气候变化领域集成服务门户(CCPortal): Uncertainty analysis of modeled ozone changes due to anthropogenic emission reductions in Eastern Texas

CCPortal

DOI	10.1016/j.atmosenv.2021.118798
	Uncertainty analysis of modeled ozone changes due to anthropogenic emission reductions in Eastern Texas
	Dunker A.M.; Nopmongcol U.; Yarwood G.
发表日期	2022
ISSN	1352-2310
卷号	268
英文摘要	We investigate whether an air quality model can predict a concentration change between two related scenarios with greater certainty than either scenario alone and also estimate the uncertainty in Relative Reduction Factors (RRFs). RRFs are ratios of future-year to base-year model results that are used by the U.S. Environmental Protection Agency and the States to predict future ozone (O3) and thus are critical to developing emission control strategies to reduce O3 and achieve compliance with the O3 standard. We conducted simulations for 2012 and 2020 using the Comprehensive Air Quality Model with Extensions and calculated the uncertainties for O3, O3 change (ΔO3), and RRFs using O3 sensitivities. These uncertainties were derived from estimated uncertainties in an extensive set of model inputs comprising the boundary concentrations, dry deposition velocities, emissions, and chemistry. We developed new equations to determine the uncertainties in ΔO3 and RRFs. We evaluated the RRFs obtained from our model by comparing them to recent ozone trends in Eastern Texas (the trends omit 2020 due to the effects of the pandemic.) Uncertainties in ΔO3 and RRFs depend strongly on the degree of correlation between errors in the anthropogenic emissions in the two years. We considered Case A, full correlation of the errors, and Case B, no correlation of errors, as limiting cases. The uncertainty in ΔO3 in Case A is 10–20% of the uncertainty in O3 over most of eastern Texas, and in Case B it is 45–75%. For monitoring sites in three Texas cities, the uncertainty in the RRFs is 0.2–1.0% of the RRFs (Case A) or 4.8–8.5% (Case B). Using ΔO3 or RRFs with base-year design values to predict O3 is likely to produce a more accurate prediction than the modeled O3 for the future year regardless of whether Case A or Case B holds. However, determining the degree of correlation of emission errors between years is necessary to refine further the uncertainty in predicted O3 and merits future study. © 2021 The Authors
关键词	Design value Ozone Ozone change Relative reduction factor Sensitivity Uncertainty
语种	英语
scopus关键词	Air quality; Air quality standards; Compliance control; Emission control; Environmental Protection Agency; Errors; Forecasting; Regulatory compliance; Uncertainty analysis; Air quality models; Anthropogenic emissions; Concentration change; Degree of correlations; Design value; Emission reduction; Ozone changes; Relative reduction factors; Sensitivity; Uncertainty; Ozone; iodine; nitrogen oxide; ozone; volatile organic compound; accuracy assessment; air quality; dry deposition; emission control; human activity; ozone; prediction; air pollution control; air quality; air quality standard; Article; calculation; carbon footprint; computer simulation; controlled study; dry deposition; geographic mapping; mathematical model; measurement accuracy; measurement error; oxygen concentration; predictive validity; sensitivity analysis; temporal analysis; Texas; uncertainty; velocity; Texas; United States
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248154
作者单位	A. M. Dunker, LLC, 4041 Vendome Drive, Auburn Hills, MI 48326, United States; Ramboll, 7250 Redwood Blvd., Suite 105, NovatoCA 94945, United States
推荐引用方式 GB/T 7714	Dunker A.M.,Nopmongcol U.,Yarwood G.. Uncertainty analysis of modeled ozone changes due to anthropogenic emission reductions in Eastern Texas[J],2022,268.
APA	Dunker A.M.,Nopmongcol U.,&Yarwood G..(2022).Uncertainty analysis of modeled ozone changes due to anthropogenic emission reductions in Eastern Texas.ATMOSPHERIC ENVIRONMENT,268.
MLA	Dunker A.M.,et al."Uncertainty analysis of modeled ozone changes due to anthropogenic emission reductions in Eastern Texas".ATMOSPHERIC ENVIRONMENT 268(2022).