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
Transportation emissions are the largest individual sector of greenhouse gas (GHG) emissions. As such, reducing transportation-related emissions is a primary element of every policy plan to reduce GHG emissions. The Berkeley Environmental Air-quality and CO Observation Network (BEACON) was designed and deployed with the goal of tracking changes in urban CO emissions with high spatial (∼1 km) and temporal (∼1 hr) resolutions while allowing the identification of trends in individual emission sectors. Here, we describe an approach to inferring vehicular CO emissions with sufficient precision to constrain annual trends. Measurements from 26 individual BEACON sites are combined and synthesized within the framework of a Gaussian plume model. After removing signals from biogenic emissions, we are able to report normalized annual emissions for 2018-2020. A reduction of 7.6 ± 3.5% in vehicular CO emissions is inferred for the San Francisco Bay Area over this 2 year period. This result overlaps with, but is slightly larger than, estimates from the 2017 version of the California Air Resources Board EMFAC emissions model, which predicts a 4.7% decrease over these 2 years. This demonstrates the feasibility of independently and rapidly verifying policy-driven reductions in GHG emissions from transportation with atmospheric observations in cities.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/acs.est.1c06828 | DOI Listing |
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