Impact Analysis of Energy Big Data Centers on Urban Air Quality in China

A research paper analyzes the environmental governance effects of China's Energy Big Data Center (EBDC) policy. The study, authored by Qiuyue Wang and published in April 2026, uses a Difference-in-Differences method to quantify the policy's impact on urban air quality. It finds the policy reduced the urban air quality index by 1.505 in pilot cities compared to non-pilot controls.

Use Cases

• Analyzing the relationship between the EBDC policy variable and changes in the urban air quality index using the DID framework.
• Investigating the mediating mechanisms of government environmental enforcement efficiency and regional green innovation metrics mentioned in the study.
• Examining heterogeneity in policy effects based on variables like local government motivation, regional fossil fuel reliance, and digital economic development level.

Strengths

• Provides a specific, quantified effect size: a 1.505 reduction in the urban air quality index attributed to the policy.
• Employs a quasi-experimental Difference-in-Differences methodology to establish causal inference from the policy rollout.

Limitations

• The dataset is a single 321.5 KB PDF document, containing summarized analysis rather than raw observational or panel data.
• No underlying tabular data (e.g., city-level air quality measurements, enforcement records) is provided for independent replication or alternative modeling.
• Temporal and geographic coverage of the original study data is not specified in the available metadata.

Provenance

Source

Research paper authored by Qiuyue Wang, shared via figshare.

Collection Method

Analysis based on empirical study using the Difference-in-Differences method on data from Chinese cities.

Time Range

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Freshness

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Geography

Focus on cities in China, with noted heterogeneity between northern and other regions.