The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India

Gao, Meng ; Beig, Gufran ; Song, Shaojie ; Zhang, Hongliang ; Hu, Jianlin ; Ying, Qi ; Liang, Fengchao ; Liu, Yang ; Wang, Haikun ; Lu, Xiao ; Zhu, Tong ; Carmichael, Gregory R. ; Nielsen, Chris P. ; McElroy, Michael B. (2018) The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India Environment International, 121 . pp. 250-259. ISSN 0160-4120

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Official URL: http://doi.org/10.1016/j.envint.2018.09.015

Related URL: http://dx.doi.org/10.1016/j.envint.2018.09.015

Abstract

Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM ≤ 2.5 μm in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Air quality modeling; Power generation; China; India; WRF-Chem
ID Code:133380
Deposited On:28 Dec 2022 06:32
Last Modified:28 Dec 2022 06:32

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