Sensitivity analysis for odour dispersion modelling: LAPMOD evaluation and comparison with CALPUFF

IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Francesca Tagliaferri, Alessandra Rota, Marzio Invernizzi
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引用次数: 0

Abstract

Accurate dispersion modelling of odour emissions is essential for assessing their environmental impact on citizens. In this context, the sensitivity analysis of dispersion models is crucial for identifying the factors that most influence their predictions, thereby improving accuracy and reliability in environmental assessments. This study aims to perform a sensitivity analysis of the Lagrangian particle model LAPMOD, focusing on some key parameters including turbulent parametrization, meteorological data interpolation, plume rise algorithms, and concentration prediction kernels. It also compares LAPMOD results with CALPUFF results, one of the most widely applied models for regulatory purposes and odour impact assessments, to evaluate dissimilarities in odour impact predictions for both area and point sources. The analysis reveals that the choice of concentration estimation kernel has a significant impact on LAPMOD's predictions, with the Gaussian Kernel yielding the most consistent results. All other investigated input parameters show minimal influence, leading to variations in the results always below 15%. Concerning the comparison between models, while both models show quite consistent trends for point sources, LAPMOD tends to estimate significantly lower odour impacts from area sources compared to CALPUFF, with estimated separation distances differing up to a factor of 4 between the two models.

气味分散模型的敏感性分析:LAPMOD评价及与CALPUFF的比较
气味排放的准确扩散模型对于评估其对市民的环境影响至关重要。在这种情况下,对分散模型的敏感性分析对于确定最影响其预测的因素至关重要,从而提高环境评估的准确性和可靠性。本研究旨在对拉格朗日粒子模型LAPMOD进行敏感性分析,重点研究湍流参数化、气象数据插值、羽流上升算法和浓度预测核等关键参数。它还将LAPMOD结果与CALPUFF结果进行比较,CALPUFF结果是用于监管目的和气味影响评估的最广泛应用的模型之一,以评估区域和点源气味影响预测的差异。分析表明,浓度估计核的选择对LAPMOD的预测结果有显著影响,其中高斯核的预测结果最一致。所有其他被调查的输入参数显示影响最小,导致结果的变化始终低于15%。关于模型之间的比较,虽然两个模型都显示了点源的相当一致的趋势,但与CALPUFF相比,LAPMOD倾向于估计区域源的气味影响显着降低,估计的分离距离在两个模型之间相差高达4倍。
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来源期刊
Air Quality Atmosphere and Health
Air Quality Atmosphere and Health ENVIRONMENTAL SCIENCES-
CiteScore
8.80
自引率
2.00%
发文量
146
审稿时长
>12 weeks
期刊介绍: Air Quality, Atmosphere, and Health is a multidisciplinary journal which, by its very name, illustrates the broad range of work it publishes and which focuses on atmospheric consequences of human activities and their implications for human and ecological health. It offers research papers, critical literature reviews and commentaries, as well as special issues devoted to topical subjects or themes. International in scope, the journal presents papers that inform and stimulate a global readership, as the topic addressed are global in their import. Consequently, we do not encourage submission of papers involving local data that relate to local problems. Unless they demonstrate wide applicability, these are better submitted to national or regional journals. Air Quality, Atmosphere & Health addresses such topics as acid precipitation; airborne particulate matter; air quality monitoring and management; exposure assessment; risk assessment; indoor air quality; atmospheric chemistry; atmospheric modeling and prediction; air pollution climatology; climate change and air quality; air pollution measurement; atmospheric impact assessment; forest-fire emissions; atmospheric science; greenhouse gases; health and ecological effects; clean air technology; regional and global change and satellite measurements. This journal benefits a diverse audience of researchers, public health officials and policy makers addressing problems that call for solutions based in evidence from atmospheric and exposure assessment scientists, epidemiologists, and risk assessors. Publication in the journal affords the opportunity to reach beyond defined disciplinary niches to this broader readership.
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