CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

Jeong, Sang Jin

doi:10.5572/ajae.2011.5.1.001

Cited by 21 publications

(15 citation statements)

References 13 publications

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“…Where C is the ground-level concentration (g m -3 ), Q is the pollutant mass (g) in the puff, x is the standard deviation (m) of the Gaussian distribution in the along-wind direction, y is the standard deviation (m) of the Gaussian distribution in the cross-wind direction, z is the standard deviation (m) of the Gaussian distribution in the vertical direction, da is the distance (m) from the puff center to the receptor in the along-wind direction, dc is the distance (m) from the puff center to the receptor in the cross-wind direction, g is the vertical term (m) of the Gaussian equation, H is the effective height (m) above ground of the puff center, and h is the mixed-layer height (m) (Jeong, 2011). The input data used for the dispersion models are summarized in Table 1.…”

Section: Modeling Methodologymentioning

confidence: 99%

Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey

Demirarslan¹,

Doğruparmak²,

Karademır³

2017

Global NEST Journal

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Air Quality Modeling is a method used to manage urban air quality. Various pollutant dispersion models are available, and each of these models is characterized by its own advantages and disadvantages. Thus, we aimed to evaluate the advantages and disadvantages of the models and to determine their performance by applying them to a specific district. This study also enabled the determination of the contribution of pollution sources to the total pollution and the current air quality of the study area according to the selected pollutants. In this study, both steady-state models (the American Meteorological Society/Environmental Protection Agency Regulatory Model-AERMOD and the Industrial Source Complex Short Term Model-ISCST-3) and the Lagrangian model (the California Puff Model-CALPUFF) were used as the dispersion models. The Körfez district of Kocaeli was selected as the study area. SO2 and PM10 emissions were observed as pollutants. The statistical methods of mean squared error (MSE) and fractional bias (FB) were employed to evaluate the performance of these models. The results of the study revealed that the highest concentration varied according to the models and time options. However, when the modeling results for all of the sources were examined, the highest concentration was calculated by ISCST-3. The effect of the line source was less than the other sources (point and area). The contributions of the pollution sources differed according to each modeling program. The results of the statistical methods, which were used for evaluating the performance of the models, varied according to both the pollutant type and the time option. An overall ranking regarding modeling performance is as follows: CALPUFF > AERMOD > ISCST-3 for PM10 and ISCST-3 > CALPUFF > AERMOD for SO2. The MSE/FB results demonstrated that the predicted values were lower than the measured outcomes. Similarly, a comparison of the predicted and measured values with national and international limits revealed that various measures are necessary to reduce SO2 and PM10.

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Section: Modeling Methodologymentioning

confidence: 99%

Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey

Demirarslan¹,

Doğruparmak²,

Karademır³

2017

Global NEST Journal

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“…Jeong [14] used the AERMOD model to predict odor concentration (regardless of the type of odorous gas, measured based on odor unit). The values of FB, MG, NMSE, VG and FAC2 were equal to -0.019, 1.392, 0.499, 2.461, and 1.019, respectively.…”

Section: Isc Outputmentioning

confidence: 99%

“…Jeong [14] used an AERMOD model to predict odor concentration (regardless of the type of odorous gas, measured based on odor unit) around an industrial complex. Samples were collected at the site in 11 stations and during 5 d, and the meteorological data were measured on the site.…”

Section: Introductionmentioning

confidence: 99%

Mathematical and experimental study of hydrogen sulfide concentrations in the Kahrizak landfill, Tehran, Iran

Asadollahfardi

Mazinani

Asadi

et al. 2019

Environmental Engineering Research

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The emission of hydrogen sulfide (H2S) from the Kahrizak landfill was studied. Firstly, the field measurements were conducted in the summer and winter seasons; and the samples were analyzed using Jacob method. We predicted the H2S concentrations in the downwind using AERMOD and ISCST3. According to the AERMOD, the maximum concentration of H2S in the summer and winter were 117 μg/m 3 and 205 μg/m 3 , respectively. The downwind concentrations reached zero at the distance of 35 km from the leachate treatment plant. The Geometric mean bias, Geometric variance, Fractional bias, Fraction of predictions within a factor of two of the observations and Normalized mean square error for the AERMOD were 0.58, 1.35,-0.12, 1.91 and 0.042, respectively in the summer and 1.39, 1.35,-0.05, 1.46 and 0.027 in the winter; and for the ISCST3, were 0.85, 1.03, 0.02, 1.45 and 0.04 in the summer and 1.18, 1.03, 0.15, 1.16 and 0.04 in the winter. The results of the AERMOD were compared with the ISCST3 and indicated that the AERMOD performance was more suitable than the ISCST3.

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“…A CAREA simulation was performed to assess the spatial distribution of the concentration on the test site assuming each orchard as an emission source of pesticide as already discussed in the literature by Wittich et al [20] and others [80,81].…”

Section: Carea Simulation On the Test Sitementioning

confidence: 99%

Atmospheric Dispersion Modelling and Spatial Analysis to Evaluate Population Exposure to Pesticides from Farming Processes

et al. 2018

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This work originates from an epidemiological study aimed to assess the correlation between population exposure to pesticides used in agriculture and adverse health effects. In support of the population exposure evaluation two models implemented by the authors were applied: a GIS-based proximity model and the CAREA atmospheric dispersion model. In this work, the results of the two models are presented and compared. Despite the proximity analysis is widely used for these kinds of studies, it was investigated how meteorology could affect the exposure assessment. Both models were applied to pesticides emitted by 1519 agricultural fields and considering 2584 receptors distributed over an area of 8430 km 2 . CAREA output shows a considerable enhancement in the percentage of exposed receptors, from the 4% of the proximity model to the 54% of the CAREA model. Moreover, the spatial analysis of the results on a specific test site showed that the effects of meteorology considered by CAREA led to an anisotropic exposure distribution that differs considerably from the symmetric distribution resulting by the proximity model. In addition, the results of a field campaign for the definition and planning of ground measurement of concentration for the validation of CAREA are presented. The preliminary results showed how, during treatments, pesticide concentrations distant from the fields are significantly higher than background values.

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CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

Cited by 21 publications

References 13 publications

Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey

Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey

Mathematical and experimental study of hydrogen sulfide concentrations in the Kahrizak landfill, Tehran, Iran

Atmospheric Dispersion Modelling and Spatial Analysis to Evaluate Population Exposure to Pesticides from Farming Processes

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