气候变化领域集成服务门户(CCPortal): Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach

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DOI	10.1016/j.atmosenv.2021.118566
	Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach
	Veratti G.; Bigi A.; Lupascu A.; Butler T.M.; Ghermandi G.
发表日期	2021
ISSN	1352-2310
卷号	261
英文摘要	Operational forecasting systems based on chemical transport models (CTMs) nowadays generally produce concentration maps with a resolution in the order of 2–5 km, very rarely exceeding the sub-kilometre scale. The main reason for this restriction is the prohibitive computing cost that a simulation covering an entire country would have if set-up with a resolution in the order of meters. In this paper a hybrid forecast system, relying on the WRF-Chem model coupled with the PMSS Lagrangian modelling suite, has been developed and applied for each day of February 2019, to predict hourly NO2 and NOx concentrations with a spatial resolution of 4 m, for the urban area of Modena (a city located in the central Po Valley). Simulated meteorological fields (temperature, wind speed and direction) were assessed at three urban stations, compliant with WMO standards, and modelled concentrations were compared with measurements at two urban air quality stations located at background and traffic sites. Results show that meteorological variables are well captured by the hybrid system and statistical performances are in line with the benchmark values suggested by the European Environmental Agency and with similar case studies focusing on the same area. Modelled NO2 and NOx concentrations, notwithstanding a slight underestimation mainly evident at urban traffic stations for NOx, present a large agreement with related observations. The NO2 Model Quality Objective, as defined by Fairmode guidelines, was met for both the urban stations and the other statistical indexes considered in the evaluation fulfilled the acceptance criteria for dispersion modelling in urban environment, for both NO2 and NOx concentrations. In the second section of the study, the population exposure to forecasted NO2 concentrations has been evaluated adopting a generic model of dynamic population activity. The population was distributed at hourly time steps in specific urban micro-environments at the same resolution of the concentration maps (4 m) and the short-term exposure has been computed as the product between the population density in each model cell and related surface NO2 concentrations. An infiltration factor was also applied to estimate indoor concentrations. The hybrid system was shown to be particularly suited for assessing short-term peak exposure in areas influenced by traffic emissions. On the other hand, due to the limited time spent by the population within traffic related environments, the long-term population exposure calculated by the hybrid system tends to be similar to the WRF-Chem stand-alone estimate. © 2021 Elsevier Ltd
关键词	Fairmode assessment Forecast system PMSS Population exposure assessment WRF-Chem
语种	英语
scopus关键词	Air quality; Hybrid systems; Nitrogen oxides; Population statistics; Urban growth; Wind; Concentration maps; Fairmode assessment; Forecast systems; NO $-2$; NO$-x$; PMSS; Population exposure; Population exposure assessments; Urban stations; WRF/Chem; Forecasting; nitrogen dioxide; nitrogen oxide; air quality; concentration (composition); detection method; flood forecasting; forecasting method; nitrogen dioxide; population density; spatial resolution; urban area; urban population; wind velocity; air monitoring; air quality; Article; atmospheric dispersion; circadian rhythm; controlled study; environmental temperature; forecasting; geographic mapping; human; intermethod comparison; maximum concentration; measurement accuracy; microenvironment; nitrogen concentration; nitrogen metabolism; performance measurement system; population density; population distribution; population exposure; spatiotemporal analysis; time series analysis; traffic pollution; urban area; urban population; wind speed; Emilia-Romagna; Italy; Modena; Po Valley
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/248338
作者单位	Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, via Pietro Vivarelli 10, Modena, 41125, Italy; Institute for Advanced Sustainability Studies, Berliner Straße 130, Potsdam, 14467, Germany
推荐引用方式 GB/T 7714	Veratti G.,Bigi A.,Lupascu A.,et al. Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach[J],2021,261.
APA	Veratti G.,Bigi A.,Lupascu A.,Butler T.M.,&Ghermandi G..(2021).Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach.ATMOSPHERIC ENVIRONMENT,261.
MLA	Veratti G.,et al."Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach".ATMOSPHERIC ENVIRONMENT 261(2021).