The application of the AERMOD model in the environmental health to identify the dispersion area of total suspended particulate from cement industry stacks

Jayadipraja, Erwin Azizi; Daud, Anwar; Assegaf, Alimuddin Hamzah; Maming,

doi:10.18203/2320-6012.ijrms20161757

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…The AERMOD dispersion model, which was approved and preferred by the U.S. EPA for regulatory purposes, is one of the well-recognized air dispersion models for simulating air concentrations from stationary point sources . Several studies applied AERMOD simulations to examine the health impacts associated with residential exposure to air pollution among residents living near industrial sites. ,, The AERMOD dispersion model was chosen due to its high accuracy and reliability in estimating stationary point sources of air concentrations. ,− In addition, the AERMOD model simulations have previously been validated against several field site measurements in Canada, Thailand, and several parts of the United States. , …”

Section: Methodsmentioning

confidence: 99%

Residential Proximity to Biorefinery Sources of Air Pollution and Respiratory Diseases in New York State

Lee

Romeiko

Zhang

et al. 2021

Environ. Sci. Technol.

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Understanding potential health risks associated with biofuel production is critical to sustainably combating energy insecurity and climate change. However, the specific health impacts associated with biorefinery-related emissions are not yet well characterized. We evaluated the relationship between respiratory emergency department (ED) visits (2011–2015) and residential exposure to biorefineries by comparing 15 biorefinery sites to 15 control areas across New York (NY) State. We further examined these associations by biorefinery types (e.g., corn, wood, or soybean), seasons, and lower respiratory disease subtypes. We measured biorefinery exposure using residential proximity in a cross-sectional study and estimation of biorefinery emission via AERMOD-simulated modeling. After controlling for multiple confounders, we consistently found that respiratory ED visit rates among residents living within 10 km of biorefineries were significantly higher (rate ratios (RRs) range from 1.03 to 3.64) than those in control areas across our two types of exposure indices. This relationship held across biorefinery types (higher in corn and soybean biorefineries), seasons (higher in spring and winter), air pollutant types (highest for NO2), and respiratory subtypes (highest for emphysema). Further research is needed to confirm our findings.

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Section: Methodsmentioning

confidence: 99%

Residential Proximity to Biorefinery Sources of Air Pollution and Respiratory Diseases in New York State

Lee

Romeiko

Zhang

et al. 2021

Environ. Sci. Technol.

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“…It is a steady-state Gaussian plume model properly used to refine dispersion of concentrations for simple and complex terrain for receptors within 50 km of a modelled source [20]. AERMOD has been widely applied for simulating pollutants and evaluating dispersion on the ambient air quality [1,7,11,27]. The model supposes the concentration distribution to be Gaussian in both the vertical and horizontal.…”

Section: Aermod Model and Its Configurationmentioning

confidence: 99%

Emission losses and dispersion of volatile organic compounds from tank farm of petroleum refinery complex

Saikomol

Thepanondh

Laowagul

2019

J Environ Health Sci Engineer

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Emission characteristics of volatile organic compounds (VOC) emitted from the tank farm of petroleum refinery were evaluated in this study in order to analyze for the potential impacts on health and odor nuisance problems. Estimation procedures were carried out by using the U.S.EPA TANK 4.0.9d emission model in conjunction with direct measurements of gas phase of each stored liquid within aboveground storage tanks. Results revealed that about 61.12% of total VOC emitted from the tank farm by volume were alkanes, in which pentane were richest (27.4%), followed by cyclopentane (19.22%), propene (19.02%), and isobutene (14.22%). Mostly of pentane (about 80%) were emitted from the floating roof tanks contained crude oil corresponded to the largest annual throughput of crude oil as compared with other petroleum distillates. Emission data were further analyzed for their ambient concentration using the AERMOD dispersion model in order to determine the extent and magnitude of odor and health impacts caused by pentane. Results indicated that there was no health impact from inhalation of pentane. However, predicted data were higher than the odor threshold values of pentane which indicated the possibility of odor nuisance problem in the vicinity areas of the refinery. In order to solve this problem, modification of the type of crude oil storage tanks from external floating roof to domed external floating roof could be significant success in reduction of both emissions and ambient concentrations of VOC from petroleum refinery tank farm.

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“…During the wet season in Factor 1, PM 2.5 , PM 10 , and TSP provided 14.8%, 14.1%, and 12.7% of the respective contributions. As demand for cement is high for development purposes, TSP levels are usually high around cement production plants [35]. Furthermore, the outcome of a study conducted by Olatunde et al [36] present important data on pollution of soils by heavy metals around Dangote cement factory, Ibese, which showed the need for an overhaul of the waste management initiatives of the factory and an emphasis on complying with the regulatory from relevant agencies.…”

Section: Source Apportionment (Examination Of Sources) For Air Qualit...mentioning

confidence: 99%

Source Apportionment of Air Quality Parameters and Noise Levels in the Industrial Zones of Blantyre City

Utsale,

Kaonga,

Thulu

et al. 2024

Air

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The increase in industrial activities has raised concerns regarding air quality in urban areas within Malawi. To assess the source apportionment of air quality parameters (AQPs) and noise levels, concentrations of AQPs (CO, TSP, PM 2.5, PM10) and noise levels were monitored at 15 sites in Makata, Limbe, Maselema, Chirimba, and Maone during dry and wet seasons, respectively. Active mobile multi-gas monitors and a Dylos DC1100 PRO Laser Particle Counter (2018 model) were used to monitor AQPs, while Integrated Sound Level Meters were used to measure noise levels. Monitoring and analysis were guided by the World Health Organization (WHO) and Malawi Standards (MS). A Positive Matrix Factorization (PMF) model was used to determine source apportionment of AQPs, and matrix trajectories analysed air mass movement. In the wet season, the average concentration values of CO, TSP, PM10, and PM2.5 were 0.49 ± 0.65 mg/m3, 85.03 ± 62.18 µg/m3, 14.65 ± 8.13 µg/m3, and 11.52 ± 7.19 µg/m3, respectively. Dry season average concentration values increased to 1.31 ± 0.81 mg/m3, 99.86± 30.06 µg/m3, 24.35 ± 9.53 µg/m3, and 18.28 ± 7.14 µg/m3. Noise levels remained below public MS and WHO standards (85 dB). Positive correlations between AQPs and noise levels were observed, strengthening from weak in the dry season to moderately strong in the wet season. PMF analysis identified key factors influencing AQPs accumulation, emphasizing the need for periodic sampling to monitor seasonal pollution trends, considering potential impacts on public health and environmental sustainability. Further studies should look at factors affecting the dynamics of PMF in Blantyre City.

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The application of the AERMOD model in the environmental health to identify the dispersion area of total suspended particulate from cement industry stacks

Cited by 8 publications

References 9 publications

Residential Proximity to Biorefinery Sources of Air Pollution and Respiratory Diseases in New York State

Residential Proximity to Biorefinery Sources of Air Pollution and Respiratory Diseases in New York State

Emission losses and dispersion of volatile organic compounds from tank farm of petroleum refinery complex

Source Apportionment of Air Quality Parameters and Noise Levels in the Industrial Zones of Blantyre City

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