| Title | Evaluating the data quality of continuous emissions monitoring systems in China |
| Authors | Wang, Xinhao Xu, Lulin Zhang, Qin Zhang, Da Zhang, Xiliang |
| Affiliation | Tsinghua Univ, Inst Energy Environm & Econ, Beijing 100084, Peoples R China Peking Univ, Sch Govt, Beijing 100871, Peoples R China Joint Program Sci & Policy Global Change, Cambridge, MA 02139 USA |
| Issue Date | 15-Jul-2022 |
| Publisher | JOURNAL OF ENVIRONMENTAL MANAGEMENT |
| 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. |
| URI | http://hdl.handle.net/20.500.11897/646679 |
| ISSN | 0301-4797 |
| DOI | 10.1016/j.jenvman.2022.115081 |
| Indexed | SCI(E) |
| Appears in Collections: | 政府管理学院 |
