material flow analysis of the city of hamburg -...

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Material Flow Analysis of the City of Hamburg

Preliminary results

DRAFT VERSION

Mark Hammer, Stefan Giljum, Friedrich Hinterberger

Sustainable Europe Research Institute (SERI)

Schwarzspanierstraße 4/8, A-1090 Wien

Tel: +43 1 96 0728 14, Fax: +43 1 969 07 28 17, [email protected]

Paper presented at the Workshop “Quo vadis MFA? Material Flow Analysis –

Where do we go? Issues, Trends and Perspectives of Research for Sustainable

Resource Use“, Wuppertal, 9.–10. October 2003. *

Abstract

In this paper we present first results of a local MFA for the City of Hamburg. Material

flows have been accounted for the years 1992-2001. Material input and consumption

indicators for Hamburg increased during this last ten years. Material flows are almost overall

dominated by imports and a big share of the imports is re-exported again showing the role of

Hamburg as an international harbour. Material consumption per capita and per GDP is lower

in Hamburg than in overall Germany. But different to Germany where material inputs and

consumption stay stayed stable in per capita terms and declined in relation to GDP in

Hamburg material inputs and consumption per capita and per GDP increased.

Keywords: Material flow analysis (MFA), regional development, environmental

indicators, sustainability.

* This paper is part of the project “Nachhaltige Entwicklung zwischen Durchsatz und Symbolik“

(NEDS) (Sustainable development between throughput and symbolism), funded by the German

Ministry of Education and Research in the context of its program on socio-ecological research.

Contract number: SÖF (#624-40007-07 NGS 11).

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1 Introduction

Issues of regional metabolism have already been discussed in the 1960s with a focus

on water use and water and air pollution of cities, for example by Wolman (1965). The fact

that cities are draining natural resources from their “Hinterland” has been discussed from an

ecological footprint perspective by Rees and Wackernagel (1996) and Luck et al. (2001). On

the one hand, they describe how Ecological Footprints are spatially distributed in a

heterogeneous way between urban areas and their surrounding regions and that cities can

not be sustainable within their boundaries. On the other hand they describe how the

population density of cities can facilitate solutions for certain environmental problems (e.g.

traffic or waste water treatment).

Several empirical MFA studies on regional or local levels have been carried out in the

past (Amann et al 2002, Barrett et al 2001 and 2002, Bringezu and Schütz 1996 a and b,

Brunner et al 1994, Daxbeck et al 1996, Gorree et al 2000, Hendriks et al 2000, IHOBE

2002, McEvoy 2001, Obernosterer et al 1998, Singh et al 2001). However, compared to the

large number of MFA studies on the national level, published studies on the regional or local

level are still very limited and a standardised method such as presented by Eurostat (2001)

for the national level does not exist yet. We consider material flow analysis on a regional or

local level as an important scientific tool on the way of regional and local sustainability

(Hinterberger 2000, Hinterberger and Schneider 2001).

In chapter 2 we will describe the methodology of material flow analyses. In chapter

three we will briefly describe the project within which this MFA has been carried out and

present the results of the MFA of Hamburg. Conclusions will be presented in chapter 4 and

the annex in chapter 5 gives a detailed description of calculation methods and data sources.

At the end of the paper one can find a summary of the data tables.

2 Description of the methodology

The principle concept underlying the economy-wide MFA approach is a simple model

of the interrelation between the economy and the environment, in which the economy is an

embedded subsystem of the environment and – similar to living beings – dependent on a

constant throughput of materials and energy. Raw materials, water and air are extracted from

the natural system as inputs, transformed into products and finally re-transferred to the

natural system as outputs (waste and emissions) (see Figure 1). To highlight the similarity to

natural metabolic processes, the terms “industrial” (Ayres, 1989) or “societal” (Fischer-

Kowalski, 1998a) metabolism have been introduced.

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Figure 1: The basic model of material flow accounting and analysis (MFA)

According to the first law of thermodynamics (the law of the conservation of mass),

total inputs must by definition equal total outputs plus net accumulation of materials in the

system. This material balance principle holds true for the economy as a whole as well as for

any sub-system (an economic sector, a company, a household).

For a consistent compilation of an economy-wide material flow account, it is

necessary to define exactly, where the boundary between the economic and the

environmental system is set, as only resources crossing this border will be accounted for. As

described in the System of Environmental and Economic Accounts (SEEA) (United Nations,

1993, 2001), the economic sphere is defined in close relation to the flows covered by the

conventional System of National Accounts (SNA). Thus all flows related to the three types of

economic activities included in the SNA (production, consumption and stock change) are

referred to as part of the economic system. On the other hand, the environmental sphere

comprises all resources other than products traded within the market system.

Therefore, for MFA on the national level, two main boundaries for resource flows can

be defined. The first is the boundary between the economy and the domestic natural

environment, from which resources (materials, water, air) are extracted. The second is the

frontier to other economies with imports and exports as accounted flows.

2.1 Categories of material flows

Before outlining a comprehensive material balance scheme, we have to explain the

differences between the different types of material flows. In its methodological guide,

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Eurostat (2001) advises to distinguish the various types of material flows according to the

following scheme:

Direct versus indirect

Direct flows refer to the actual weight of the products and thus do not take into

account the life-cycle dimension of production chains. Indirect flows, however, indicate all

materials that have been required for manufacturing (up-stream resource requirements) and

comprise both used and unused materials (see also Chapter 5 and 6 of this thesis for a

discussion on direct and indirect flows and their relevance for analyses of international

trade).

Used versus unused

The category of used materials is defined as the amount of extracted resources,

which enters the economic system for further processing or direct consumption. All used

materials are transformed within the economic system. Unused extraction refers to materials

that never enter the economic system and thus can be described as physical market

externalities (Hinterberger et al., 1999). This category comprises overburden and parting

materials from mining, by-catch and wood harvesting losses from biomass extraction and soil

excavation as well as dredged materials from construction activities.

Domestic versus Rest of the World (ROW)

This category refers to the origin and/or destination of the flows. Combining these

three dimensions to one table shows the 5 categories of material inputs relevant for

economy-wide MFA (Table 1):

Table 1: Categories of material inputs for economy-wide MFA

Weight Economic treatment Origin Term to be used

Direct Used Domestic Domestic extraction (used) (Not applied) Unused Domestic Unused domestic extraction Direct Used Rest of the world Imports Indirect Used Rest of the world Indirect Unused Rest of the world

Indirect input flows associated to imports

Source: modified from EUROSTAT, 2001

A standard material flow account focuses on flows of solid materials. This group is

further classified into 3 main subgroups of material inputs:

• Minerals (metal ores and non-metallic minerals like stones, clays, etc.),

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• Fossil energy carriers (coal, oil, gas), and

• Biomass (from agriculture, forestry and fishery).

The material stock

From the viewpoint of physical accounting, the accumulation of a large physical stock

is one main characteristic of modern industrialised societies. Stocks in the MFA framework

mainly comprise man-made assets: infrastructure and buildings on the one hand and durable

consumption goods (like cars, household equipment) and investment goods (machinery) on

the other hand. Forests and agricultural plants are considered part of the environmental

system and are therefore not included in the physical stock, whereas harvests of timber and

crops are accounted as inputs to the socio-economic system. EUROSTAT (2001) suggests

treating waste deposited in controlled landfills as outputs of the economy to the environment

rather than a physical stock.

2.2 A general scheme for economy-wide MFA

After having explained the various categories of material flows and the importance of

the physical stock, a general balance scheme including all relevant input and output flows

can be presented (Figure 2). The material balance reveals the composition of the physical

metabolism of an economy and depicts domestic material extraction, imports and exports in

physical units, the physical growth of its infrastructure as well as the amount of materials

released back to nature.

Figure 2: General scheme for economy-wide MFA, excluding water and air flows

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Source: EUROSTAT, 2001

Material inputs to the economic system comprise used domestic extraction of various

material groups (fossil fuels, minerals and ores, and biomass). In addition, material inputs

include so-called “unused domestic extraction (UDE)”. UDE comprises materials that had to

be moved during extraction activities, but do not enter the economic system for further

processing (such as cover material or overburden from mining and residuals from harvest in

agriculture). Consequently, unused flows do not have an economic value. These flows have

been termed “hidden flows” in earlier MFA publications, as they are not “visible” in the

monetary economy (for example, Adriaanse et al., 1997). Finally, material inputs include

physical imports and indirect flows associated with them.

Material inputs are (a) accumulated within the socio-economic system (net addition to

stock, such as infrastructure and durable consumer goods), (b) consumed domestically

within the accounting period (in most cases one year) and thus crossing the system

boundary as waste and emissions back to nature or (c) exported to other economies.

2.3 Indicators derived from economy-wide MFA

Within the internationally harmonised classification systems for environmental

indicators, like the pressure-state-response (PSR) framework of the OECD (1994) or the

extended Driving Forces-Pressures-State-Impact-Response (DPSIR) system of the

European Union (EUROSTAT, 1999), material-flow based indicators are part of the pressure

indicator group. These indicators identify and describe socio-economic activities, which

cause pressures on the environment. However, their ability to provide information on the

actual environmental impacts is very limited (see below).

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A large number of resource-use indicators can be derived from economy-wide

material flow accounts as illustrated in Figure 2, providing a comprehensive description of the

biophysical metabolism of societies. These indicators can be grouped into (a) input, (b)

output and (c) consumption indicators and have been developed in international co-

operations in the course of the last 5-10 years (see, for example, Adriaanse et al. 1997,

Matthews et al. 2000).

The following section lists the main indicators of each indicator group and is based on

the suggestions in the methodological guide, published by EUROSTAT (2001).

Main input indicators:

• Direct material input (DMI) comprises all materials, which have economic

values and are directly used in production and consumption activities. DMI equals the sum of

domestic extraction plus imports.

• Total material input (TMI) is the DMI plus the unused domestic extraction.

• Total material requirement (TMR) includes - in addition to TMI - the indirect

(used and unused) flows associated to the imports of an economy. TMR thus is the most

comprehensive material input indicator, comprising all input flows illustrated in Figure 2.

Main output indicators:

• Domestic processed output (DPO) equals the flow „outputs to nature“ in

Figure 2 and comprises all outflows of used materials from domestic or foreign origin. DPO

includes emissions to air and water, wastes deposited in landfills and dissipative flows.

Recycled materials are not included in the DPO indicator.

• Total material output (TMO) includes additionally to the DMO also the

unused domestic extraction thus comprises all three categories of output flows shown in

Figure 2.

Main consumption indicators:

• Domestic material consumption (DMC) measures the total quantity of

materials used within an economic system, excluding indirect flows. Thus DMC is the closest

equivalent to aggregate income in the conventional system of national accounts. DMC is

calculated by subtracting exports from DMI.

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• Total material consumption (TMC) includes, in addition to DMC, also the

indirect flows associated to imports and exports and can be calculated using either LCA-

oriented or input-output techniques (see also below). TMC equals TMR minus exports and

their indirect flows.

Physical Trade Balance (PTB): A PTB expresses whether resource imports from

abroad exceed resource exports of a country or world region and to what extent domestic

material consumption is based on domestic resource extraction or on imports from abroad. A

physical trade balance is compiled in two steps. A PTB for direct material flows equals

imports minus exports of a country or region. A comprehensive PTB can also be calculated

including indirect flows associated to imports and exports.

Net addition to stock (NAS) describes the annual accumulation of materials within

the economic system and thus could also be termed „physical growth of the economy“.

Materials forming the stock mainly consist of construction materials for new infrastructure

and durable goods, such as cars and industrial machinery.

3 Case study of the City of Hamburg

3.1 The NEDS project

This paper is part of the project “Nachhaltige Entwicklung zwischen Durchsatz und

Symbolik“ (NEDS) (Sustainable development between throughput and symbolism), funded

by the German Ministry of Education and Research in the context of its program on socio-

ecological research. The main objective of NEDS is integrating approaches of ecological

economics, environmental accounting (in particular material flow accounting - MFA),

discourse analysis (for the aspect of interlinking MFA with discourse analysis see Luks and

Hammer, unpublished) and constructivist aspects, in order to explicitly take into account the

complex relationship between science and policy1.

In the NEDS project, 3 European regions are selected as case studies for regional

MFAs. The regions are: the metropolitan region of Hamburg (the city of Hamburg and 6

NUTS 3 regions surrounding the city), the metropolitan region of Vienna (the city of Vienna

and two NUTS 3 regions) and the metropolitan region of Leipzig (including one NUTS 3

1 Further information on the project can be found in the internet at www.neds-project.de or

www.seri.at/neds.

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region of surrounding area). The regions have been selected from a database of 73

European regions, which have been classified as active promoters of regional sustainable

development (BBR 2001). In the course of the project, parallel analyses of the biophysical

metabolism (assessed with an MFA approach) and the discourse on sustainability are carried

out in each of the selected regions, in order to identify their linkages and to formulate

possible paths towards a more efficient use of natural resources on the regional level.

The 3 regional MFA accounts compiled in the course of the project will as close as

possible be compiled in accordance with the standardized method of the Eurostat guide for

economy-wide material flow accounts (Eurostat, 2001). This is of importance, as, on the one

hand, regional MFAs can only enable the cross-checking with and completion of national

MFAs, when following the same methodological procedure. On the other hand, when

regional MFA data is not available and estimation methods have to be applied, national MFA

data can only serve as a starting point for estimations, when using the same classification of

material flows.

Given sufficient data availability, the regional material flow accounts will also include

unused domestic extraction and indirect flows associated to imports. If data concerning

unused domestic extraction (mainly overburden from mining activities) is not available from

official statistical sources, a first estimation of overburden should be obtained through

personal communication with the most important mining co-operations in the regions.

Indirect flows associated to imports will be estimated by applying “rucksack factors”

for the German economy, which have been calculated by the Wuppertal Institute and are so

far the most detailed data for indirect flows available world-wide (for example, Bringezu

2001). For the 2 regions located in Germany this procedure should deliver reliable results.

For the third region in another European country, the estimation is based on the assumption

of an identical import structure of the region compared to Germany. This procedure has been

used for a number of other MFA studies on the regional and national level (for example,

Hammer and Hubacek 2002, IHOBE 2002, Juutinen and Mäenpää 1999). However, one

should be aware of deviations from results based on country- or region-specific rucksack

factors for imports.

Provided a sufficient availability of data, the 3 regional MFAs will be compiled in a

time series from 1992-2001. We choose this period of 10 years, as, on the one hand, we can

expect that data availability will be the higher the more recent the time period of our

investigation is set. This is of particular importance, as data availability will be one of the

crucial points for the success of the regional MFA studies. On the other hand, a period of 10

years is long enough to capture recent changes in the metabolic profile of the regions and to

analyse impacts of changed political / discursive frameworks on regional material flows. A

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detailed description of the methodology used for the projects MFAs can be found in Hammer

et. al. (2003).

3.2 Method and data sources

The method followed as far as possible the method of Eurostat (2001). For this paper

only the MFA of the City of Hamburg (without its surrounding regions) has been calculated.

The material inputs and outputs have been classified according to Eurostat (2001). Unused

domestic extraction and indirect flows associated to imports and exports have not been

calculated as material input data was available only highly aggregated which did not allow an

useful estimation of indirect flows. Material input data was in many cases available in tons.

Where this was not the case estimation had been made as far as possible. A detailed

description of the used data sources and the calculation of the MFA are given in the technical

annex of this paper.

3.3 Results

3.3.1 Material inputs and consumption per capita

Direct Material Input (DMI) in absolute numbers increased from about 98 million tons

in 1992 to about 117 million tons in 2002. Domestic extraction accounted for only

approximately 160.000 tons or 1,6 per mill of DMI. Therefore DMI is dominated almost

overall by imports. DMI per capita increased from 75,8 tons in 1992 to 68,3 in 2003. About 80

million tons of DMI have been exported again. Therefore direct Material Consumption (DMC)

is significantly lower than DMI with 10,9 tons per capita in 1992 and 18,9 tons per capita in

2002. These trends and a comparison with German MFA data (from Moll et al 2003) is

shown in Figure 3. DMI per capita for Hamburg was much higher than the German average

which is at approximately 20 tons per capita and year. On the other hand DMC per capita

was lower. The trends also show that material inputs and consumption of Hamburg

increased during the last decade whereas these indicators stayed more or less constant for

Germany. The importance of imports for material inputs is not very surprising as in a

metropolitan region like Hamburg no big extraction activities (mining, quarrying, agriculture)

exist. The high DMI and the large difference between DMI and DMC of Hamburg can be

explained by the so-called “harbour-effect” (Eurostat 2001). Hamburg is one of the big

European harbours receiving big amounts of raw materials and products from overseas

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which are re-exported again. Due to this effect a comparison of material input indicators

alone is not scientifically sound.

Figure 3: DMI and DMC per capita

DMI/DMC per capita, Germany and Hamburg

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

1992

1994

1996

1998

2000

Years

tons

per

cap

ita

DMI per capitaHamburg

DMC per capitaHamburg

DMI per capitaGermany

DMC per capitaGermany

Source: Own calculations, for German data: Moll et. al. 2003.

3.3.2 Resource productivity or eco-efficiency

DMI per GDP stayed more or less constant around 1.600 tons per million Euros GDP

produced. DMC increased from 300 tons per million Euros to 460 tons. Therefore Hamburg

shows no trend of dematerialisation. Eco-efficiency stayed constant in terms of DMI and

even decreased in terms of DMC. A different picture can bee seen for overall Germany

where resource productivity slightly increased and a growing GDP could be produced with

less units of material input or consumption per unit of GDP. On the other hand resource

productivity (GDP produced by material use) in terms of material consumption is much higher

in Hamburg than in overall Germany. Much less material consumption has been used to

generate the GDP of Hamburg in comparison to Germany. A comparison based on the

material input is again not useful due to the above mentioned “harbour-effect”. The results

are shown in Figure 4.

Figure 4: DMI and DMC per GDP

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DMI/DMC per GDP, Germany and Hamburg

0,000,200,400,600,801,001,201,401,601,80

1992

1994

1996

1998

2000

Years

1000

to

ns

per

mill

ion

eu

ro

1995

DMI per GDPHamburg

DMC per GDPHamburg

DMI/GDPGermany

DMC/GDPGermany

Source: Own calculations, for German data: Moll et. al. 2003.

3.3.3 Imports, exports and physical trade balance

Imports increased by approximately 20% from about 98 million tons in 1992 to 118

million tons in 2002. The biggest import category is ores and industrial minerals followed by

industry products, biomass and fossil fuels. The composition of imports changed slightly

during the past 10 years mainly due to the increase in imports of industry products.

Figure 5: Imports

Imports, City of Hamburg 1992-2001

0

20.000

40.000

60.000

80.000

100.000

120.000

140.000

1992

1994

1996

1998

2000

Years

1000

tons

Other imports

Other industryproducts

Chemical products

Fossils and fossilproducts

Ores and industrialminerals

Biomass and biomassproducts

Source: Own calculations.

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Exports account for approximately 20% of the imports showing the importance of the

harbour of Hamburg as a centre of international trade. Exports showed a slower increase,

from 81 to 85 million tons between 1992 and 2002. The largest exports groups are ores and

minerals and chemical products. Exports show a more homogenous distribution between

export groups than imports.

Figure 6: Exports

Exports, City of Hamburg 1992-2001

0

20.000

40.000

60.000

80.000

100.000

1992

1994

1996

1998

2000

Years

1000

to

ns

Other exports


Chemical products



Biomass and biomassproducts

Source: Own calculations

The physical trade balance shows that imports exceeded exports in every year

analysed. As for national economies the physical trade balance can differ remarkably

depending on the size of the country and the availability of natural resources within its

borders this result is not very surprising for a city as almost all of its material consumption

has to be feed by imports and natural resources that could expand exports are missing.

Therefore for the city of Hamburg the physical trade balance amounts for almost 100% of

DMC.

Figure 7: Physical Trade Balance

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Physical Trade Balance, City of Hamburg 1992-2001

0

20.00040.000

60.000

80.000

100.000120.000

140.000

1992

1994

1996

1998

2000

Years

1000

ton

s

Imports

Exports

Physical TradeBalance

Source: own calculations

The physical trade balance shows large differences for the different commodity

categories traded as shown in Figure 8. As the physical trade balance has been calculated

by subtracting exports from imports a positive trade balance means that imports exceeded

exports. Only for to categories the exports have been bigger than the imports: for chemical

products and for a group called “other imports/exports” summarizing not specified imports

and exports. Chemical product showed a big negative trade balance but with a decreasing

trend as exports of chemical products declined during the observed period.

Figure 8: Physical trade balance by commodities

Physical Trade Balance, City of Hamburg 1992-2001

-15.000

-10.000-5.000

05.000

10.00015.000

20.000

1992

1994

1996

1998

2000

Years

1000

tons

Biomass andbiomass products



Chemical products


Otherimports/exports


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3.3.4 “Domestic” extraction

Domestic extraction within a metropolitan region is certainly a special case for a MFA

as no remarkable extraction activities can exist within a densely built up area. No extraction

of ores or fossil fuels exists within the area of Hamburg. According to personal

communication with members of the statistical office of Hamburg extraction of minerals exists

(for example sand and gravel) but underlies secrecy as the number of extraction firms is very

low. Extraction of minerals normally builds up an important input category and therefore the

lack of this data is one of the weakest points for the results. There fore domestic extraction

data only was included for agriculture, forestry, fishery and was estimated for grazing

animals.

Figure 9: „Domestic extraction

"Domestic" extraction, City of Hamburg 1992-2001

020406080

100120140160180

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Years

1000

ton

s

Fish

Grazing

Forestry

Agriculture


Total domestic extraction amounted for about 160.000 tons in 2002 being

approximately 1 per mille of DMI. The largest input came from agriculture with approximately

100.000 tons. At the moment of the publication of this paper no data has been included for

agricultural extraction for the years 1992-1994. Data for domestic extraction of agricultural

biomass was for the most commodities not available in tons but had to be estimated from

area and yield data. The statistical source used also changed the output of reporting within

the observed period (summing up Berlin, Bremen and Hamburg in the statistics for the years

1997-1999 for some commodities). Therefore different calculation and estimation methods

had to be applied over the whole time period which results in huge fluctuations in MFA data

which are object for future revision.

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4 Conclusions

The material flows of the city of Hamburg are almost overall dominated by its trade

flows. Direct extraction of materials does not play an important role. Hamburg as an

important international harbour shows much higher material inputs per capita than overall

Germany which is due to high imports which are to a big extend re-exported again. Material

consumption per capita in Hamburg is lower than in Germany. Also material consumption per

unit GDP produced is lower and both consumption indicators show an increasing trend.

Therefore neither absolute nor relative dematerialisation is taking place. At the moment

material intensity and consumption in Hamburg is lower than in Germany but the trend goes

into “materialisation”.

On the methodological point of view the following main problems occurred: Very

aggregated data did not allow the calculation of unused domestic extraction and indirect

flows associated to imports and exports. Important categories of domestic extraction (sand

and gravel) exist but underlie secrecy. Data sources changed in their quality and way of

reporting during the observed period. This made necessary estimations and extrapolations of

data for several material categories for several years.

5 Technical Annex

The technical annex describes the data sources and the methods of calculation used

for this study.

5.1 Domestic extraction of fossil fuels

No extraction of fossil fuels exists within the city of Hamburg (Statistical office of the

City of Hamburg, personal communication).

5.2 Domestic extraction of metal ores

No extraction of metal ores exists within the city of Hamburg (Statistical office of the


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5.3 Domestic extraction of construction materials

Domestic extraction of construction materials exists (for example, sand and gravel)

but underlies secrecy as the number of extracting firms is very small (Statistical office of the


5.4 Domestic extraction of industrial minerals

No extraction of industrial minerals exists within the city of Hamburg (Statistical office

of the City of Hamburg, personal communication).

5.5 Domestic extraction of biomass from agriculture

Data was taken from (Statistisches Bundesamt various years-c).

Normally this source shows the area, yield and harvest for several agricultural

products. But for some agricultural products the statistics show data only for an area of some

hundred or thousand hectares in Hamburg but no data on yield or harvest. In those cases the

harvest was estimated by using the mean of the yields of Schleswig-Holstein and

Niedersachsen which are the provinces closest to Hamburg. For these provinces yields are

reported for every year for every agricultural product within the same table. If yields were

reported only for one of this provinces this value has been taken. If no yield was reported for

neither of these provinces the yield for Germany has been taken.

For some years and some products harvest for Hamburg was also reported in tons. In

that case these values have been used as primary data.

Data for some cereals and industrial plants for 1997 to 1999 was summarized in the

statistics for Berlin, Hamburg and Bremen, which also constitute German provinces

(“Stadtstaaten”). Therefore the harvest values for these commodities had to be estimated.

First for all commodity categories concerned the share of agricultural area of Hamburg of all

the cities was calculated from the shown areas in the separated statistics in the year 2000.

The harvest of Hamburg was estimated by dividing the reported harvest (in tons) for all three

cities with this share. If we compare this data with the data for earlier and later years we see

that this approach leads to a serious under estimation. Therefore the harvest for this years

has to be estimated again with another method in a revision.

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For various vegetables, strawberries and garden plants2 only the used area has been

reported in our source (in sum: 1054 hectares for 2001). Yields or production are not

reported. No conversion into production has been made and therefore this group is not

included in the MFA data. For some industrial plants3 also only the area has been reported

(between 2 and 199 hectares for 2000 and 2001). Within the category of fodder plants under

“other fodder plants” only the area is stated (64 hectares for 2001; compared to 967 total

area for fodder plants) and no conversion into production has been made.

Fruits data contains only data for market production (”Marktobstanbau”). For most

fruits the statistics contain the number of trees instead of areas and the yield is reported in

yield per tree (kg/tree). If for the city of Hamburg only the number of trees was reported the

harvest was estimated by multiplying this number with the mean of the yields of

Niedersachsen and Schleswig-Holstein (or only one yield if both were not available).

For some berries (currants, gooseberries, raspberries) only the yield per bush was

reported. No conversion into harvest has been made.

For vegetables grown in greenhouses areas where reported for Germany an all

provinces. Harvest was reported only for Germany. Therefore, the area and harvest for

Germany was used to calculate a value for the yield which was also used for converting the

area of greenhouse agriculture in Hamburg into an estimated harvest for Hamburg.

Production of ornamental plants is also reported in the statistics used but only in

hectares of used area and numbers of plants produced. In 2000 more than 45 million plants

have been produced on an area of 81 hectares. No estimation for the weight of the plants

has been made and therefore they are not included in the material flow analysis.

5.6 Domestic extraction of biomass from forestry

In the (Statistisches Bundesamt various years-e) data for wood extraction is reported

in cubic meters. This data has been converted into weight units by factors taken from (FAO

2001). The data was reported from October of one year to September of the following year

and was for the calculation of the MFA allocated to the latter. At the moment of the

2 „Gemüse, Erdbeeren und Gartengewächse“: Gemüse, Spargel, Erdbeeren ohne Samenbau;

Blumen und Zierpflanzen einschließlich Stauden und Jungpflanzen ohne Samenbau;

Gartenbausämereien, Vermehrungsanbau von Blumenzwiebeln und Knollen.

3 Flachs, „andere Ölfrüchte“, Hopfen, Tabak, Rübsen und Gräser zur Samengewinnung, Heil-

und Gewürzpflanzen, „andere Arten“.

19

calculation no data was available for 2001. Data for 2001 has been estimated by

extrapolating data from the years between 1993 and 20004. Also No data has been available

for 1992. The value for 1992 has been estimated by extrapolating the trend between 1993

and 2000.

5.7 Domestic extraction of biomass – grazing

Biomass from grazing has been estimated using numbers of heads of animals from

(Statistisches Bundesamt various years-e) and factors for estimated daily biomass

consumption per animal. For the years 1997–1999 no new counting for cattle, poultry, sheep

and horses is listed in the source, instead the numbers from 1996 were taken.

5.8 Domestic extraction of biomass – hunting

The number of hunted animals per year is reported in (Statistisches Bundesamt

various years-e). No estimation for the weight of the hunted animals has been made and

therefore biomass from hunting is not included in the MFA.

5.9 Domestic extraction of biomass – fisheries

Data has been taken from (Statistisches Bundesamt various years-b). Data for

extraction of fish which was landed in Hamburg by ship was only available for single years

which made no useful estimation possible for other years. As the total of fish landed amounts

for approximately 250 tons per year out of approximately 1 million tons of Direct Material

Input we consider the mistake as neglectible.

5.10 Imports and exports

Data for imports and exports was available for different modes of transport. For each

mode of transport – except of air transport – data was available disaggregated by commodity

groups. For the MFA the data was then aggregated by commodity groups.

4 For extrapolations the automatic extrapolation function of excel has been used.

20

Data has been taken from the following sources: inland water transport (Statistisches

Landesamt der Freien und Hansestadt Hamburg various years-a), maritime goods traffic

(Statistisches Landesamt der Freien und Hansestadt Hamburg various years-b), railroad

traffic 1997-2001 (Statistisches Bundesamt various years-g), railroad traffic 1992-1996

(Statistisches Bundesamt various years-f)5, road traffic 2001-1997 (Statistisches Bundesamt

various years-g), air traffic (Statistisches Bundesamt various years-d)6.

Data for road traffic for 1994-1996 has been extrapolated from the trend between

1997 and 2001. Data for road traffic for 1992 and 1993 was also available from (Statistisches

Bundesamt various years-a). Here only a single number for total imports/exports has been

reported. As this number was significantly lower than the 1994 number estimated from the

trend between 1997 and 2001 (for example only the imports of stones and earth [“Steine und

Erden”] from the estimation for 1994 and its actual values in 1999-2000 was higher than the

total imports reported for 1992 or 1993). For railroad traffic for 1992 and 1993 data was only

available in total imports/exports. Therefore the values for these years have been

extrapolated from the trend of the detailed data for the years 1994-2001.

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25

Data summary

CODE MATERIALS 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

I N P U T1 Water & Air 0 0 0 0 0 0 0 0 0 01.1 Water for homes and industry1.2 Air

2 Direct Material Input 97.632 97.931 99.430 102.706 102.285 106.130 105.712 116.450 105.191 117.8452.1 DOMESTIC EXTRACTION 68 71 56 168 167 110 119 129 169 1622.1.1 Biomass 68 71 56 168 167 110 119 129 169 162

Agriculture 0 0 0 105 111 55 59 70 113 102Forestry 21 24 14 21 15 14 18 17 12 13Grazing 47 47 42 42 41 41 41 42 44 48Fish 0 0 0 0 0 0 0 0 0 0

2.1.2 Minerals 0 0 0 0 0 0 0 0 0 0Metal ores 0 0 0 0 0 0 0 0 0 0Industrial minerals 0 0 0 0 0 0 0 0 0 0Construction minerals 0 0 0 0 0 0 0 0 0 0

2.1.3 Fossils 0 0 0 0 0 0 0 0 0 0Coal 0 0 0 0 0 0 0 0 0 0Crude oil 0 0 0 0 0 0 0 0 0 0Natual gas 0 0 0 0 0 0 0 0 0 0

2.2 IMPORTS 97.565 97.860 99.374 102.538 102.118 106.020 105.593 116.321 105.022 117.682Biomass and biomass products 17.982 17.487 18.313 19.453 19.014 18.208 19.354 21.369 19.725 20.512Ores and industrial minerals 33.494 33.503 33.297 33.774 31.392 32.028 31.294 34.490 29.480 32.775Fossils and fossil products 17.454 16.658 15.464 15.604 16.492 18.056 17.586 17.287 13.273 17.298Chemical products 9.823 9.671 10.144 9.627 9.225 9.672 9.869 10.074 9.406 9.877Other industry products 15.503 16.990 18.389 19.915 21.924 23.785 23.183 28.488 27.489 29.870Other imports 3.308 3.551 3.769 4.165 4.071 4.272 4.306 4.614 5.649 7.352

3. Indirect and Unused Flows 0 0 0 0 0 0 0 0 0 03.1 Indirect Flows of Imports 0 0 0 0 0 0 0 0 0 03.2 Unused Domestic Extraction 0 0 0 0 0 0 0 0 0 0

O U T P U T4. EXPORTS 79.200 78.562 80.659 81.186 78.585 78.821 81.628 86.362 81.534 85.250

Biomass and biomass products 7.125 6.584 7.431 8.618 7.507 7.051 8.199 10.439 11.913 10.807Ores and industrial minerals 23.307 22.683 22.329 22.342 21.001 21.697 20.895 20.846 18.315 19.396Fossils and fossil products 8.238 8.326 9.038 9.126 9.150 8.898 11.090 11.368 10.898 11.672Chemical products 23.081 22.134 22.088 21.209 20.463 19.011 19.578 21.712 16.012 16.470Other industry products 10.139 10.804 11.290 11.917 12.036 12.475 12.405 12.034 13.166 14.715Other exports 7.311 8.031 8.483 7.975 8.428 9.688 9.460 9.964 11.231 12.190

5. Indirect Flows of Exports 0 0 0 0 0 0 0 0 0 0

PHYSICAL TRADE BALANCE 18.365 19.298 18.715 21.353 23.533 27.200 23.965 29.960 23.488 32.432Biomass and biomass products 10.857 10.902 10.882 10.835 11.507 11.157 11.155 10.931 7.812 9.705Ores and industrial minerals 10.187 10.820 10.967 11.432 10.391 10.331 10.399 13.644 11.166 13.378Fossils and fossil products 9.217 8.332 6.426 6.478 7.342 9.158 6.496 5.919 2.375 5.626Chemical products -13.258 -12.463 -11.945 -11.581 -11.239 -9.339 -9.709 -11.638 -6.607 -6.593Other industry products 5.365 6.185 7.098 7.999 9.888 11.310 10.778 16.454 14.324 15.156Other exports -4.003 -4.479 -4.714 -3.810 -4.357 -5.416 -5.154 -5.350 -5.582 -4.838

I N D I C A T O R SDMI Direct Material Input 97.632 97.931 99.430 102.706 102.285 106.130 105.712 116.450 105.191 117.845DMC Domestic Material Consumption 18.432 19.369 18.771 21.520 23.700 27.309 24.084 30.089 23.657 32.595

C O M P A R I S O N I N D I C A T O R SPopulation (Thousands) 1688,785 1702,887 1705,872 1707,901 1707,986 1704,731 1700,089 1704,735 1715,392 1726,363DMI per capita Hamburg 57,8 57,5 58,3 60,1 59,9 62,3 62,2 68,3 61,3 68,3DMC per capita Hamburg 10,9 11,4 11,0 12,6 13,9 16,0 14,2 17,6 13,8 18,9Gross National Product (million euro 1995) 62219 62214 62734 63456 64156 65392 66861 68076 70098 70994DMI per GDP Hamburg 1,57 1,57 1,58 1,62 1,59 1,62 1,58 1,71 1,50 1,66DMC per GDP Hamburg 0,30 0,31 0,30 0,34 0,37 0,42 0,36 0,44 0,34 0,46

Germany (from Moll et al 2003)DMI 1.734.442 1.730.359 1.838.614 1.798.803 1.780.408 1.767.794 1.756.092 1.770.845 1.737.384DMC 1.530.214 1.528.788 1.615.440 1.574.108 1.542.150 1.518.481 1.496.180 1.505.403 1.463.860DMI per capita Germany 21,5 21,3 22,6 22,0 21,7 21,5 21,4 21,6 21,1DMC per capita Germany 19,0 18,8 19,8 19,3 18,8 18,5 18,2 18,3 17,8GDP (million euro 1995) 1825720 1805887,7 1848266,2 1880206,6 1894611,1 1921019,4 1958596,4 1998678,5 2055774,7DMI/GDP Germany 0,95 0,96 0,99 0,96 0,94 0,92 0,90 0,89 0,85DMC/GDP Germany 0,84 0,85 0,87 0,84 0,81 0,79 0,76 0,75 0,71

Remarks on data summary: At the moment of the publication of this paper domestic extraction of

agriculture for the years 1992-1994 has not yet been included. Domestic extraction of agriculture for the other

years shows remarkable irregularities due to different estimation methods. No corrections have been made until

the time of publication. However, it has to be mentioned that domestic extraction of agriculture accounts only for

about 1 per mille of total DMI and therefore this mistake seems negligible for general conclusions and a

comparison with German MFA indicators. Data for extraction of minerals underlies secrecy.

material flow analysis of the city of hamburg -...

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