Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Fine particulate matter (PM) pollution poses a serious threat to public health, and there has been a recent resurgence in PM pollution levels in China. Inter-provincial trade has further complicated the allocation of responsibility for PM emissions. An in-depth analysis of the Air Pollution Prevention and Control Action Plan (APPCAP), a highly effective environmental policy, offers new perspectives and avenues for reflection. Using the multi-regional input-output model and structural decomposition analysis model, this study provides insights into the interlinkages of PM emissions, and their influencing mechanisms among different regions from the perspective of source emissions by quantifying the dynamics of production-related PM emissions (PE) associated with energy consumption and the key driving socio-economic factors in the pre-and post-APPCAP phases. The results indicate that PE initially increased and then decreased over the study period. In the pre-policy stage, only five provinces exhibited a decrease in PE, and this number increased to 21 provinces post-policy. Manufacturing and energy utilities consistently account for significant PE contributions, particularly in Shanghai, Inner Mongolia, and Shanxi. This study finds that pre-policy, the industrial structure effect, the demographic effect, and the level of affluence effect primarily drove PE increases. The post-policy decrease was influenced by industrial structure and consumption pattern effects. Although China's PE remains higher than the consumption-based PM emissions (PE), significant provincial variations exist. Notably, while changes in PE do not always align with PM concentration changes, simultaneous reductions following policy implementation signal positive progress in pollution control. This underscores the necessity of continuously optimizing policy strategies to accommodate regional characteristics.
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Source |
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http://dx.doi.org/10.1016/j.jenvman.2024.123615 | DOI Listing |
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