Evaluating the data quality of continuous emissions monitoring systems in China

Xinhao Wang; Lulin Xu; Qin Zhang; Da Zhang; Xiliang Zhang

doi:10.1016/j.jenvman.2022.115081

Evaluating the data quality of continuous emissions monitoring systems in China

J Environ Manage. 2022 Jul 15:314:115081. doi: 10.1016/j.jenvman.2022.115081. Epub 2022 Apr 20.

Authors

Xinhao Wang¹, Lulin Xu², Qin Zhang¹, Da Zhang³, Xiliang Zhang¹

Affiliations

¹ Institute of Energy, Environment and Economy, Tsinghua University, Beijing, 100084, China.
² School of Government, Peking University, Beijing, 100871, China.
³ Institute of Energy, Environment and Economy, Tsinghua University, Beijing, 100084, China; MIT Joint Program on the Science and Policy of Global Change, Cambridge, MA, 02139, USA. Electronic address: zhangda@tsinghua.edu.cn.

PMID: 35460987
DOI: 10.1016/j.jenvman.2022.115081

Abstract

Starting in 2013, China's key polluting firms have been required to install continuous emissions monitoring systems (CEMS) and to publish the data for real-time oversight and public scrutiny. However, the CEMS data has rarely been used in local environmental law enforcement because its quality is still of great concern. A lack of criteria to evaluate data quality is one of the causes. In this paper, we design a comprehensive analytical framework for evaluating the quality of CEMS data, which includes completeness, accuracy, and authenticity. To demonstrate the applicability of the framework, we build a CEMS dataset for key polluting firms in Henan province from 2017 to 2019 by scraping the CEMS data from a public platform. We then conduct a comprehensive evaluation using our proposed framework. Some data quality issues are identified. About one-third of the firms did not meet official guidelines for data completeness. When comparing the CEMS data with onsite measurement results, we observe statistically significant inconsistencies in about one-fifth of the firms. In addition, we find evidence that some firms might manipulate CEMS data by strategically turning down the CEMS when a pollutant's concentration is expected to exceed the limit. Our framework can be expanded by incorporating more evaluation methods and data. We suggest that government agencies should implement a comprehensive framework to enhance the quality of CEMS data, thereby facilitating its application in law enforcement.

Keywords: Continuous emissions monitoring systems; Data quality evaluation; Environmental law enforcement; Key polluting firm; Public scrutiny.

MeSH terms

China
Data Accuracy*