Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model

Afzali, Afsaneh; Rashid, M.; Afzali, Mahboubeh; Younesi, Vahid

doi:10.1016/j.jclepro.2017.07.196

Cited by 50 publications

(11 citation statements)

References 33 publications

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“…It is known that the prevailing meteorological conditions, especially the predominant wind can effectively affect the isopleths distribution of pollutants. 42 The wind rose (shown in Fig. 2 ) shows the prevailing wind direction and that its speed was stronger in the north-west direction, which carried the pollutants downwind towards the south-eastern direction.…”

Section: Resultsmentioning

confidence: 99%

Modeling the air pollutant concentration near a cement plant co-processing wastes

Yang

Gao

Hu³

2021

RSC Adv.

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Section: Resultsmentioning

confidence: 99%

Modeling the air pollutant concentration near a cement plant co-processing wastes

Yang

Gao

Hu³

2021

RSC Adv.

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“…It is a steady-state model which assumes that a plume disperses in the horizontal and vertical directions resulting in Gaussian (i.e., bell shaped) concentration distributions [16][17]. This model is a regulatory model used by the US EPA and has been widely applied as a useful tool to estimate source-receptor relationships of air pollutants as well as assessing the contributions from different emission sources to establish a control strategy [18][19].…”

Section: Materials and Methods 1) Emission Datamentioning

confidence: 99%

Source Contribution of 1,3 Butadiene in the Vicinity of Petrochemical Industrial Area

et al. 2021

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Emissions and ambient concentrations of 1,3 butadiene released from the synthetic rubber industries in the largest petroleum and petrochemical complex in Thailand were evaluated in this study. The industrial emissions in this analysis were those emitted from process fugitive, combustion stack, flare, and wastewater treatment facility. It was found that wastewater treatment units were the largest emission source among other potential sources. The contribution of emission from wastewater treatment plants were about 92% of total 1,3 butadiene emission. The extent and magnitude of 1,3 butadiene in ambient air were further evaluated through the simulation of AERMOD dispersion model using these emission data together with local meteorological and topographical characteristics. Predicted annual 1,3 butadiene concentrations at every receptor were lower than its ambient air quality standard (< 0.33 μg m-3). Source apportionment analysis was performed with the objective to reveal the contribution of each emission source to the ambient concentrations at each receptor. Analytical results indicated that wastewater treatment units were the major emission source affected to the environmental concentrations of 1,3 butadiene in the study area. Evaluation of the potential adverse health impact of this chemical revealed that there may be a potential carcinogenic risk from inhalation exposure of 1,3 butadiene. Therefore, an effort in controlling emission of 1,3 butadiene should be given the priority to effectively manage the level of this compound in the environment.

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“…(Fadavi, Abari, & Nadoushan, 2016) WRF which stands for Weather Research and Forecasting Model is one of the options to get meteorological data. This model needs to be compared with observed data for selected study area to make sure the model is ready to use in AERMOD environment and also for model evaluation (Afzali, Rashid, Afzali, & Younesi, 2017). For the purpose of model evaluation, two important parameters are required to be computed which are RMSE (Root Mean Square Error) and MAE (Mean Absolute Error).…”

Section: Aermodmentioning

confidence: 99%

Visualising Urban Air Quality Using Aermod, Calpuff and CFD Models: A Critical Review

Ridzuan

Ujang

Azri

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Degradation of air quality level can affect human’s health especially respiratory and circulatory system. This is because the harmful particles will penetrate into human’s body through exposure to surrounding. The existence of air pollution event is one of the causes for air quality to be low in affected urban area. To monitor this event, a proper management of urban air quality is required to solve and reduce the impact on human and environment. One of the ways to manage urban air quality is by modelling ambient air pollutants. So, this paper reviews three modelling tools which are AERMOD, CALPUFF and CFD in order to visualise the air pollutants in urban area. These three tools have its own capability in modelling the air quality. AERMOD is better to be used in short range dispersion model while CALPUFF is for wide range of dispersion model. Somehow, it is different for CFD model as this model can be used in wide range of application such as air ventilation in clothing and not specifically for air quality modelling only. Because of this, AERMOD and CALPUFF model can be classified in air quality modelling tools group whereas CFD modelling tool is classified into different group namely a non-specific modelling tool group which can be implemented in many fields of study. Earlier air quality researches produced results in two-dimensional (2D) visualization. But there are several of disadvantages for this technique. It cannot provide height information and exact location of pollutants in three-dimensional (3D) as perceived in real world. Moreover, it cannot show a good representation of wind movement throughout the study area. To overcome this problem, the 3D visualization needs to be implemented in the urban air quality study. Thus, this paper intended to give a better understanding on modeling tools with the visualization technique used for the result of performed research.

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Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model

Cited by 50 publications

References 33 publications

Modeling the air pollutant concentration near a cement plant co-processing wastes

Modeling the air pollutant concentration near a cement plant co-processing wastes

Source Contribution of 1,3 Butadiene in the Vicinity of Petrochemical Industrial Area

Visualising Urban Air Quality Using Aermod, Calpuff and CFD Models: A Critical Review

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