Air Pollution Dispersion Research Articles

Nonlinear changes in urban heat island intensity, urban breeze intensity, and urban air pollutant concentration with roof albedo

This study systematically examines how the urban heat island (UHI) and urban breeze circulation (UBC) respond to an increase in roof albedo (αr) and its influence on urban air pollutant dispersion. For this, idealized ensemble simulations are performed using the Weather Research and Forecasting (WRF) model. The increase in αr from 0.20 to 0.65 decreases the UHI intensity, UBC intensity, and urban planetary boundary layer (PBL) height in the daytime (from 1200 to 1700 LST) by 47%, 36%, and 6%, respectively. As both UBC intensity and urban PBL height decrease, the daytime urban near-surface passive tracer concentration increases by 115%. The daytime UHI intensity, UBC intensity, and urban tracer concentration nonlinearly change with αr: For 0.10 ≤ αr < 0.80, the rates of changes in the UHI intensity, UBC intensity, and urban tracer concentration with αr overall increase as αr increases. For αr ≥ 0.80, the daytime roof surface temperature is notably lower than the daytime urban near-surface air temperature, the UHI intensity, UBC intensity, and urban tracer concentration very slightly changing with αr. This study provides insights into the associations between changes in roof surface temperature and roof surface energy fluxes with αr and those in UHI intensity.

Experimental assessments of anthropogenic emissions of nitrogen oxides from the territory of St. Petersburg based on data from long-term mobile measurements

The results of a series of spectroscopic measurements of NO2 content in the troposphere, carried out on a closed route of the ring road (KAD) of St. Petersburg in different seasons of 2012, 2014, 2015 and 2016, are considered. A unified approach to the interpretation of all experimental data using numerical modeling of the dispersion of air pollution and a priori information on the spatial distribution of its anthropogenic sources made it possible to significantly reduce the error in determining the integral NOx emission. The total amount, converted into gross annual anthropogenic emission from the territory of St. Petersburg, constitutes to 81 ± 17 thousand tons of NOx. This value exceeds the official data of the city inventory of air pollution which is 61...63 thousand tons, but is consistent (within the error limits) with the estimate previously obtained on the basis of similar mobile measurements in the spring of 2019 (75 ± 26 thousand tons).

Dynamic patterns of particulate matter concentration and size distribution in urban street canyons: insights into diurnal and short-term seasonal variations.

Time-varying characteristics of particulate matter (PM) pollution play a crucial role in shaping atmospheric dynamics, which impact the health and welfare of urban commuters. Previously published studies on the diurnal patterns of PMs are not consistent, especially in the context of field experiments in central China, and most field studies have only focused on particles with a single particle size. This study conducted regional-scale studies across 72 street canyon sets in Wuhan, China, investigated diurnal and seasonal PM concentration variations while also evaluating various PM size and the key driving factors. During summer (July, August, and September), evergreen tree-lined street canyons maintained a stable linear trend for smaller dp particulates (i.e., PM1, PM2.5, and PM4), while deciduous street canyons exhibited a bimodal distribution. In winter (January and February), fine particulates (i.e., PM1 and PM2.5) remained a linear trend in evergreen street canyons, while deciduous street canyons show a slightly wavy fluctuating pattern. Meanwhile, it exhibited quadrimodal-peak and triple-trough patterns in both PM7, PM10, and TSP concentrations. The lowest PM concentrations were observed between 14:00 and 16:00 for all particle sizes, with decreased summer pollution (7.81% lower in PM2.5, 53.47% lower in PM10, and 50.3% lower in TSP) noted in our seasonal analysis. Among the various meteorological factors, relative humidity (RH) was identified as the dominant influencing PM factor in both summer and winter. Results from this study will help us better understand field-based air pollutant dispersion processes within pedestrian spaces while laying the groundwork for future research into street PM experiments.

Effects of sea-land breeze on air pollutant dispersion in street networks with different distances from coast using WRF-CFD coupling method

A WRF-CFD coupled model with high-temporal resolution is employed to investigate pollutant dispersions during a sea-land breeze (SLB) day in an identical building block configuration at three locations in Shanghai, China, and the blocks are set at the coast (L1), downtown (L2) and inland (L3). The results show that the localized wind speed drops below 1 m/s during the sea-land-breeze collision period (SLBCP), which leads to pollutant accumulation. The closer the block is to the coast, the earlier occurrence and longer duration of SLBCP, and Blocks L1, L2, and L3 experience SLBCPs during the morning peak traffic period (MPTP), low-traffic-volume period (at midday), and evening peak traffic period (EPTP), with durations of 2.5 h, 2 h, and 1 h, respectively. Due to the low wind speeds of both land breezes and sea breezes during the overlap of MPTP and SLBCP, the pollutant concentration in Block L1 is significantly elevated, and the peak concentration is two times higher than that in the non-coastal blocks (L2 and L3). Block L2 shows a peak concentration during the midday low-traffic-volume period, while no evident peak concentration is found in L3 in EPTP. The mean concentrations in Blocks L1, L2, and L3 during EPTP are 72 %, 57 %, and 31 % lower than those during MPTP, respectively. This suggests that SLB has significantly different effects on wind fields and pollutant dispersion in building blocks with different distances from the coast and can provide reference data for transport planning in coastal cities.

Comparing Large-Eddy Simulation and Gaussian Plume Model to Sensor Measurements of an Urban Smoke Plume

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low-cost sensors, a fire broke out from an outbuilding containing roughly 3000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modeling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, and the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 min at an emission rate of 50 g/s of PM2.5. The emission was significantly greater than a ‘normal’ house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast-response numerical models at various compromised levels of accuracy, efficiency and cost.

Resilience to climate change by improving air circulation efficiency and pollutant dispersion in cities: A 3D-UFO approach to urban block design

Urbanization presents significant challenges to air quality and climate resilience, necessitating pioneering urban design solutions to enhance air circulation and mitigate pollutants. This urgency intensifies in densely populated and rapidly evolving regions like Wuhan, China, where effective strategies are crucial for sustainable development. This study introduces an innovative 3D Urban Form Optimization (3D-UFO) methodology aimed at advancing urban block design configurations to improve urbanization quality. The 3D-UFO approach systematically addresses the multifaceted challenges of climate change and air quality degradation in rapidly urbanizing areas. Integrating GIS-based analysis for comprehensive Land-Use and Land-Cover Change (LULCC) evaluation with Computational Fluid Dynamics (CFD), our approach employs systematic exploration guided by established urban airflow study protocols. Robust metrics—Airspeed-Ratio (ASR) and Average-Age-of-Local-Air (ALA)—quantify the impact of diverse urban block design strategies on air-circulation efficiency and pollutant dispersion. Analysis across various urban scenarios, yielded by the proposed 3D-UFO approach, reveal significant variations in air-circulation efficiency at street and building levels (SBLs). Optimal urban air circulation achieves efficiency levels of 50–70 % when airflow aligns orthogonally across and parallel to streets. Adjusting street-level building heights, especially incorporating taller structures, boosts ventilation efficiency by 20–30 %, which is crucial for improving airflow dynamics in urban settings. Higher Height-to-Width (H/W) ratios (>5.5) yield a 218.5 % increase in ventilation in specific urban layouts. Notably, the synergy of street-aspect-ratio and building-height-ratio adjustments significantly enhance ASR and ALA, providing a quantitative foundation for sustainable urban development. This 3D-UFO methodology, fusing LULCC analysis, CFD simulations, and systematic exploration, emerge as a valuable framework for urban planners and designers. The study offers informed insights into urban sustainability challenges, demonstrating advancements in addressing environmental concerns and improving living conditions within densely populated environments.

The Gaussian Plume Model Equation for Atmospheric Dispersion Corrected for Multiple Reflections at Parallel Boundaries: A Mathematical Rewriting of the Model and Some Numerical Testing

The well-known Gaussian plume model has proven to be very useful in simulating the atmospheric dispersion of air pollutants (both gaseous and particulates). Nevertheless, the nature of the model presents problems in the actual computation of concentrations when the plume is confined between two parallel boundaries due to the occurrence of multiple reflections. The ground and temperature inversion lid (especially, when the inversion layer is at low levels in the atmosphere) with a chimney stack releasing the effluent below the latter, is one contextual example of horizontal parallel reflecting boundaries. A second example is buildings confining a roadway on either side, with motor vehicles emitting pollution within the street canyon (or urban notch). In such cases, multiple reflections should be accounted for, otherwise the model underpredicts the resulting concentration. This paper presents a mathematical rewriting of the Gaussian plume model equation corrected for multiple reflections when the pollution source is confined between parallel boundaries. The obtained result is most appropriate when the parallel boundaries are rigid, and near-complete reflection is achieved, e.g., street canyon environment (second quoted example). It is worth noting that the relevant mathematical derivations and definitions are all included in the paper to facilitate reading and to ensure comprehensiveness in the presentation. Additionally, the outcome of some preliminary numerical testing is presented. The latter indicates that the new formulation is mathematically stable and yields interesting results. Further numerical investigation and experimental evaluation are merited.

Dynamic coordinated air supply for moving individuals in industrial settings: Effectiveness evaluation and demonstration

Tracking occupant movement and reducing pollution exposure in industrial settings utilizing intelligent ventilation modes without human intervention is a challenge. This work proposes a dynamic coordinated air supply (DCAS) system incorporating static and dynamic ventilation modules, which is capable of switching air supply modes and adjusting air supply parameters in response to changing occupant positions with the assistance of computer vision technology and Internet of Things (IoT). Air movement and pollutant dispersion in an experimental chamber equipped with a DCAS system during occupant movement are analyzed through computational fluid dynamics with overset mesh method. The feasibility of the dynamic simulation method is verified by a walking experiment in the chamber. Three assessment indicators, namely, inhalation exposure, protection factor, and effective protective ratio, are identified to comprehensively evaluate the pollutant removal effectiveness of DCAS. Results show that the static ventilation module can remarkably reduce the occupant's exposure risk within its protective range. The proposed sliding and rotating modes for the dynamic ventilation module are effective in reducing occupant inhalation exposure during movement if the advance operation strategies are specified to eliminate the negative effects of protection lag. In addition, the feasibility of the IoT architecture-based DCAS system is demonstrated in a schematic laboratory. This work helps drive industrial ventilation development toward smart, healthy purposes.

Pollutant Dispersion Around a Single Tall Building

An experiment was carried out using a scale model of a tall building, with the goal of investigating the role of individual buildings in the dispersion of air pollution. Pollutant dispersion around an isolated building with a height-to-length aspect ratio of 1.4 is investigated using simultaneous particle image velocimetry and planar laser induced fluorescence. Dye is released from a ground-level point source five building heights upstream of the tall building. It was found that in this case the scalar plume was dispersed laterally strongly by the building, but only slightly vertically. It is hypothesized that this is due to 94% of the plume impinging below the stagnation point on the front of the building and being drawn into the horseshoe vortex. We expect this fraction would be lower in a case in which the building is in an array of smaller buildings, and that this would lead to more vertical dispersion.

Estimating Chemical Concentrations of Dust PM2.5 in Iraq: A Climatic Perspective Using Polynomial Model and Remote Sensing Technology

Air pollution and climate change are interrelated issues, with air pollution levels in Iraq currently exceeding World Health Organization standards. This study aimed to evaluate air quality in Iraq by utilizing climatic data, such as temperature, humidity, and gaseous pollutants for assessing the health effects based on processed and estimated data. The research was conducted between August and November 2020, using remotely sensed images and geographical information techniques. Two methods; Geographic Information Systems GIS-based multiple regression and a polynomial model, were employed to estimate PM2.5 levels in the study area. The results showed a significant influence of climatic variables on air pollution in Iraq, with varying effects on PM2.5 estimation. The health impact ranged from good to unhealthy, with most provinces experiencing poor air quality. Southern parts of Iraq exhibited PM2.5 levels surpassing the healthy threshold. The predictive linear and polynomial model's accuracy was assessed through regression, yielding high correlation coefficients (R2 ) of 0.89, 0.95, 0.98, and 0.96 for August to November, respectively. While model validation accuracy ranged between 85–94 %. The study emphasizes the vital role of climate data in understanding the dispersion of air pollutants and their significant impacts on the environment. Addressing air pollution and climate change, as per the SGS-13 "Climate Action", are interconnected and require comprehensive strategies for mitigation.

Environmental conditions affecting air pollution dispersion over Richards Bay, South Africa

Air pollution dispersion over Richards Bay, South Africa is studied using satellite, reanalysis and in-situ measurements. Near-surface concentrations of trace gases and particulates reach high concentrations under dry stable ‘berg’ winds. Temporal records of CO, NO2, O3, PM2.5, SO2 (2000-2023) exhibit no trend and short-term dose exceedances of individual pollutants are rare and confined to winter mornings. Regional point-to-field correlation maps of a Richards Bay winter air pollution index found that anomalous warming of the west Indian Ocean accelerates the jet stream over Madagascar and pulls smoke- and dust-laden north-westerly winds across the South African plateau, implicating long-range transport. At daily and hourly time scales dewpoint temperature and boundary layer height best indicate changes in local air pollution dispersion that impact respiratory health. A case study of 15-17 June 2021 revealed a 10ºC thermal inversion caused by negative sensible heat fluxes of -40 W/m2 through the night, leading to SO2 concentrations above 100 ppb in the morning along the main access road (28.8ºS, 32ºE). Poor dispersion seldom happens in the summer when turbulent mixing and rainfall cleanse the air.

Analysis of Sulfur Dioxide (SO2) Exhaust Gas Emission Distribution Patterns from Airport’s Incinerators in East Java

The airport in this study is one of the airports in East Java that uses an incinerator to process its waste. Emissions generated by the incinerator will disperse in the area surrounding one of the airports in East Java. With the increasing interest of the public in air travel, activity at the airport also increases. This increase also impacts the amount of waste processed by the incinerator and the emissions produced, including Sulfur Dioxide (SO2). The aim of this study is to analyze the dispersion of air pollutants using Aermod View modeling software with SO2 parameters from environmental document data of the airport from January to June and from July to December generated by the incinerator stack. The model produces isopleths representing the dispersion of SO2 emissions. The results of the SO2 model still meet ambient air quality standards, as indicated in Appendix VII of Government Regulation Number 22 of 2021.

Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation

Abstract. A novel atmospheric layer detection approach has been developed based on deep learning techniques for image segmentation. Our proof of concept estimated the layering in the atmosphere, distinguishing between pollution-rich layers closer to the surface and cleaner layers aloft. Knowledge of the spatio-temporal development of atmospheric layers, such as the mixing boundary layer height (MBLH), is important for the dispersion of air pollutants and greenhouse gases, as well as for assessing the performance of numerical weather prediction systems. Existing lidar-based layer detection algorithms typically do not use the full resolution of the available data, require manual feature engineering, often do not enforce temporal consistency of the layers, and lack the ability to be applied in near-real time. To address these limitations, our Deep-Pathfinder algorithm represents the MBLH profile as a mask and directly predicts it from an image with backscatter lidar observations. Deep-Pathfinder was applied to range-corrected signal data from Lufft CHM15k ceilometers at five locations of the operational ceilometer network in the Netherlands. Input samples of 224 × 224 px were extracted, each covering a 45 min observation period. A customised U-Net architecture was developed with a nighttime indicator and MobileNetV2 encoder for fast inference times. The model was pre-trained on 19.4×106 samples of unlabelled data and fine-tuned using 50 d of high-resolution annotations. Qualitative and quantitative results showed competitive performance compared to two reference methods: the Lufft and STRATfinder algorithms, applied to the same dataset. Deep-Pathfinder enhances temporal consistency and provides near-real-time estimates at full spatial and temporal resolution. These properties make our approach valuable for application in operational networks, as near-real-time and high-resolution MBLH detection better meets the requirements of users, such as in aviation, weather forecasting, and air quality monitoring.

European air quality in view of the WHO 2021 guideline levels: Effect of emission reductions on air pollution exposure

Although anthropogenic emissions have decreased during the last 2 decades, air pollution is still problematic in Europe. This study analyzes the air quality in Europe using simulations by EURopean Air pollution Dispersion—Inverse Model for the year 2016 with updated emissions in view of the annual guideline levels for particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) released in 2021 by the World Health Organization (WHO). Three different emission scenarios are applied, including a scenario for the committed emission reductions from the European Union (EU), a scenario including additional reductions to specifically mitigate PM2.5, and a scenario in which all anthropogenic emissions are eliminated. Model results show that in Europe, the concentrations of PM2.5 and NO2 exceed the annual WHO guideline levels by up to a factor of 5.6 and 5.2, respectively, in the main polluted regions and by up to a factor of 2 for O3 in Southern Europe. High concentrations of PM2.5 and O3 are homogeneously distributed across Europe with 99% and 100% of the European population exposed to concentrations above the WHO guideline levels, respectively. NO2 concentrations above the annual WHO guideline level are primarily found in populated areas, affecting 323 million inhabitants in 2016. Although the emission scenario designed to mitigate PM2.5 shows a decrease of the highest annual mean concentrations of PM2.5 from 28 µgm−3 to 12 µgm−3, 527 million European inhabitants remain affected by PM2.5 annual mean concentrations above the WHO guideline level. Seasonal mean O3 concentrations after eliminating all anthropogenic emissions (between 60 and 82 µgm−3) are found to be above the WHO guideline level for the entire European continent. The mortality attributable to air pollution is reduced by 47% in the emission scenario for committed emissions by the EU. In the more aggressive scenario designed to mitigate PM2.5, the mortality is reduced by 72%. The study reveals that the emission scenarios and, therefore, the reduction in premature deaths are subject to sectoral emission reductions between 41% and 79%.

Effect of urban street canyon aspect ratio on fire-induced air pollutants dispersion under cross wind

The incidence of vehicle fires in urban street canyons has continuously increased with the process of urban modernization. The dispersion and accumulation of fire-induced air pollutants seriously affect residents’ safety. The effects of the street canyon aspect ratio and fire source location on fire-induced air pollutants dispersion under cross wind were numerically investigated in the paper. The results show that the street canyon aspect ratio can affect flow patterns and vortex structure and then lead to different accumulation states of air pollutants. Smoke development can be divided into four different regimes according to cross wind velocity. The re-entrainment phenomenon occurs when the fire source is close to the windward building or in the center of the street, but it does not occur when the fire source is close to the leeward building. Smoke tends to accumulate in street canyons when the aspect ratio is smaller and the fire source is closer to the leeward building. The variation of critical velocity with the aspect ratio can be divided into three regions, i.e., initial linear growth region (0.5 ≤ W/H < 1), constant region (1 ≤ W/H ≤ 1.5), and second linear growth region (1.5 < W/H ≤ 2). The dimensionless critical velocity and critical Froude number are used to quantify the re-entrainment phenomenon in different fire scenarios, and prediction models are finally proposed. The main findings can provide a more detailed reference for urban layout and air pollution control to reduce fire-induced air pollutants.

Influence of building spatial patterns on wind environment and air pollution dispersion inside an industrial park based on CFD simulation.

The "spatial pattern-wind environment-air pollution" within building clusters is closely interconnected, where different spatial pattern parameters may have varying degrees of impact on the wind environment and pollutant dispersion. Due to the complex spatial structure within industrial parks, this complexity may lead to the accumulation and retention of air pollutants within the parks. Therefore, to alleviate the air pollution situation in industrial parks in China and achieve the circular transformation and construction of parks, this study takes Hefei Circular Economy Demonstration Park as the research object. The microscale Fluent model in computational fluid dynamics (CFD) is used to finely simulate the wind flow field and the diffusion process of pollutants within the park. The study analyzes the triad relationship and influence mechanism of "spatial pattern-wind environment-air pollution" within the park and studies the influence of different spatial pattern parameters on the migration and diffusion of pollutants. The results show a significant negative correlation between the content of pollutants and wind speed inside the industrial park. The better the wind conditions, the higher the air quality. The spatial morphology parameters of the building complex are the main influences on the condition of its internal wind environment. Building coverage ratio and degree of enclosure have a significant negative correlation with wind conditions. Maintaining them near 0.23 and 0.37, respectively, is favorable to the quality of the surrounding environment. Moreover, the average height of the building is positively correlated with the wind environment condition. The rate of transport and dissipation of pollutants gradually increases as the average building height reaches 16 m. Therefore, a reasonable building planning strategy and arrangement layout can effectively improve the wind environment condition inside the park, thus alleviating the pollutant retention situation. The obtained results serve as a theoretical foundation for optimizing morphological structure design within urban industrial parks.

SO2 emission rates and incorporation into the air pollution dispersion forecast during the 2021 eruption of Fagradalsfjall, Iceland

During the low-effusion rate Fagradalsfjall eruption (19 March – 18 September 2021), the emission of sulfur dioxide (SO2) was frequently measured using ground-based UV spectrometers. The total SO2 emitted during the entire eruption was 970 ± 540 kt, which is only about 6% of the SO2 emitted during the similar length Holuhraun eruption (2014–2015). The eruption was divided into five phases based on visual observations, including the number of active vents and the occurrence of lava fountaining. The SO2 emission rate ranged from 44 ± 19 kg/s in Phase 2 to 85 ± 29 kg/s in Phase 5, with an average of 64 ± 34 kg/s for the entire eruption. There was notable variability in SO2 on short timescales, with measurements on 11 August 2021 ranging from 17 to 78 kg/s.SO2 flux measurements were made using scanning DOAS instruments located at different distances from and orientations relative to the eruption site augmented by traverses. Four hundred and forty-four scan and traverse measurements met quality criteria and were used, along with plume height and meteorological data, to calculate SO2 fluxes while accounting for wind-related uncertainties.A tendency for stronger SO2 flux concurrent with higher amplitude seismic tremor and the occurrence of lava fountaining was observed during Phases 4 and 5 which were characterized by intermittent crater activity including observable effusion of lava and gas release interspersed with long repose times. This tendency was used to refine the calculation of the amount of SO2 emitted during variably vigorous activity. The continuous seismic tremor time series was used to quantify how long during these eruption phases strong/weak activity was exhibited to improve the calculated SO2 flux during these Phases.The total SO2 emissions derived from field measurements align closely with results obtained by combining melt inclusion and groundmass glass analyses with lava effusion rate measurements (910 ± 230 kt SO2). Specifically, utilizing the maximum S content found in evolved melt inclusions and the least remaining S content in accompanying quenched groundmasses provides an identical result between field measurements and the petrological calculations. This suggests that the maximum SO2 release calculated from petrological estimates should be preferentially used to initialize gas dispersion models for basaltic eruptions when other measurements are lacking.During the eruption, the CALPUFF dispersion model was used to forecast ground-level exposure to SO2. The SO2 emission rates measured by DOAS were used as input for the dispersion model, with updates made when a significant change was measured. A detailed analysis of one mid-distance station over the entire eruption shows that the model performed very well at predicting the presence of volcanic SO2 when it was measured. However, it frequently predicted the presence of SO2 that was not measured and the concentrations forecasted had no correlation with the concentrations measured. Various approaches to improve the model forecast were tested, including updating plume height and SO2 flux source terms based on measurements. These approaches did not unambiguously improve the model performance but suggest that improvements might be achieved in more-polluted conditions.

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

Soil erosion is a severe problem in Taiwan due to the steep terrain, fragile geology, and extreme climatic events resulting from global warming. Due to the rapidly changing hydrological conditions affecting the locations and the amount of transported sand and fine particles, timely impact evaluation and riverine dust control are difficult, particularly when resources are limited. To comprehend the impact of desertification in estuarine areas on the variation of air pollutant concentrations, this study utilized remote sensing technology coupled with an air pollutant dispersion model to determine the unit contribution of potential pollution sources and quantify the effect of riverine dust on air quality. The images of the downstream area of the Beinan River basin captured by Formosat-2 in May 2006 were used to analyze land use and land cover (LULC) composition. Subsequently, the diffusion model ISCST-3 based on Gaussian distribution was utilized to simulate the transport of PM across the study area. Finally, a mixed-integer programming model was developed to optimize resource allocation for dust control. Results reveal that sand deposition in specific river sections significantly influences regional air quality, owing to the unique local topography and wind field conditions. The present optimal plan model for regional air quality control further showed that after implementing engineering measures including water cover, revegetation, armouring cover, and revegetation, total PM concentrations would be reduced by 51%. The contribution equivalent calculation, using the air pollution diffusion model, was effectively integrated into the optimization model to formulate a plan for reducing riverine dust with limited resources based on air quality requirements.

High-Resolution Simulation of the Near-Field Pollutant Dispersion in a Nuclear Power Plant Community with High-Performance Computing

This study aims to employ numerical simulations to understand the dynamics of wind fields and air pollutant dispersion in the proximity of a nuclear plant, situated within a specified urban environment. By leveraging computational fluid dynamics (CFD) combined with geographical information system (GIS) data, the research comprehensively models atmospheric interactions in terms of wind flow patterns, building-induced pressure variances, and pollutant trajectories. The computational domain extends over an area of 8.8km×8.4km\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$8.8\\,\ extrm{km} \ imes 8.4\\,\ extrm{km}$$\\end{document}, vertically stretching to 0.5 km. The wind and pollutant distribution equations are discretized using the finite volume method, providing detailed insights into fluid interactions with urban topographies. Key findings highlight the profound influences of terrain, urban structures, and wind flow behavior on the dispersion of radioactive aerosols, shedding light on potential risks and safety protocols for nuclear plant environments.

GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system

Abstract. A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelized Large-Eddy Simulation (PALM) model system. PALM is a community-driven large-eddy simulation model for atmospheric and environmental research. Throughout PALM's 20-year development, research interests have been increasing in its application to realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, geospatial data availability and quality are highly variable and inconsistent. Currently, the geospatial static input generation tools in the PALM community heavily rely on users for data acquisition and pre-processing. New PALM users face large obstacles, including significant time commitments, to gain the knowledge needed to be able to pre-process geospatial data for PALM. Expertise beyond atmospheric and environmental research is frequently needed to understand the data sets required by PALM. Here, we present GEO4PALM, which is a free and open-source tool. GEO4PALM helps users generate PALM static input files with a simple, homogenised, and standardised process. GEO4PALM is compatible with geospatial data obtained from any source, provided that the data sets comply with standard geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available, with several data sets having the finest resolution of 1 m. In addition, GEO4PALM provides a graphical user interface (GUI) for PALM domain configuration and visualisation. Two application examples demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany, and Ōtautahi / Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting. The wide applicability of GEO4PALM makes PALM more accessible to a wider user base in the scientific community.