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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. [Display omitted] • Data quality evaluation criteria of continuous emissions monitoring systems. • Evaluating completeness, accuracy, and authenticity of the data in China. • Policy recommendations for the data quality improvement. [ABSTRACT FROM AUTHOR]