11.8.1.2 Co-benefits for human health
Epidemiological studies have identified consistent asso-ciations between human health (mortality and morbidity) and exposure to fine particulate matter and ground-level ozone, both in industrialized and developing countries (WHO, 2003; HEI, 2004). Because the burning of fossil fuels is linked to both climate change and air pollution, lowering the amount of fuel combusted will lead to lower carbon emissions as well as lower health and environmental impacts from reduced emissions of air pollutants and their precursors.
Since the TAR, an increasing number of studies have demonstrated that carbon mitigation strategies result in significant benefits, not only as a result of improved air quality in cities, but also from reduced levels of regional air pollution. These benefits affect a larger share of the population and result from lower levels of secondary air pollutants. Although the literature employs a variety of methodological approaches, a consistent picture emerges from the studies conducted for industrialized regions in Europe and North America, as well as for developing countries in Latin America and Asia (see Table 11.18). Mitigation strategies aiming at moderate reductions of carbon emissions in the next 10 to 20 years (typically involving CO2 reductions between 10 to 20% compared to the business-as-usual baseline) also reduce SO2 emissions by 10 to 20%, and NOx and PM emissions by 5 to 10%. The associated health impacts are substantial. They depend, inter alia, on the level at which air pollution emissions are controlled and how strongly the source sector contributes to population exposure. Studies calculate for Asian and Latin American countries several tens of thousands of premature deaths that could be avoided annually as a side-effect of moderate CO2 mitigation strategies (Wang and Smith, 1999; Aunan et al., 2003; O’Connor et al., 2003; Vennemo et al., 2006 for China; Bussolo and O’Connor, 2001 for India; Cifuentes et al., 2001a; Dessus and O’Connor, 2003; McKinley et al., 2005 for Latin America). Studies for Europe (Bye et al., 2002; van Vuuren et al., 2006), North America (Caton and Constable, 2000; Burtraw et al., 2003) and Korea (Han, 2001; Joh et al., 2003) reveal fewer, but nevertheless substantial, health benefits from moderate CO2 mitigation strategies, typically in the order of several thousand premature deaths that could be avoided annually.
Table 11.18: Implications for air-quality co-benefits from GHG mitigation studies
Authors | Country | Target year | Sector | Delta CO2 emissions | Carbon price (US$/tCO2) | Impact on air pollutant emissions | Difference in health impacts | Health benefits (US$/tCO2) | Difference in air pollution control costs | Total benefits |
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Burtraw et al., 2003 | US | 2010 | Power sector | | 7 | | | 2 | 1–2 US$/tCO2 | |
Caton and Constable, 2000 | Canada | 2010 | All sectors | -9% | | SO2: -9% NOx: -7% PM: -1% | | 11 (12–77) | | |
Wang & Smith, 1999 | China | 2020 | Power sector | 15% below BAU | 11 | | 4,400-5,200 premature deaths per year | | | |
| | 2020 | Domestic sector | 15% below BAU | 1.4 | | 120,000-180,000 premature deaths per year | | | |
O’Connor, 2003 | China | 2010 | All sources | 15% below BAU | | | | | | No loss in net welfare |
Aunan et al., 2004 | Shanxi, China | 2000 | Cogeneration | | -30 (net benefit) | | | 32 | | |
| | | Modified boiler design | | -6 | | | 23 | | |
| | | Boiler replacement | | -3 | | | 32 | | |
| | | Improved boiler management | | 9 | | | 32 | | |
| | | Coal washing | | 22 | | | 86 | | |
| | | Briquetting | | 27 | | | 118 | | |
Kan et al., 2004 | Shanghai, China | 2010 | All sources | | 24 | | 608–5144 premature deaths per year | | | |
| | 2020 | | | | | 1189–10462 premature deaths per year | | | |
Li, 2006 | Thailand | | | | | | | | | 45% lower welfare losses |
Vennemo et al., 2006 | China | 2008-2012 | Power production, industrial boilers, steel making, cement, chemical industry | 80-236 MtCO2 annually | 6 for the 80 Mt potential; unknown for the upper estimate | SO2: 0.5–3 million tons; TSP: 0.2–1.6 million tons | 2700 - 38000 lives saved annually (34–161 lives saved per million tons CO2) | Avoided deaths: 4.1–20; all health effects: 5–44 | | |
Morgenstern, 2004 | Taiyuan, China | | Phase-out of small boilers | 80% | | -95% | | 38–175 US$/tCO2 | | |
Bussolo & O’Connor, 2001 | India | | All sources | 13-23% below BAU | | | | | | No welfare loss |
Joh et al., 2003 | Korea | 2020 | All sources | 5–15% | | | | 2 US$/tCO2 | | |
Han, 2001 | Korea | 2010 | All sources | -10% | | SO2: -10% NOx: -9.6% PM: -10% | | 58–76 | | |
Van Vuuren, 2006 | Europe | 2020 | All sources | 4–7% | | SO2: 5–14% | | | | |
Syri et al. 2001 | EU-15 | 2010 | All sources | -8% | | SO2: 13-40% NOx: 10–15% | | | -10% | |
Proost et al., 2003 | Belgium | 2010-2030 | All sources | 7–15% | | | | | | 30% of mitigation costs |
Syri et al., 2002 | Finland | 2010 | All sources | Kyoto compliance | | SO2: -10% NOx : -5% PM: -5% | | | | |
Bye et al., 2002 | Nordic countries | | All sources | 20–30% | | | | | 9-22 US$/tCO2 | 0.4% to 1.2% of GDP |
Cifuentes et al., 2001a , 2001b | Mexico City, Santiago, Sao Paulo, New York | 2020 | | | | | 64,000 premature deaths per year | | | |
West et al., 2004 | Mexico City | 2010 | 18 GHG measures (mainly transport) | 9% | | PM10: -1.3% NOx: 1.4% HC: 3.2% | | | | |
McKinley et al., 2005 | Mexico City | 2020 | 5 mitigation options | 0.8 Mt C/yr (1.1%) | | | 100 premature deaths per year | | | |
Dessus et al., 2003 | Santiago de Chile | 2010 | | 20% below BAU | | | | | | No welfare loss |
Several authors conducted an economic valuation of these health effects in order to arrive at a monetary quantification of the benefits, which can then be directly compared with mitigation costs. While the monetization of health benefits remains controversial, especially with respect to the monetary value attributed to mortality risks in an international context, calculated benefits range from 2 US$/tCO2 (Burtraw et al., 2003; Joh et al., 2003) up to a hundred or more US$/tCO2 (Han, 2001; Aunan et al., 2004; Morgenstern et al., 2004). This wide range is partially explained by differences in methodological approaches. The lower estimates emerge from studies that consider health impacts from only one air pollutant (such as SO2 or NOx), while the higher estimates cover multiple pollutants, including fine particulate matter, which has been recently shown to have the greatest impact. Differences in mortality evaluation methods and results also constitute a substantial source of discrepancy in the estimated value of health impact as well.
The benefits also largely depend on the source sector in which the mitigation measure is implemented. Decarbonization strategies that reduce fossil fuel consumption in sectors with a strong impact on population exposure (such as domestic stoves for heating and cooking, especially in developing countries) can typically result in health benefits that are 40 times greater than a reduction in emissions from centralized facilities with high stacks such as power plants (Wang and Smith, 1999). Mestl et al., (2005) show that the local health benefits of reducing emissions from power plants in China are small compared to abating emissions from area sources and small industrial boilers. A third factor is the extent to which air pollution emission controls have already been applied. Health benefits are larger in countries and sectors where pollutants are normally emitted in an uncontrolled way, for instance for small combustion sources in developing countries.
Despite the large range of benefit estimates, all studies agree that monetized health benefits make up a substantial fraction of mitigation costs. Depending on the stringency of the mitigation level, the source sector, the measure and the monetary value attributed to mortality risks, health benefits range from 30 to 50% of estimated mitigation costs (Burtraw et al., 2003; Proost and Regemorter, 2003) up to a factor of three to four (Aunan et al., 2004; McKinley et al., 2005). Particularly in developing countries, several of the studies reviewed indicate that there is scope for measures with benefits that exceed mitigation costs (no-regret measures).
Such potential for no-regret measures in developing countries are consistently confirmed by studies applying a general-equilibrium modelling approach, which takes into account economic feedback within the economy. Bussolo & O’Connor (2001) estimate that the potential for CO2 mitigation in India for 2010, without a net loss in welfare, is between 13 and 23% of the emissions for a business-as-usual scenario. For China, this potential has been estimated by O’Connor (2003) for 2010 at 15 to 20%, and Dessus and O’Connor (2003) arrive at a figure of 20% for Chile compared with the business-as-usual emissions in 2010. Li (2002; 2006) finds for Thailand that inclusion of health impacts reduces the negative impacts on GDP of a carbon tax by 45%, improving welfare for households and resulting in cleaner producers.