dispersion modeling
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2022 ◽  
Vol 14 (2) ◽  
pp. 793
Gregorio Sgrigna ◽  
Hélder Relvas ◽  
Ana Isabel Miranda ◽  
Carlo Calfapietra

Particulate matter represents a serious hazard to human health, and air quality models contribute to the understanding of its dispersion. This study describes particulate matter with a ≤10 μm diameter (PM10) dynamics in an urban–industrial area, through the comparison of three datasets: modeled (TAPM—The Air Pollution Model), measured concentration (environmental control stations—ECS), and leaf deposition values. Results showed a good agreement between ECS and TAPM data. A steel plant area was used as a PM10 emissions reference source, in relation to the four sampling areas, and a distance/wind-based factor was introduced (Steel Factor, SF). Through SF, the three datasets were compared. The SF was able to describe the PM10 dispersion values for ECS and leaf deposition (r2 = 0.61–0.94 for ECS; r2 = 0.45–0.70 for leaf); no relationship was found for TAPM results. Differences between measured and modeled data can be due to discrepancies in one district and explained by a lack of PM10 inventory for the steel plant emissions. The study suggests the use of TAPM as a suitable tool for PM10 modeling at the urban scale. Moreover, tree leaves are a low-cost tool to evaluate the urban environmental quality, by providing information on whether and when data from leaf deposition can be used as a proxy for air pollution concentration. Further studies to include the re-suspension of particles as a PM10 source within emission inventories are suggested.

2022 ◽  
Vol 301 ◽  
pp. 113913
Zheng Wang ◽  
Chunjiang An ◽  
Kenneth Lee ◽  
Edward Owens ◽  
Michel Boufadel ◽  

2021 ◽  
Vol 62 (2) ◽  
pp. 239-244

A short range model calculating ground-level concentration from elevated sources is estimated, which realized a Fickian-type formula. Taking the source and mixing height are functions of the wind velocity and eddy diffusivity profiles. The model estimated with an exact solution of the advection diffusion equation is compared with experimental ground level concentrations using meteorological data collected near the ground.

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8236
Kamila Przespolewska-Gdowik ◽  
Remigiusz Jasiński

The dynamic development of aviation is associated with many benefits, but also, unfortunately, with negative effects. One of the adverse consequences is the exhaust emissions that have a negative impact on human health. It particularly affects the residents of areas neighboring airports, as airport activity deteriorates local air quality. Using the Emissions and Dispersion Modeling System, the activity of the Nicolaus Copernicus Airport was assessed in terms of the flight operations’ contribution to air contamination in the area adjacent to the airport. Emissions from three sources were compared: aircraft, ground support equipment and auxiliary power units. The concentrations of pollutants in inhabited areas located in three different directions in relation to the airport were also estimated. In addition, the effect of distance from the airport on contaminant concentrations was assessed as a function of wind direction. It was noticed that small values of pollutant concentrations, originating from airport activity, appeared within a few kilometers from the airport, even if the prevailing wind direction on a given day was opposite to the analyzed dispersion direction.

Kevin Wolz ◽  
Sonja Leitner ◽  
Lutz Merbold ◽  
Benjamin Wolf ◽  
Matthias Mauder

AbstractThis study provides methane (CH4) emission estimates for mature female African beef cattle in a semi-arid region in Southern Kenya using open-path laser spectroscopy together with a backward Lagrangian Stochastic (bLS) dispersion modeling technique. We deployed two open-path lasers to determine 10-min averages of line-integrated CH4 measurements upwind and downwind of fenced enclosures (so-called bomas: a location where the cattle are gathered at night) during 14 nights in September/October 2019. The measurements were filtered for wind direction deviations and friction velocity before the model was applied. We compared the obtained emission factors (EFs) with the Intergovernmental Panel on Climate Change (IPCC) Tier 1 estimates for the Sub-Saharan African (SSA) countries, which were mostly derived from studies carried out in developed countries and adapted to the conditions in Africa. The resulting EF of 75.4 ± 15.99 kg year−1 and the EFs calculated from other studies carried out in Africa indicate the need for the further development of region-specific EFs depending on animal breed, livestock systems, feed quantity, and composition to improve the IPCC Tier 1 estimates.

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2246
David Janke ◽  
Senthilathiban Swaminathan ◽  
Sabrina Hempel ◽  
Robert Kasper ◽  
Thomas Amon

Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.

2021 ◽  
Vol 13 (2) ◽  
Dewi Eviane ◽  
Taufik Abdillah Natsir ◽  
Nur Iswanto ◽  
Zulfadly Urufi ◽  
Mardiyanto Adji

Air pollution generated from airport activities has become public concern and the subject of more rigorous government regulations.  The Airport Operators are stipulated to control the pollution and for the accountability of air quality that might affect public health. The main objective of this study is to establish a model for the distribution of air pollutants and to predict their concentrations generated by the runway and apron operations at Sam Ratulangi International Airport (Manado) until 2024, in accordance with the airport expansion program. The data was collected in the airport surrounding area in 2018, while the climate data over a span of 10 years, from 2009 to 2018, was obtained from Sam Ratulangi Meteorological Station. The modeling on dispersion of air pollutant gases was developed by the Gaussian Plume Equation. The simulation was performed using AERMOD software, and the results visualized by GIS software. AERMOD software was recommended by the US-EPA to predict the impact of air pollutants. The results predicted that the maximum concentrations of NOx; HC; and CO generated by runway activities modeling in 2024 were 250 μg.m-3; 6.4 μg.m-3; and 87 μg.m-3 respectively. The results also predicted that the maximum concentrations of NOx; CO; and PM10 due to apron operational activities in 2024 were 260 μg.m-3; 892 μg.m-3; and 2.5 μg.m-3 respectively. The model predicted that in 2024 the air pollution at Sam Ratulangi International Airport will remain under the limit as defined in Indonesian Government Regulation No. 22 of 2021. To mitigate the future increase in air emissions due to the increase in airport capacity, the recommendation were proposed in the several areas, which were including operation management, technology, policies and airport regulations, as well as the provision of green area.

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