A PHP Error was encountered

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

Observing Annual Trends in Vehicular CO Emissions. | LitMetric

Observing Annual Trends in Vehicular CO Emissions.

Environ Sci Technol

Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, California 94720, USA.

Published: April 2022

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
http://dx.doi.org/10.1021/acs.est.1c06828DOI Listing

Publication Analysis

Top Keywords

emissions
12
vehicular emissions
12
ghg emissions
12
annual trends
8
emissions transportation
8
observing annual
4
trends vehicular
4
transportation emissions
4
emissions largest
4
largest individual
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!