Performance evaluation of AERMOD, CALPUFF, and legacy air dispersion models using the Winter Validation Tracer Study dataset

Rood, Arthur S.

doi:10.1016/j.atmosenv.2014.02.054

Cited by 108 publications

(61 citation statements)

References 7 publications

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“…AERMOD has been compared with ADMS-Urban and CALPUFF and results show AERMOD has lower as well as higher correlations than these models with various case studies. There is no static conclusion based on predicted concentration that any air quality model such as AERMOD, CALPUFF, ISC2 is better (Vieira de Melo et al, Tartakovsky et al, 2013;Rood, 2014). The data generation from meteorological model WRF can provide meteorological parameters to AQM and this can help to accurately estimate health risk, analysis of future impact assessment and Environment Impact Assessment (EIA) for air quality management.…”

Section: Resultsmentioning

confidence: 99%

“…The prediction of AERMOD may not be in good agreement with observation at a distance of 5 km from the reference point and reaction module should be considered for estimation of NO 2 concentrations to obtain more accurate results (Seangkiatiyuth et al, 2011). Health impact assessment and cost benefit analysis can be carried out with output of AERMOD ( (2011) concluded that ADMS-Urban performs better than AERMOD in a particular study but there is no static conclusion based on predicted concentration that any air quality model such as AERMOD, CALPUFF, ISC2 is better (Vieira de Melo et al, 2012;Tartakovsky et al, 2013;Rood, 2014). The development of model based emission factors and aerosols' properties can be carried out using AERMOD (O'Shaughnessy and Altmaier, 2011;Podrez, 2015).…”

Section: Summary Of Aermod Studiesmentioning

confidence: 99%

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Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Kumar

Patil

Dikshit

et al. 2017

Aerosol Air Qual. Res.

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Meteorology plays a crucial role in air quality. The presence of uncertainties of a significant nature in the meteorological profile used during air quality model simulation has the potential to affect negatively the results of the simulations. This paper describes a most recent version of the meteorological model called Weather Research and Forecasting (WRF) model and its importance in air quality. The performance of WRF depends upon the intended application and parameterization scheme of physics options. WRF model is also applied to investigate the simulation results with various land surface models (LSMs) and Planetary Boundary Layer (PBL) parameterizations and various set of microphysics options. It predicts various meteorological spatial parameters like mixing layer height, temperature, humidity, rain fall, cloud cover and wind. The WRF results are integrated with air quality model (AQM) and the AQM depends upon the performance of WRF. It has been applied for evaluation of national pollution control policy, behaviour of plume rise, property of aerosols, prediction of Ozone, SO 2 , NO x , PM 10 , PM 2.5 etc. using AQM for various sources. The effect of topography and different seasons on the concentration of pollutants in the atmosphere has also been studied using AQM. AQM AERMOD has also been reviewed with various other AQM models such as ADMS-Urban and CALPUFF. AERMOD has been used for different time scales, health risk assessment, evaluation of various control strategies, Environmental Impact Assessment (EIA) studies and emission factor estimation. This paper presents the importance of meteorological model to AQM as well as many applications of AQM to demonstrate various scientific questions and policies.

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Section: Resultsmentioning

confidence: 99%

Section: Summary Of Aermod Studiesmentioning

confidence: 99%

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Kumar

Patil

Dikshit

et al. 2017

Aerosol Air Qual. Res.

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“…It is harder to use the Lagrangian puff model since it requires more data entries, a better computer, and more effort, although Gaussian models are easy to use, require less user decision, and can be performed with a cheaper computer [11]. In addition, AERMOD and ISC steady-state models are suggested by the U.S. EPA for close ranges (<50 km) and CALPUFF Lagrangian puff model for long ranges (>50 km) [37].…”

Section: Discussionmentioning

confidence: 99%

“…The ideal value for FB is 0; however, the interval for the obtained results may be between -2.00 (overestimation) and +2.00 (underestimation) [34][35][36][37]. According to Chang and Hanna (2003), suitability of a model could be mentioned if FB value were calculated between -0.7 and +0.7 [38].…”

Section: Methodsmentioning

confidence: 99%

Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

Demirarslan¹,

Doğruparmak²

2016

Pol. J. Environ. Stud.

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Air quality modellings are highly useful systems used to investigate the possible impact of emissions diffusing into the atmosphere in any area they might have on that area. There are many modelling methods whose capacities are limited by their advantages and disadvantages or the equipment they use. In this study, therefore, both steady-state models (AERMOD and ISCST-3) and the Lagrangian model (CALPUFF) are used. This study has two purposes: one is to specify performance of the models. Performances were determined with various statistical methods such as fractional bias (FB), mean squared error (MSE), and geometric mean bias (MG). The other purpose of this study is to evaluate temporal and spatial variations of point (P), area (A), and line (L) -sourced CO and NO x emissions in the research area by using the modelling methods. The district of Körfez, which is one of the districts of the province of Kocaeli, was chosen as the study area.When the results obtained with modelling all P and A sources by three programs are analyzed, the highest annual concentration AERMOD, ISCST-3, and CALPUFF were found as 128.82, 86.96, and 201.30 µg/m 3 for CO, and 7.56, 26.31, and 6.10 µg/m 3 for NO x , respectively. On the other hand, when the results obtained with modelling all P and A and L sources by two programs are investigated, the highest annual concentration AERMOD and ISCST-3 were found to be 155.12, 92.46 µg/m 3 for CO, and 166.93 and 89.98 µg/m 3 for NO x , respectively. When contributions of the pollutant sources on pollution are evaluated, it was observed that area sources and line sources are more predominant than other sources for CO and NO x emissions. It was observed by analyzing the diffusion maps that residential areas in the district are more concentrated. Therefore, in the study the predicted and observed values were also compared with national and international limit values and determined to meet these limit values. According to the results obtained by evaluation of performances of the models with FB, MS, and MG statistical methods, performance sorting for NO x emissions was found to be ISCST-3 > CALPUFF > AERMOD, while for CO emissions it is given as

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“…The parameters R1 and R2 are the distance from an observation where the observation and the initial guess field are equally weighted for surface and layers aloft, respectively. The RMAX1 and RMAX2 parameters define the maximum radius of influence for surface and upper data, respectively, over land surfaces [29]. The surface meteorological data were obtained from 6 stations located within the domain area for hourly data of temperature (°K), precipitation (mm), pressure (mb), relative humidity (%), wind direction (°), wind speed (ms -1 ), opaque sky cover (tenths), and Ceiling height (ft).…”

Section: Air Dispersion Modelmentioning

confidence: 99%

Using CALPUFF to determine the environmental impact of a coal mine open pit

Arregocés

Rojano

Restrepo³

et al. 2016

WIT Transactions on Ecology and the Environment

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This analysis seeks to evaluate the impacts of an open-pit coal mine located in the north of Colombia. It was used as the main tool CALPUFF, model Lagrangian, to determine the dispersion and transport of PM 10 due to the emissions of the mining activities. The model was calibrated and validated with the environmental concentrations data of PM 10 in 5 receivers. It was determined the contributions above of 45 km distances from sources. We use the concept of intake fraction, which is defined as the fraction of material or its precursor released from a source that finally is inhaled or ingested by a population. The results of the model show that the PM 10 can be transported over long distances. to 50 km from the industrial zone of the mine, the average contribution of emissions of the mine can reach 9.12 µg/m 3 and to 60 km contributions of 6.13 µg/m 3 . The modelling estimates that simulations of domain extending about 45 km from the source would only capture on average 54.83% of the total population intake fractions of PM 10 , and less for many geographic settings. The results show that the emission of PM 10 is a problem of pollution on a regional scale. This analysis can serve as input to the competent authorities for better environmental management.

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Performance evaluation of AERMOD, CALPUFF, and legacy air dispersion models using the Winter Validation Tracer Study dataset

Cited by 108 publications

References 7 publications

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

Using CALPUFF to determine the environmental impact of a coal mine open pit

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