Air pollution emissions from Chinese power plants based on the continuous emission monitoring systems network

Author:

Tang LingORCID,Xue XiaodaORCID,Qu Jiabao,Mi ZhifuORCID,Bo XinORCID,Chang Xiangyu,Wang ShouyangORCID,Li Shibei,Cui Weigeng,Dong Guangxia

Abstract

AbstractTo meet the growing electricity demand, China’s power generation sector has become an increasingly large source of air pollutants. Specific control policymaking needs an inventory reflecting the overall, heterogeneous, time-varying features of power plant emissions. Due to the lack of comprehensive real measurements, existing inventories rely on average emission factors that suffer from many assumptions and high uncertainty. This study is the first to develop an inventory of particulate matter (PM), SO2 and NOX emissions from power plants using systematic actual measurements monitored by China’s continuous emission monitoring systems (CEMS) network over 96–98% of the total thermal power capacity. With nationwide, source-level, real-time CEMS-monitored data, this study directly estimates emission factors and absolute emissions, avoiding the use of indirect average emission factors, thereby reducing the level of uncertainty. This dataset provides plant-level information on absolute emissions, fuel uses, generating capacities, geographic locations, etc. The dataset facilitates power emission characterization and clean air policy-making, and the CEMS-based estimation method can be employed by other countries seeking to regulate their power emissions.

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

Reference55 articles.

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