High Concentrations Of Particulate Matter Research Articles

Feeding Habits and Prey Composition of Six Mesopelagic Fish Species from an Isolated Central Mediterranean Basin

Mesopelagic fishes hold an important position in marine food webs, serving as a link between lower trophic levels and top predators and transferring energy from their deep mesopelagic habitat to shallower oceanic layers. Despite their ecological importance, research on mesopelagic fishes’ diet and feeding habits in the Mediterranean Sea is far from thorough. The present work attempts to assess the preying patterns and diet composition of four myctophid (Benthosema glaciale, Ceratoscopelus maderensis, Myctophum punctatum, Notoscopelus elongatus) and two sternoptychid (Argyropelecus hemigymnus, Maurolicus muelleri) species from the Corinthian Gulf (Ionian Sea, Greece), sampled during pelagic trawl surveys in 2018 and 2019. Stomach vacuity was high for myctophids caught during daytime, a pattern which sternoptychids did not follow. Estimated trophic indices revealed high dietary diversity (Shannon’s H’ index) for most investigated species, but a narrow trophic niche breadth (Levins’ normalized Bn index). Copepods and various marine crustaceans were dominant in all diets, classifying them under the zooplanktivorous trophic guild, while A. hemigymnus exhibited high concentrations of particulate organic matter in their stomachs and N. elongatus exhibited consumption of fish. Diet overlap was significant among most studied mesopelagic species, as indicated by Shoener’s S index and confirmed by both the multidimensional scaling ordination and a hierarchical cluster analysis. Information on mesopelagic fishes’ diet composition in this poorly studied part of the Mediterranean is useful in further assessing and parameterizing marine food webs and midwater trophic interactions, as well as in quantifying the ensued energy transfer to top predators of commercial interest or conservation concerns.

Seasonal variation in exposure to particulate matter among children attending different levels of education: Comparison of two dosimetry models

Exposure to particulate matter (PM) has been associated with several adverse health outcomes. Studies indicate that children may be exposed to much higher concentrations of PM at school than in other environments. There exists very little data on the deposited dose of PM while children attend classes. This study was carried out in a school located near an industrial complex in Portugal and attended by children aged 3–12 years. Indoor PM10, PM2.5 and PM1 were measured over two seasons in classrooms representing different school year groups. Particle deposition fractions in the respiratory tract, as well as the deposited doses, were calculated using the Multiple-Path Particle Dosimetry (MPPD) and the Exposure Dose Model (ExDoM2). Both models were implemented assuming an 8-h exposure scenario to represent the school day. In general, differences in PM concentrations were observed depending on room occupancy periods and season. The highest mean PM2.5 concentration was recorded in winter when the classroom was vacant (23.7 ± 20.5 μg m−3), while the highest mean PM10 level was observed in spring during school hours (61.7 ± 24.2 μg m−3). Regardless of the dosimetry model, the highest deposition of PM10 and PM2.5 was in the upper region, while the lowest was in the tracheobronchial (TB) region. The results indicate that deposited dose and deposition fraction in spring may be more harmful to pupils’ health than in winter. PM10 presented the highest doses, ranging from 54.2 to 128 μg and from 83.9 to 185 μg, according to MPPD and ExDoM2 estimates, respectively.

Analysis of PM2.5, black carbon, and trace metals measurements from the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS)

ABSTRACT Communities near transportation sources can be impacted by higher concentrations of particulate matter (PM) and other air pollutants. Few studies have reported on air quality in complex urban environments with multiple transportation sources. To better understand these environments, the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS) was conducted in three neighborhoods in Southeast Kansas City, Kansas. This area has several emissions sources including transportation (railyards, vehicles, diesel trucks), light industry, commercial facilities, and residential areas. Stationary samples were collected for 1-year (October 24, 2017, to October 31, 2018) at six sites using traditional sampling methods and lower-cost air sensor packages. This work examines PM less than 2.5 μm in diameter (PM2.5), black carbon (BC), and trace metals data collected during KC-TRAQS. PM2.5 filter samples showed the highest 24-h mean concentrations (9.34 μg/m3) at the sites located within 20–50 m of the railyard. Mean 24-h PM2.5 concentrations, ranging from 7.96 to 9.34 μg/m3, at all sites were lower than that of the nearby regulatory site (9.83 μg/m3). Daily maximum PM2.5 concentrations were higher at the KC-TRAQS sites (ranging from 25.31 to 43.76 μg/m3) compared to the regulatory site (20.50 μg/m3), suggesting short-duration impacts of localized emissions sources. Across the KC-TRAQS sites, 24-h averaged PM2.5 concentrations from the sensor package (P-POD) ranged from 3.24 to 5.69 µg/m3 showing that, out-of-the-box, the PM sensor underestimated the reference concentrations. KC-TRAQS was supplemented by elemental and organic carbon (EC/OC) and trace metal analysis of filter samples. The EC/OC data suggested the presence of secondary organic aerosol formation, with the highest mean concentrations observed at the site within 20 m of the railyard. Trace metals data showed daily, monthly, and seasonal variations for iron, copper, zinc, chromium, and nickel, with elevated concentrations occurring during the summer at most of the sites. Implications: This work reports on findings from a year-long air quality study in Southeast Kansas City, Kansas to understand micro-scale air quality in neighborhoods impacted by multiple emissions sources such as transportation sources (including a large railyard operation), light industry, commercial facilities, and residential areas. While dozens of studies have reported on air quality near roadways, this work will provide more information on PM2.5, black carbon, and trace metals concentrations near other transportation sources in particular railyards. This work can also inform additional field studies near railyards.

Local climate, air quality and leaf litter cover shape foliar fungal communities on an urban tree

Foliar fungi on urban trees are important for tree health, biodiversity and ecosystem functioning. Yet, we lack insights into how urbanization influences foliar fungal communities. We created detailed maps of Stockholm region’s climate and air quality and characterized foliar fungi from mature oaks (Quercus robur) across climatic, air quality and local habitat gradients. Fungal richness was higher in locations with high growing season relative humidity, and fungal community composition was structured by growing season maximum temperature, NO2 concentration and leaf litter cover. The relative abundance of mycoparasites and endophytes increased with temperature. The relative abundance of pathogens was lowest with high concentrations of NO2 and particulate matter (PM2.5), while saprotrophs increased with leaf litter cover. Our findings show that urbanization influences foliar fungi, providing insights for developing management guidelines to promote tree health, prevent disease outbreaks and maintain biodiversity within urban landscapes.

PM reduction performance according to filter grade and diffuser position in a school classroom

Ventilation performance for indoor air quality (IAQ) in schools has emerged as an important social issue due to the high concentrations of particulate matter (PM). The PM reduction performance is analyzed according to filter grade and the location of return diffusers, upper and floor return, selected based on indoor airflow distribution. Performance evaluation has been experimentally analyzed in the full-scale school environmental performance test-bed equipped with a fan filter unit (FFU). Through the experimental measurements in the classroom, it is found that the PM reduction time of the floor return is relatively shorter than that of the upper return. This is due to the increased ventilation efficiency by decreasing the stagnation flow inside the classroom. Although the supply air flowrate is relatively small at 800 cubic meter per hour (CMH), it has a PM reduction effect similar to 1200 CMH for all particle sizes due to the replacement of the conventional upper return with a floor return. Considering that the energy consumption of the Minimum Efficiency Reporting Value (MERV) 16 filter is approximately 1.7 times that of the MERV13 filter, a MERV13 filter is sufficient to demonstrate the performance of a MERV16 filter with the optimal installation of return diffusers.

Selected legal instruments for air protection against low emissions in Poland

Abstract A fundamental problem during the heating season is the above-normal concentrations of pollutants, especially particulate matter, which are often exceeded. Currently, the main source of air pollution in Poland is low emissions, which consists of from the inefficient burning of fossil fuels in single-family homes and road transportation. This article discusses the permissible particulate matter standards and identifies the anti-smog resolution as a legal instrument to reduce low emissions. For the purpose of this research, field measurements of particulate matter of various fractions were carried out using the specialist equipment of the University Laboratories for Atmosphere Control of the University of Silesia in Katowice. Field measurements were carried out in early 2023 using the Overhead Mobile Laboratory and the Field Mobile Laboratory in selected districts of Katowice. When conducting the study, attention was paid to the type of development, which determines the specifics of heating and the proximity of roads, which are a source of traffic pollution. Due to the high variability of atmospheric conditions and other components, such as current traffic, the data should be treated as indicative. The results of the study depend primarily on the conditions found and reflect the situation at a particular place and time. The occurrence of low emissions was confirmed by the results of the study, which showed very high concentrations of particulate matter in the southern districts of Katowice, where single-family old buildings predominate and building heating is unsuitable. An impact of automobile traffic on air quality was found.

Productivity of Spitsbergen fjords ecosystems in summer-Spatial changes of insitu primary production in Kongsfjorden and Hornsund in the period 1994-2019.

This comprehensive study examines primary production (PP) within the Spitsbergen fjords, Hornsund, and Kongsfjord, over a 25-year period (1994-2019), across 45 stations and 348 incubation levels at various depths. PP and hydrological parameters were measured at 28 sampling stations in Kongsfjorden and 17 in Hornsund, with the locations of "Glacier," "Inner," and "Outer" zones defined to reflect the varying influence of glacial meltwater. Our study revealed spatial and temporal variability in PP, both at the surface and within the water column with very high depth resolution. The highest PP values were observed in the Glacier and Inner zones of Hornsund, particularly in the water layer up to 3 m depth, exceeding 20 mgC m-3 h-1. A notable decline in PP with increasing depth was observed in both fjords, with the Glacier zones displaying the highest productivity at the surface. The study also highlights the influence of glacial meltwater on surface water conditions, affecting the PP in the upper layers of both fjords. The observed gradient in the depth of maximum PP toward the mouth of the fjord varied between the two fjords, with Kongsjord displaying more dynamic variations. The spatial distribution of integrated primary production (Pi) suggested lower productivity in the glacial regions, likely due to light limitation caused by high concentrations of mineral particulate matter. The values of Pi were considerably higher in Hornsund, approximately twice as high overall, with specific emphasis on the Glacier and Inner zones where Pi values were about 6.5 and 2.5 times higher, respectively, when compared to those observed in Kongsfjord.

Environmental factors as drivers of the spatial distribution of the copepods Eurytemora affinis affinis and Eurytemora velox in the Scheldt tributaries

The main tributaries of the Scheldt estuary offer an interesting setting to study the response of organisms to various environmental conditions. The Bovenscheldt and the Dender are closed to tidal entrance by locks, and are hence essentially fresh water systems with low turbulence. The Durme and the Rupel, with its two sub-tributaries (the Beneden-Nete and the Dijle), receive estuarine water at each tide and as such, present a fresh-brackish water gradient according to the geographic location of their confluence with the estuary and the tidal phase. This paper aims (1) to determine the spatial-temporal distribution of two calanoid copepod species: Eurytemora affinis affinis (Poppe, 1880) and E. velox (Lilljeborg, 1853) in these tributaries and (2) the environmental conditions favoring each species development. Species distribution and abundance data, collected in the four tributaries between 2018 and 2021 are analyzed by Generalized Linear Mixed Models (GLMM) and the results are interpreted in the context of ecosystem functioning. A spatial structuring between E. affinis affinis and E. velox was revealed. Whilst E. affinis affinis develops best in the tidal tributaries such as the Durme and Rupel, E. velox is more typical of the non-tidal ones: the Bovenscheldt and the Dender. The tidal tributaries have high Particulate Organic Matter (POM) concentrations due to tidal turbulence, and hence generally lower oxygen concentrations than the non-tidal ones (<10–11 mg L−1). Factors favoring E. affinis affinis development in the tidal tributaries are higher chlorinity, pH and diatom abundance than in the non-tidal ones. In the non-tidal tributaries, with lower POM concentrations, phytoplankton activity more strongly influences the overall oxygen balance, with oxygen concentrations often rising above 10–11 mg L−1 and sometimes showing high variability. The results suggest that E. affinis affinis might suffer from hyperoxia-induced oxidative stress under these high oxygen conditions and advocate the necessity to include this aspect in further research. E. velox, which is most abundant in those tributaries, seems to be more tolerant to hyperoxia and strong fluctuations in O2 concentrations than E. affinis affinis.

Investigating the Correlation between Air Pollution and Housing Prices in Seoul, South Korea: Application of Explainable Artificial Intelligence in Random Forest Machine Learning

South Korea’s Particulate Matter (PM) concentration is among the highest among Organization for Economic Cooperation and Development (OECD) member countries. However, many studies in South Korea primarily focus on housing characteristics and the physical built environment when estimating apartment prices, often neglecting environmental factors. This study investigated factors influencing apartment prices using transaction data for Seoul apartments provided by the Ministry of Land, Infrastructure, and Transport (MOLIT) in 2019. For this purpose, the study compared and analyzed a traditional hedonic price model with a machine learning-based random forest model. The main findings are as follows: First, the evaluation results of the traditional hedonic price model and the machine learning-based random forest model indicated that the random forest model was found to be more suitable for predicting apartment prices. Second, an importance analysis using Explainable Artificial Intelligence (XAI) showed that PM is more important in determining apartment prices than access to education and bus stops, which were considered in this study. Finally, the study found that areas with higher concentrations of PM tend to have higher apartment prices. Therefore, when proposing policies to stabilize apartment prices, it is essential to consider environmental factors. Furthermore, it is necessary to devise measures such as assigning PM labels to apartments during the home purchasing process, enabling buyers to consider PM and obtain relevant information accordingly.

A Quantitative Assessment of Air Particulate Matter Concentration and Its Correlation with the Climatic Factor of Dinajpur City, Bangladesh

Particulate matter (PM) is the air pollutant that poses the most significant risk to human health compared to other measured criteria pollutants. One of our main goals was to assess the quantities of particulate matter (0.3-10µm) in the Dinajpur municipality's sensitive zones, roads, and residential and commercial buildings. Light scattering particle counters, the Extech VPC-300, were used to measure particulate matter and climatic data at 26 distinct locations in Dinajpur. R 4.2.2 and the data analysis tool in Microsoft Excel were utilized for the statistical analysis. The highest values for PM 0.3, 0.5, 1, 2.5, 5, and 10 µm are 335195, 138118, 37965, 12995, 2087, and 2507 and medium value is accordingly 221304, 71873, 16681, 3393, 361 and 454, respectively. The PM 0.5 μm particle range, which includes 12 samples, is highly concerned and getting closer to the hazardous red polluted zone. Most places of PM 2.5 µm exceed the 2000 particles, which are hazardous for people. The link between climatic variables and particulate matter (PM 0.5-10 µm) significantly correlated with temperature. Humidity and PM (0.3-10 µm) measurements in the study area show a negative correlation. According to observations, factors contributing to the high PM concentration include excessive human movement, combustion byproducts of black smoke, road dust, waste, garbage in every possible place, and rice mill industry emissions.

Effect modification of diabetic status on the association between exposure to particulate matter and cardiac arrhythmias in a general population: A systematic review and meta-analysis.

Particulate matter (PM) has various health effects, including cardiovascular diseases. Exposure to PM and a diagnosis of diabetes mellitus (DM) have been associated with an increased risk of cardiac arrhythmias. However, no comprehensive synthesis has been conducted to examine the modifying effect of DM on the association between PM and arrhythmia events. Thus, the objectives of this review were to investigate whether the association of PM is linked to cardiac arrhythmias and whether DM status modifies its effect in the general population. The search was conducted on PubMed/MEDLINE and Embase until January 18, 2023. We included cohort and case-crossover studies reporting the effect of PM exposure on cardiac arrhythmias and examining the role of diabetes as an effect modifier. We used the DerSimonian and Laird random-effects model to calculate the pooled estimates. A total of 217 studies were found and subsequently screened. Nine studies met the inclusion criteria, and five of them were included in the meta-analysis. The participants numbered 4,431,452, with 2,556 having DM. Exposure to PM of any size showed a significant effect on arrhythmias in the overall population (OR 1.10, 95% CI 1.04-1.16). However, the effect modification of DM was not significant (OR 1.18 (95% CI 1.01-1.38) for DM; OR 1.08 (95% CI 1.02-1.14) for non-DM; p-value of subgroup difference = 0.304). Exposure to higher PM concentrations significantly increases cardiac arrhythmias requiring hospital or emergency visits. Although the impact on diabetic individuals is not significant, diabetic patients should still be considered at risk. Further studies with larger sample sizes and low bias are needed.

Long term trend of particulate matter in Philadelphia, Pennsylvania and its association with introduction of environmental policies

Since the 1970s, air quality has improved at the national level in the United States, coincident with the introduction of the Clean Air Act and other air pollution regulations at a greater frequency. We present a case study from Philadelphia, Pennsylvania—the sixth most populous city in the United States. The main objectives of this study are to analyze long-term trends of particulate matter (PM) from 1986 to 2021 in Philadelphia and to examine their association with the introduction of environmental policies relevant to air pollution at the federal, state, and local levels. We find that annual PM10 concentration decreased by 47% from 1986 to 2021 and annual PM2.5 concentration decreased by 31% from 2000 to 2021 in Philadelphia. We find that carbonaceous content (both elemental and organic carbon) has declined over the same period of 2000 to 2021, demonstrating its contribution to overall PM2.5 reduction in Philadelphia. In Philadelphia, high PM concentrations occur in the summer months; however, seasonal patterns have changed for PM10 in the last decade (2011–2020). Overall, PM reductions occurred over all seasons, with the greatest reductions occurring for PM2.5 during summer months and for PM10 during winter months. The Clean Air Act contributed to the creation of many regulatory policies that address unhealthy levels of PM. The introduction of various environmental policies that target the transportation sector has contributed to the reduction of PM levels in Philadelphia. Air quality would continue being improved by implementing such environmental policies specific to the emissions sectors.

Microbial dynamics and climatic interactions in pig sheds: Insights into airborne microbes and particulate matter concentrations.

Emissions of airborne pollutants from livestock buildings affect indoor air quality, the health and well-being of farmers, animals and the environment. This study aimed to evaluate the microbial count within pig sheds and its relationship with meteorological variables (temperature, relative humidity and air velocity) and particulate matter (PM10 and PM2.5) and microbial diversity. Sampling was conducted both inside and outside of two pig sheds over three seasons (summer, rainy and winter), with regular monitoring at fortnightly intervals. Results showed that the bacterial and fungal counts ranged from 0.07 to 3.98 x 103 cfu/m3 inside the sheds and 0.01 to 1.82 x 103 cfu/m3 outside. Seasonal variations were observed, with higher concentrations of particulate matter detected during the winter season, followed by summer. Climatic variables such as temperature, air velocity and relative humidity demonstrated significant impacts on the abundance of Enterobacteriaceae and fungi, while air velocity specifically influenced the presence of mesophilic bacteria and staphylococci. Importantly, no significant disparities were found between microbial counts and particulate matter levels. Staphylococcaceae emerged as the predominant bacterial family, while Aspergillus and Cladosporium spp. were the dominant fungal species within the pig sheds. The average levels of airborne bacteria and fungi in pig sheds were found to be within the recommended range, which can be attributed to the loose housing design and lower animal population on the farms.

Deep learning models for air quality forecasting based on spatiotemporal characteristics of data

The distribution of air-borne pollutants is governed by complex fluid dynamics processes involving convection and diffusion. The process is further affected by the characteristics of emission sources, meteorological parameters, socioeconomic factors, and land use patterns. Compared to deterministic and probabilistic air quality forecasting methods, data driven modeling of air quality parameters can address the large degree of freedom in air quality influencing parameters as well as offer interpretability and understanding of air pollutants' distribution at an increased spatial and temporal resolutions. This study focuses on the citywide prediction of air quality index (AQI) based on observations of pollutant concentrations, meteorological parameters, and spatiotemporal data. The study area includes Ansan city in South Korea, which has been observed as a hotspot for high concentrations of particulate matter. The air quality and meteorological were collected from 16 monitoring stations located in Ansan city. A detailed spatiotemporal analysis was performed to investigate the correlation between AQI records at the air quality monitoring stations. Based on strong spatiotemporal correlations observed between stations, several deep learning (DL) models were proposed, and their performance was investigated for different scenarios. It was observed that the selection of appropriate DL models should be based on (1) understanding of the underlying fluid dynamics process that control pollutant distribution and (2) spatiotemporal characteristics of data. Additionally, the complexity of DL models does not always guarantee the accuracy of the forecasts, and simple models can give good performance if the predictors are selected carefully to reflect the underlying physical process.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020–21 winter

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020–21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42−, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3−, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42−, NO3−, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42− could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3−, and NH4+ concentrations in BJ when Gobi dust storms occur.

Exploring role-playing as a tool for involving citizens in air pollution mitigation urban policies

The design of air pollution control policies is a complex decision-making process. Public participation can enhance the legitimacy and effectiveness of environmental urban regulations but does not always occur naturally. This article presents the experience of the use of role-playing in six mid-sized cities in southern Chile to evaluate how residents affected by high concentrations of fine particulate matter perceive the problem and debate possible solutions. For this, the participants were asked to assume the role of advisors. On that premise, they had to prioritize between a series of mitigation measures and reach a consensus with other advisors. The results show the potential of role-playing games, on the one hand, to promote critical thinking and argument skills among the general public and, on the other, to help policymakers in the design of more operative and fair plans of action.

Existence of typical winter atmospheric circulation patterns leading to high PM2.5 concentration days in East Asia

Understanding the atmospheric circulation patterns responsible for severe air pollution events in East Asia is important because East Asia is one of the most polluted regions in the world, particularly during the boreal winter (December-January-February). Here, by conducting GEOS-Chem simulation with fixed anthropogenic emission sources, we found that there exist three typical atmospheric circulation patterns conducive to leading to high concentrations of particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) in East Asia. These atmospheric circulation patterns are characterized by weakened horizontal winds, which allows PM2.5 to accumulate, and by enhanced relative humidity, which can favor secondary formation of PM2.5. The occurrence of these atmospheric circulation patterns is associated with increased sea ice cover over the Barents Sea and heavy precipitation over the tropical western Indian Ocean. The existence of these atmospheric circulation patterns among typical atmospheric circulation patterns indicates high PM2.5 days in East Asia are unavoidable given current level of anthropogenic emissions in the region. This conclusion indicates that sustained efforts to reduce anthropogenic emission sources in East Asia should be warranted to avoid high PM2.5 days.

Numerical analysis and improvement strategy of particulate matter concentration in underground subway stations

Particulate matter (PM) is an important air pollutant in subway systems. Exposure to high PM concentrations poses a threat to human health and raises concerns. Piston effect can provide the outdoor fresh air to subway stations through station exits, but it also brings PM from tunnels to platforms when the train enters the station. In this paper, a transient numerical model is developed according to an actual subway station and validated by field tests. The model is used to investigate PM10 concentration at platform induced by train movement. The cumulative PM10 concentration at platform in one day is calculated according to the train schedule. Platform screen door (PSD) with adjustable vents is studied to control the PM10 level at platform and energy saving in 27 cities of five climatic zones in China are discussed. The results show that adjustable vent height should be less than 0.70 m to ensure that PM10 concentrations at platform can be maintained at an acceptable level and the requirement of fresh air can be met. Moreover, energy consumption can be reduced by more than 70 % in different cities compared with the conventional mechanical ventilation system. The optimized adjustable vent can provide an important reference for improving indoor air quality (IAQ) and saving energy consumption of ventilation systems in underground facilities.

Overview of the Alaskan Layered Pollution and Chemical Analysis (ALPACA) Field Experiment.

The Alaskan Layered Pollution And Chemical Analysis (ALPACA) field experiment was a collaborative study designed to improve understanding of pollution sources and chemical processes during winter (cold climate and low-photochemical activity), to investigate indoor pollution, and to study dispersion of pollution as affected by frequent temperature inversions. A number of the research goals were motivated by questions raised by residents of Fairbanks, Alaska, where the study was held. This paper describes the measurement strategies and the conditions encountered during the January and February 2022 field experiment, and reports early examples of how the measurements addressed research goals, particularly those of interest to the residents. Outdoor air measurements showed high concentrations of particulate matter and pollutant gases including volatile organic carbon species. During pollution events, low winds and extremely stable atmospheric conditions trapped pollution below 73 m, an extremely shallow vertical scale. Tethered-balloon-based measurements intercepted plumes aloft, which were associated with power plant point sources through transport modeling. Because cold climate residents spend much of their time indoors, the study included an indoor air quality component, where measurements were made inside and outside a house to study infiltration and indoor sources. In the absence of indoor activities such as cooking and/or heating with a pellet stove, indoor particulate matter concentrations were lower than outdoors; however, cooking and pellet stove burns often caused higher indoor particulate matter concentrations than outdoors. The mass-normalized particulate matter oxidative potential, a health-relevant property measured here by the reactivity with dithiothreiol, of indoor particles varied by source, with cooking particles having less oxidative potential per mass than pellet stove particles.