Literature DB >> 31229833

A high temporal-spatial emission inventory and updated emission factors for coal-fired power plants in Shanghai, China.

Xiaojia Chen1, Qizhen Liu2, Tao Sheng2, Fang Li2, Zhefeng Xu1, Deming Han1, Xufeng Zhang1, Xiqian Huang1, Qingyan Fu2, Jinping Cheng3.   

Abstract

With the implementation of the ultra-low emission policy in China, emission factors (EFs) of power plant pollutants are constantly changing. Emission inventories developed using the recommended EFs contain high levels of uncertainty and it is difficult to achieve a high temporal resolution. Detailed sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission data based on a continuous emission monitoring system (CEMS) were obtained from 33 units at 13 power plants in Shanghai in 2017. The data were used to develop an hourly unit-based emission inventory and to devise updated EFs for coal-fired power plants. Emissions of SO2, NOx, and PM typically met the ultra-low emission limit, with total emissions of SO2, NOx, and PM of 2895.0, 5348.3, and 503.8 tons, respectively. Emission proportions of SO2 and NOx for 300-600, 600-1000, and above 1000 MW units were similar, while the emission proportion of PM decreased with an increase in unit capacity. Emissions of SO2, NOx, and PM displayed similar monthly variations, peaking in winter and summer. Diurnal hourly variations of SO2, NOx, and PM emissions displayed a bimodal trend, with higher emissions at night on weekends than on weekdays. EFs based on CEMS (EFC) of SO2, NOx, and PM were 0.10, 0.36, and 0.04 g kg-1 of coal, respectively, which were one or two orders of magnitude lower than the widely-used EFs and 4-30 times lower than EFs based on the mass balance approach. After replacing the recommended fixed decontamination efficiencies with individually fitted values, the calculated EFs were consistent with the corresponding EFC and discrepancies were further reduced. The new inventory and updated EFs will enable a better understanding of the temporal variations of power plant emissions and reduce the uncertainty caused by the overestimation of EFs after the implementation of ultra-low emissions technology.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  CEMS; Coal-fired power plants; Emission factor; Unit-based

Year:  2019        PMID: 31229833     DOI: 10.1016/j.scitotenv.2019.06.201

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

1.  A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China.

Authors:  Xue Hu; Qizhen Liu; Qingyan Fu; Hao Xu; Yin Shen; Dengguo Liu; Yue Wang; Haohao Jia; Jinping Cheng
Journal:  Environ Sci Pollut Res Int       Date:  2021-04-16       Impact factor: 4.223

2.  Uncovering the characteristics of air pollutants emission in industrial parks and analyzing emission reduction potential: case studies in Henan, China.

Authors:  Gengyu Gao; Shanshan Wang; Ruoyu Xue; Donghui Liu; He Ren; Ruiqin Zhang
Journal:  Sci Rep       Date:  2021-12-09       Impact factor: 4.379

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

Authors:  Ling Tang; Xiaoda Xue; Jiabao Qu; Zhifu Mi; Xin Bo; Xiangyu Chang; Shouyang Wang; Shibei Li; Weigeng Cui; Guangxia Dong
Journal:  Sci Data       Date:  2020-10-05       Impact factor: 6.444

  3 in total

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