Impact Of Dust Research Articles

Comprehensive analysis of dust impact on photovoltaic module temperature: Experimental insights and mathematical modeling

Dust accumulation substantially impacts the efficiency and thermal behavior of photovoltaic (PV) modules. Addressing a current knowledge gap, this article presents a comprehensive assessment of the impact of dust on PV module temperature. This endeavor includes a combination of systematic experiments with a novel developed mathematical model that uniquely incorporates key dust parameters such as emissivity, absorbance, and transmittance. The model enhances accuracy in estimating PV module temperature compared to existing mathematical models, which often overlook heat absorption due to dust and specific dust characteristics. These parameters are measured using specialized devices to ensure realistic values. Outdoor experiments are conducted to validate the model's predictions under real weather conditions, further highlighting the importance of accurate PV temperature estimation in dusty environments. Additionally, a comparative analysis is performed with existing mathematical models for PV temperature prediction, demonstrating the superior performance of the proposed model, which achieves the lowest average prediction error (mean absolute error of 1.4). These findings provide valuable insights into the estimation of PV temperature in dusty conditions, bridging the gap between theoretical modeling and practical application and underscoring the novelty and innovation introduced in this research.

Production of pro-inflammatory mediators stimulated by exposure of poultry house workers to airborne dust particulates.

Poultry house employees spend a significant part of their work shift being exposed to airborne particulate pollutants. The aim of this study was to assess their exposure at different stages of chicken production cycle, based on quantification of pro-inflammatory mediators (IL-1β, IL-6, IL-8, and TNFα) in nasal lavage (NAL) samples. The concentrations of airborne dust at 3 different stages of the production cycle (i.e. empty poultry house, with 7- and 42-day-old chickens) were stationary measured using Grimm spectrometer, as well as CIS and Button samplers. The dust collected by the latter 2 samplers was analyzed for endotoxin and (1→3)-β-D-glucan content. NAL samples were collected from employees after their work shift to determine the pro-inflammatory mediator levels. The maximum particulate aerosol, endotoxin, and (1→3)-β-D-glucan concentrations at workplaces reached the levels of 4.12mg/m3, 45.21 ng/m3, and 56.54 ng/m3, respectively. The IL-1β, IL-6, and IL-8 concentrations in NAL samples ranged between 0.62-18.12 pg/mL, <0.70-25.37 pg/mL, and <3.50-259.5 pg/mL, respectively. All TNFα levels were below 4pg/mL. There were no significant differences between these cytokine concentrations in NAL samples collected at different stages of chicken breeding in either 'winter' or 'summer' seasons. Inhalation stimulation with poultry dust containing endotoxins and (1→3)-β-D-glucans resulted in the production of pro-inflammatory mediators, which proves the course of immunological processes in the exposed employees that may lead to adverse effects. The use of nasal lavage fluid in the control of such exposure confirms that NAL analysis is a reliable laboratory tool for assessing the impact of poultry dust on exposed farm workers.

Long-term study of desert dust deposition effects on phytoplankton biomass in the Persian Gulf using Google Earth Engine

Persian Gulf is surrounded by the most active dust source regions of the world. Every year, millions of tons of dust are deposited in this area causing significant adverse effects. This research aimed to fill the gap in the field of dust impact quantification regarding different and important regions in the Persian Gulf. We evaluated aerosol optical thickness (AOT) as dust, chlorophyll a (Chl a) as phytoplankton biomass, sea surface temperature (SST), and particulate organic carbon (POC) using Moderate Resolution Imaging Spectroradiometer (MODIS) data to quantify and analyze the impacts of dust. According to dust frequency maps over 21 years, 4 critical regions were selected including the Northern, Central, and Southern regions of the Persian Gulf and Strait of Hormuz. Slightly lower Chl a values were noted in the southern region and Strait of Hormuz compared to the Northern and Central regions. The Mann-Kendall (MK) test and Sen's slope estimator, which can determine trend parameters, were used to analyze 4 selected regions using 8 days, monthly, and yearly averaged data. The results of the MK test showed a significant positive trend for SST and a significant negative trend for POC. AOT and Chl a trends varied based on their locations. The cross-correlation test with a time lag showed maximum correlations between Chl a and dust (AOT) with a delay of 6–7 months. Also, to quantify the impacts of dust on phytoplankton biomass, R2 and analysis of variance (ANOVA) regression were used for data with a 6–7-month time lag. The results showed that the contribution of dust in the amount of Chl a variation was about 10 %–20 %. This study showed that the simultaneous use of remote sensing and statistical methods could provide necessary and timely warnings (regarding management) to prevent algal blooms and aquatic loss in this important and strategic area.

Hazardous Impact of Coal Dust on Hematological Parameters of Underground Coal Mine Workers

Due to the nature of their work, coal miners have historically faced significant exposure to large amounts of dust, placing them at a heightened risk. The present study was conducted to explore the hazardous effects of inhalation of coal dust on the haematological parameters of underground coal miners. 120 underground coal miners (60 workers having 5-10 years of experience and the other 60 having 10-20 years of experience) and 62 matched non-exposed to coal dust subjects as control from the locality were recruited for the study. After obtaining consent, different physiological parameters were measured, and blood was collected for assessment of haematological parameters. Observations revealed that there were lower mean values of total RBC count, haemoglobin level, MCV, PCV, MCHC and MCH in coal mine workers whereas mean values of Red Cell Distribution Width (RDW) and ESR were increased in the workers group. Further, coal dust exposure causes increased total leucocyte to count as well as a differential count of lymphocyte, neutrophil, monocyte, and eosinophil in the workers group but, a decreased differential count of basophils was detected among coal dust-exposed workers. All the changes in haematological parameters were found to occur experience-dependent and maximum changes were observed in workers having 10-20 years of working experience. There is a significant likelihood of coal mine workers experiencing changes in their blood composition, which suggests the harmful impact of coal dust on this group. Further, haematological parameters will help health professionals to screen any pathologic conditions and may help to prevent coal dust exposure-associated haematological disorders and complications thereof.

Identification of aeolian dust hotspots in the lower reaches of Zhuoshui river in Taiwan using environmental indicators

This study introduces a risk model that utilizes the ventilation index (VI), Temperature Vegetation Dryness Index (TVDI), and coefficient of variation (CV) of soil moisture content to identify dust supply hotspots in the exposed riverbed of Taiwan's Zhuoshui River during the dry season. The research demonstrates a positive correlation between PM10 concentration and high-risk locations, achieving an 80% interpretation rate. The average bare riverbed area is approximately 3,500 ha, with the M2 area being a significant contributor to PM10 (covering around 1,186 ha). The dust source hotspot (high CV in soil moisture) spans about 141 ha, accounting for approximately 34% and 4.02% of the bare land, respectively. To effectively mitigate the impact of river dust on nearby residents' health and the environment, employing unmanned aerial vehicles (UAVs) for precise prevention and management is recommended. This study successfully integrates theory and practice, introducing a conceptual model that combines risk analysis with environmental indicators to identify potential river dust emission areas. The model's adaptability allows for its application and expansion to other regions and internationally, making significant contributions to dust risk management strategies.

Impact of hot exozodiacal dust on the polarimetric analysis of close-in exoplanets

Context. Hot exozodiacal dust (HEZD) found around main-sequence stars through interferometric observations in the photometric bands H to L is located close to the dust sublimation radius, potentially at orbital radii comparable to those of close-in exoplanets. Consequently, HEZD has a potential influence on the analysis of the scattered-light polarization of close-in exoplanets and vice versa. Aims. We analyze the impact of HEZD on the polarimetric characterization of close-in exoplanets. This study is motivated in particular by the recently proven feasibility of exoplanet polarimetry. Methods. Applying the 3D Monte Carlo radiative transfer code POLARIS in an extended and optimized version for radiative transfer in exoplanetary atmospheres and an analytical tool for modeling the HEZD, we simulated and compared the polarization characteristics of the wavelength-dependent scattered-light polarization of HEZD and close-in exoplanets. As a starting point for our analysis, we defined a reference model consisting of a close-in exoplanet with a scattered-light polarization consistent with the upper limit determined for WASP-18b, and a HEZD consistent with the near-infrared excess detected for HD 22484 (10 Tau). Results. The varied parameters are the planetary phase angle (0°–180°), the dust grain radius (0.02 µm−10 µm), the HEZD mass (10−10 M⊙−10−8 M⊙), the orbital inclination (0°−90°), the composition of the planetary atmosphere (Mie and Rayleigh scattering atmosphere), the orbital radius of HEZD (0.02 au−0.4 au), and the planetary orbital radius (0.01 au−0.05 au). The dust grain radius has the strongest influence on the polarimetric analysis due to its significant impact on the wavelength-dependent polarization characteristics and the total order of magnitude of the scattered-light polarization. In certain scenarios, the scattered-light polarization of the HEZD even exceeds that of the close-in exoplanet, for example for a dust grain radius of 0.1 µm, a HEZD mass of 8 × 10−10 M⊙, an orbital radius of HEZD of 0.04 au and an orbital inclination of 90°. Conclusions. The presence of HEZD potentially has a significant impact on the polarimetric investigations of close-in exoplanets. Furthermore, interferometric observations are required to better constrain the parameter space for HEZD and thus the possible resulting scattered-light polarization.

Modeling of cotton dust effects using indigenously designed experimental setup for solar powered textile industry in Pakistan

ABSTRACT The performance improvement of solar photovoltaic (PV) systems is envisaged to be one of the prime concerns for today’s energy sector to ensure optimal power yield. This paper investigates the impact of cotton dust on the solar-powered PV plant in the textile industry. In the first stage, using HM3301, the hourly data of cotton dust (6759 µg/m3) has been collected from an installed 250 kW system of a textile industry located in the hot-humid area of Pakistan. In the second stage, to model the same collected data, an indigenous experimental chamber has been constructed. The chamber has been designed to facilitate the fixed and moveable PV module. In the former type, the panel orientation was fixed at 30°, while the later configuration incorporates the moveable module that rotates with respect to the sun rotation. The experiment has been conducted for 96 hours spread over 12 days for each configuration, which collects the hourly data of humidity, temperature, voltage, current, and dust through five different dedicated sensors. The observed results show that the power output from the fixed PV configuration is 5.32% lesser than the movable configuration. PV panel power output efficiency of fixed configuration decreases from 0.134% to 0.102%. Similarly, the power output efficiency of movable PV module decreases from 0.147% to 0.115%.This illustrates cotton dust reduces the power output greater in fixed configuration as compared to movable configuration. Furthermore, linear regression analysis has been used on acquired data of power output and cotton dust accumulation that shows both quantities are highly correlated up to 97.6% and 95.1%, respectively. Also, by using the regression equation maximum quantity of cotton dust has been computed, which shows 0.116 grams for fixed and 0.129 grams for moveable configuration that will minimize the power output of the PV module. Through this study, textile units can devise periodic cleaning and assessment patterns that will help to maintain the power output and increase the life of the PV power plant.

Compliant mechanisms for dust mitigation in Lunar hardware development: technology and material considerations

During the Apollo missions, astronauts observed negative impact of Lunar dust on the surface hardware. The characteristics of Lunar environment and the regolith properties accelerate the contamination and promote the abrasion and clogging of different components in the equipment. To protect the hardware from damages in the future Lunar missions, several mitigation technologies must be adapted. In this work, we propose to consider application of solutions that are naturally dust resilient. Such solutions, called implicit dust mitigation technologies, include usage of compliant mechanisms. Compliant mechanisms use elastic deformation to achieve motion and can replace rigid-body mechanisms that suffer increased friction and jamming due to dust accumulation in the inter-element gaps. Material selection for compliant mechanisms needs to be considered very early in the design process, and as demonstrated in our work, it is crucial to the final mechanism performance.

Investigation of the effects of the Greek extreme wildfires of August 2021 on air quality and spectral solar irradiance

Abstract. In August 2021, a historic heatwave was recorded in Greece which resulted in extreme wildfire events that strongly affected the air quality over the city of Athens. Saharan dust was also transferred over Greece on certain days of the same period due to the prevailing southern winds. The impact of these events on air quality and surface solar radiation is investigated in this study. Event characterization based on active and passive remote sensing instrumentation has been performed. The study shows that significantly increased levels of air pollution were recorded from the end of July to the first week of August. The smoke led to unusually high aerosol optical depth (AOD) values (up to 3.6 at 500 nm), high Ångström exponent (AE) (up to 2.4 at 440–870 nm), and a strong and negative dependence of single-scattering albedo (SSA) on wavelength that was observed to decrease from 0.93 at 440 nm to 0.86 at 1020 nm, while the dust event led to high AOD (up to 0.7 at 500 nm), low AE (up to 0.9 at 440–870 nm), and a positive dependence of SSA on wavelength that was observed to increase from 0.89 at 440 nm to 0.95 at 1020. Furthermore, the smoke plume was also detected over the PANhellenic GEophysical observatory of Antikythera on 7 August, which is about 240 km away from Athens. Increased AOD values (up to ∼ 0.90 at 500 nm) associated with a high fine-mode AOD (up to ∼ 0.85 at 500 nm) and decrease in SSA with wavelength suggested the dominance of fine biomass burning aerosols. The impact of dust and smoke on solar irradiance revealed significant differences in the spectral dependence of the attenuation caused by the two different aerosol types. The attenuation of solar irradiance in the ultraviolet (UV-B) spectrum was found to be much lower in the case of dust compared to smoke for similar AOD500 values. Differences were less pronounced in the near-infrared and visible spectral regions. The large AODs during the wildfires resulted in a decrease in the noon UV index by up to 53 %, as well as in the daily effective doses for the production of vitamin D (up to 50 %), in the daily photosynthetically active radiation (up to 21 %) and in the daily global horizontal irradiance (up to 17 %), with serious implications for health, agriculture, and energy. This study highlights the wider impacts of wildfires that are part of the wider problem for Mediterranean countries, whose frequency is predicted to increase in view of the projected increasing occurrence of summer heatwaves.

Predictions of the 21 cm global signal in the JWST and ALMA era

ABSTRACT We calculate the redshift evolution of the global 21 cm signal in the first billion years using an advanced semi-analytical galaxy formation model delphi. Employing only two redshift- and mass-independent free parameters, our model predicts galaxy populations in accord with data from both the JWST and the Atacama Large Millimetre Array (ALMA) at z ∼ 5–12. In addition to this ‘fiducial’ model, which fully incorporates the impact of dust attenuation, we also explore an unphysical ‘maximal’ model wherein galaxies can convert a 100 per cent of their gas into stars instantaneously (and supernova feedback is ignored) required to explain JWST data at z &amp;gt; =13. We also explore a wide range of values for our 21 cm parameters that include the impact of X-ray heating (fX,h = 0.02–2.0) and the escape fraction of Lyman Alpha photons (fα = 0.01–1.0). Our key findings are (i) the fiducial model predicts a global 21 cm signal, which reaches a minimum brightness temperature of Tb, min ∼ −215 mK at a redshift zmin ∼ 14; (ii) since the impact of dust on galaxy properties only becomes relevant at z &amp;lt; = 8, dust does not have a sensible impact on the global 21 cm signal; (iii) the ‘maximal’ model predicts Tb, min = −210 mK as early as zmin ∼ 18; and (iv) galaxy formation and 21 cm parameters have a degenerate impact on the global 21 cm signal. A combination of the minimum temperature and its redshift will therefore be crucial in constraining galaxy formation parameters and their coupling to the 21 cm signal at these early epochs.

The problem of dust attenuation in photometric decomposition of edge-on galaxies and possible solutions

ABSTRACT The presence of dust in spiral galaxies affects the ability of photometric decompositions to retrieve the parameters of their main structural components. For galaxies in an edge-on orientation, the optical depth integrated over the line of sight is significantly higher than for those with intermediate or face-on inclinations, so it is only natural to expect that for edge-on galaxies, dust attenuation should severely influence measured structural parameters. In this paper, we use radiative transfer simulations to generate a set of synthetic images of edge-on galaxies that are then analysed via decomposition. Our results demonstrate that for edge-on galaxies, the observed systematic errors of the fit parameters are significantly higher than for moderately inclined galaxies. Even for models with a relatively low dust content, all structural parameters suffer offsets that are far from negligible. In our search for ways to reduce the impact of dust on retrieved structural parameters, we test several approaches, including various masking methods and an analytical model that incorporates dust absorption. We show that using such techniques greatly improves the reliability of decompositions for edge-on galaxies.

A Comprehensive Review of Stone Dust in Concrete: Mechanical Behavior, Durability, and Environmental Performance

The escalating demand for natural resources within the construction industry is progressing upward. At the same time, however, there is a great concern regarding the depletion of these resources. This review paper emphasizes the significance of utilizing alternative aggregate materials in concrete. Particularly, it aims to explore replacing natural sand with stone dust. On the one hand, the depletion of primary sources of natural sand worldwide, combined with environmental and ecological concerns, drives the adoption of alternative aggregate materials for sustainable concrete construction. On the other hand, stone dust, a waste from the quarrying industry, offers a cost-effective and practical solution for producing concrete. This article presents a comprehensive literature review of the main trends in utilizing stone dust in recycled aggregates in the past decade and its influence on concrete properties. It addresses critical research questions regarding the physical and chemical properties of stone dust aggregates compared to natural sand; the impact of stone dust on the workability, mechanical, physical, and durability properties of recycled concrete; and the potential reduction of environmental impacts in terms of energy consumption and emissions through the replacement of natural sand with stone dust. Ultimately, this paper proposes future investigative work based on identified research gaps.

Dust detection and susceptibility mapping by aiding satellite imagery time series and integration of ensemble machine learning with evolutionary algorithms

To mitigate the impact of dust on human health and the environment, it is crucial to create a model and map that identifies the areas susceptible to dust. The present study focused on identifying dust occurrences in the Bushehr province of Iran between 2002 and 2022 using moderate-resolution imaging spectroradiometer (MODIS) imagery. Subsequently, an ensemble machine learning model was improved to prepare a dust susceptibility map (DSM). The study employed differential evolution (DE), genetic algorithm (GA), and flower pollination algorithm (FPA) - three evolutionary algorithms - to enhance the random forest (RF) ensemble model. A spatial database was created for modeling, including 519 dust occurrence points (extracted from MODIS imagery) and 15 factors affecting dust (Slope, bulk density, aspect, clay, altitude, sand, rainfall, lithology, soil order, distance to river, soil texture, normalized difference vegetation index (NDVI), soil water content, land cover, and wind speed). By utilizing the differential evolution (DE) algorithm, we determined the significance of these factors in impacting dust occurrences. The results indicated that altitude, wind speed, and land cover were the most influential factors, while the distance to the river, bulk density, and soil texture had less impact on dust occurrence. Data were preprocessed using multicollinearity analysis and the frequency ratio (FR) approach. For this research, three RF-based meta-heuristic optimization algorithms, namely RF-FPA, RF-GA, and RF-DE, were created for DSM. The effectiveness prediction of the constructed models by indexes of root-mean-square-error (RMSE), the area under the receiver operating characteristic (AUC-ROC), and coefficient of determination (R2) from best to worst were RF-DE (RMSE = 0.131, AUC-ROC = 0.988, and R2 = 0.93), RF-GA (RMSE = 0.141, AUC-ROC = 0.986, and R2 = 0.919), RF-FPA (RMSE = 0.157, AUC-ROC = 0.981, and R2 = 0.9), and RF (RMSE = 0.173, AUC-ROC = 0.964, and R2 = 0.878). The results showed that combining evolutionary algorithms with an RF model improves the accuracy of dust susceptibility modeling.

A new method for DEM simulation of dust-bearing granular flow – Modeling the effect of dust on the change in granule friction coefficient

The simulation of dust-bearing granular accumulation flow in the theoretical and practical aspects of the engineering field poses a significant challenge due to the massive computational requirements associated with cross-scale simulations. In this study, a novel approach is proposed to address this issue by developing a model that accounts for the impact of dust on granular flow through changes in the granule friction coefficient. Initially, the theoretical analysis was conducted to examine the effects of dust on granular flow. Subsequently, a method was developed to measure the equivalent friction coefficient of granules by combining theoretical analysis and experimental work. The proposed method was then employed to simulate the stability of a spherical granule pile in a drum influenced by dust content and compared against experimental results. The simulation results demonstrate agreement with the experimental results, indicating the feasibility of modeling the effect of dust on dust-bearing granular flow through the granule equivalent friction coefficient. The dust effect can be considered equivalent to a change in the granule friction coefficient, which facilitates the reduction of the computational load generated by the Discrete Element Method (DEM) method and enables cross-scale simulations.

Pozzolanic properties of marble industrial waste and its used in concrete

Concrete needs to use alternative materials to reduce cement content to limit the effect of carbon emissions. Marble dust as a waste of the marble industry has very fine grains. X-Ray Fluorescence (X-RF) method was conducted to determine the mineral properties of marble dust. Marble dust was found to contain 98.62% Calcium Oxide (CaO), 0.17% Sulfur Trioxide (SO3) and some elements in small levels. To determine the impact of marble dust on the mechanical characteristics of concrete, an experimental study was conducted. Test specimens were made with four different levels of marble dust, namely 0%, 5%, 10%, and 15%. The experimental results showed that the optimum usage was 6.62% by weight of cement which gave the advantage of increasing the compressive strength of concrete by 11.77%.

Regional Impact of Snow‐Darkening on Snow Pack and the Atmosphere During a Severe Saharan Dust Deposition Event in Eurasia

AbstractLight‐absorbing impurities such as mineral dust can play a major role in reducing the albedo of snow surfaces. Particularly in spring, deposited dust particles lead to increased snow melt and trigger further feedbacks at the land surface and in the atmosphere. Quantifying the extent of dust‐induced variations is difficult due to high variability in the spatial distribution of mineral dust and snow. We present an extension of a fully coupled atmospheric and land surface model system to address the impact of mineral dust on the snow albedo across Eurasia. We evaluated the short‐term effects of Saharan dust in a case study. To obtain robust results, we performed an ensemble simulation followed by statistical analysis. Mountainous regions showed a strong impact of dust deposition on snow depth. We found a mean significant reduction of −1.4 cm in the Caucasus Mountains after 1 week. However, areas with flat terrain near the snow line also showed strong effects despite lower dust concentrations. Here, the feedback to dust deposition was more pronounced as increase in surface temperature and air temperature. In the region surrounding the snow line, we found an average significant surface warming of 0.9 K after 1 week. This study shows that the impact of mineral dust deposition depends on several factors. Primarily, these are altitude, slope, snow depth, and snow cover fraction. Especially in complex terrain, it is therefore necessary to use fully coupled models to investigate the effects of mineral dust on snow pack and the atmosphere.

Impact of Dust and Shade on Solar Panel Efficiency and Development of a Simple Method for Measuring the Impact of Dust in any Location

Impact of Dust and Shade on Solar Panel Efficiency and Development of a Simple Method for Measuring the Impact of Dust in any Location

The shrinking Great Salt Lake contributes to record high dust-on-snow deposition in the Wasatch Mountains during the 2022 snowmelt season

Seasonal snowmelt from the Wasatch Mountains of northern Utah, USA, is a primary control on water availability for the metropolitan Wasatch Front, surrounding agricultural valleys, and the Great Salt Lake (GSL). Prolonged drought, increased evaporation due to warming temperatures, and sustained agricultural and domestic water consumption have caused GSL water levels to reach record low stands in 2021 and 2022, resulting in increased exposure of dry lakebed sediment. When dust emitted from the GSL dry lakebed is deposited on the adjacent Wasatch snowpack, the snow is darkened, and snowmelt is accelerated. Regular observations of dust-on-snow (DOS) began in the Wasatch Mountains in 2009, and the 2022 season was notable for both having the most dust deposition events and the highest snowpack dust concentrations. To understand if record high DOS concentrations were linked to record low GSL levels, dust source regions for each dust event were identified through a backward trajectory model analysis combined with aerosol measurements and field observations. Backward trajectories indicated that the exposed lakebed of the GSL contributed 23% of total dust deposition and had the highest dust emissions per surface area. The other potential primary contributors were the GSL Desert (45%) and the Sevier +Tule dry lakebeds (17%), both with lower per-area emissions. The impact on snowmelt, quantified by mass and energy balance modeling in the presence and absence of snow darkening by dust, was over 2 weeks (17 d) earlier. The impact of dust on snowmelt could have been more dramatic if the spring had been drier, but frequent snowfall buried dust layers, delaying dust-accelerated snowmelt later into the melt season.

Assessment of PM2.5 particulate air pollution near highways

Introduction. The purpose of this study is to investigate air pollution with respect to PM2.5 particulate matter hazardous to the health of the urban population, generated by the movement of motor vehicles. The development of existing and construction of new transport networks in large cities leads to the fact that the problem of air pollution by PM2.5 particles becomes extremely urgent.&#x0D; &#x0D; Materials and methods. The ENVI-met calculations were based on the data provided by the meteorological station. The following methods were applied: system analysis, numerical modelling method — finite difference method, processing of numerical results.&#x0D; &#x0D; Results. A calculation model of Moscow district territory was developed in ENVI-met programme in order to determine PM2.5 dispersion patterns along the road network of the selected district. The calculation was carried out for a 24-hour time period. The schemes of fine particles dispersion on the territory of the building at a height of 1.5 and 10 m are obtained. Their evaluation shows that the highest concentration of PM2.5 is observed along the most frequent wind direction near roads. The width of the roadway and, accordingly, the number of cars passing per hour plays a paramount role in the formation of PM2.5.&#x0D; &#x0D; Conclusions. The greatest negative impact of fine dust occurs in residential buildings located along highways. It is most rational to increase the density of landscaping in areas with a high concentration of PM2.5 along the main roads and on the roofs of existing low-rise buildings and medium-rise buildings.

CALIOP-Based Evaluation of Dust Emissions and Long-Range Transport of the Dust from the Aral−Caspian Arid Region by 3D-Source Potential Impact (3D-SPI) Method

The average monthly profiles of the dust extinction coefficient (ε) were analyzed according to the CALIOP lidar data from 2006–2021 for 24 cells (size of 2° × 5°) in the Aral-Caspian arid region (ACAR; 38–48°N, 50–70°E). Using the NOAA HYSPLIT_4 trajectory model and the NCEP GDAS1 gridded (resolution of 1° × 1°) archive of meteorological data, the array of &gt;1 million 10-day forward trajectories (FTs) of air particles that started from the centers of the ACAR cells was calculated. On the basis of the FT array, the average seasonal heights of the mixed layer (ML) for the ACAR cells were reconstructed. Estimates of the average seasonal dust optical depth (DOD) were obtained for ACAR’s lower troposphere, for ACAR’s ML (“dust emission layer” (EL)), and for the lower troposphere above the ML (“dust transit layer” (TL)) above each of the ACAR cells. Using the example of ACAR, it is shown that the analysis of DOD for the EL, TL and the surface layer (SL; the first 200 m AGL) makes it possible to identify dusty surfaces that are not detected on DOD diagrams for the entire atmospheric column, as well as regions where the regular transport of aged dust from remote sources can generate false sources. Based on FT array, the fields of the potential contribution of both the ACAR’s dust transit and the ACAR’s dust emission layers as well as of the entire ACAR’s lower troposphere into the DOD of the surrounding and remote regions are retrieved using the original method of potential impact of a three-dimensional source (3D-PSI). It has been found out that ACAR dust spreads over almost the entire Northern Hemisphere; the south and southeast regions of the ACAR are subject to the maximum impact of the ACAR dust. Quantitative estimates of the potential contribution of ACAR dust to the regional DODs are given for a number of control sites in the Northern Hemisphere. The results could be useful for climatological studies.