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      The Regional Impacts of Cooking and Heating Emissions on Ambient Air Quality and Disease Burden in China.

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          Abstract

          Exposure to air pollution is a major risk factor globally and particularly in Asia. A large portion of air pollutants result from residential combustion of solid biomass and coal fuel for cooking and heating. This study presents a regional modeling sensitivity analysis to estimate the impact of residential emissions from cooking and heating activities on the burden of disease at a provincial level in China. Model surface PM2.5 fields are shown to compare well when evaluated against surface air quality measurements. Scenarios run without residential sector and residential heating emissions are used in conjunction with the Global Burden of Disease 2013 framework to calculate the proportion of deaths and disability adjusted life years attributable to PM2.5 exposure from residential emissions. Overall, we estimate that 341 000 (306 000-370 000; 95% confidence interval) premature deaths in China are attributable to residential combustion emissions, approximately a third of the deaths attributable to all ambient PM2.5 pollution, with 159 000 (142 000-172 000) and 182 000 (163 000-197 000) premature deaths from heating and cooking emissions, respectively. Our findings emphasize the need to mitigate emissions from both residential heating and cooking sources to reduce the health impacts of ambient air pollution in China.

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          Author and article information

          Journal
          Environ. Sci. Technol.
          Environmental science & technology
          1520-5851
          0013-936X
          Sep 6 2016
          : 50
          : 17
          Affiliations
          [1 ] National Center for Atmospheric Research (NCAR), Boulder, Colorado 80301, United States.
          [2 ] Institute on the Environment, University of Minnesota , St. Paul, Minnesota United States.
          [3 ] Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.
          [4 ] Institute for Health Metrics and Evaluation, University of Washington , Seattle, Washington United States.
          [5 ] Health Effects Institute, Suite 500, 101 Federal Street Boston, Massachusetts 02110, United States.
          [6 ] School of Population and Public Health, The University of British Columbia , 2206 East Mall, Vancouver, British Columbia V6T1Z3, Canada.
          [7 ] Institute for Health and Social Policy and Department of Epidemiology, Biostatistics and Occupational Health, McGill University , 1130 Pine Avenue West, Montreal, Quebec H3A1A3, Canada.
          Article
          10.1021/acs.est.6b02533
          27479733
          654a6735-c77e-4694-b59e-6c0d63c702b7

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