A Parallel Computing Algorithm for the Emergency-Oriented Atmospheric Dispersion Model CALPUFF

Yang, Dongou; Li, Mei; Liu, Hui

doi:10.3390/atmos13122129

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…CALPUFF software is an advanced air quality modeling system for unsteady state weather conditions capable of simulating point, line, surface, and volume sources [35]. The three main components of this software are as follows: CALMET (a three-dimensional recognition model of meteorological data), CALPUFF (an air quality distribution model), and CALPOST (a post-processing suite)…”

Section: Calpuff Softwarementioning

confidence: 99%

Human health risk assessment for NO2, SO2 and CO emissions from a refinery using CALPUFF; A case study Kangan, Iran

Kiaei,

Pardakhti,

Zahed

2023

Preprint

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Nowadays, remarkable attention is being devoted to the issue of air pollutants like NO2, SO2, and CO emitted from refineries. Such contaminants have hazardous effects on people's health. They are regarded as the main contributors to lung cancer, heart disease, pulmonary lesions, etc. Hence, it is essential to provide basic solutions for reducing the effects of air pollutants or preventing their emission. For this purpose, the related studies considered risk assessment of air pollution in cities with high concentrations of pollutants. The current paper models the dispersion of NO2, SO2, and CO emitted from flares and chimneys of Phase 12 of the South Pars refinery, considering risk assessment for the citizens of Kangan, Iran. CALPUFF software was employed for simulating the conditions of the considered case study, and the outcomes were compared with those presented by Iran's air quality monitoring system. An acceptable agreement was observed between the results, while the difference could not be ignored. According to the modeling results and risk assessment, there is no risk for CO and NO2. Nevertheless, there is a risk for SO2 based on the modeling and results of Iran's air pollution monitoring system. Thus, the essence of taking preventative actions and reducing SO2 emissions is required. The novelty of this paper lies in the heart of the accuracy and authenticity of the numerical results achieved for the citizens of Kangan, Iran. Additionally, the results of the other works confirm the findings of this paper which is evidence for the validation of the findings.

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Section: Calpuff Softwarementioning

confidence: 99%

Human health risk assessment for NO2, SO2 and CO emissions from a refinery using CALPUFF; A case study Kangan, Iran

Kiaei,

Pardakhti,

Zahed

2023

Preprint

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“…In this regard, to explore more and new possible scenarios, it is fundamental and necessary to reduce the computational execution time of the involved simulation processes. Many areas pursue this goal and employ parallel programming for it, for instance in [2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Parallel Algorithm to Simulate the Type I Error Probability

Novoa-Muñoz

2024

Mathematics

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Simulating the probability of type I error is a powerful statistical tool that allows confirming if the statistical test achieves the established nominal level. However, its computational implementation has the drawback of significantly long execution times. Therefore, this article analyzes the performance of two parallel implementations (parRapply and boot) which significantly reduce the execution time of simulations of type I error probability for a goodness-of-fit test for the bivariate Poisson distribution. The results obtained demonstrate how the parallelization strategies accelerate the simulations, reducing the time by 50% to 90% when using 2 to 12 processors running in parallel. This reduction is graphically evidenced as the execution time of the analyzed parallel versions fits almost perfectly (R2≈0.999) to the power model y=apb, where p is the number of processors used, and a>0 and b<0 are the constants of the model. Furthermore, it is shown that the parallelization strategies used scale with an increasing number of processors. All algorithms were implemented in the R programming language, and their code is included at the end of this article.

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Impact assessment of spatial–temporal distribution of riverine dust on air quality using remote sensing data and numerical modeling

Chen,

Lin

2024

Environ Sci Pollut Res

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A Parallel Computing Algorithm for the Emergency-Oriented Atmospheric Dispersion Model CALPUFF

Cited by 4 publications

References 3 publications

Human health risk assessment for NO2, SO2 and CO emissions from a refinery using CALPUFF; A case study Kangan, Iran

Human health risk assessment for NO2, SO2 and CO emissions from a refinery using CALPUFF; A case study Kangan, Iran

Implementation of a Parallel Algorithm to Simulate the Type I Error Probability

Impact assessment of spatial–temporal distribution of riverine dust on air quality using remote sensing data and numerical modeling

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