{"title":"Calculation of Sensitivity Coefficients for Individual Airport Emissions in the Continental U.S. using CMAQ-DDM/PM","authors":"S. Boone, S. Arunachalam","doi":"10.1145/2616498.2616504","DOIUrl":null,"url":null,"abstract":"Fine particulate matter (PM2.5) is a federally-regulated air pollutant with well-known impacts on human health. The FAA's Destination 2025 program seeks to decrease aviation-related health impacts across the U.S. by 50% by the year 2018. Atmospheric models, such as the Community Multiscale Air Quality model (CMAQ), are used to estimate the atmospheric concentration of pollutants such as PM2.5. Sensitivity analysis of these models has long been limited to finite difference and regression-based methods, both of which require many computationally intensive model simulations to link changes in output with perturbations in input. Further, they are unable to offer detailed or ad hoc analysis for changes within a domain, such as changes in emissions on an airport-by-airport basis. In order to calculate the sensitivity of PM2.5 concentrations to emissions from individual airports, we utilize the Decoupled Direct Method in three dimensions (DDM-3D), an advanced sensitivity analysis tool recently implemented in CMAQ. DDM-3D allows calculation of sensitivity coefficients within a single simulation, eliminating the need for multiple model runs. However, while the output provides results for a variety of input perturbations in a single simulation, the processing time for each run is dramatically increased compared to simulations conducted without the DDM-3D module.\n Use of the XSEDE Stampede computing cluster allows us to calculate sensitivity coefficients for a large number of input parameters. This allows for a much wider variety of ad hoc aviation policy scenarios to be generated and evaluated than would be possible using other sensitivity analysis methods or smaller-scaled computing systems. We present a design of experiments to compute individual sensitivity coefficients for 139 major airports in the US, due to six different precursor emissions that form PM2.5 in the atmosphere. Simulations based on this design are currently in progress, with full results to be published at a later date.","PeriodicalId":93364,"journal":{"name":"Proceedings of XSEDE16 : Diversity, Big Data, and Science at Scale : July 17-21, 2016, Intercontinental Miami Hotel, Miami, Florida, USA. Conference on Extreme Science and Engineering Discovery Environment (5th : 2016 : Miami, Fla.)","volume":"54 1","pages":"10:1-10:8"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of XSEDE16 : Diversity, Big Data, and Science at Scale : July 17-21, 2016, Intercontinental Miami Hotel, Miami, Florida, USA. Conference on Extreme Science and Engineering Discovery Environment (5th : 2016 : Miami, Fla.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2616498.2616504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Fine particulate matter (PM2.5) is a federally-regulated air pollutant with well-known impacts on human health. The FAA's Destination 2025 program seeks to decrease aviation-related health impacts across the U.S. by 50% by the year 2018. Atmospheric models, such as the Community Multiscale Air Quality model (CMAQ), are used to estimate the atmospheric concentration of pollutants such as PM2.5. Sensitivity analysis of these models has long been limited to finite difference and regression-based methods, both of which require many computationally intensive model simulations to link changes in output with perturbations in input. Further, they are unable to offer detailed or ad hoc analysis for changes within a domain, such as changes in emissions on an airport-by-airport basis. In order to calculate the sensitivity of PM2.5 concentrations to emissions from individual airports, we utilize the Decoupled Direct Method in three dimensions (DDM-3D), an advanced sensitivity analysis tool recently implemented in CMAQ. DDM-3D allows calculation of sensitivity coefficients within a single simulation, eliminating the need for multiple model runs. However, while the output provides results for a variety of input perturbations in a single simulation, the processing time for each run is dramatically increased compared to simulations conducted without the DDM-3D module. Use of the XSEDE Stampede computing cluster allows us to calculate sensitivity coefficients for a large number of input parameters. This allows for a much wider variety of ad hoc aviation policy scenarios to be generated and evaluated than would be possible using other sensitivity analysis methods or smaller-scaled computing systems. We present a design of experiments to compute individual sensitivity coefficients for 139 major airports in the US, due to six different precursor emissions that form PM2.5 in the atmosphere. Simulations based on this design are currently in progress, with full results to be published at a later date.
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使用CMAQ-DDM/PM计算美国大陆个别机场排放的敏感系数
细颗粒物(PM2.5)是一种由联邦政府监管的空气污染物,对人体健康的影响众所周知。美国联邦航空局的“目的地2025”计划旨在到2018年将全美与航空相关的健康影响减少50%。大气模型,如社区多尺度空气质量模型(CMAQ),被用来估计PM2.5等污染物的大气浓度。长期以来,这些模型的敏感性分析一直局限于有限差分和基于回归的方法,这两种方法都需要大量的计算密集型模型模拟,以将输出变化与输入扰动联系起来。此外,它们无法对一个领域内的变化提供详细的或特别的分析,例如逐个机场的排放量变化。为了计算PM2.5浓度对各个机场排放的敏感性,我们使用了三维解耦直接法(DDM-3D),这是CMAQ最近实施的一种先进的敏感性分析工具。DDM-3D允许在一次模拟中计算灵敏度系数,从而消除了多次模型运行的需要。然而,虽然输出在一次模拟中提供了各种输入扰动的结果,但与没有DDM-3D模块的模拟相比,每次运行的处理时间大大增加。使用XSEDE Stampede计算集群允许我们计算大量输入参数的灵敏度系数。与使用其他敏感性分析方法或较小规模的计算系统相比,这允许生成和评估更广泛的特别航空政策情景。我们提出了一种实验设计,用于计算美国139个主要机场的个别敏感性系数,因为在大气中形成PM2.5的六种不同的前体排放。基于这种设计的模拟目前正在进行中,完整的结果将在晚些时候公布。
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