Sustainability in Slums Tripple bottom line approach to Dharavi, Kibera, and Khayelitsha

Laleh Gharanjik, Shantaram Parab, Nick Nussdorfer, Mengyu Zhang, Narendra Jhabakh, Aditya Chaganti

12-712: Introduction to Sustainable Engineering

Table of Contents

Summary/Abstract ........................................................................................................................................ 2

Slum Definition ............................................................................................................................................. 3

Problem Definition & Methodology ............................................................................................................. 3

I. Dharavi, India ............................................................................................................................................ 4

Background ............................................................................................................................................... 4

Current issues ............................................................................................................................................ 4

Sustainable Solutions ................................................................................................................................ 5

II. Khayelitsha ............................................................................................................................................... 7

Background ............................................................................................................................................... 7

Environment .............................................................................................................................................. 7

Economy ................................................................................................................................................... 9

Social ...................................................................................................................................................... 10

III. Kibera .................................................................................................................................................... 11

Background ............................................................................................................................................. 11

Environment ............................................................................................................................................ 11

Economy ................................................................................................................................................. 13

Social ...................................................................................................................................................... 14

Conclusion .................................................................................................................................................. 16

Bibliography ............................................................................................................................................... 17

Appendix-A: Dharavi, India ....................................................................................................................... 20

Appendix-B: Khayelitsha, South Africa ..................................................................................................... 23

Appendix C: Kibera, Kenya ........................................................................................................................ 29

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Summary/Abstract

The UN-Habitat organization estimated that 863 million people lived in slum-like conditions in 2012. By 2050 the number of urban residents is expected in increase from 3.5 billion to 6 billion with 96% of the growth will be in developing countries. (LEDERER, 2013) People living in slum conditions use resources in a manner that focuses on survival and not their impact. This use is unsustainable and places a tremendous strain on the environment. The following report takes three case studies for the largest slums in India, South Africa and Kenya and addresses a range of sustainable solutions and their impact on the triple bottom line. There are tremendous opportunities for a wide range of sustainable solutions that vary in scale, price, impact and efficiency. Our goal was to use the framework from David MacKay and Hans Rosling to propose renewable energy options combined with a focus on promoting sustainable growth and ending poverty through societal improvements. We found that promoting sustainable development in these three slums in the form renewable energy production, improvements to sanitary conditions and social infrastructure helped millions of slum dwellers live in better conditions and preserved their local resources for future generations.

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Slum Definition Based on UN Habitat estimates approximately nearly 900 million people live in slums. In some cities up to 80% of population lives in slums. United Nations defines slums as “a clear manifestation of a poorly planned and managed urban sector and, in particular, a malfunctioning housing sector.” Additionally, The United Nations define slums with 5 main characteristics which are: Inadequate access to safe water, inadequate access to sanitation and infrastructure, poor structural quality of housing, overcrowding, and insecure residential status (Housing and Slum

Upgrading).

Problem Definition & Methodology Slums around the world are characterized by burgeoning populations, resulting in increased concentrations of people in limited areas. Given that these populations are predominantly low income groups, finding the resources to meet this demand is a constant problem, a classic case of the tragedy of the commons. Therefore, with respect to the triple bottom line, there is a widening gap between the metrics of these slums, relative to national averages.

The three slums, Dharavi (India), Khayelitsha(South Africa) and Kibera(Kenya) were selected based on their diversity and their negative impacts on society, economy and environment, the triple bottom line approach. Current issues including energy production, energy consumption, socio-economic conditions were analyzed (Rosling’s approach) and proposals were arrived upon based on estimation using MacKay’s approach to estimating energy consumption in a slum.

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I. Dharavi, India

Background The slum of Dharavi India is a lesson on sustainability. It provides many negative examples of people living with a lack of concern for the environment and the synergy of negative effects of exposure for the people living there. A substantial investment by the Indian government to promote sustainability in the small but dense community would have a great impact on the quality of life, the economy and the environmental conditions of over one million people in India’s largest city. Dharavi was originally a small fishing community in Mumbai along the banks of the Indian Ocean. People came for work and as the neighborhood grew in population, conditions grew worse. Fishermen depleted stocks of fish and the abundance overcrowding of people polluted the waters and depleted the source of their livelihood. The crowded former fishing village was forced to adapt to survive and switched industry over to pottery, leatherworking and small industrial operations. The slum became home to an estimated 1 million people living in an area of 223 hectares, roughly three times the city of Pittsburgh packed in an area smaller than Central Park. (Sendin, 2011) Dharavi is roughly ten times denser than the city of Mumbai in which it is located. Current issues Pollution The dense agglomeration of people in Dharavi strains the local environment. Resources are used and discarded based on economics and utility. The lack of concern for their surroundings degrades health and environmental conditions. Pollution from industry, sewage and burning combustibles are the main sources of air and water pollution. The lack of sanitation contributes to human waste runoff directly into the nearby Mithi River which discharges into the Arabian Sea. Water monitoring readings indicate that biochemical oxygen demand (BOD) and chemical oxygen demand (COD) are highest at sites around Dharavi and exceed 50 mg/L (BOD) and 300 mg/L (COD) (Avdhi ShahA, July 2014). Air pollution is also an issue, both from industry and household use. Particulate matter (PM10) is highest (in excess of 240 micro g/m3) in Dharavi due to smelting, biomass burning, coal combustion and burning kerosene (Institute, NOV 2010). Air quality is also degraded from the local pottery colony where large outdoor kilns emit CO2, CO, NO2, lead, arsenic and other heavy metals (News). Social Cost due to CO2 emissions from Kerosene burning

• The social cost for burning Kerosene in Dharavi households is $2 million USD/ 120 million Rupees per year (see appendix A for calculations).

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Sanitary Conditions • Dharavi is infamous for its lack of sanitation and poor hygiene. It has a reported 162 taps

for water, which are usually blocked, and 842 sanitation facilities, which equates to around one toilet for every 150 people (TISB, 2011). The poor environmental and sanitary conditions contribute to a high prevalence of waterborne and other diseases such as malaria, typhoid, cholera and other forms of dysentery. The nearby public Sion Hospital reports over 3,000 patients per day that arrive from Dharavi (YARDLEY, 2011).

Sustainable Solutions Energy production:

• Decreasing the amount of people burning kerosene and switching over to abundant renewable energy production will provide sustainable solutions for power generations while helping to decrease particulate matter air emissions.

• The table below illustrates three renewable options for power generation for Dharavi: Renewable Energy Source Result Analysis Wind 1.1 watts per square meter

of land 17 kW per wind turbine

Relatively low wind speed and small land area do not make wind turbines a viable option-offshore turbines might work slightly better

Tidal 926 kWhr per tide Mumbai is a busy port and does not generate much power from a 3m tide rise

Solar 900 kWh of energy per square meter of solar panel on an annual basis

Great latitude and abundance of sunny days makes this a viable option

Analysis The southern latitude of Mumbai and the high solar insolation makes solar the best energy option for Dharavi. A single square meter solar panel, assuming we can increase efficiency up to 50% conversion of the suns energy, will produce 1.5 times the average use of energy for the average Indian citizen. This is a huge success for a community that only uses a fraction of electricity when compared with the rest of India. Tidal power is not a great option because the port of Mumbai is used heavily for commerce and will not generate a large amount of power with each tide. Dharavi does not have room for wind turbines on land but offshore wind generation could be an option. However, the low wind speed does not make wind a great option. The average energy consumption of a person in India is around 681 kWh/per capita per year (1.9 kWhr/m2/day) while an average family of 5 people in Dharavi use approximately the same amount (Electric power consumption (kWh per capita)).So one square meter of solar panel will provide around

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130% of the current families requirements while reducing the air emissions from burning kerosene. New Technologies

• The Carbon dioxide emission from the Kerosene burning is a major air pollution issue in Dharavi as calculated previously. The social cost due to emission from the use of Kerosene for various purposes is nearly $2 Million per year. A solution to this problem is to install LED bulbs in households to reduce the environmental impact.

• Cost of LED Light ≈ $8/bulb Assuming 3 LED’s are installed per household, Total Cost of installing LED’s = $8 X 3/household X 200,000 households ≈ $5 Million

• Considering the fact that the usage of Kerosene for lighting purposes will greatly reduce, there will be a saving of $2 Million every year. Hence, the payback period for the investment in LED’s will be around 3 years. Additional benefits also include a better air quality, which would reduce any ailments occurring due to bad air quality.

Environmental and Sanitary Infrastructure Waste Water

• To help improve sanitary conditions in Dharavi a waste treatment plan of around 1 million gallons per day is required. This treatment facility will help curb the raw sewage effluent polluting the nearby waterways with excessive BOD and will help improve the sanitary conditions of hundreds of thousands of residents by decreasing the prevalence of waterborne diseases. The cost of treating 3000 patients per day for dysentery illness will offset the costs of waste treatment infrastructure and maintenance.

• Installation Cost of a 100 MLD capacity Treatment plant ≈ $11.5 Million (India waterportal,

2008) • In the case of Dharavi, a treatment plant of 10 MLD capacity. This assumption was

made taking into account the total sewage generated (as calculated in Appendix A) plus the future increase in the water consumption.

• Using a social discount rate of 4% per year, the cost of Investment in the Waste Water Treatment Plant will break even i.e. will be a profit after 12 years. In addition to the profit, Dharavi will become a much cleaner and a more habitable place. The living conditions will certainly be better and will be accompanied by very high social benefits

Water Supply • Rainwater capture can also help improve the supply of water to the slum. Mumbai

receives and abundance or rainwater during the summer monsoon months and using a 10% capture rate, can supply 1/3rd of the annual water requirement for people living in the slum (see Appendix A for calculations).

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II. Khayelitsha

Background Khayelitsha is a partially informal township located in Cape Town, South Africa, a slum of around 350,000 people. It was formed as a result of the Group Areas Act, passed in 1950 under the apartheid government of South Africa that segregated cities on ethnic lines. The act, in effect, excluded non-whites from living in the most developed areas, and was discriminatory in nature. Plans to build Khayelitsha were announced in 1983, primarily in view of two problems: growing migrants from the Eastern Cape, and overcrowding in other segregated townships in the city. The slum has seen steady growth ever since, although it is seen by many as a dark reminder of the apartheid era given the fact that it still lags considerably with respect to critical human development indices. Environment Khayelitsha is one of the poorest parts of the city of Cape Town, and severely lags behind on a number of indicators that reflect the standing with respect to the Environment, and related factors. The issues discussed in the study include the following:

• Energy Use and Consumption Practices in Khayelitsha: A quantitative estimate of monthly energy use per household, and the entire slum. Sources of energy (Fuels) Exploring effectiveness of a move towards renewable sources of energy-

MacKay’s Model Estimating cost, and cost effectiveness of the proposed model Recommendations

• Sources of Air pollution

Energy Use and Sources The monthly household fuel consumption estimated by scaling up from the Khayelitsha Energy Survey, 2004 is as follows: The per household energy consumption per month was estimated:

Fuel Consumption/month kWh Consumption Electricity 195 kWh 195 Paraffin 14 liters 141 LPG 9 kg 115.25

The following estimates were arrived upon, building on the estimates already presented above:

• The total energy consumption per household (renewable energy serviceable) is estimated to be 450 kWh/month.

• Estimated monthly household income in the year 2014 is equal to R5600≈ $500. • Fraction of income spent on energy consumption: 12.3 %

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• Estimated total energy requirement for the slum: 53.5 Million kWh/month

Sustainable Options: Renewable Energy production • Alternatives such as nuclear, wind, hydroelectric, wave, tide and geothermal power, by

virtue of their costs would require significant investment on part of the government. Setting up facilities exclusively for Khayelitsha would be economically inefficient, and thus, each one of these services would have to be made available for a larger population (also covering Khayelitsha) if implemented. However, government policy and decisions fall outside the gamut of this study, and we therefore assume solar power to be the only plausible renewable alternative

• Estimated energy Generation per m2 per day for solar panels is 6.31 kWh/m2/day (NASA

Surface meteorology and Solar Energy ) • Area required to install solar panels to supply energy to Khayelitsha≈0.3 million m2 • Area per household = Area required/Number of Households

= 0.28*106/118809 ≈ 2.4 m2 • Therefore, solar panels would have to cover only about 0.64% of Khayelitsha’s area in

order to supply renewable energy to all households. Problem Definition: Social Cost of Non-Renewables The CO2 emissions per kWh of energy produced is as follows: Coal Power

• Generating electricity from coal emits 0.89 kg of CO2 per kWh electricity produced. • CO2 emissions = 38.5*106*0.89 ≈ 34.3 million kilograms of CO2

Oil Power

• Generating electricity from oil emits 0.25 kg of CO2 per kWh electricity produced. • CO2 emissions = 11.8*106*0.25 ≈ 3 million kilograms of CO2 • Combining the two, it is estimated that CO2 emissions forgone would be in the tune of 37

million kilograms/month, or 37,000 tons/month if solar power is adopted to power all households.

Sustainable Energy Solution: Solar PV • Using 6 ReneSola : Virtus II 300W : Solar Panels would generate 1800 Watts, close

enough to the demand. Each of these panels, including value added tax costs R 3,504≈$310. Six of these, would therefore cost R 21,024≈ $1900.

• Total cost for all the households in Khayelitsha= 21,024*118,809 = R2.5 Billion≈$220 Million

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• Government costs for this project would be in the range of $200 Million - $210 Million given that subsidies are granted so that residents only pay $60 which ranges up to 30% of their current budgeted amount which was initially 12% of the amount spent on energy.

• This estimate was made not factoring in interest free loans that a government might provide to citizens to repay the entire amount. However, given that the households pay $60/month on energy, it would take them, on a loan that charges the same amount per month and free of interest, 30 months, or 2.5 years to repay this amount. This seems a reasonable time-frame, given that in the long term, there will be minimal operational and maintenance costs associated with solar power. There would need to be further investment into outreach programs aimed at convincing people of the need to make this change.

Economy An assessment of the following parameters was carried out:

• The proportion of shacks in this slum. • The household income in this slum. • Gini coefficient of the slum, to assess income disparity. • Job profiles-Skilled labor versus unskilled labor.

Housing

• Around 70% of Khayelitsha’s residents still live in shacks. Shacks lack the durability and weather adaptaability that permanent structures possess. They are also typically very small in area (Landgren, Funk For Life moves to Khayelitsha, South Africa.!, 2013).

Household income

• Average Household Income of Khayelitsha is $1900/year, as compared to the provincial average income of $6900/year in year 2001.

• Gini coefficient of Khayelitsha is 65.31, slightly higher than 65 of South African in year 2014. This, therefore represents an income disparity within the slum, a measure that is on par with the national average. The worrying aspect of this, however, is the fact that given the lower than average incomes in the slum, an income disparity of this size implies the presence of acute poverty among certain sections of the slum population. The following table and chart is the calculation process of the Gini coefficient (The World Bank, 2014).

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• A large percentage of the employed population in Khayelitsha is trained in unskilled

labor, and service work. The following two tables are the detailed working information in Khayelitsha (Dr Johannes Erasmus, 2003).

Recommendations • Increased investment in the academic system, aimed at fostering interest in skilled

professions and promoting diverse interests. • Existing social welfare schemes are not optimal and must be sustained and improved • A policy framework aimed at inculcating a self-sustaining framework to incentivize

collaboration across income groups within the population of Khayelitsha. • Encouraging increased external economic investment in the significantly underpaid

human capital of Khayelitsha.

Social Current Issues:

• Khayelitsha carries one of the highest burdens of both HIV and tuberculosis (TB) in the country. 20% of the total population is HIV infected; 1,000 new people find out that they are HIV positive every month.

• Thirty percent of the population are children under the age of 14, and 46% of the total population is between 15 and 34. The ratio man to women is approximately 50:50. Over 70% of the population lives in informal housing (shacks), with the remaining one-third in brick structures.

• The literacy rate approximately 94%. More boys than girls attend primary school. Overall, 70% of the people have obtained their Junior Certificate and an estimated 25% of the population has graduated from high school. There is no gender disparity in high school graduation (Landgren, Funk For Life moves to Khayelitsha, South Africa, 2013).

• Demographics: 76.7% of people in Khayelitsha are Christian, 0.2% of them are Islam and 20.5% of them do not affiliate themselves with any religion. (The Unit for Religion and Development

Research, 2003)

y = 5341.5x4 - 7270x3 + 2889.2x2 - 151.08x + 0.4327

-200

0

200

400

600

800

1000

0% 20% 40% 60% 80% 100%

Khayelitsha

baseline

Log. (Khayelitsha )

Linear (baseline)

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• According to South Africa's 2013 crime statistics, Khayelitsha has the highest number of reported crimes for murder, sexual crimes, attempted murder and assault (Khayelitsha

Commission, 2014).

Recommendations • Investment in bridging relations between enforcers and civilians to ensure a dynamic,

cooperative framework that would help improve law enforcement in Khayelitsha. • Given that a significant proportion of the population affiliate themselves with

Christianity, investment in collaborative educational programs with churches could be adopted. This effort would be ancillary to the larger educational program, previously stated, that would have the objective of propogating education centered around a system that is based on emphasizing on skilled learning.

• Renewed efforts towards improving the efficiency of public outreach programs aimed at mitigating the spread HIV, while also reducing the incidence of new cases.

III. Kibera

Background Kibera is one of the largest slums in Africa with an average population of approximately more than six hundred thousand people (Appendix C: Figure 1) over an area of 2.5 square kilometers and is approximately five kilometers away from the city. It was a settlement in a forest outside Nairobi and as a result of World War I it became a resettlement area for Nubian soldiers returning from service. The government then, allowed settlements to grow and opened gates to other tribes from across the country. Environment Environmental issues:

• Energy: The primary source of energy for the slum dwellers is obtained by burning either kerosene or biomass (wood and charcoal). It is inefficient but causes air pollution due to incomplete combustion. Inefficient cooking practices have serious implications for the environment, including land degradation and local and regional air pollution. Fuel wood is not gathered sustainably.

• People live with and inhale the smoke generated from cooking and heating fires. The most recent estimates, which are part of the Global Burden of the Study (Horton, 2010), indicate that approximately 20% of the people die prematurely each year from illness attributable to household air pollution due to biomass and coal cooking fuels.

• Solid Waste Disposal: Without access to public infrastructure services, residents rely on the river water source of relief. Open defecation and the infamous “flying toilets” are

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common alternatives for the slum dwellers without latrine access, littering walkways and rooftops.

• Issues pertaining to Water: Most slums dwellers have three major problems with respect to water: access, cost and quality. There is limited access to water points, which are located far from their houses, some landlords ration the water such that it is only available on specific days of the week and at specific times (Emmanuel MUTISYA, 2011). Most slums dwellers use sewerage water for bathing and washing. They also use borehole, rainwater water from broken pipes, which is highly contaminated and filthy. During the two rainy seasons the river rises, brought the wastewater flowing into homes thus spreading water- and vector-borne infectious disease

Environmental Proposals: Energy

• Based on a MacKay estimate (MacKay, 2008), the average daily energy usage by a slum dwelling (shack consisting of 7-8 people) is in between 20-25 kWh per day. This figure is arrived at by summing the energy usage (Stephen Karekezi, 2008) for activities including:

• Heating/Cooking: 10-15 kWh /day • Commercial activities (construction/industrial): 8-10 kWh /day (20% of the estimate

which is used in the case for United Kingdom citizens in proportion to the GDPs). • One of the major problems in Kibera is solid waste disposal. Assuming that an average

person produces 300 grams of volatile waste in a day (Poo power: turning human waste into clean energy in

Kenya's slums). • Using it as an input into a Bioreactor, the amount of energy produced on a daily basis per

shack would be around 15-25 kWh (Cook, 2010). This would also decrease the emissions due to burning kerosene oil and biomass.

• Although this would lead to the burning of biogas as fuel the emission released would be considerably low.

• Assuming the daily usage of power is around 25 kWh (higher limit for worst case), and that 60% of the usage is from Kerosene, 30% that of charcoal, while the rest 10% is from other sources. This would result in 7.5 kg of CO2 released into the atmosphere ( Volker

Quaschning) for every shack per day. • It’s given that there are 30,000 of these shacks in Kibera, which would result in around

200 tons of CO2, produced each day. This would be reduced to less than 25% of initial amount if natural gas were burnt.

• Also, installing a Bioreactor would be very cost effective due to the fact that one bioreactor can serve around 1000 residents, hence can be shared by 125 shacks and the cost of a bioreactor for this capacity is $7,000-$10,000 (LABX) leading to a total cost of a meager $1.7 million.

• Solar power was not considered due to the fact that, only 10-20% of the slum dwellers have electricity and there are hardly any grid lines in Kibera. Also the costs of a Solar PV

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system is high and not feasible as it is already difficult for the government to make ends meet given that Kenya is one of the poorest countries with a very high inequality index.

• Wastewater Sanitation: Given that there is a high pressure on land usage and area, in-situ wastewater treatment plants, would be a very good option.

Economy Kenya’s Gini coefficient was approximately 42 in 2008 and 2013 GDP was approximately $80 billion. 45% of population lives under poverty line and unemployment is 40%. Generally Kenya is one of the poorest countries in the world and Kibera and other slums economic conditions should be analyzed in this context. Slums in Nairobi are result of explicit government policies and inequity in the society. In Nairobi the government did not recognize slums as official residential areas for decades and did not provide essential services for them. (MUTISYA & YARIME, 2011) Economic and social issues as well as environmental problems are extremely integrated and the incidence of social misbehaviors undermines both macro and micro economic growth and productivity of a country’s development (UN Habitat 2007). Thus, studying the economic problems is critical for Kibera and other slums. Kibera Current Economic issues

• Low income: The average income in Kibera is less than a $1/day, which is significantly lower than poverty line. (Facts and information about Kibera)

• Unemployment: Kibera is located near the industrial area of Nairobi and approximately 50% of the available workforce is employed in the neighboring industrial area. However, the unemployment rate is about 50%. Most of the residents have fairly unskilled jobs. (Facts and information about Kibera)

• Environmental costs, Externality: Mentioned environmental issues in the environment section result in high external costs. Some of these costs include cost of emissions and medical costs.

Proposals • Increasing job opportunities: By providing education and teaching professional skills to

slum residents they could work in the neighboring industrial area. In Kenya 17.4% of GDP is generated by tax (The World Factbook, Kenya). Job creation would generate tax revenue.

• Supporting Home-based Income generating activities and Small and Micro Enterprises (SME). (Labor Markets & Employment)

• Environmental improvements: Implementation of environmental proposals will result in less externality and environmental costs. The social costs of emitting harmful gases based on that the status quo costs would be approximately $20 million per year. By using renewables these costs would be cut down by a large amount.

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Social Kibera slum has profoundly problematic social conditions. There is improvement going on by international and charitable organizations, however it is inadequate. Following are some of the problems and some proposals for enhancing the situation: Current issues

• High HIV/AIDS Rate: Africa is the global epicenter for HIV/AIDS and youth (15-25) consist half of the new reported cases of HIV. 6.1% (2012) of total population in Kenya is HIV Positive (The World Factbook, Kenya). About 150,000 to 250,000 of the 2.2 million HIV positive Kenyans live in Kibera. Another estimate shows that 20% of people between 15-49 years old are HIV positive in Kibera. There are over 40 charitable organizations working on HIV prediction and treatment in Kibera (Oballa, 2007). However, there are no governmental hospitals or clinics in Kibera for providing health services. (Facts and information

about Kibera) • High Infant Mortality Rate: Table below shows infant mortality rate for Kibera, Kenya

and some developed countries. As shown in the table Kibera has a significantly high infant mortality rate. (Facts and information about Kibera)

• Child Labor: Some estimates show that 50-75% of Kibera’s population is under 25 years

old (Facts and information about Kibera) and 25% of boys and 15% of girls work. (Kibera, Shining Hope for

Communities) • Lack of Education and Literacy: Literacy rate range in Kenya is between 75%-85% (Oballa,

2007) (The World Factbook, Kenya) which is lower than global average. Many families in Kibera could not afford education for their children. According to Oxfom study in 2003, 37% of children do not have access to education. 30% of remaining are provided with free formal primary school and 70% have limited access to non-formal schools and community centers. Child labor and poverty are the most important impediments for education in Kibera. (Levene, 2006) A good example of new efforts for improving education in Kibera is the Kibera School for Girls (KSG) which was founded in 2009 and is the slum’s first free

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primary school for girls and serves 180 students in pre-K through 5th grade. (The Kibera School

for Girls) Table 1 in appendix shows number of facilities in each village of Kibera.

• Low life expectancy: The life expectancy in Kenya is 48 years for women and 46 years for men (Oballa, 2007). Based on WHO estimates, the life expectancy in Kibera is 35 years, which is significantly lower than the country’s average and global standards.

• Lack of Women rights: 43% of sexually active female adolescents living in Kibera reported that their first sexual experience was forced. Also girls have less access to education (43% of girl’s verses 29% of boys) 54% of women and 23% of men living in Kibera have no reliable source income. (Kibera, Shining Hope for Communities)

Proposals • Providing vaccination and health services: For HIV and other diseases prevention a

combination of medical and educational methods should be implemented. Based on WHO estimates, 70% of early child deaths in the developing world are preventable with basic healthcare. Currently some charitable organizations such as AMREF, MSF, and churches provide some of the health services including free HIV test and free generic ARV medicine (Facts and information about Kibera) which is not adequate. More vaccination and health services should be provided especially by governmental entities for Kibera.

• Education: Both physical infrastructure and cultural preparation should be provided for Kibera. Physical infrastructure includes schools and cultural preparation means overcoming cultural and traditional education barriers especially for girls. Based on our estimates Kibera needs 290 more schools.

• Cultural improvements: More cultural centers such as libraries should be provided for Kibera. Based on our estimates Kibera needs minimum of 30 more libraries and cultural centers. (Housing and Slum Upgrading)

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Conclusion

Slums across the world share similar characteristics but the multitude of solutions all tie together in support of the triple bottom line. Solutions often have a synergistic effect on the human condition; investments in sanitary infrastructure and renewable energy also aid pollution prevention while helping improve public health. Different geography, social conditions, and resources required different approaches that are summarized below:

Citizens of Dharavi, India are using resources for survival. The expense of their consumption is the health of their neighbors, themselves and the surrounding environment. As the local Koli fishermen once depleted and polluted the fish population, Dharavi will continue to tax the environment beyond its carrying capacity unless a substantial investment by the Indian government reverses the trend through a focus achieving a sustainable future for Asia’s second largest slum. Feasible options most applicable are renewable power generation, reversing the pollution trends through wastewater treatment and capturing rainwater for potable water supply. These will ease the strain on the environment around the slum and improve sanitary conditions and the health of over a million Indians.

Similarly, Khayelitsha, South Africa faces significant challenges with respect to human development and long-term sustainability. These issues are surmountable given concerted efforts on the part of policy makers and citizens. The recommendations stated are the adoption of solar energy, renewed efforts towards implementation of the Khayelitsha Air Pollution Act, and investments into social welfare and education to move towards supporting the three pillars of sustainability for 350,000 people in South Africa.

The other African slum analyzed, Kibera, Nairobi, has slum dwellers living in extremely poor conditions but with slightly difference challenges. Open defecation is one of the biggest problems, so the usage of Bio-reactors is the most viable options to both control pollution and generate energy. This intervention would also cut down external costs due to emissions. Additionally, Kibera dwellers suffer high rate of HIV/AIDS, lack of education, low life expectancy and lack of women rights. Infrastructure improvements, such as providing sanitation, education and heating are critical for Kibera. Prioritizing the mentioned proposals in the report based on cost effectiveness of each option is extremely important for both governmental entities and charitable organizations. Providing health services is the first priority for this slum.

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Oballa. (2007). Experiences and Perception of Youths towards HIV/AIDS Prevention Campaigns in Kibera Slums: Nairobi Kenya. Retrieved from Universitetet i Oslo: https://www.duo.uio.no/handle/10852/30152

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Sendin, P. (2011, March). Dharavi, Mumbai: The Future of Asia's Second Largest Slum. Retrieved from http://www.patriciasendin.com/2011/03/dharavi-mumbai-future-of-asias-second.html

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Appendix-A: Dharavi, India Social Cost of Burning Kerosene:

• Average use of Kerosene per household = 25L per month (Rao, 2012)= 300L per year • Population in Dharavi = 1 million • Assume 5 people per household, hence total households = 200000 • Therefore total Kerosene used = 60 million liters • Total CO2 emitted = 60 million X 2.5 kg CO2 per litre = 150 million kg = 165000 tons • Social cost of CO2 emissions = $12/ton (EERE, 2007)

• Hence Cost of Emissions = 165000 X 12 $/ton = ~ $2 million per year

Renewable Energy Sources Calculations Wind Power

• Geographical Data: • Average wind speed of 4.77 m/s (Wind Speed Data) produces 1.1 Watts/m2 of land area • Calculations (MacKay, 2008): • Power per square meter: 1

2𝑝𝑣3 = 1

2(1.3)(4.77)3 = 70 𝑊 𝑚2⁄

• Power of single wind mill = efficiency x power x area • 50% 𝑋 1

2(1.3)(4.77)3 𝑋 𝜋

4(25)2 = 17 𝑘𝑊

• Power per wind mill/land area per wind mill:

• 12𝑝𝑣3 𝑋 𝜋

8𝑑2

5𝑑2= 0.016 𝑋 (70 𝑤 𝑚2⁄ ) = 1.1𝑤 𝑚2⁄

Tidal Power

• Geographical Data: tidal rise in Mumbai Harbor is 3m (Weather details) • Result: power density of 2 w/ m² • Size of Mumbai harbor: 46.3 hectares (463000 m²) • Power generated from Tidal power for the port of Mumbai (MacKay, 2008): • (2𝑤 𝑚2⁄ )(463000 𝑚2) = 926 𝑘𝑊ℎ𝑟 𝑝𝑒𝑟 𝑡𝑖𝑑𝑒

Solar Power

• Geographical Data: • Mumbai is 19 N (degrees latitude) • Solar insolation annual average: 5.90 (kWh/m2/day) (Solar Insolation)

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• Assume a 50% efficiency = 2.9 kWh (kWh/m2/day) • Using 1 square meter solar panel and 310 days (of sun) per year = 900 kWh of energy per

(MacKay, 2008)square meter throughout the year

Sanitary Infrastructure Calculations Waste capacity calculations (Rode, 2013):

• 𝑇𝑆 = 𝑇𝑊 ∗ 𝑆𝑊100

• TS: total sewage • TW: total water supply • SW: proportion sewage • 𝑇𝑆 = 40 𝐿𝑝𝑑 ∗ 10

100= 4.0 𝐿𝑝𝑑 ∗ 1 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 𝑝𝑒𝑜𝑝𝑙𝑒 = 4𝑀𝐿𝑃𝐷 ~1𝑚𝑖𝑙𝑙𝑖𝑜𝑛 𝐺𝑃𝐷

Economic considerations for WWTP • Installation Cost of a 100 MLD capacity Treatment plant = ~ $11.5 Million (India

waterportal, 2008) • In the case of Dharavi, a treatment plant of 10 MLD capacity. This assumption was

made taking into account the total sewage generated (as calculated in Appendix A) plus the future increase in the water consumption.

• Hence, the Installation Cost for a capacity of 10 MLD = ~ $1.2 Million • Cost of operation of a 100 MLD plant =~ $340,000/month (Cost Water) • A plant of 10 MLD capacity, the operation cost ~ $35,000/mo or $420,000/yr • Therefore, total 1st year Investment = $1.6 Million • Amount saved by developing WWTP infrastructure: assume the cost per checkup of a

patient due to water borne disease = $1 (since cost of medical treatment in India is very low)

• Also, assuming that the number of patients treated in a day will reduce by 50% due to the clean water supply from the Treatment Plant.

• Therefore, we used the savings from treating a lower number of patients for waterborne diseases to offset the operational costs of operating a wastewater treatment plant.

• Cost savings due to the lower number of patients treated in a day = 3000*0.5*$1 = 1500

• Hence, total cost saving in a year = 1500*365 =~ $550,000 • Using a social discount rate of 4% per year, the cost of Investment in the Waste Water

Treatment Plant will break even i.e. will be a profit after 12 years. In addition to the profit, Dharavi will become a much cleaner and a more habitable place. The living conditions will certainly be better and will be accompanied by very high social benefits

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Rainwater Capture

• Dharavi’s high annual precipitation as reported from the Regional Meteorological is 220 cm. (Regional Meteorological Centre, Mumbai, 2014)

• 10% of land (22 hectares) = 22,000 m² X 2.2 m of rainfall = 48,400 m3 or 48.4 X 106 L • This volume of water per year accounts for 48.4 L per person captured during the

summer monsoon season. • Using capture devices of 10% of the slum’s land area would provide enough water for

1/3rd of the annual requirement of the average Indian citizens water need of 135 L/day. (Average Water Use - India)

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Appendix-B: Khayelitsha, South Africa

Cost Effectiveness Study of Renewable Energy Sources

It is important to remember that the effectiveness goal of this project is to completely power Khayelitsha with renewable sources. Therefore, any analysis to maximize cost effectiveness would have to be aimed at minimizing the costs associated with each technology. Towards this end, the decision context is measured in terms of three plausible scenarios:

a) A single renewable source to power the entire area. b) A mixture of renewable sources to power the entire area. c) Status Quo

Estimation of Current Energy Consumption in Khayelitsha:

Statistics for this discussion were taken entirely from the Khayelitsha Energy Survey.

• The monthly household consumption of fuels is as follows: Fuel Median Consumption

Per Month Number of Households

Electricity 195 kWh/month 152 Paraffin 14 litres/month 168 LPG 9 kg/month 18 Candles 6/month 77

The survey has a sample size of 226 households. Assuming the fuel use trends hold good for the larger population in Khayelitsha, the usage statistics for the number of households using a particular fuel can be arrived upon for the entire slum.

From the above table, inferences can be made pertaining to the percent of the total sample that use a particular fuel. These percentages then applied to the entire slum would then give us an estimate of the energy use of the slum.

Fuel Number of Households in Sample

Total Number of Households in sample

Percentage of Households that use fuel

Total Number of Households in Khayelitsha

Number of Households that use fuel

Electricity 152 226 67 118809 79602 Paraffin 168 74

87919

LPG 18 8 9506 Candles 77 34 40395

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Although documented, candles are at this point assumed not to contribute significantly to the steady annual energy consumption. This assumption is made given that it is likely that they are used only in situations where other sources of energy were rendered unavailable, and if not, are used for purposes other than acting as a substitute for electricity. Without the end use information, it is difficult to accurately assess whether it makes sense accounting for these when considering replacement with renewable energy.

The total Per Household Energy Consumption:

Fuel Consumption/month kWh Consumption Electricity 195 kWh 195 Paraffin 14 litres 141 LPG 9 kg 115.25

Therefore, the total energy consumption per household (renewable energy serviceable) is estimated to be the sum of the three kWh consumptions above, that is, 450 kWh/month.

It is important, at this point, to note that these figures are arrived upon using statistics from a survey conducted in 2004. However, given the lack of sufficient data subsequent to that, it is assumed that energy use patterns (source, and magnitude) have not changed considerably since then. The power tariff incurred by a household consuming 450 kWh/month (2014-15 value) is R691.34, approximately a 600% increase from the power tariffs being incurred by households in 2004, as stated in the Khayelitsha Energy Survey.

It is plausible that there are a number of people in Khayelitsha who consume less than 200 kWh/month on an average, especially given the disparity in income among residents. However, a lack of data pertaining to the same has led us to assume that no residents of Khayelitsha are beneficiaries of this scheme.

This study therefore, by virtue of the assumptions made in the previous two paragraphs, establishes a baseline scenario, or a worst case. It is highly likely that ground reality is a lot better than that stated here. However, establishing a worst case serves well for the purposes of an analysis.

Estimation of monthly income per Household

The average monthly per capita income per household in Khayelitsha was approximately R3700 as per a study conducted in 2008. In 2001, household income per year was $1918, or $160/month. In 2001 values, that is equal to R 1900/month. (Based on U.S Dollar to Rand exchange rates as per December 30th , 2001)

The average inflation rate in South Africa between the years 2001 and 2008 was 5.3%.

Therefore, the real household income in 2008 normalized to 2001 values=3700/(1.053)8 = R2448

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Therefore, the annual rate of growth of income is given by the following formula:

Present value=Future Value/(Rate of Growth)no. of years

1900=2448/R8 = 3.2 % per annum

Therefore, the 2014 estimate for household income, normalized to the 2001 value= 1900*(1.03)13= R 2868.1

The average interest rate from 2001 to 2014 is 5.3%.

Therefore, an estimate of monthly household income in the year 2014 is given by;

Income/month=2868.1*(1.053)13= Approximately R 5600.

Fraction of income spent on energy consumption= (691.34/5600)*100 = 12.3 %

Households in Khayelitsha are therefore estimated to have spent approximately 12% of their monthly income on energy consumption considering the three primary sources, i.e, Elecricity, Parrafin, and LPG.

Estimate of the energy requirement per month in Khayelitsha

As per 2011, there were 118,809 households in Khayelitsha.

Thus,

Estimated total energy requirement for the slum per month

=Energy consumption estimate per household * Number of households

= 450*118809= 53.5 Million kWh/month

Possible Renewable Energy Sources:

Most renewable energy discourses talk of particular energy sources in reference to renewable sources of energy that could be used to replace existing conventional energy sources. These are as follows:

• Wind • Solar • Biomass • Hydroelectric • Wave • Tide • Geothermal

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However, alternatives such as wind, nuclear, hydroelectric, wave, tide and geothermal power, by virtue of their costs would require significant investment on part of the government. Setting up facilities exclusively for Khayelitsha would be economically inefficient, and thus, each one of these services would have to be made available for a larger population (also covering Khayelitsha) if implemented. However, government policy and decisions fall outside the gamut of this study, and we therefore assume solar power to be the only plausible renewable alternative.

Nuclear energy is not considered due to recent global resistance to the idea of making nuclear reactors central to sustainable policy. It is questionable if they indeed are sustainable sources of energy, and therefore, have been overlooked.

Energy Generation Through Solar Panels

Energy Required (kWh/month)= Energy generation per m2 per day*30*Area

Estimated energy required= 53.5 million kWh/month

Energy Generation per m2 per day for solar panels placed at a 31.1 degree tilt (optimal) on the coordinates 33.9253° S, 18.4239° E (Coordinates of Cape Town)=6.31 kWh/m2/day

Therefore,

53.5*106=6.31*30*Area (m2)

Therefore, Area required to supply energy to Khayelitsha=0.28 million m2

Area per household = Area required/Number of Households

= 0.28*106/118809 = 2.4 m2

The area of Khayelitsha is 44 km2, or 44 million m2

Therefore, solar panels would have to cover only about 0.64% of its area in order to supply renewable energy to all households in Khayelitsha.

This suggests that on itself, solar energy is entirely capable of powering all households in the slum for the baseline case, thus resolving the issue of power consumption through non-renewable sources of energy.

South Africa generates 72% of its electricity using coal, and 22% using oil. (REFERENCE) Assuming power supply for Khayelitsha follows the same proportional split;

Coal Power consumed/month = 72%*53.5*106= 38.5 million kWh

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Oil Power consumed/month = 22%*53.5*106= 11.8 million kWh

Estimate of Externality

From David MacKay’s book, ‘Sustainable Energy-Without the Hot Air’, the CO2 emissions per kWh of energy produced is as follows:

Coal Power:

Generating electricity from coal emits 0.89 kg of CO2 per kWh electricity produced.

Therefore, CO2 emissions = 38.5*106*0.89 = 34.3 million kilograms of CO2

Oil Power:

Generating electricity from oil emits 0.25 kg of CO2 per kWh electricity produced.

Therefore, CO2 emissions = 11.8*106*0.25 = 3 million kilograms of CO2

Combining the two, it is estimated that CO2 emissions forgone would be in the tune of 37 million kilograms/month, or 37,000 tons/month if solar power is used to power all households in Khayelitsha.

Cost Estimates

The aim of this estimate is to calculate the wattage of solar panels required per household in Khayelitsha, and the costs associated with the same. A solar panel wattage calculator was used. The estimated power consumption per household (450 kWh/month), 100% powering, and assuming 8 hours of peak sunlight per day were the basic metrics used to calculate the wattage required.

Using these parameters, the wattage required per household is equal to 1829 Watts.

Using six ReneSola : Virtus II 300W : Solar Panels would generate 1800 Watts, close enough to the demand. Each of these panels, including value added tax costs R 3,504. Six of these, would therefore cost R 21024.

Thus, the per-household cost of switching to solar energy is equal to R 21024.

Therefore, the total cost for all the households in Khayelitsha= 21024*118809 = R 2.5 Billion

Given that residents currently spend an estimate of 12% of their monthly income on energy, the amount each household would be willing to pay to install solar panels would be a minimum of

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R700 (Approximately 12%). It is assumed that the highest they would be willing to pay a maximum of 30% of their monthly income for solar energy (bearing in mind an assumption that they are already aware of it’s benefits with respect to minimal O&M costs). 30% of their monthly income would be equal to 30% or 5600 = R1680

Therefore, it is estimated that each household would be willing to pay between R700-R1680 for solar energy. Therefore, multiplying this range by the number of households, all the households combined would be willing to spend in the range of R 83 million-R 200 million.

Thus, government costs for this project would be in the range of 2.3 Billion-2.4 Billion.

This estimate was made not factoring in interest free loans that a government might provide to citizens to repay the entire amount. However, given that the households pay R700/month on energy, it would take them, on a loan that charges the same amount per month and free of interest, 30 months, or 2.5 years to repay this amount. This seems a reasonable time frame, given that in the long term, there will be minimal operational and maintenance costs associated with solar power. There would need to be further investment into outreach programs aimed at convincing people of the need to make this change.

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Appendix C: Kibera, Kenya

Figure 1: Kibera’s Population Growth (Emmanuel MUTISYA, 2011)

Figure 2: Social facilities in Kibera slums (MUTISYA & YARIME, 2011)

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