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Title: Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation

Abstract

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and sulfur dioxide (SO2) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively largemore » increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NOx, VOC, and NH3, while emissions from both the on-road and non-road modes have strong contributions to PM and SO2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.« less

Authors:
; ; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
National Science Foundation (NSF); U.S. Department of Agriculture (USDA)
OSTI Identifier:
1482101
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
Environmental Pollution
Additional Journal Information:
Journal Volume: 238; Journal Issue: C; Journal ID: ISSN 0269-7491
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
SPEW-trend; WRF/CMAQ; climate change; dynamical downscaling; technology driver model; transportation sector emissions

Citation Formats

Campbell, Patrick, Zhang, Yang, Yan, Fang, Lu, Zifeng, and Streets, David. Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation. United States: N. p., 2018. Web. doi:10.1016/j.envpol.2018.04.020.
Campbell, Patrick, Zhang, Yang, Yan, Fang, Lu, Zifeng, & Streets, David. Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation. United States. doi:10.1016/j.envpol.2018.04.020.
Campbell, Patrick, Zhang, Yang, Yan, Fang, Lu, Zifeng, and Streets, David. Sun . "Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation". United States. doi:10.1016/j.envpol.2018.04.020.
@article{osti_1482101,
title = {Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation},
author = {Campbell, Patrick and Zhang, Yang and Yan, Fang and Lu, Zifeng and Streets, David},
abstractNote = {Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and sulfur dioxide (SO2) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NOx, VOC, and NH3, while emissions from both the on-road and non-road modes have strong contributions to PM and SO2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.},
doi = {10.1016/j.envpol.2018.04.020},
journal = {Environmental Pollution},
issn = {0269-7491},
number = C,
volume = 238,
place = {United States},
year = {2018},
month = {7}
}