Emissions inventory and scenario analyses of air pollutants in Guangdong Province, China View Full Text


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Article Info

DATE

2017-01-26

AUTHORS

Hui Chen, Jing Meng

ABSTRACT

Air pollution, causing significantly adverse health impacts and severe environmental problems, has raised great concerns in China in the past few decades. Guangdong Province faces major challenges to address the regional air pollution problem due to the lack of an emissions inventory. To fill this gap, an emissions inventory of primary fine particles (PM2.5) is compiled for the year 2012, and the key precursors (sulfur dioxide, nitrogen oxides) are identified. Furthermore, policy packages are simulated during the period of 2012‒2030 to investigate the potential mitigation effect. The results show that in 2012, SO2, NOx, and PM2.5 emissions in Guangdong Province were as high as (951.7, 1363.6, and 294.9) kt, respectively. Industrial production processes are the largest source of SO2 and PM2.5 emissions, and transport is the top contributor of NOx emissions. Both the baseline scenario and policy scenario are constructed based on projected energy growth and policy designs. Under the baseline scenario, SO2, NOx, and PM2.5 emissions will almost double in 2030 without proper emissions control policies. The suggested policies are categorized into end-of- pipe control in power plants (ECP), end-of-pipe control in industrial processes (ECI), fuel improvement (FI), energy efficiency improvement (EEI), substitution-pattern development (SPD), and energy saving options (ESO). With the implementation of all these policies, SO2, NOx, and PM2.5 emissions are projected to drop to (303.1, 585.4, and 102.4) kt, respectively, in 2030. This inventory and simulated results will provide deeper insights for policy makers to understand the present situation and the evolution of key emissions in Guangdong Province. More... »

PAGES

46-62

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11707-016-0551-x

DOI

http://dx.doi.org/10.1007/s11707-016-0551-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009383871


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