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Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China

Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed therm...

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Detalles Bibliográficos
Autores principales: Wang, Liqiang, Li, Pengfei, Yu, Shaocai, Mehmood, Khalid, Li, Zhen, Chang, Shucheng, Liu, Weiping, Rosenfeld, Daniel, Flagan, Richard C., Seinfeld, John H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5772530/
https://www.ncbi.nlm.nih.gov/pubmed/29343860
http://dx.doi.org/10.1038/s41598-018-19481-0
Descripción
Sumario:Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed thermal power plant emission controls in the Beijing-Tianjin-Hebei (BTH) region on air quality over Beijing using the Community Multiscale Air Quality(CMAQ) atmospheric chemical transport model to predict CO, SO(2), NO(2), PM(2.5), and PM(10) levels. A baseline simulation of the hypothetical removal of all thermal power plants in the BTH region is predicted to lead to 38%, 23%, 23%, 24%, and 24% reductions in current annual mean levels of CO, SO(2), NO(2), PM(2.5), and PM(10) in Beijing, respectively. Similar percentage reductions are predicted in the major cities in the BTH region. Simulations of the air quality impact of six proposed thermal power plant emission reduction strategies over the BTH region provide an estimate of the potential improvement in air quality in the Beijing metropolitan area, as a function of the time of year.