Climate policies targeting energy-related CO2 emissions, which act on a global scale over long time horizons, can result in localized, near-term reductions in both air pollution and adverse human health impacts. Focusing on China, the largest energy-using and CO2-emitting nation, we develop a cross-scale modelling approach to quantify these air quality co-benefits, and compare them to the economic costs of climate policy. We simulate the effects of an illustrative climate policy, a price on CO2 emissions. In a policy scenario consistent with China’s recent pledge to reach a peak in CO2 emissions by 2030, we project that national health co-benefits from improved air quality would partially or fully offset policy costs depending on chosen health valuation. Net health co-benefits are found to rise with increasing policy stringency.
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Aunan, K., Fang, J., Vennemo, H., Oye, K. & Seip, H. M. Co-benefits of climate policy—lessons learned from a study in Shanxi, China. Energy Policy 32, 567–581 (2004).
Shindell, D. et al. Simultaneously mitigating near-term climate change and improving human health and food security. Science 335, 183–189 (2012).
McCollum, D. L. et al. Climate policies can help resolve energy security and air pollution challenges. Climatic Change 119, 479–494 (2013).
West, J. J. et al. Co-benefits of global greenhouse gas mitigation for future air quality and human health. Nat. Clim. Change 3, 885–889 (2013).
China’s Intended Nationally Defined Contribution (INDC): Enhanced Actions on Climate Change (Department of Climate Change, National Development and Reform Commission, 2015).
Nemet, G. F., Holloway, T. & Meier, P. Implications of incorporating air-quality co-benefits into climate change policymaking. Environ. Res. Lett. 5, 14007 (2010).
Vos, T. et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386, 743–800 (2015).
Parry, I., Veung, C. & Heine, D. How much carbon pricing is in countries’ own interests? The critical role of co-benefits. Clim. Change Econ. 6, 1550019 (2015).
Dong, H. et al. Pursuing air pollutant co-benefits of CO2 mitigation in China: a provincial leveled analysis. Appl. Energ. 144, 165–174 (2015).
Thompson, T. M., Rausch, S., Saari, R. K. & Selin, N. E. A systems approach to evaluating the air quality co-benefits of US carbon policies. Nat. Clim. Change 4, 917–923 (2014).
Nielsen, C. P. & Ho, M. S. Clearer Skies Over China (MIT Press, Cambridge, 2013).
Shindell, D. T., Lee, Y. & Faluvegi, G. Climate and health impacts of US emissions reductions consistent with 2 °C. Nat. Clim. Change 6, 503–507 (2016).
Nam, K. M., Waugh, C. J., Paltsev, S., Reilly, J. M. & Karplus, V. J. Carbon co-benefits of tighter SO2 and NOx regulations in China. Glob. Environ. Change 23, 1648–1661 (2013).
He, K. et al. Co-benefits from energy policies in China. Energy 35, 4265–4272 (2010).
Zhou, D. China Sustainable Energy Scenarios in 2020 (China Environmental Science Press, 2003).
Zhang, D., Rausch, S., Karplus, V. J. & Zhang, X. Quantifying regional economic impacts of CO2 intensity targets in China. Energy Econ. 40, 687–701 (2013).
Luo, X., Caron, J., Zhang, D., Zhang, X. & Karplus, V. J. Interprovincial migration and the stringency of energy policy in China. Energy Econ. 58, 164–173 (2016).
Springmann, M., Zhang, D. & Karplus, V. J. Consumption-based adjustment of emissions-intensity targets: an economic analysis for China’s provinces. Environ. Resour. Econ. 61, 615–640 (2015).
Karplus, V. J., Rausch, S. & Zhang, D. Energy caps: Alternative climate policy instruments for China? Energ. Econ. 56, 422–431 (2016).
Zhang, D., Springmann, M. & Karplus, V. J. Equity and emissions trading in China. Climatic Change 134, 131–146 (2016).
Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R. & Liu, P. Less than 2 °C warming by 2100 unlikely. Nat. Clim. Change 7, 637–641 (2017).
Kurokawa, J. et al. Emissions of air pollutants and greenhouse gases over Asian regions during 2000–2008: Regional Emission inventory in ASia (REAS) version 2. Atmos. Chem. Phys. 13, 11019–11058 (2013).
MEIC v1.2 (MEIC Research Group, Tsinghua University, 2015); http://www.meicmodel.org/dataset-meic.html
Burnett, R. T. et al. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ. Health Perspect. 122, 397–403 (2014).
Driscoll, T. C. et al. US power plant carbon standards and clean air and health co-benefits. Nat. Clim. Change 5, 535–540 (2015).
Fu, T. M. et al. Carbonaceous aerosols in China: top-down constraints on primary sources and estimation of secondary contribution. Atmos. Chem. Phys. 12, 2725–2746 (2012).
Wang, S. et al. Impact assessment of ammonia emissions on inorganic aerosols in East China using response surface modeling technique. Environ. Sci. Technol. 45, 9293–9300 (2011).
Wang, Y., Zhang, Q. Q., He, K., Zhang, Q. & Chai, L. Sulfate-nitrate-ammonium aerosols over China: response to 2000–2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia. Atmos. Chem. Phys. 13, 2635–2652 (2013).
Tol, R. S. J. The social cost of carbon. Annu. Rev. Resour. Econ. 3, 419–443 (2011).
Ambient Air Quality Standards GB 3095–2012(China MEP, 2012); http://english.mep.gov.cn/Resources/standards/Air_Environment/quality_standard1/201605/W020160511506615956495.pdf
The China Regional Input–Output Tables 2007 (National Bureau of Statistics of China, 2011).
China Energy Statistical Yearbook 2008 (National Bureau of Statistics of China, 2011).
Narayanan, G. B., Aguiar, A. & McDougall, R. Global Trade, Assistance, and Production: The GTAP 8 Data Base (Center for Global Trade Analysis, Purdue University, 2012).
Arrow, K. J. & Debreu, G. Existence of an equilibrium for a competitive economy. Econometrica 22, 265–290 (1954).
Rutherford, T. F. Applied general equilibrium modeling with MPSGE as a GAMS subsystem: an overview of the modeling framework and syntax. Comput. Econ. 14, 1–46 (1999).
Zhang, X., Karplus, V. J., Qi, T., Zhang, D. & He, J. Carbon emissions in China: How far can new efforts bend the curve? Energy Econ. 54, 388–395 (2016).
China Statistical Database (National Bureau of Statistics of China, 2012).
2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2006).
Streets, D. G. et al. An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J. Geophys. Res. 108(D21), 8809 (2003).
Kharol, S. K. et al. Persistent sensitivity of Asian aerosol to emissions of nitrogen oxides. Geophys. Res. Lett. 40, 1021–1026 (2013).
Webster, M., Paltsev, S., Parsons, J., Reilly, M. J. & Jacoby, H. D. Uncertainty in Greenhouse Gas Emissions and Costs of Atmospheric Stabilization Report No. 165 (MIT Joint Program on the Science and Policy of Global Change, 2008).
Quarterly Coal Report April–June 2017 (US Energy Information Administration, 2017).
Air Pollutant Emissions Trends Data (US Environmental Protection Agency, 2016); https://www.epa.gov/air-emissions-inventories/air-pollutant-emissions-trends-data
Wang, Y. X., McElroy, M. B., Jacob, D. J. & Yantosca, R. M. A nested grid formulation for chemical transport over Asia: Applications to CO. J. Geophys. Res. 109, D22307 (2004).
Walker, J. M., Philip, S., Martin, R. V. & Seinfeld, J. H. Simulation of nitrate, sulfate, and ammonium aerosols over the United States. Atmos. Chem. Phys. 12, 11213–11227 (2012).
Heald, C. L. et al. Atmospheric ammonia and particulate inorganic nitrogen over the United States. Atmos. Chem. Phys. 12, 10295–10312 (2012).
Zhang, X. Y. et al. Atmospheric aerosol compositions in China: Spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols. Atmos. Chem. Phys. 12, 779–799 (2012).
He, K. et al. Spatial and seasonal variability of PM2.5 acidity at two Chinese megacities: insights into the formation of secondary inorganic aerosols. Atmos. Chem. Phys. 12, 1377–1395 (2012).
Xu, L. et al. Seasonal variations and chemical compositions of PM2.5 aerosol in the urban area of Fuzhou, China. Atmos. Res. 104-105, 264–272 (2012).
Zhao, P. S. et al. Characteristics of concentrations and chemical compositions for PM2.5 in the region of Beijing, Tianjin, and Hebei, China. Atmos. Chem. Phys. 13, 4631–4644 (2013).
Zhang, R. et al. Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective. Atmos. Chem. Phys. 13, 7053–7074 (2013).
Acid Deposition Monitoring Network in East Asia (Asia Center for Air Pollution Research, 2012); http://www.eanet.asia/product/index.html
Wang, Y. et al. Enhanced sulfate formation during China’s severe winter haze episode in January 2013 missing from current models. J. Geophys. Res. Atmos. 119, 10425–10440 (2014).
Holt, J., Noelle, E. S. & Susan, S. Changes in inorganic fine particulate matter sensitivities to precursors due to large-scale US emissions reductions. Environ. Sci. Technol. 49, 4834–4841 (2015).
Xing, L. et al. Seasonal and spatial variability of the OM/OC mass ratios and high regional correlation between oxalic acid and zinc in Chinese urban organic aerosols. Atmos. Chem. Phys. 13, 4307–4318 (2013).
Environmental Benefits Mapping and Analysis Program–Community Edition User’s Manual (RIT International, 2015).
Global Burden of Disease Study 2010: Ambient Air Pollution Risk Model 1990–2010 (Institute for Health Metrics and Evaluation, 2013); http://ghdx.healthdata.org/record/global-burden-disease-study-2010-gbd-2010-ambient-air-pollution-risk-model-1990-2010
WHOSIS: Detailed Data Files of the WHO Mortality Database (World Health Organization, 2015); http://www.who.int/healthinfo/statistics/mortality_rawdata/en/
Gridded Population of the World Version 3 (Center for International Earth Science Information Network, 2005); http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-count-future-estimates
World Population Prospects: The 2015 Revision (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
Voorhees, A. S. et al. Public health benefits of reducing air pollution in Shanghai: a proof-of-concept methodology with application to BenMAP. Sci. Total Environ. 485–486, 396–405 (2014).
Cao, J. et al. Association between long-term exposure to outdoor air pollution and mortality in China: a cohort study. J. Hazard. Mater. 186, 1594–1600 (2011).
Krewski, D. et al. Extended Follow-Up and Spatial Analysis of the American Cancer Society Study Linking Particulate Air Pollution and Mortality Report No. 140 (Health Effects Institute Research, 2009).
Guidelines for Preparing Economic Analyses (US EPA, 2014); https://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0568-50.pdf/$file/EE-0568-50.pdf
Viscusi, W. K. in Handbook of the Economics of Risk and Uncertainty Vol. 1 (eds Machina, M. & Viscusi, W. K.) 385–452 (Elsevier, Amsterdam, 2014).
Hammitt, J. K. & Robinson, L. A. The income elasticity of the value per statistical life: transferring estimates between high and low income populations. J. Ben. Cost. Anal. 2, 1–29 (2011).
Wang, H. & He, J. J. The Value of a Statistical Life: A Contingent Investigation in China Working Paper 5421 (The World Bank Development Research Group, 2010); http://elibrary.worldbank.org/doi/abs/10.1596/1813-9450-5421
We acknowledge the support of Eni S.p.A., the French Development Agency (AFD), ICF International and Shell International Limited, founding sponsors of the China Energy and Climate Project (CECP), and the National Science Foundation of China (project no. 71690244). We further thank the US Department of Energy, Energy Information Agency, for ongoing support for this work under a cooperative agreement (grant no. DE-EI0003030). At MIT the China Energy and Climate Project is part of the MIT Joint Program on the Science and Policy of Global Change, funded through a consortium of industrial sponsors and Federal grants, including the US Department of Energy (DOE) under Integrated Assessment Grant (grant no. DE-FG02-94ER61937). We also acknowledge the MIT Environmental Solutions Initiative, the Tang Fellowship (M.L.) and the MIT Leading Technology and Policy Initiative (K.M.M.).
The authors declare no competing interests.
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Li, M., Zhang, D., Li, C. et al. Air quality co-benefits of carbon pricing in China. Nature Clim Change 8, 398–403 (2018). https://doi.org/10.1038/s41558-018-0139-4
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