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Carbon Monoxide Emissions from the Washington, DC, and Baltimore Metropolitan Area: Recent Trend and COVID-19 Anomaly

  • Israel Lopez-Coto
  • , Xinrong Ren
  • , Anna Karion
  • , Kathryn McKain
  • , Colm Sweeney
  • , Russell R. Dickerson
  • , Brian C. McDonald
  • , Doyeon Y. Ahn
  • , Ross J. Salawitch
  • , Hao He
  • , Paul B. Shepson
  • , James R. Whetstone
  • University of Maryland, College Park
  • National Oceanic and Atmospheric Administration
  • National Institute of Standards and Technology
  • University of Colorado Boulder

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

We analyze airborne measurements of atmospheric CO concentration from 70 flights conducted over six years (2015-2020) using an inverse model to quantify the CO emissions from the Washington, DC, and Baltimore metropolitan areas. We found that CO emissions have been declining in the area at a rate of ≈−4.5 % a-1 since 2015 or ≈−3.1 % a-1 since 2016. In addition, we found that CO emissions show a “Sunday” effect, with emissions being lower, on average, than for the rest of the week and that the seasonal cycle is no larger than 16 %. Our results also show that the trend derived from the NEI agrees well with the observed trend, but that NEI daytime-adjusted emissions are ≈50 % larger than our estimated emissions. In 2020, measurements collected during the shutdown in activity related to the COVID-19 pandemic indicate a significant drop in CO emissions of 16 % relative to the expected emissions trend from the previous years, or 23 % relative to the mean of 2016 to February 2020. Our results also indicate a larger reduction in April than in May. Last, we show that this reduction in CO emissions was driven mainly by a reduction in traffic.

Original languageEnglish
Pages (from-to)2172-2180
Number of pages9
JournalEnvironmental Science and Technology
Volume56
Issue number4
DOIs
StatePublished - Feb 15 2022

Keywords

  • CO emissions
  • COVID-19
  • inverse modeling
  • recent trend
  • urban monitoring system

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