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: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
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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The wind erosion source is the greatest contributor of PM₁₀ in Tianjin, China. It is difficult to establish a PM₁₀ emission inventory for the wind erosion source because of the complicated conditions affecting PM₁₀ emissions from wind erosion. In this study, a novel method is developed to establish a PM₁₀ emission inventory for the wind erosion source by using the Wind Erosion Prediction System (WEPS) model with 1 × 1 km spatial resolution. In 2011, the average annual emission of PM₁₀ in Tianjin was 0.373 tons km(-2) (1.113 tons km(-2) in the heating period, 0.237 tons km(-2) in the sand period, and 0.013 tons km(-2) in the non-heating period), and the total PM₁₀ emission was 904,871.6 tons (221,080.7 tons in the heating period, 52,977.8 tons in the sand period, and 1953.2 tons in the non-heating period). After establishing the PM₁₀ emission inventory for the wind erosion source in this manner, the data were input into Model-3/SMOKE. The contribution of the PM₁₀ concentration from the wind erosion source was estimated using the Community Multi-scale Air Quality (Model-3/CMAQ) model and was compared with the monitoring value and the source apportionment results using the chemical mass balance (CMB) method. For this comparison, over the entire year, the R(2) was 0.711. More specifically, R(2) was 0.664, 0.733, and 0.679 in the heating, non-heating, and sand periods, respectively. Thus, we have obtained a reliable method for estimating the source of PM₁₀ from wind erosion.
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http://dx.doi.org/10.1016/j.scitotenv.2013.07.090 | DOI Listing |