extend to about 150m east and 100m south. The predicted isopleth depicting this NAAQS with no mitigation, is marginally

offsite for Phase 1A, and about 20m (east) and 15 m (west) of the extended portion of the CLS for Phase 1B. With 75%

mitigation, the NAAQS is predicted not to be exceeded.

As a conservative approach, the health impact zone may be expressed by the combined unmitigated isopleth for the three

scenarios. However, since the Baseline condition would terminate once Cell 7 is operational, this section of the impact zone

would only be temporary. Furthermore, given that regular watering of the access roads would be taking place, as per current

practice, the predicted unmitigated impact zones would most likely not be realistic. A more realistic prediction would more

likely be closer to the mitigated predictions. Therefore, it is predicted that the NAAQS may be exceeded only immediately

beyond the eastern boundary of the expansion, i.e. east of Phase 1B Cell 2.



Figure 5-2: The predicted incremental cancer risk based on exposure to benzene emissions from the CLS (an

incremental cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see Table 2-5)

The predicted annual average benzene concentration is predicted to be below 5 µg/m³ for all three scenarios, and therefore

meets the NAAQS. The Baseline incremental cancer risk based on benzene is predicted to be trivial (1-in-10 million chance),

as shown in Figure 5-2. Whilst still very low, the incremental cancer risks predicted for Phase 1A (& Cell 7) and Phase 1B are

slightly above 1-in-a-million, respectively. As indicated in the figure, the 1-in-a-million incremental risk isopleth extends about

20m (east) and 10m (west) of the CLS boundary for Phase 1A (& Cell 7). The same isopleth extends a little further east,

approximately 100m (east), and about 50m (north) for Phase 1B.

Given that a risk smaller than 1-in-a-million is regarded as trivial, this isopleth may be considered for the definition of

demarcating the health impact zone. The land currently included by this isopleth forms part of the aggregate works in the east

and undeveloped land to the north. However, as noted in Table 5-2, the maximum incremental cancer risk is about 6-in-a-



million and 1-in-a hundred thousand for Phase 1A (& Cell 7) and Phase 1B, respectively. These maximums were predicted to

occur inside the CLS. The predicted impact in the nearby residential areas is insignificant.

Figure 5-3: Potential zone of odour nuisance based the 98th percentile hourly average H2S concentrations

(isopleths represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria Table

2-7)

The odour impact from the CLS is based on the quantification of H2S emissions from the landfill, leachate dams/tanks and the

flares. It was recommended to follow the NSW EPA odour assessment policy, as discussed Section 2.2.3. The NSW EPA

found that it is accepted that existing facilities with an odour performance criterion of 7OU (i.e. approximately 7-fold the odour

threshold concentration) is likely to represent the level below which “offensive” odours should not occur for an individual with

a “standard sensitivity” to odours. However, the NSW EPA also recognises that this criterion does not adequately address

the nuisance value with denser populations. Accordingly, they recommend a sliding scale, starting with 7OU (sparsely

populated) down to 2OU for urban areas, where more than 2000 people could be affected by the odour (Table 2-7).



Furthermore, the NSW EPA applies the odour recognition concentration to the short-term, 1- to 3-minute averaged

concentrations. The AERMOD model is restricted to providing hourly average concentrations (or longer), and shorter

averaging times need to be extrapolated (Section 1.3.5). Hourly and 3-minute average predictions are provided in Figure 5-3

and Figure 5-4, respectively.

Figure 5-4: Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations (isopleths

represent the equivalent of 2OU – assessment follows New South Wales odour performance criteria Table 2-7)

Whereas the hourly average 2OU is predicted to extend by about 500m towards the northeast of the CLS expansion, the

3-minute average 2OU is predicted to include a large portion of Commercia to the northeast (a distance of about 950m from

the CLS expansion). The impact zones towards the east and west are less significant, i.e. approximately 300m for the 3-minute

average prediction. The odour impact to the south is confined to the CLS.

Unlike PM2.5 and PM10, that remains airborne over relatively large distances, larger particles (typically larger than 75 micron),

fall out relatively close to the source. The travelling distances also depend on wind strength, with stronger winds offering more

carrying capacity and hence deposits particles further downwind than during calm low wind conditions. The predicted



deposition patterns for the three simulation scenarios are provided in Figure 5-5. The isopleth represents the maximum

tolerable fallout rate for residential areas, namely 600 mg/m²-day (NDCR). Both unmitigated and mitigated conditions have

been provided.

Figure 5-5: Predicted highest monthly average fallout dust (residential areas should not exceed more than 600

mg/m²-day)

The unmitigated fallout zone based on this limit for the Baseline scenario depicts a zone enclosed by a distance of about 200m

south and 100m to the east, as shown in the figure. The mitigated fallout zone stretches about 50m to the east and south.

The predicted fallout zones for Phases 1A and 1B are limited to about 30m east and west of the CLS expansion. With

mitigation, the fallout is predicted to be within the landfill boundaries.



6 CONCLUSIONS AND RECOMMENDATIONS

Many trace gas emissions are possible from the CLS. These gases were screened in two steps. The first step was done

using the GasSim Tier 1 screening methodology using health risk endpoints (EQS/EAL). According to the GasSim screening,

only arsenic, ethylene dichloride and H2S were identified for inclusion in further analyses. However, based on the Geozone

Environmental passive diffusive sampling campaigns conducted at the CLS and comparisons with relevant health risk

endpoints, it was further decided to also include limonene, NH3, acetaldehyde, benzene and formaldehyde. Since the flares

produce insignificant particulate matter (PM2.5 and PM10), only emissions from fugitive landfill sources were assumed for

further analyses. To be conservative, the emission rates corresponding to the end of each scenario (Baseline, Phase 1A &

Cell7 and Phase 1B) were used in the atmospheric dispersion simulations. The US EPA AERMOD model was used to

simulate the atmospheric dispersion of the selected pollutants. Three years of hourly average meteorological data which were

measured at OR Tambo International Airport by the SAWS, were used in these simulations. This weather station is

approximately 13km from the CLS and since the terrain including both the CLS and OR Tambo is relatively flat, these

meteorological observations are considered adequate for use in the dispersion model representing the CLS. In the second

screening of the selected pollutants, the predicted maximum ground level air concentration was used to determine the health

and nuisance risks each compound. Key-pollutants were selected with each representing carcinogenic and non-carcinogenic

(irritational) impacts, as well as nuisance impacts (odour and dustfall). This screening resulted in the selection of benzene for

carcinogenic impacts, PM10 for irritational impacts, H2S for odour impacts and total suspended particulates for fallout dust.

The odour impact from the CLS was based on the NSW EPA odour assessment policy which accepts that existing facilities

with an odour performance criterion of 7OU (i.e. approximately 7-fold the odour threshold concentration) is likely to represent

the level below which “offensive” odours should not occur for an individual with a “standard sensitivity” to odours. However,

the NSW EPA also recognises that this criterion does not adequately address the nuisance value with denser populations.

Accordingly, they recommend a sliding scale, starting with 7OU (sparsely populated) down to 2OU for urban areas, where

more than 2000 people could be affected by the odour.

The results from the dispersion simulations are summarised in Table 6-1: Assessment of health risk impactsTable 6-1

for the predicted health risks, and Table 6-2 for predicted nuisance impacts, i.e. odour and fallout dust. The health risk results

are also summarised in Figure 6-1. The figure combines the zones predicted by the incremental cancer risk of 1-in-a-million

and PM10 exceedances of the. For the Base Case, only the unmitigated PM10 impact is shown since the mitigated impacts

are confined to the CLS. The zone of impact for Phase 1A and Phase 1B are mainly due to the predicted incremental cancer

risk. The cancer risk is based on the 95th percentile benzene emission rates at the end of each of the two expansion phases

(Phase 1A and Phase 1B), and therefore reflect an upper, worst case estimate. A more realistic emission rate would have

been the 50th percentile, which for the Base Case (1997-2019) is a factor of 2.2 lower, and for Phase 1A+Cell 7 (2019-2024)

and Phase 1B (2019-2028), a both factor of 5.5 lower. Given this level of conservatism, it is more likely that the 1-in-a-million

isopleth is within the proposed CLS expansion.

Given that regular watering of the access roads would be taking place, as per current practice, the predicted unmitigated

impact zones in Figure 6-1 would most likely not be realistic. A more realistic prediction would more likely be closer to the

mitigated predictions. Therefore, it is predicted that the NAAQS may be exceeded only immediately beyond the eastern

boundary of the expansion, i.e. east of Phase 1B Cell 2.



Figure 6-1: Prediction results for combined health risks, including the PM10 (unmitigated and mitigated) and

benzene incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth represents the 1-

in-a-million incremental cancer risk)



Table 6-1: Assessment of health risk impacts


The exceedance of the daily average PM10 NAAQS,

showing both unmitigated and 75% mitigated scenarios

Baseline Mitigated – PM10 daily average concertation exceedances is limited to four exceedances just offsite of the CLS,

i.e. by about 50m to the east and 30m to the south of the landfill boundary

No mitigation, PM10 daily average concentration exceedances extends to about 150m east and 100m south. The

predicted isopleth depicting this NAAQS with no mitigation is marginally offsite for Phase 1A, and about 20m (east)

and 15 m (west) of the extended portion of the CLS for Phase 1B. With 75% mitigation, the NAAQS is predicted

not to be exceeded

Phase 1A Mitigated – no exceedances of the PM10 daily average concertation beyond the landfill boundary

No mitigation – PM10 daily average concentration exceedances marginally offsite towards the east

Phase 1B Mitigated – no exceedances of the PM10 daily average concertation beyond the landfill boundary

No mitigation – PM10 daily average concertation exceedances extends about 20m (east) and 15 m (west) of the

extended portion of the CLS

The incremental cancer risk based on the predicted annual

average benzene concentrations

Baseline The predicted annual average benzene concentration is predicted to be below the NAAQS limit value of 5 µg/m³

The incremental cancer risk is predicted to be trivial (1-in-10 million increased risk)

Phase 1A With gas collection and flaring, the predicted annual average benzene concentration is predicted to be below the


The 1-in-a-million incremental risk (generally accepted as a Low Risk) isopleth extends about 20m (east) and 10m

(west) of the CLS boundary for Phase 1A (& Cell 7)

Phase 1B With gas collection and flaring, the predicted annual average benzene concentration is predicted to be below the


The 1-in-a-million incremental risk isopleth extends about 100m (east), and about 50m (north) for the CLS boundary

for Phase 1B



Table 6-2: Assessment of nuisance impacts


Odour Impact

The NSW EPA applies the odour recognition concentration

to the short-term concentrations (1- to 3-minute averages).

The AERMOD model is restricted to providing hourly

average concentrations (or longer), and shorter averaging

times were therefore extrapolated

Baseline The hourly average 2OU is predicted to marginally extend by about 20m towards the east of the CLS leachate dam

The 3-minute average 2OU is predicted to extend by about 300m towards the east of the CLS leachate dam

Phase 1A The hourly average 2OU is predicted to extend by about 400m towards the east of the CLS leachate dam


the CLS expansion)



Phase 1B The hourly average 2OU is predicted to extend by about 500m towards the east of the CLS leachate dam

The 3-minute average 2OU is predicted to include a large portion of Commercia to the northeast (a distance of

about 950m from the CLS expansion)



Fallout dust Baseline The unmitigated fallout zone is enclosed by a distance of about 200m south and 100m to the east

The mitigated fallout zone stretches about 50m to the east and south

Phase 1A With mitigation, the fallout is predicted to be within the landfill boundaries


expansion

Phase 1B With mitigation, the fallout is predicted to be within the landfill boundaries


expansion



6.1 Conclusions

The significance of the health risk is based on the following classifications as defined in the SLR Significance Rating Criteria

provide in Appendix C:

Phase 1A & Cell 7 – Health Risk

Unmitigated – No dust suppression Mitigated – Dust suppression





H:


Extent of Impacts L:

Whole site

L:

Whole site


Probability H:

Probable

M:

Possible/frequent


Phase 1B Cell 1 and Cell 2 – Health Risk

Unmitigated – No dust suppression Mitigated– Dust suppression





H:


Extent of Impacts M:

Beyond the site boundary, affecting immediate

neighbours

L:

Whole site


Probability H:

Probable

M:

Possible/Frequent


The predicted nuisance impact zone is mainly determined by the potential odour impacts from the CLS. Whereas the worse-

case predictions for the Base Case was predicted to impact mainly over the industrial activities to the east of the CLS, a

significant portion of Commercia, to the northeast of the CLS could experience odours from facility during Phases 1A and 1B.



The worse-case prediction is based on the highest 95th percentile emission rates calculated in GasSim for each phase.

Furthermore, it represents any short-term exposure of a few minutes in duration. With the hourly average odour estimates,

which provide the odour levels for durations from 15 minutes to one hour, the impacts were predicted to be limited to the

aggregate works, east and north-east of the CLS. The significance of the odour risk is as follows:

Phase 1A & Cell 7 – Odour Risk






H:




H:



Probability H:

Probable

M:

Possible/Frequent


Phase 1B Cell 1 and Cell 2 – Odour Risk






H:




H:



Probability H:

Probable

M:

Possible/Frequent


6.2 Recommendations



Background concentrations of airborne particulates are already high and the CLS operator should therefore control on-site

fugitive dust emissions by effective management and mitigation. At least a 70% dust control efficiency is required on unpaved

roads to ensure dustfall rates are reduced to the levels predicted.

It is recommended to continue gas collection and flaring, as with the current operation of the CLS. Flares should be maintained

in accordance with the manufacturer’s recommendations. Full records should be available for inspection.

Management measures should be put in place to ensure

• that upsets in the landfill gas collection system are avoided, which would result in the flares not operating effectively;

• that upsets such as the emission of concentrated, un-combusted organic compounds during flare downtime do not

occur. If the flare is not operational no gas extraction and venting through the stack should be permitted.

• minimal downtime of flares since the odour impact could otherwise be significant

Measures should be put in place to reduce the potential for subsurface gas liberation during waste disturbance and gas

extraction network installation activities.



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8 APPENDIX A: GASSIM MODEL INPUT PARAMETERS



9 APPENDIX B: SLR SIGNIFICANCE RATING CRITERIA



10 APPENDIX C: CURRICULUM VITAE OF SPECIALIST

Curriculum Vitae: Lucian Burger

Page 1 of 13

CURRICULUM VITAE LUCIAN BURGER

CURRICULUM VITAE

Name of Staff Lucian Burger

Name of Firm Airshed Planning Professionals (Pty) Ltd

Position Director and Principal Consultant

Profession Chemical Engineer/Air Quality and Process Risk Specialist

Date of Birth 24 May 1960

Years with Firm 28 years

Nationalities South African

MEMBERSHIP OF PROFESSIONAL SOCIETIES Registered with the Engineering Council of South Africa (ECSA) as a Professional Engineer

(Registration No. 20170291)

Fellow of the South African Institute of Chemical Engineers (FSAIChE) (Fellow: No. 4533)

Associate Fellow of the Institute of Chemical Engineers (AFIChemE) (Fellow: No. 99963108)

National Association of Clean Air (NACA)

Accredited Inspectorate Authority (AIA) for completion of risk assessments as partial fulfilment

of Major Hazard Installation Regulations (SANAS No. MHI0013 and Department of Labour No.

MHI0005) (2005 - 2008)

SANAS Risk Assessment Specialist Technical Committee (2003 - 2010)

Member of the Technical Committee on Air Quality Standards Setting (2002 - 2003)

SABS Air Quality Standards Specialist Technical Committee (Chairman of Working Group 1)

KEY QUALIFICATIONS Air Pollution Dispersion Modelling (execution and development of models)

Loss of Containment Simulations and Consequence Modelling (Fires, Explosions, Toxic

Clouds - execution and development of models)

Process Failure Rate Analysis

Micrometeorology

Quantitative Risk Assessment

Nuclear Site Safety Report Analysis – Meteorology and Dispersion Modelling

Ambient Air Monitoring

Chemical Engineering

Development of Air Emissions Inventories (Mining and Ore Handling, Metal Recovery,

Chemical Industry, Petrochemical Industry, Power Generation, Pulp and Paper, Waste

Disposal (landfills, incineration, pyrolysis) and Recycling, Transport [motor vehicles, aircraft,

ships])

Air Quality Management Programmes

Formulation of National Strategies

Project Management


Page 2 of 13

RELEVANT EXPERIENCE Policy, Strategic Planning and Air Quality Management:

Co-author of Air Quality Section in Fuggle & Rabie’s Environmental Management in South

Africa (2nd edition [2011] ISBN No. 978-0-7021-8134-4 (2011) and 3rd edition [2018] ISBN No.

9781485126102, Juta). The book sheds light on the legal frameworks in regional and

international environmental law, administrative law and the National Environmental

Management Act (NEMA).

Development of Guidelines For Thermal Treatment of Wastewater Sludge – Development of

the position paper and subsequent guidelines on the air emissions impact from thermal

treatment options of wastewater sludge. The Water Research Commission published the

complete set of guidelines in 2009 [Herselman JE; Burger LW; Moodley P (2009) Guidelines

for the utilisation and disposal of wastewater sludge Volume 5 of 5: Requirements for

thermal sludge management practices and for commercial products containing sludge, ISBN

No: 978-1-77005-711-1].

Site selection for South Africa’s Nuclear Installations. Specialist (climatology, micro-

meteorology and atmospheric dispersion modelling) with the Nuclear Site Safety Team

appointed by Eskom for the period 2007 to 2021.

Dispersion modelling regulations – Group Chairman of the Dispersion Modelling Working

Group for standardizing and setting requirements for the use of dispersion models for

regulatory purposes, in conjunction with the South African Department of Environmental

Affairs. Published in 2014 (National Environmental Management: Air Quality Act, 2004 (Act

No. 39 of 2004) Regulation No. R 533, Government Gazette 37804).

Review and Implementation of the new Air Emission License (National Environmental

Management Air Quality Act) role out programme (2006-2008). This included the

development of the framework, technical workshops with industry and training of local

authorities. The tasks were divided between principal consultants within Airshed Planning

Professionals. Lucian Burger was responsible for the Power Generation and Pulp & Paper

sectors.

List of Activities, Setting of Minimum Emission Standards. Served as technical advisor to the

Department of Environmental Affairs for the development of air pollution emission rates for

all major stationary industrial activities. Original published in 2010 (Government Gazette

33064)

As chairman of Working Group 1, Lucian Burger was involved in the development of the

South African Air Quality Standards Framework (SANS 69) and the Air Quality Standards for

Criteria Pollutants (SANS 1929), in conjunction with the South African Bureau of Standards

(SABS).

Low Smoke Fuels Standards- Served on the Technical Committee on the Low Smoke Fuels

Standards Development Committee administered by the Department of Minerals and

Energy (1998-2003).

Mercury emission limits - The South African Regulations for Mercury Waste Disposal was


Page 3 of 13

drafted in 2001. These regulations were completed together with Infotox (Pty) Ltd,

specialists in toxicology.

Air Quality Management for Development Planning

o Gauteng Pollution Buffer Zones Guideline – Gauteng Department of Agriculture and

Rural Development (GDARD) commissioned the development of buffer zone

guidelines in 2002, which was reviewed in 2006 and 2017, respectively. The

guideline was developed to ensure that pollution buffer areas are created between

the pollution sources and the nearest human settlements. The guideline includes

air, noise, water and land-based pollution, as well as risks associated with nuclear

facilities. Dr Burger provided recommended buffer zones for different industry

categories defined by size and industry type, as well as sewerage treatment works,

landfill sites, mine dumps and slimes dams, and ash dumps.

o Coega Industrial Development Zone (IDZ) - An air pollution management strategy

was developed in 1997 for the Coega IDZ. Air quality guidelines were developed and

a method of determining emissions for potential developers. The objective was to

allow equal opportunity for development without exceeding unacceptable air

pollution levels. Developed an air-shed air quality management model for

application at Coega in 1999. The model was developed in-house so as to assist the

Coega Development Corporation in the proactive allocation of emission limits to

prospective investors in the IDZ. The purpose being to maximise development

opportunities whilst ensuring the maintenance of good air quality in the long-term.

o Saldanha IDZ – Part of an integrated team of specialists appointed by Wesgro that

developed the proposed development and management strategies for the IDZ. Air

quality guidelines were developed and a method of determining emissions for

potential developers. The investigation included the establishment of the current

air emissions and air quality impacts (baseline) with the objective to further

development in the IDZ and to allow equal opportunity for development without

exceeding unacceptable air pollution levels.

Air Quality Baseline Assessments for the Development of Air Quality Management Plans

o National Economic Development and Labour Council (NEDLAC) 'Dirty Fuels Project' -

The project undertaken for NEDLAC comprised the development of emissions

inventories for several major conurbations across South Africa, the prediction of

resultant air pollutant concentrations and the quantification and costing of health

risks due to inhalation exposures. The study enabled the identification and

quantification of various implementation plans to reduce air pollution on a

nationwide scale, whilst focussing on energy generated air pollution sources. The

project included a detailed cost-benefit analysis. Project was completed in 2004.

o Vaal Triangle Airshed Priority Area Air Quality Management Plan– Served as

technical advisor to the Department of Environmental Affairs for the development

of South Africa’s first Air Pollution Priority Area Air Quality Management Plan. This

included the establishment of a comprehensive air pollution emissions inventory,


Page 4 of 13

atmospheric dispersion modelling, focusing on impact area “hotspots” and

quantifying emission reduction strategies. The management plan was published in

the Government Regulation Gazette No. 32263 on 28 May 2009, Viol. 57 No. 9090

(Part1 and 2)

o Cape Town - An air quality situation assessment was undertaken on behalf of the

City of Cape Town in 2002 in support of their plans for the development of an air

quality management plan for the City.

o Johannesburg - An air quality baseline assessment was undertaken and an air quality

management plan compiled for Johannesburg on behalf of the City. The project was

completed during September 2003.

o Gauteng - An air quality baseline assessment was completed for Gauteng in 1999 to

inform their proposed air quality management plan. This project was funded by

Danish International Development Agency (DANIDA).

o Ekurhuleni – An air quality baseline study and an Air Quality Management Plan has

been developed for the Ekurhuleni Metropolitan Municipality. This work was

completed in 2005.

o UMhlathuze – An air quality situation analysis has being undertaken for the

uMhlathuze District Municipality and guidance given in terms of the air quality

implication of the municipality’s spatial development framework. Work is was

completed in 2005.

o Tswane – An air quality baseline study was completed for the Tswane Metropolitan

Municipality (2005).

Landfill Waste Disposal

Health Impact Assessments:

o Proposed Chloorkop Class1 Landfill Site (Kempton Park) [Waste-Tech] 1993

o Margolis Landfill Site (Germiston) [Waste-Tech] 1994

o Umlazi H:H Landfill Site (Isipingo, KZN, RSA) [Waste-Tech] 1996

o Bissasar Road Landfill Site (Durban) [Durban Metropolitan Council] 1996

o Vissershok CoCT Waste Disposal Site and Evaporating Ponds) [City of Cape Town] 1996

o Aloes Landfill Site (Port Elizabeth) 1996 and 2009

o Sasol 2 & 3 Black Products Disposal Site (Secunda) [Sasol] 1998

o Holfontein H:H Landfill (Pretoria) [Enviroserv] 1998

o Goudkoppies GLB Landfill (Johannesburg) 1998

o Rosslyn H:H Landfill (Pretoria) [Enviroserv] 1998 and 1999

o Proposed Lekoa Vaal Regional H:H Waste Disposal Facility (Vereeniging) 1999

o ISCOR Hazardous Waste Disposal Site (Vereenging) [Iscor] 1999

o ISCOR Solid Waste Disposal Site (Vanderbiljpark) [Iscor] 1999

o Sasol 1 GLB Landfill (Sasolburg) [Sasol] 1999

o Shongweni H:H Landfill (Shongweni, KZN) [Enviroserv] 1999

o Luipaardsvlei Landfill (Krugersdorp) [Mogale City Local Municipality 2004


Page 5 of 13

o Proposed Kingstonvale Waste Disposal Site (Nelspruit) [MMC] 2004

o Proposed Hazardous Waste Site In Cacucao (Luanda, Angola) [Intels] 2004

o Pappas Quarry Manganese Waste Disposal Site (Nelspruit) [MMC] 2005

o East London Regional Waste Disposal site (East London) [Buffalo City Council] 2006

o Ekundustria Landfill (Bronkorstspruit) 2008

o Devon Landfill Site (Devon) [Lesedi Local Municipality] 2012

Health Impact Assessments and Buffer Zone Delineations:

o Vissershok HH Landfill Site (Cape Town) 1996, 2004 and 2009

o Proposed East London Regional Hazardous Waste Disposal site (Berlin, East London)

1998 and 1999

o Holfontein H:H Landfill (Pretoria) [Enviroserv] 2001, 2003 and 2009

o Proposed Beluluane Hazardous Waste Landfill Site(Matola, Mozambique) [Mozal &

Mozambique Authorities] 2002

o Proposed City of Cape Town New Regional Landfill Site (Atlantis) [CoCT] 2002-2007 and

2010

o Proposed City of Cape Town New Regional Landfill Site Kalbaskraal [CoCT] 2002-2007

and 2010

o Shongweni H:H Landfill (Shongweni, KZN) [Enviroserv] 2003, 2008 and 2018

o Proposed Coega Landfill (Coega, Port Elizabeth) [Coega IDZ] 2003 and 2008

o Aloes Landfill Site (Port Elizabeth) [Enviroserv] 2004

o Rosslyn H:H Landfill (Pretoria) [Enviroserv] 2004, 2006 and 2011

o Proposed ISPAT ISCOR Solid Waste Disposal Site (Vanderbijlpark) [Iscor] 2005

o Proposed Waterfal General Landfill (Rustenburg) 2009

o Luipaardsvlei Landfill (Krugersdorp) [Mogale City Local Municipality 2009 and 2011

o Proposed Eden District Municipality (Mossel Bay) [Eden District Municipality] 2011

o Vissershok CoCT Waste Disposal Site Expansion[City of Cape Town] 2014

Waste Incineration

Existing Operations, including Medical waste incinerators at Rietfontein (Germiston) [Waste-

Tech] 1995; Medical waste incinerators at Aloes Landfill Site (Port Elizabeth) [Waste-Tech] 1996;

Medical waste incinerators at Vissershok Landfill Site (Cape Town) [Waste-Tech] 1996; Medical

waste incinerators at Tembisa Hospital (Tembisa) 2001; Medical waste incinerators Thembo

Memorial Hospital (Boksburg) 2001; Waste Rubber Incinerators at Ergo (Brakpan) [Ergo] 2002;

Voorberg Correctional Facility Incinerator (Porterville) (Department of Correctional Services,

DCS) 2012; Drakenstein Correctional Facility Incinerator (Paarl) (DCS) 2012; Helderberg

Correctional Facility Incinerator (Caledon) (DSC) 201

Proposed Operations, including Medical Waste Incinerator at Two Potential Sites (Rietfontein

and Randvaal) [Waste-Tech] 1996; Proposed Eastern Cape Medical and General Waste

Incinerator 2001; Thor Chemicals Plant (Kwazulu-Natal) [Department of Environmental Affaisrt

and Tourism] 2001; Aid Safe Waste Incinerator (Benoni) [Aid Safe] 2001; Startech Plasma Gas

Converter [Startech] 2002; KwaMashu Waste Water Treatment Facility Incinerator (Phoenix,


Page 6 of 13

Durban) [EThekwini Municipality] 2002; Shongweni Medical Waste Incinerator (Shongweni, KZN)

[Enviroserv] 2003;

Wastewater Treatment Works

Rondebult Wastewater Treatment Plant (Germiston) [East Rand Water Care Company, Erwat];

Waterval Wastewater Treatment Plant (Klip River) [Erwat], Vlakplaats Wastewater Treatment Plant

(Vosloorus) [Erwat], Dekema Wastewater Treatment Plant (Katlehong) [Erwat]; Zeekoegat

Wastewater Treatment Plant (Roodeplaat Dam, Nokeng tsa Taemane Local Municipality);

Baviaanspoort Wastewater Treatment Plant (Mamelodi, Pretoria); Rooiwal Wastewater Treatment

Plant ( ; Proposed Sishen South Sewerage Treatment Plant (Sishen); Fishwater Flats Wastewater

Treatment Plant (Port Elizabeth); Lusikisiki Wastewater Treatment Plant (Lusikisiki, Eastern Cape

Province)

Transport Sector: Bakwena Toll Road Concession (Pretoria – Rustenburg); N1/N2 Protea Toll Road

(Cape Town – Paarl – Somerset West); Protea Toll Road Tunnel Options; N14 (Germiston) On-

/Offramp; N3TC Toll Road Concession De Beers Pass Alternatives; Gauteng Heavy Vehicles Freeway

Re-Routing Study; SAPIA Vehicle Emissions Management Strategy; Gauteng Department of

Transport Air Quality Management Plan; MMT Fuel Additive Monitoring Campaign (Afton); Sasol

Vehicle Emissions Ambient Air Monitoring Campaign; Cape Town International Airport Air Quality

Management Plan; OR Tambo International Airport Detailed Air Emission Inventory and Air Quality

Management Plan; Sir Seretse Kama (Botswana) Air Impact Assessment; Iron Ore Train Transport

(Sishen Mine to Saldanha Bay Iron Ore Port); Coal Train Transport (Moatize to Nicala Port,

Mozambique); Bauxite Ore Long-haul Road Transport (Bakhuis to Nickerie, Suriname); Baseline

Assessment of Iron Ore Transport (Zanaga Mine to Pointe Noir, Republic of Congo (Brazzaville)).

Quantitative Risk Assessments and Consequence Modelling: Air Products Durban plant (Hydrogen);

Comprehensive Risk Assessment of AECI (chlorine, ammonia, acrylonitrile, sulphur dioxide),

Umbogintwini Factory Complex; Oleum Storage Tank Farm Lever Brothers. Boksburg; Ammonia

Tank Farm Palabora Mining Company, Palaborwa; Ammonia Refrigeration Unit, Palabora Mining

Company, Palaborwa; Chlorine Dosing facility Palabora Mining Company, Palaborwa; Accidental

liquid Bromine spills and fugitive gas emissions at Delta-G Scientific, Halfway House; Accidental

emissions and spills of organo-pesticides at Sanachem, Verulam. Burning of waste dumps in

Botswana (Botswana Government). Chlorine Dosing Facility at mining operations (Rustenburg);

Dispersion and Consequence Modelling of Toxic Liquid Spills (e.g. Acrylonitrile and Propylene Oxide),

Combustion Products (e.g. Hydrogen Cyanide), Bund Fires and Vapour Cloud Explosions of a large

number of storage tanks at Vopak Tank Terminals, Durban Harbour, Investigation of Fire at Sapref

Refinery Alkylation Unit; Risk assessment of ammonia, hydrogen fluoride and nitric acid Columbus

Stainless (Middelburg); Natural Gas Pipeline from Mozambique to Secunda (Sasol Gas). Hydrogen

gas pipeline from Vanderbijlpark to Springs (Air Products), Crude oil and white product pipelines

from Chevron Refinery (Cape Town) to Cape Town Harbour, Crude oil and white product pipelines

from Chevron Refinery (Cape Town) to Saldanha Bay, Liquid Fuels Transportation Infrastructure from


Page 7 of 13

Staatsolie Refinery To Ogane, Sol And Chevron Product Storage Depots, Suriname (Staatsolie

Maatschappij Suriname N.V.) – Overland and Riverbed assessments; Liquid Fuels Transportation

Infrastructure From Milnerton Refinery Area To Ankerlig Power Station (Atlantis Industrial Area),

Western Cape Province (Eskom). Sunrise Liquid Petroleum Gas Ship Offloading and Pipeline

Transportation Saldanha Bay – Sea and Land Spillages, Transnet Pipeline Greenvale Diesel Spill –

Hillcrest, KwaZulu-Natal

Mining and Ore Handling (Blasting; quarrying; grinding; crushing; conveying; vehicles; tailings dams).

BHP-Billiton Bauxite Mine (Suriname), Exxaro Heavy Minerals Mine and Processing (Madagascar),

Tenke Copper Mine and Processing Plant (DRC), Sari Gunay Gold Mine (Iran), Zaldivar Copper Mine

(Chile); Gold Mine at Omagh (Ireland); ZCCM Luancha Copper mine (Zambia); Skorpion Zinc mine

(Namibia); Rossing Uranium (Namibia); Trekkopje Uranium (Namibia); Gokwe Coal Mine

(Zimbabwe); Murowa Diamond Mine (Zimbabwe); Gamsberg Zinc Mine (Aggeneys); Prieska Copper

mine (Prieska); Numerous coal collieries, including Riversdale (Tete Province Mozambique, Anglo

Coal, Exxaro, Xstrata); Lime Quarries (La Farge, formerly Blue Circle, East London and Otjiwarongo,

Namibia); Clinker Grinding and Cement Blending Plant (La Farge, Richards Bay); Bluff Mechanical

Appliances – Durban Coal Terminal; Portnet’s Saldanha Ore Port Facility; and others.

Metal Recovery (Smelting; electro-wining). Samancor Air Quality Baseline for all South African

Chromium Smelter and Mines (Ferroveld, Ferrometals, MFC, Columbus, Tubatsi, Western Chrome

Mines, Eastern Chrome Mines), Hexavalent Chromium Air Quality Reference Document (FAPA),

Hartley Platinum Smelter (Zimbabwe); Mufulira Smelter (Zambia), Nkana Smelter (Kitwe, Zimbia);

Waterval Smelter (Amplats, Rustenburg); Lonrho Smelter (Brits); Ergo (Anglo American Corporation,

Springs); Coega Zinc Refinery (Billiton, Port Elizabeth); Hexavalent Chrome and Lead (Winterveld

Chrome Mines); Hexavalent Chrome Xstrata (Rustenburg); Pitch releases from graphite electrode

(EMSA, Union Carbide, Meyerton); Copper Smelting (Palabora Mining Company, Phalaborwa);

Portland Cement Plant (La Farge, East London and Otjiwarongo, Namibia); Westplats – Mooinooi

Smelter (Brits), Holcim Alternative Fuels Project (Lichtenburg, Ulco and Blending Plant –

Roodepoort), PPC Riebeeck West Expansion Project, Expansion projects for ArcelorMittal South

Africa Vanderbijlpark Works, Expansion projects for ArcelorMittal South Africa Saldanha Bay Works

Chemical Industry (bulk chemical; fertilizer; herbicides; pesticides). Comprehensive air pollution

impact assessment of AECI (Pty) Ltd Operations, including Modderfontein, Umbogintwini, Somerset

West, New Germany and Richards Bay; Kynoch Fertilizer plants in Milnerton and Potchefstroom;

Fedmis Fertilizer Plant in Phalaborwa; Pesticides and Herbicides at Sanachem (Canelands); Chrome

Impacts from various Bayer (Pty) Ltd operations (Newcastle and Durban); Fibre Production (Sasol

Fibres, Durban); NCP Chloorkop Expansion project, NCP Chloorkop Contaminated Soils Recovery

Petrochemical Industry (Petroleum refineries, tank farms). Baseline and Expansion of Liquid Natural

Gas Refinery (Equatorial Guinea); Site Selection for New South African Petroleum Refinery (DME),

Proposed new Greenfields Petroleum Refinery at Coega (PetroSA), Hydrogen sulphide and sulphur


Page 8 of 13

dioxide emissions from SASOL operations (Sasolburg and Secunda); Sasol Coal to Gas Conversion

Project (Sasolburg), Natref Refinery Expansion Project (Sasolburg); Engen Emissions Inventory

Functional Specification (Durban); Air impact of air emissions from Sapref Refinery (Durban) Odour

Impact assessment at ChevronTexaco Refinery (Cape Town); StaatsOlie expansion project

(Suriname); Marathon LNG Expansion (Equatorial Guinea); PetroSA (Mossel Bay), Air impact of air

emissions from Killarney, Milnerton and Saldanha Bay bulk storage tanks, Ambient air sampling

campaign and Health Risk Analysis at Highway, Toll Plazas, Filing Stations & Taxi Ranks (Sasol), Air

Products - Cryodrains at Sasol Secunda Oxygen Plants: Steam Ejector Vaporiser Vent Design

Pulp and Paper Industry. Expansion of Mondi Richards Bay, Odour Assessment and Panel

Development for Mondi Richards Bay, Multi-Boiler Impact Assessment for Mondi Merebank

(Durban), Impact Assessment for Sappi Ngodwana (Nelspruit), Impact Assessment for Sappi Stanger,

Air Quality Monitoring Network and Air Pollution Management Plan for Sappi Saiccor (Umkomaas),

Comprehensive Emissions Inventory and Screening Health Risk Assessment for Sappi Enstra

(Springs), Impact Assessment for Sappi Tugela, Expansion Project for Cape Sawmills (Stellenbosch),

Comprehensive Emissions Inventory and Screening Health Risk Assessment for Global Forest (Sabie),

Air Impact Assessment for Pulp United (Richards Bay), MTO George Saw Mill (George)

Power Generation:

Coal Power Stations

Kelvin Power Station (Johannesburg); Athlone Power Station (Cape Town); Tatuka, Kendal,

Matimba, Duvha and Majuba Power Stations, ESKOM; Open Cycle Gas Turbine Peaking Power

Station (Mosselbay), Inhambane Power Station, Mozambique, Combined Cycle Gas Turbine Power

Plant In Moamba, Mozambique.

Nuclear Installations

Participating member in the ATMES Phase 1 project to assess the emergency preparedness to

nuclear accidents following the Chernobyl Accident, Development and Implementation of a real-

time emergency dispersion model for NECSA (Pelindaba); Development of a real-time emergency

dispersion model for Koeberg Nuclear Power Station; Environmental Impact Assessment for the

proposed demonstration Pebble Bed Modular Reactor (PBMR); Environmental Impact Assessment

for the proposed Nuclear-1 Power Station; Meteorological monitoring and development of

Meteorological Chapter of Site Safety Report for potential Nuclear-1 Power Station (Thyspunt,

Bantamsklip and Duynefontein).

Solar Installations

Proposed 150 MWp Photovoltaic (PV) Power Plant (Bronkhorstspruit), Baseline and Impact

Assessment near Grootvlei Power Station for Solar Energy PV Power Facility, Air Quality Impact

Assessment for the Abengoa KaXu Concentrated Solar Power (CSP) station (Pofadder, Northern

Cape).

Software Development. Development of real time atmospheric dispersion model - HAWK: Atomic

Energy Corporation of South Africa; CALTEX, Cape Town; NCP CHLOORKOP, Kempton Park;


Page 9 of 13

MOSSGAS, Mosselbay; PALABORA MINING COMPANY, Palaborwa; AECI, Umbogintwini; AECI,

Modderfontein; SASOL, Secunda; SASOL, Sasolburg; SAPREF Refinery, Durban; ENGEN Refinery,

Durban; ESKOM, Majuba Power Station; South Durban Air quality management system (Joint

venture between major industries, authorities and community); SAPPI-SAICCOR, Umkomaas;

HARTLEY PLATINUM, Zimbabwe, Richards Bay Air Quality Committee (Joint venture between major

industries, authorities and community), ISCOR, Newcastle; ISCOR, Vanderbijlpark.

Provision of Expert Testimony: [e.g. Herbicide Contention Case: Victory Farm v HL&H Timber

Products (Pty) Ltd, Rautenbach Aerial Spraying Ltd, Alan James McEwan; SAPREF Alkylation Unit Fire,

Rhone-Poulenc Warehouse fire, Shell-Sasol Alcohol Reformulation Contention; Kudu Oils v

Department of Environmental Affairs and Tourism), Global Forest Products (Pty) Ltd & Others v Lone

Creak River Lodge (Pty) Ltd & Others; Pride Milling Company (Pty) Ltd v Klipspruit Colliery & Others;

Triple S Diensstasie Edms Bpk / P Senekal; PetroSA v Langeberg Shopping Mall, PetroSA v Visigro

Investments, Koedoeskloof Landfill in Uitenhage Nelson Mandela Municipality v Pentree; Interwaste

(Pty) Ltd FG Landfill//Abader, Ishaam N.O. and Others; Enviroserv Waste Management (Pty) Ltd//The

Department of Environmental Affairs and Others.]

EDUCATION University

1984 - 1986 : PhD student at the University of Natal (Department of Chemical Engineering), Durban.

Completed December 1986. Degree awarded March 1987

Supervisor: Prof M Mulholland

1983 - 1984 : MSc Eng student at the University of Natal (Department of Chemical Engineering), Durban.

Completed April 1984. Degree awarded March 1985

Supervisor: Prof M Mulholland

1980 - 1982 : BSc Eng student at the University of Natal, Durban. Completed a BSc Eng (Chemical Engineering) - Cum Laude

1979 : BSc Eng student at the University of Port Elizabeth, 1st Year Chemical Engineering

Matriculated

1978 : Cradock High School, Cradock, South Africa. Aggregate: A

ADDITIONAL COURSES

1996 Risk Assessment for Environmental Decision Making - Presented by Harvard University

School of Public Health at the CSIR, Pretoria, RSA.


Page 10 of 13

COUNTRIES OF WORK EXPERIENCE

Central African Republic, Republic of Chile, Democratic Republic of Congo, Federal Democratic

Republic of Ethiopia, Republic of Equatorial Guinea, Republic of Ghana, Kingdom of Lesotho,

Republic of Liberia, Republic of Madagascar, Republic of Mozambique, Republic of Namibia, Republic

of Congo, Republic of South Africa, Republic of Suriname Togolese Republic, Republic of Zambia,

Republic of Zimbabwe

EMPLOYEMENT RECORD Jan 1990 to 2018 Managing Director/Director. Airshed Planning Professionals (Pty)

Ltd, Midrand (Previously known as Environmental Management

Services 1990 to 2003)

A consulting firm providing services in the Air Quality and Noise Assessments and Management field

to industry and national, provincial and local authorities. Work includes the preparation of emission

inventories, dispersion modeling, impact assessment and mitigation planning in the mining,

metallurgical and general industrial sectors. Legal compliance audits have been carried out.

Jan 1989 to Dec 1990 Process Engineer, AECI Engineering Department, Modderfontein,

Johannesburg.

Part of process engineering team for the design of Coal to Liquid (CTL) processing plant, responsible

for energy integration. Conceptual design of new Calcium Carbide smelter. Detailed engineering and

commissioning of Gold Potassium Cyanide Plant.

Jul 1987 to Dec 1988 Research Engineer, Council for Scientific and Industrial Research

(CSIR), Pretroria

Responsible for the development (design and construction) of a gas dynamic laser for industrial

applications. Development of a real-time atmospheric dispersion model for emergency response

applications

Jan 1984 to Dec 1986 Research Assistant, Department Chemical Engineering, University of

Natal, Durban.

Development of prototype real-time atmospheric dispersion model for air pollution management


Page 11 of 13

applications at a petroleum refinery. Development of a new theoretical model for complex

atmospheric applications.

CONFERENCE AND WORKSHOP PRESENTATIONS AND PAPERS

Burger L W and Mulholland M. Real-time prediction of point-source distributions using an

anemometer-bivane and a microprocessor, Atmospheric Environment, Volume 22, Issue 7, 1988,

Pages 1309–1317

Burger L W Air pollution modelling as part of an EIA study, Western Cape Annual Air Pollution

Symposium, National Association for Clean Air, 11 September 1997

Burger, C.J.H. & Kornelius, G. Dust dispersion from a dust road and the attenuation thereof by tree

plantations beside the road: A mathematical model. CEMSA ‘98 International Conference and

Exhibition on Integrated Environmental Management. East London, February 1998

Burger, L.W., Coetzee, L.A., Sowden, M., Kornelius, G., Simpson, D., Swanepoel, P.A., van Niekerk, A.S., &

van Niekerk, W.C.A. Development and implementation of the Integrated Energy Decision Support

Model (IEDS) to improve health conditions in residential areas. Proc 11th World Clean Air and

Environment Congress, Durban 1998.

Hurt Q E, Burger L W, Bell C. A Tool For Air Quality Management : The Importance Of Quality Assurance,

Intelligent Assimilation Of Data And The Effective Representation Thereof To Industry, The Regulatory

Authorities And The Community. Proc 11th World Clean Air and Environment Congress, Durban 1998.

Burger L W and Scorgie Y The Value Of A Quantitative Acute And Chronic Health Risk Assessment In

Town Planning Around A Large Industrial Complex. Proc 11th World Clean Air and Environment

Congress, Durban 1998

Burger L W, Coetzee L A, Sowden M, Kornelius G, Simpson D, Swanepoel P A , Van Niekerk A S and Van

Niekerk WCA, Development And Implementation Of The Integrated Energy Decision Support Model

(Ieds) To Improve Health Conditions In Residential Areas. Proc 11th World Clean Air and Environment

Congress, Durban 1998

Burger L W and Hurt QE, A Tool for Air Quality Management: Real-Time Atmospheric Dispersion

Modelling In Two Large Industrial Regions - South Durban And Richards Bay. Proc 11th World Clean Air

and Environment Congress, Durban 1998


Page 12 of 13

Burger L W and Terblanche A P, Atmospheric Dispersion Calculations Of Toxic Gases Originating From

Waste Disposal Facilities, Proc 11th World Clean Air and Environment Congress, Durban 1998

Burger L W, Grundling A, Van Heerden J, Truter T, Rautenbach H. A Case Study: Predicting the Surface

and Upper Atmospheric Dispersion Of Satellite Launching Rocket Exhaust Gases, Proc 11th World Clean

Air and Environment Congress, Durban 1998

Burger L W. Quantifying Flue Gas Temperature to Minimise Condensation in Scrubber Stack Plumes,

National Association for Clean Air Conference 2004

Burger L W and Scorgie Y, Air Quality Management Systems: Pitfalls and Harmonization, National

Association for Clean Air Conference, 2005

Burger, L W, Uncertainty in Atmospheric Dispersion Modelling, National Association for Clean Air

Conference, East London 2006

Burger L W, Stead M and Moldan A. Prediction Of Motor Vehicle Air Emission Reductions Through

Intervention Policies, National Association for Clean Air Conference, Vereenging 2009

Burger L W, Complexities In The Estimation Of Emissions And Impacts Of Wind Generated Fugitive Dust,

National Association for Clean Air Conference, Polokwane 2010

Burger L W, A Dynamic Model for The Simulation Of Sulphur Dioxide Emissions From A Self-Propagating

Sulphur Storage Fire, 16th IUAPPA World Clean Air Congress, 29 Sep to 4 Oct 2013, Cape Town

Herselman JE; Burger LW; Moodley P (2009) Guidelines for the utilisation and disposal of wastewater

sludge Volume 5 of 5: Requirements for thermal sludge management practices and for commercial

products containing sludge, ISBN No: 978-1-77005-711-1].

Liebenberg-Enslin, H, Annegarn, H.J and Burger, L.W (submitted Aeolian Research for publication in

2015), A Best Practice Prescription For Quantifying Wind-Blown Dust Emissions from Gold Mine Tailings

Storage Facilities.

Scorgie Y, Burger L W and Sowden, M: Application of Source-Receptor Modelling to Regional Air Quality

Management, National Association for Clean Air Conference, ‘Into the Next Millennium’, held at BMW

Pavilion, Cape Town on 6-8 October 1999.

Scorgie Y, Burger L W and Annegarn, H.J: Air Quality Management within the Vaal Triangle, Air Pollution

Action Committee (APAC) meeting, held at the Lethabo Power Station, Sasolburg, South Africa, 24 May


Page 13 of 13

2000.

Scorgie Y, Burger L W, Annegarn, H.J and Piketh S: Background Study for the Development of an Air

Quality Management Strategy for Gauteng: Characterisation of Existing Air Quality and Assessment of

Future Trends and Driving Forces, National Environmental Research Institute of Denmark, 25 October

2000.

Scorgie Y, Burger L W and Annegarn, H.J: Air Quality Management System Development and

Implementation in South Africa, paper to be presented at the Third International Conference on Urban

Air Quality Conference entitled Measurement, Modelling and Management, 19-23 March 2001,

Loutraki, Greece.

Scorgie Y, Annegarn, H.J and Burger L W: Air Quality over South Africa – Persistent Problems And

Emerging Issues, 14th IUAPPA World Congress, Brisbane, 2007

LANGUAGES

Speak Read Write

English Home language Good Good

Afrikaans Good Good Good

CERTIFICATION

I, the undersigned, certify that to the best of my knowledge and belief, these data correctly describe

me, my qualifications, and my experience.

_ 30/10/2018 _

Physical: 480 Smuts Drive, Halfway Gardens, Halfway House, 1685

Postal : P O Box 5260, Halfway House, 1685

Tel : +27 (0)11 805 1940

Email : [email protected]



11 APPENDIX D: DISPERSION MODEL RESULTS

11.1 Dispersion Model Results for Phase 1A (including Cell 7)

Figure 11-1: Phase 1A - Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4

daily exceedances per calendar year)



Figure 11-2: Phase 1A - The predicted incremental cancer risk based on exposure to benzene emissions from

the CLS (an incremental cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see

Table 2-5)



Figure 11-3: Phase 1A - Potential zone of odour nuisance based the 98th percentile hourly average H2S

concentrations (isopleths represent the equivalent of 2OU – assessment follows New South Wales odour

performance criteria Table 2-7)



Figure 11-4: Phase 1A - Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations


2-7)



Figure 11-5: Phase 1A - Predicted highest monthly average fallout dust (residential areas should not exceed

more than 600 mg/m²-day)



Figure 11-6: Potential zone of odour nuisance over lifetime of landfill up to and including Cell 7 and Phase 1A



Figure 11-7: Phase 1A - Prediction results for combined health risks, including the PM10 (unmitigated and

mitigated) and benzene incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth

represents the 1-in-a-million incremental cancer risk)



11.2 Dispersion Model Results for Phase 1B

Figure 11-8: Phase 1B - Predicted daily exceedances of the NAAQS limit value of 75 µg/m³ (NAAQS allows 4

daily exceedances per calendar year)



Figure 11-9: Phase 1B - The predicted incremental cancer risk based on exposure to benzene emissions from

the CLS (an incremental cancer risk of 1 in a million (or 1:1 000 000) and less is considered to be Very Low – see

Table 2-5)



Figure 11-10: Phase 1B - Potential zone of odour nuisance based the 98th percentile hourly average H2S

concentrations (isopleths represent the equivalent of 2OU – assessment follows New South Wales odour

performance criteria Table 2-7)



Figure 11-11: Phase 1B - Potential zone of odour nuisance based on estimated 3-minute peak H2S concentrations


2-7)



Figure 11-12: Phase 1B - Predicted highest monthly average fallout dust (residential areas should not exceed

more than 600 mg/m²-day)



Figure 11-13: Potential zone of odour nuisance over lifetime of landfill up to and including Phase 1B



Figure 11-14: Phase 1B - Prediction results for combined health risks, including the PM10 (unmitigated and

mitigated) and benzene incremental cancer risk (PM10 isopleth represents the NAAQS, and the benzene isopleth

represents the 1-in-a-million incremental cancer risk)

air quality impact assessment of the proposed enviroserv ...€¦ · 1. description of baseline...

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