CCPortal
DOI10.5194/acp-18-2615-2018
Southeast Atmosphere Studies: learning from model-observation syntheses
Mao, Jingqiu1,2; Carlton, Annmarie3,24; Cohen, Ronald C.4; Brune, William H.5; Brown, Steven S.6,7,8; Wolfe, Glenn M.9,10; Jimenez, Jose L.6,7; Pye, Havala O. T.11; Ng, Nga Lee12,13; Xu, Lu12,13,25; McNeill, V. Faye14; Tsigaridis, Kostas15,16; McDonald, Brian C.8,9; Warneke, Carsten8,9; Guenther, Alex17; Alvarado, Matthew J.18; de Gouw, Joost6,7; Mickley, Loretta J.19; Leibensperger, Eric M.20; Mathur, Rohit11; Nolte, Christopher G.11; Portmann, Robert W.8; Unger, Nadine21; Tosca, Mika22; Horowitz, Larry W.23
发表日期2018-02-22
ISSN1680-7316
卷号18期号:4页码:2615-2651
英文摘要

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.


This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.


语种英语
WOS记录号WOS:000425816600002
来源期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
来源机构美国环保署
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/62082
作者单位1.Univ Alaska Fairbanks, Inst Geophys, Fairbanks, AK 99775 USA;
2.Univ Alaska Fairbanks, Dept Chem, Fairbanks, AK 99775 USA;
3.Rutgers State Univ, Dept Environm Sci, New Brunswick, NJ USA;
4.Univ Calif Berkeley, Dept Earth & Planetary Sci, Berkeley, CA 94720 USA;
5.Penn State Univ, Dept Meteorol, 503 Walker Bldg, University Pk, PA 16802 USA;
6.Univ Colorado, Dept Chem, Boulder, CO 80309 USA;
7.Univ Colorado, CIRES, Boulder, CO 80309 USA;
8.Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA;
9.NOAA, Chem Sci Div, Earth Syst Res Lab, Boulder, CO USA;
10.Univ Maryland Baltimore Cty, Joint Ctr Earth Syst Technol, Baltimore, MD 21228 USA;
11.US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA;
12.Georgia Inst Technol, Sch Chem & Biomol Engn, Atlanta, GA 30332 USA;
13.Georgia Inst Technol, Sch Earth & Atmospher Sci, Atlanta, GA 30332 USA;
14.Columbia Univ, Dept Chem Engn, New York, NY USA;
15.Columbia Univ, Ctr Climate Syst Res, New York, NY USA;
16.NASA, Goddard Inst Space Studies, New York, NY 10025 USA;
17.Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA USA;
18.Atmospher & Environm Res, Lexington, MA USA;
19.Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA;
20.SUNY Coll Plattsburgh, Ctr Earth & Environm Sci, Plattsburgh, NY 12901 USA;
21.Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England;
22.SAIC, Chicago, IL 60603 USA;
23.NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA;
24.Univ Calif Irvine, Dept Chem, Irvine, CA 92717 USA;
25.CALTECH, Div Geol & Planetary Sci, Pasadena, CA 91125 USA
推荐引用方式
GB/T 7714
Mao, Jingqiu,Carlton, Annmarie,Cohen, Ronald C.,et al. Southeast Atmosphere Studies: learning from model-observation syntheses[J]. 美国环保署,2018,18(4):2615-2651.
APA Mao, Jingqiu.,Carlton, Annmarie.,Cohen, Ronald C..,Brune, William H..,Brown, Steven S..,...&Horowitz, Larry W..(2018).Southeast Atmosphere Studies: learning from model-observation syntheses.ATMOSPHERIC CHEMISTRY AND PHYSICS,18(4),2615-2651.
MLA Mao, Jingqiu,et al."Southeast Atmosphere Studies: learning from model-observation syntheses".ATMOSPHERIC CHEMISTRY AND PHYSICS 18.4(2018):2615-2651.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Mao, Jingqiu]的文章
[Carlton, Annmarie]的文章
[Cohen, Ronald C.]的文章
百度学术
百度学术中相似的文章
[Mao, Jingqiu]的文章
[Carlton, Annmarie]的文章
[Cohen, Ronald C.]的文章
必应学术
必应学术中相似的文章
[Mao, Jingqiu]的文章
[Carlton, Annmarie]的文章
[Cohen, Ronald C.]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。