Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China
In China, the central government assesses local governments based on data monitored and reported by local agencies, and the accuracy of local statistics has been controversial. In order to further guarantee the authenticity and reliability of surface water monitoring data, the central government wil...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/20/2917 |
| _version_ | 1797512961621753856 |
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| author | Liange Zhao Mengyao Hong Xueyuan Wang |
| author_facet | Liange Zhao Mengyao Hong Xueyuan Wang |
| author_sort | Liange Zhao |
| collection | DOAJ |
| description | In China, the central government assesses local governments based on data monitored and reported by local agencies, and the accuracy of local statistics has been controversial. In order to further guarantee the authenticity and reliability of surface water monitoring data, the central government will gradually withdraw the local monitoring powers of the national surface water assessment section and implement third-party monitoring to achieve “national assessment and national monitoring.” This paper is based on the time-point water data of important national water quality automatic monitoring stations from 2015 to 2020, using the McCrary (2008) density test to infer possible data manipulation phenomena, and analyze whether third-party monitoring has improved the accuracy of China’s environmental data. The results of the study show that between 2015 and 2020, the observed 81 monitoring sites had varying degrees of data discontinuity. The discontinuity of the data after third-party monitoring was reduced in dissolved oxygen (DO) measurement, an important indicator in the assessment, implying that third-party monitoring has improved the quality of water environment data and the accuracy of the data. The research in this article provides a reference for third-party participation in environmental governance and proves that the participation of these organizations can reduce data manipulation behaviors of local governments and ensure the effectiveness of environmental data. |
| first_indexed | 2024-03-10T06:08:03Z |
| format | Article |
| id | doaj.art-eeb985f5d16742f5a3859f4e248a96b4 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T06:08:03Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-eeb985f5d16742f5a3859f4e248a96b42023-11-22T20:22:38ZengMDPI AGWater2073-44412021-10-011320291710.3390/w13202917Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in ChinaLiange Zhao0Mengyao Hong1Xueyuan Wang2School of Economics, Zhejiang Gongshang University, Hangzhou 310018, ChinaSchool of Economics, Zhejiang Gongshang University, Hangzhou 310018, ChinaSchool of Economics, Zhejiang Gongshang University, Hangzhou 310018, ChinaIn China, the central government assesses local governments based on data monitored and reported by local agencies, and the accuracy of local statistics has been controversial. In order to further guarantee the authenticity and reliability of surface water monitoring data, the central government will gradually withdraw the local monitoring powers of the national surface water assessment section and implement third-party monitoring to achieve “national assessment and national monitoring.” This paper is based on the time-point water data of important national water quality automatic monitoring stations from 2015 to 2020, using the McCrary (2008) density test to infer possible data manipulation phenomena, and analyze whether third-party monitoring has improved the accuracy of China’s environmental data. The results of the study show that between 2015 and 2020, the observed 81 monitoring sites had varying degrees of data discontinuity. The discontinuity of the data after third-party monitoring was reduced in dissolved oxygen (DO) measurement, an important indicator in the assessment, implying that third-party monitoring has improved the quality of water environment data and the accuracy of the data. The research in this article provides a reference for third-party participation in environmental governance and proves that the participation of these organizations can reduce data manipulation behaviors of local governments and ensure the effectiveness of environmental data.https://www.mdpi.com/2073-4441/13/20/2917surface water quality monitoringthird-party monitoringwater environment managementincentive compatibilitydata manipulation |
| spellingShingle | Liange Zhao Mengyao Hong Xueyuan Wang Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China Water surface water quality monitoring third-party monitoring water environment management incentive compatibility data manipulation |
| title | Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China |
| title_full | Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China |
| title_fullStr | Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China |
| title_full_unstemmed | Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China |
| title_short | Has Third-Party Monitoring Improved Water Pollution Data Quality? Evidence from National Surface Water Assessment Sections in China |
| title_sort | has third party monitoring improved water pollution data quality evidence from national surface water assessment sections in china |
| topic | surface water quality monitoring third-party monitoring water environment management incentive compatibility data manipulation |
| url | https://www.mdpi.com/2073-4441/13/20/2917 |
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