Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Fine particulate matter (PM) samples were collected in two neighboring cities, Beijing and Baoding, China. High-concentration events of PM in which the average mass concentration exceeded 75 µg/m were frequently observed during the heating season. Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities. Secondary nitrate had the highest contribution for Beijing (37.3 %), and residential heating/biomass burning was the largest for Baoding (27.1 %). Secondary nitrate, mobile, biomass burning, district heating, oil combustion, aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period (2019.01.10-2019.08.22) (Mann-Whitney Rank Sum Test P < 0.05). In case of Baoding, soil, residential heating/biomass burning, incinerator, coal combustion, oil combustion sources showed significant differences. The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients. Conditional Bivariate Probability Function (CBPF) was used to identify the inflow directions for the sources, and joint-PSCF (Potential Source Contribution Function) was performed to determine the common potential source areas for sources affecting both cities. These models facilitated a more precise verification of city-specific influences on PM sources. The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.
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http://dx.doi.org/10.1016/j.jes.2024.10.029 | DOI Listing |