Abstract
Construction noise has become a critical environmental pollution source with serious impacts due to rapid urbanization in China. However, studies on construction noise pollution throughout the country are lacking. Meanwhile, emerging social media enables real-time information exchange and can act as a society monitoring sensor. Accordingly, this study employs an innovative approach utilizing web crawler technology and text mining to investigate national construction noise pollution from public feedback on social media platforms. Results showed that construction noise pollution was more severe at around 4:00 am, while more serious in the morning than in the afternoon at the national level. At the regional level, construction noise is most pronounced in the second quarter, relatively light in the first quarter, and generally more severe in the northeast areas. Besides, a weak positive correlation was explored between the construction noise severity and regional economic development. Moreover, through the policy content analysis, the important measures summarized from regional policies were categorized into different groups with the demonstration of recommended practical policy settings. The framework and findings of this study provide a theoretical and practical reference and guideline for future environmental investigation, noise management strategy development, and related policy formulation.
| Original language | English |
|---|---|
| Article number | 106863 |
| Journal | Environmental Impact Assessment Review |
| Volume | 97 |
| DOIs | |
| Publication status | Published - Nov 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
Keywords
- Construction noise pollution
- Policy analysis
- Resilience
- Social media platform
- Text mining
- Web crawler
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