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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Based on the monitoring data of atmospheric pollutants and the meteorological data in Harbin in 2017, the temporal spatial distribution characteristics of PM pollution and the relationships between PM concentration and meteorological factors in this region were analyzed. The PM concentration data and the meteorological data in 2017 were comprehensively analyzed by using ArcGIS and R. The results show that spatially, the PM concentration in the central districts of Harbin are high in the southeast and low in the northwest; temporally, PM pollution is most serious in autumn and winter, with multiple spells of heavy pollution and an obvious "weekend effect", while the air quality is better in spring and summer; overall, relative humidity is positively correlated to PM concentration, while temperature, wind direction, and wind speed are negatively correlated to PM mass concentration, and low wind speed and high relative humidity are major contributors to increase of PM concentration.: Highlight: The use of big data to deal with the data of air pollution and meteorology.Key points: The air pollution data of Harbin in autumn and winter is more serious than that in spring and summer, and is closely related to meteorological factors. Attraction: Big data is used to process air pollution data and meteorological data, and R language is used to describe the relationship between them.
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Source |
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http://dx.doi.org/10.1080/10962247.2021.1902423 | DOI Listing |
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