Casillas, Kammen 2010 Energy Poverty Climate Nexus, Science

Energy Poverty
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POLICYFORUM ENVIRONMENT AND DEVELOPMENT The Energy-Poverty-Climate Nexus Christian E. Casillas, 13 Daniel M. Kammen1234* Community-level carbon abatement curves highlight opportunities for increased access to clean, efficient energy for the poor. C lose to two-thirds of the world’s poor- vulnerable, poor populations, many living areas has the potential to produce greater est people live in rural areas (1). Erad- in rural areas (1, 12). Improving delivery of human development, savings, and carbon ication of rural poverty depends on affordable, reliable energy services to rural mitigation returns than in more industrialized increased access to goods, services, and infor- communities is critical for helping them areas (if economies of scale do not domimation, targets detailed in the United Nations develop human and economic capacity to nate). However, debates about climate change Millennium Development Goals. However, adapt in the face of a changing climate. and vulnerability have been slow to highlight alleviating poverty is hindered by two interGreenhouse gas emissions in industri- the energy-poverty-climate nexus. This has linked phenomena: lack of access been due, in part, to the lack of meaningful to improved energy services and Pull quote TKTK Pull quote TKTK Pull quote metrics needed to stimulate social, economic, worsening environmental shocks and technical innovation in this sector. due to climate change. Mitigating TKTK Pull quote TKTK Pull quote TKTK climate change, increasing energy Marginal Abatement Cost Curves access, and alleviating rural poverty can all alized countries are dominated by electric- A marginal abatement cost (MAC) curve be complementary, their overlap defining an ity generation and transportation, whereas typically shows the annual carbon abatement energy-poverty-climate nexus. We describe the majority of emissions from the world’s potential for an intervention, and the cost per interventions in a rural Nicaraguan com- poorest countries come from agriculture quantity of carbon emissions abated, relative munity to show that energy services can be and changes in land use (1). However, with to the emission costs for a baseline case (14, provided in cost-effective manners, offering 1.5 billion people without access to elec- 15). A community-level MAC curve derived potential to address aspects of rural poverty tricity, combustion-related emissions from from ongoing research on the Atlantic coast while also transitioning away from fossil fuel the rural power sector are expected to grow. of Nicaragua demonstrates that low-carbon dependence. Because of low capital costs and a large net- rural energy services can be delivered at cost work of suppliers, diesel generators are often savings in cases where communities use dieThe Energy-Poverty-Climate Nexus the technology of choice in rural areas, with- sel powered generation, isolated from the Increased access to energy services alone will out sufficient consideration of the volatility of national grid (microgrids). not eradicate poverty, but it can have immedi- fuel prices, resulting in expensive generation The rural communities of Orinoco and ate effects (2, 3). More than 1.5 billion people costs (9, 13). Marshall Point share a diesel microgrid servlive without access to electricity, another bilGiven the relationships outlined above, ing 172 households. In partnership with the lion only have access to unreliable electric- every dollar spent on the transition to more Nicaraguan government and a local nongovity, and close to half the global population efficient low-carbon energy systems in rural ernment organization, several energy effidepends on traditional biomass fuels for cooking and heating (4). Energy poverty results in 400 unmet basic needs and depressed economic Solar PV Energy efficiency and conservation and educational opportunities that are parRenewable energy 300 ticularly pervasive among women, children, and minorities (5, 6). Electricity catalyzes 200 rural economic activity (7–10) and increases 100 the quality of services available to meet CFL installation Biogas Wind turbine basic business and domestic needs through 0 improved lighting, labor saving devices, and Replace street –100 access to information through TV , radio, and light sensors Reduce cellular telephones (11). Provision of high–200 generator quality public lighting can increase security capacity –300 and improve delivery of health and education services (7, 11). –400 Environmental shocks related to climate More effective public lighting Meter installation change will first and most severely affect –500 Abatement cost relative to baseline (2010$/tCO2) 0 50 100 150 200 Energy and Resources Group, University of California, Berkeley, Berkeley, CA 94720 USA. 2Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA 94720 USA. 3Renewable and Appropriate Energy Laboratory, University of California, Berkeley, Berkeley, CA 94720 USA. 4The World Bank, Washington, DC 20443, USA. 1 Carbon abatement potential (tCO2/year conserved) *Author for correspondence: [email protected] Bold lede-in needed. MAC curve of the electricity sector for Orinoco and Marshall Point.Abatement cost is with respect to a baseline diesel carbon price of $397 per metric ton of CO2 (tCO2). (Negative cost indicates savings.) Abatement potential is due to the reduction of diesel use, relative to each previous measure. Multiplying abatement potential and abatement cost gives total annual costs relative to baseline, assuming that the previous measure was implemented. Only the most economic technologies appropriate for the community resources, capacity, and grid sophistication are included. See SOM for details. www.sciencemag.org SCIENCE VOL 330 26 NOVEMBER 2010 1181 POLICYFORUM ciency measures were implemented in 2009 [see the supporting online material (SOM)]. Based on this work, we developed a MAC curve for the electricity sector of these communities (see the figure) (Fig. 1). The first two efficiency measures in the curve [installation of meters and compact fluorescent lights (CFLs)] were actually implemented, whereas impacts of subsequent measures are based on estimations (SOM). With the price of diesel fuel at US$1.06 per liter, the generation cost for each additional unit of electricity in the village (its marginal generation cost) is $0.54 per kilowatt-hour (kWh) (SOM), compared with costs on the order of $0.10 per kWh in the national grid (16). This difference in generation costs creates potential for greater savings available from mitigation in diesel microgrids (although the total capacity for carbon abatement is considerably less than in the national grid). The majority of the abatement measures in the figure can be achieved at negative costs relative to the diesel baseline (i.e., costs are outweighed by savings). There are a number of ways an intervention’s impact on poverty can be assessed. For this study, we quantify the potential for increase in availability of energy and reduction in household consumption, which can translate to reduced expenditures without decreasing the quality of energy service. Future work could explore how interventions create jobs and increase earnings and how benefits are distributed by using inequality metrics such as the Gini coefficient or Kuznets ratios. Decreasing Consumption ation of the microgrid was increased by 2 hours, providing households the opportunity to invest in additional electricity use (19). In the month following the two measures, 37% of the households in Orinoco received lower electricity bills. However, benefits to the poorest households were mitigated due to a regressive tariff structure in which the smallest consumers pay a fixed rate (SOM). The MAC curve also highlights estimated benefits of replacing a portion of diesel fuel with biogas. The biogas can be produced locally through anaerobic digestion of animal dung and agricultural residues. This introduces the opportunity for a large part of the gross carbon abatement cost to be captured within the community through local, lowcarbon fuel production rather than paying for imported fossil fuel. Although communityscale biogas systems have had mixed success, often depending on the model of ownership, they highlight opportunities for implementing sustainable biofuel systems with current technology (20). Suite of Tools for Poverty-Climate Analysis sis, and interventions based on those analyses, is needed to allow us to reduce poverty while also confronting climate change. 1. R. Bierbaum, M. Fay, World Development Report 2010: Development and Climate Change (World Bank, Washington, 2010). 2. V. Modi, S. McDade, D. Lallement, J. Saghir, Energy Services for the Millennium Development Goals (World Bank, New York, 2005). 3. E. Mills, Science 308, 1263 (2005). 4. United Nations Development Programme, Energy for a Sustainable Future: The Secretary-General’s Advisory Group on Energy and Climate Change Summary Report and Recommendations (UNDP, New York, 2010). 5. International Energy Agency, World Energy Outlook (IEA, Paris, 2005). 6. A. Jacobson, A. D. Milman, D. M. Kammen, Energy Policy 33, 1825 (2005). 7. E. Cecelski, Enabling Equitable Access to Rural Electrification: Current Thinking and Major Activities in Energy, Poverty and Gender (World Bank, Washington, 2000). 8. R. A. Cabraal, D. F. Barnes, S. G. Agarwal, Annu. Rev. Environ. Resour. 30, 117 (2005). 9. C. Flavin, M. H. Aeck, Energy for Development: The Potential Role of Renewable Energy in Meeting the Millennium Development Goals (Worldwatch Institute, Washington, 2005). 10. C. Kirubi, A. Jacobson, D. M. Kammen, A. Mills, World Dev. 37, 1208 (2009). 11. Independent Evaluation Group, The Welfare Impact of Rural Electrification: A Reassessment of the Costs and Benefits (World Bank, Washington, 2008). 12. Intergovernmental Panel on Climate Change, Climate Change 2007: Impacts, Adaptation and Vulnerability (Cambridge Univ. Press, Cambridge, UK, 2007). 13. Energy Sector Management Assistance Programme, Technical and Economic Assessment of Off-Grid, MiniGrid and Grid Electrification Technologies (World Bank, Washington, 2007). 14. McKinsey & Company, Pathways to a Low-Carbon Economy (McKinsey, London, 2009). 15. T. M. Johnson, C. Alatorre, Z. Romo, F. Liu, Low-Carbon Development for Mexico (World Bank Publications, Washington, 2009). 16. W. Mostert, Unlocking Potential, Reducing Risk: Renewable Energy Policies for Nicaragua (World Bank, Washington, 2007). 17. A. B. Jaffe, R. N. Stavins, Energy Policy 22, 804 (1994). 18. P. C. Stern, G. T. Gardner, M. P. Vandenbergh, T. Dietz, J. M. Gilligan, Environ. Sci. Technol. 44, 4847 (2010). 19. In the case where an electricity grid is operating for only a fixed number of hours each day, based on a limited supply of fuel, increased demand-side efficiency allows for fuel savings to be invested in longer hours of operation, which will not immediately result in a reduction of total carbon emissions but rather a reduction of carbon emissions per delivery of energy services. 20. H. Romijn, R. Raven, I. de Visser, Environ. Sci. Policy 13, 326 (2010). 21. K. R. Smith et al., J. Expo. Sci. Environ. Epidemiol. 20, 406 (2010). 22. M. Ezzati, D. M. Kammen, Lancet 358, 619 (2001). 23. M. A. Altieri, Agric. Ecosyst. Environ. 93, 1 (2002). 24. We thank blueEnergy, and its directors M. and G. Craig, for resources and support, and R. Ghanadan, A. Kantenbacher, A. Mason, I. Ray, and reviewers for comments. C.C. is an advisor to blueEnergy. This work was supported by the Energy Foundation, the Karsten Family Foundation, and the Class of 1935 of the University of California, Berkeley. References and Notes The installation of electricity meters allowed accurate billing of household consumption, instead of using unmetered, fixed tariffs. This resulted in a 28% decrease in daily energy consumption, which could translate into household savings. The relatively greater reduction in daytime load suggests that meter installation resulted in reduction of less-valued energy services (e.g., lights being left on during the day). To increase lighting efficiency, every household was given the option to replace two incandescent bulbs with CFLs, resulting in an additional 17% drop in daily consumption and the potential for additional household savings. The large demand response due to metering and efficient lighting was the result of both behavioral changes and a market intervention (17, 18). The combination of the meter and CFL installations led to an increased availability of 84 liters of diesel per day. The daily oper- Although this MAC curve focused on carbon abatement in the electricity sector, similar curves can be created for different rural energy services such as cooking and transportation, as well as agriculture. For example, 57% of households use charcoal for cooking, the majority having unimproved stoves. More efficient stoves would mitigate black carbon emissions, lessening impacts on climate and also respiratory harm most prominent among women and children (21, 22). Using MAC curves in conjunction with a clear understanding of how various measures will support community development goals ensures that climate change dollars also address the most pressing challenges of the poorest communities. However, MAC curves must be part of a suite of analytic tools for understanding various poverty-climate nexuses. For example, investment in agro-ecological farming practices may not necessarily appear favorable in a MAC curve but will likely be critical in the agricultural-povertyclimate nexus (23). Integration of development agendas into climate change frameworks has been limited, in part, by a lack of both easy-to-understand metrics and systems-level planning tools necessary for prioritizing the allocation of limited capital. Using one such tool, MAC curves, it is apparent that increasing access to energy services can reduce carbon emissions and monetary expenditures, with great potential to affect development and reduce poverty. Continued development of methods of analy- Supporting Online Material www.sciencemag.org/cgi/content/full/[vol]/[issue no.]/[page]/ DC1 10.1126/science.1197412 1182 26 NOVEMBER 2010 VOL 330 SCIENCE www.sciencemag.org