Particulate Research Articles

Ratios of organic mass to organic carbon in fine particulate matter at urban sites in China and Korea during winter and summer.

This study evaluates the composition and seasonal characteristics of fine particulate matter (PM2.5) during winter and summer through simultaneous measurements conducted at the Gwangju Institute of Science and Technology in South Korea and the Changping campus of Peking University in China. PM2.5 samples were concurrently collected at both sites, and chemical analyses were conducted to quantify various components, including carbonaceous materials, ionic species, and metals. Although the average PM2.5 concentrations were comparable between the two sites, there were distinct differences in the concentrations of major components. Organic indicator compounds were analyzed to discern the contributions of primary and secondary pollution sources. Changping displayed a mix of primary and secondary pollution, characterized by higher concentrations of primary organic carbon (POC) such as polycyclic aromatic hydrocarbons and hopanes, compared to Gwangju. In contrast, Gwangju demonstrated a higher prevalence of secondary organic carbon (SOC), particularly water-soluble organic carbon not related to biomass burning (WSOCnbb) and various polar organic compounds. The organic mass to organic carbon (OM/OC) ratios estimated using the mass balance method revealed significant differences, with Gwangju showing a higher ratio of 2.3 compared to 1.9 at Changping, indicating a greater influence of secondary pollutants at Gwangju. Additionally, both Changping and Gwangju exhibited higher OM/OC ratios in summer (Changping: 2.0, Gwangju: 2.5) compared to winter (Changping: 1.8, Gwangju: 2.2), indicating seasonal differences in organic mass contributions to PM2.5. These findings underscore the importance of accounting for spatial and seasonal variations in air pollution studies and suggest that updating commonly used OM/OC ratios could enhance the reliability of research outcomes.

Development of Air Pollution Forecasting Models Applying Artificial Neural Networks in the Greater Area of Beijing City, China

The ever-increasing industrialization of certain areas of the planet combined with the simultaneous degradation of the natural environment are alarming phenomena, especially in the field of human health. The concentration of particulate matter with an aerodynamic diameter of 2.5 μm (PM2.5) and 10 μm (PM10), nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3) needs constant monitoring, as they consist of the main cause for many diseases. Based on the existence of statutory limits from the World Health Organization (WHO) for the concentration of each of the aforementioned air pollutants, it is considered necessary to develop forecasting systems that have the ability to correlate the current meteorological data with the concentrations of the above pollutants. In this work, the attempt to predict air pollutant concentrations in the wider area of Beijing, China, is successfully carried out using artificial neural network (ANN) models. In the frame of a specific work, a significant number of ANNs are developed. For this purpose, an open-access meteorological and air pollution database was used. Finally, a statistical evaluation of the developed prognostic models was carried out. The results showed that ANNs present a remarkable prognostic ability in order to forecast air pollution levels in an urban environment.

Impacts from air pollution on respiratory disease outcomes: a meta-analysis.

Air pollution is widely acknowledged as a significant factor in respiratory outcomes, including coughing, wheezing, emergency department (ED) visits, and even death. Although several literature reviews have confirmed the association between air pollution and respiratory outcomes, they often did not standardize associations across different studies and overlooked other increasingly impactful pollutants such as trace metals. Recognizing the importance of consistent comparison and emissions of non-exhaust particles from road traffic, this study aims to comprehensively evaluate the standardized effects of various criteria pollutants and trace metals on respiratory health. We conducted a comprehensive meta-analysis of peer-reviewed journal articles on air pollution and respiratory outcomes published between 1 January 2000, and 1 June 2024. The study included children (age < 18 years), adults (age ≥ 18 years), and all age groups exposed to criteria pollutants established by the US Environmental Protection Agency National Ambient Air Quality Standards and over 10 trace metals. Using databases, such as PubMed, MEDLINE, Web of Science Core Collection, and Google Scholar, we identified 579 relevant articles. After rigorous screening and quality assessment using the Newcastle-Ottawa Scale, 50 high-quality studies were included. We converted various reported outcomes (e.g., odds ratios, relative risk, and percent increase) to a standardized odds ratio (OR) for comparability and performed meta-analyses using R 4.4.0 and related packages, ensuring the robustness of our findings. Our meta-analysis indicated significant associations between air pollutants and respiratory outcomes. For particulate matter with diameter ≤ 2.5 μm (PM2.5), the overall ORs for children, adults, and combined age groups were 1.31, 1.10, and 1.26, respectively, indicating a consistent positive association. Similar positive associations were observed for particulate matter with diameter ≤ 10 μm (PM10) and other pollutants, with children showing higher susceptibility than adults. The analysis of trace metals also showed significant associations; however, these findings require cautious interpretation due to the small number of studies. Our study supports associations between air pollutants, including non-exhaust trace metals, and respiratory outcomes across different age groups. The findings underscore the need for stringent environmental health policies and further research, especially in regions with higher pollution levels. The future studies should consider long-term and short-term exposures separately and include diverse populations to improve the accuracy and generalizability of the results.

Early life air pollution exposures and thyroid function in children: A prospective cohort study

Studies on early life ambient air pollution exposures and childhood thyroid function are scarce. This study aimed to evaluate the relationships between early life fine particulate matter (≤2.5 μm; PM2.5) and nitrogen dioxide (NO2) exposures and thyroid function in children. We measured the levels of thyrotropin, triiodothyronine, and free thyroxine in children (n = 684) residing in a rural Korean area at age 2, 4, 6, or 8 years from 2012 to 2020 in the Environment and Development of Children cohort. The relationship between residential average exposure levels of PM2.5 and NO2 during pregnancy and 1-year average levels before visit and thyroid function during childhood were analyzed. Inverse association between increases of 10 μg/m3 in PM2.5 during the first trimester and thyrotropin levels at aged 4 (β, −0.12; 95% CI: −0.22, −0.02) and 6 years (β, −0.16; 95% CI: −0.26, −0.06) were observed. No association was found between PM2.5 exposure during the second and third trimester and childhood TSH levels. Childhood PM2.5 exposure was positively associated with thyrotropin rise at aged 4 (β, 0.2; 95% CI: 0.06, 0.35) and 6 years (β, 0.16; 95% CI: 0.02, 0.29) and inversely related with free thyroxine levels at aged 8 years (β, −0.04; 95% CI: −0.07, −0.01). No relationship between NO2 exposure and thyroid function was found. In conclusion, association between PM2.5 exposure and childhood thyrotropin levels varied depending on exposure timing. Early gestational exposure showed an inverse relationship, whereas childhood exposure were positively associated with childhood thyrotropin levels. The long-term effects of early life air pollution exposure and underlying mechanisms should be investigated in future studies.

Estimation of nighttime PM2.5 concentrations over Seoul using Suomi NPP/VIIRS Day/Night Band

With rapid economic development and urban growth, Seoul experiences severe air pollution due to fine particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), which is detrimental to human health. Although recent studies have extensively focused on estimating daytime PM2.5 concentrations using various types of satellite data, there remains a significant lack of research on nighttime PM2.5 estimations. This study estimated nighttime PM2.5 in Seoul from December 2018 to November 2019 using multiple linear regression (MLR) and random forest (RF) models. These models, which incorporated data on radiance, moon illumination fraction, and terrain height from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi National Polar-orbiting Partnership satellite covering all moon phases, also utilized meteorological data from the ERA5 reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF). To address multicollinearity, seasonal models were developed using forward stepwise regression and variance inflation factor analysis. DNB radiance analysis indicates that the high intensity of artificial light sources in Seoul significantly reduces the impact of moonlight, leading to notable changes in the DNB radiation associated with PM2.5 concentrations. Consequently, this study estimated nighttime PM2.5 over Seoul across all moon phases. These estimates were then validated through 10-fold cross-validation. The RF model exhibited superior accuracy, with a coefficient of determination (R2) of 0.65–0.90, compared to MLR, with R2 of 0.15–0.50, reflecting seasonal fluctuations in the model performance. The developed models can be applied to estimate reliable nighttime PM2.5 concentrations in megacities with strong artificial light sources, utilizing a comprehensive dataset from satellite observations for all moon phases. Additionally, our findings can serve as scientific data for establishing environmental policies by providing valuable insights into understanding air pollution primarily caused by PM2.5.

Impact of elevated fine particulate matter (PM2.5) during landscape fire events on cardiorespiratory hospital admissions in Perth, Western Australia

BackgroundAustralia has experienced extreme fire weather in recent years. Information on the impact of fine particulate matter (PM2.5) from landscape fires (LFs) on cardiorespiratory hospital admissions is limited.MethodsWe conducted a...

Washable oil-coated structured support for passive outdoor particulate matters trapping

Direct outdoor air depollution represents an interesting path for preventing indirect disease. In the present work, a simple and efficient PMs trapping media based on the use of an oil-coated structured polymer media was developed for passive trapping of various PMs, ranging from coarse (PM10), to fine (PM2.5) and ultra-fine (PM1) dimension in outdoor environment. The device can be easily regenerated by a simple washing with a mixture of water and detergent followed by a new oil coating cycle. The total PM loading mass of the passive trap and the recovered PMs are analyzed through different techniques and confirm the great efficiency of such filter to trap various PMs when exposed to a high traffic road. The spent filter can be regenerated through a simple washing step and can be repeatedly re-used with similar PM loading mass. The high and long-lasting total PM loading mass were also supported by numerical simulations based on computational fluid dynamics, also used to propose an optimization implementation of such system for future deployment at scale.

An Application of Mist Generator as a Way to Reduce Particulate Matter during High Concentration Episodes in Urban Forests

Previous conventional mist devices can induce a detrimental effect of leaf burn by intense, focused sunlight in summer. A mist generator is designed to prevent particulate matter (PM) damage to trees by combining mist with PM during high PM episodes. We measured changes in microclimate conditions and the concentration of PM before, during, and after mist spraying in urban parks (Yangjae Citizen Forest, YCF; Cheongdam Road Park, CRP) from May 6 to 8, 2020. PM changes in YCF and CRP were observed immediately after mist spraying and were found to return to the previous concentrations. Mist spraying had no significant effects on the meteorological traits of air temperature, humidity, and wind speed but had significant effects on the concentration of PMx and the ratio of PM during a short time. Also, the ratio of PMx was partially affected by mist spraying. During the morning rush hour and lunch, mist, high wind speed, and low relative humidity conditions were related to the increase in mist movement, resulting in increasing PM (2.5–10 μm) and the deposition of these PM. During the evening rush hour, high relative humidity and low wind speed affected PM concentrations more than mist. This prototype of mist spraying could effectively condense and deposit the PM during high PM episodes.

Association between air pollutants, thyroid disorders, and thyroid hormone levels: a scoping review of epidemiological evidence.

Over the past two decades, the incidence of thyroid disorders has been steadily increasing. There is evidence to suggest that air pollution may be one of the etiological factors of thyroid diseases. This comprehensive review aimed to examine the evidence related to air pollutants and thyroid disorders and thyroid hormones levels from an epidemiological perspective. The scoping review adopted a systematic approach to search for, identify, and include peer-reviewed articles published in English. We performed a comprehensive search of three databases-PubMed, Embase, and Web of Science to identify relevant literature on the relationship between air pollution [particulate matter, nitrogen oxide, carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2)] exposure and thyroid disorders, including hypothyroidism, congenital hypothyroidism (CH), thyroid nodules, thyroid cancer, autoimmune thyroid diseases, as well as thyroid hormone levels, such as thyroid-stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4). Articles published until August 1, 2023, were included. A total of 3,373 studies were retrieved, and among them, 25 studies covering eight different air pollutants were relevant. The most frequently studied air pollutants in this review included fine particulate matter (with fine particulate matter (PM2.5), n=21; inhalable particles (PM10), n=10; PM10-2.5, n=1) and nitrogen oxides (with NO2, n=13; NOx, n=3). The thyroid disorders and thyroid hormone levels most commonly associated with evidence of air pollution exposure were hypothyroidism (n=7) and TSH (n=12). Despite variations in study designs and exposure assessments, the findings consistently highlight the substantial health risks that air pollution, particularly PM2.5, poses to thyroid health, especially among vulnerable populations. Given that our study was limited to epidemiological investigations and the increasing prevalence of toxic substances in the environment, there is an urgent need for further research to elucidate the mechanisms by which these pollutants disrupt thyroid function and contribute to the development of thyroid diseases.

Pore Structures in Detritusphere of Soils Under Switchgrass and Restored Prairie Vegetation Community

ABSTRACTRoot detritusphere, that is, the soil in the vicinity of decomposing root residues, plays an important role in soil microbial activity and C sequestration. Pore structure (size distributions and connectivity of soil pores) in the detritusphere serves as a major driver for these processes and, in turn, is influenced by the physical characteristics of both soil and roots. This study compared pore structure characteristics in the root detritusphere of soils of contrasting texture and mineralogy subjected to &gt; 6 years of contrasting vegetation: monoculture switchgrass and polyculture prairie systems. Soil samples were collected from five experimental sites in the US Midwest representing three soil types. Soil texture and mineralogy were measured using a hydrometer and x‐ray powder diffraction, respectively. The intact cores were scanned with x‐ray computed micro‐tomography to identify visible soil pores, biopores, and particulate organic matter (POM). We specifically focused on pore structure within the detritusphere around the POM of root origin. Results showed that the detritusphere of coarser textured soils, characterized by high sand and quartz contents, had lower porosity in the vicinity of POM compared with finer textured soils. POM vicinities in finer textured soils had high proportions of large (&gt; 300 μm diameter) pores, and their pores were better connected than in the coarser soils. Lower porosity in the outer (&gt; 1 mm) parts of the detritusphere of switchgrass than of prairie suggested soil compaction by roots, with the effect especially pronounced in the coarser soils. The results demonstrated that soil texture and mineralogy played a major, while vegetation played a more modest, role in defining the pore structure in the root detritusphere.

Air Pollution and Breast Cancer Incidence in the Multiethnic Cohort Study.

Recent studies suggested fine particulate matter (PM2.5) exposure increases the risk of breast cancer, but evidence among racially and ethnically diverse populations remains sparse. Among 58,358 California female participants of the Multiethnic Cohort (MEC) Study followed for an average of 19.3 years (1993-2018), we used Cox proportional hazards regression to examine associations of time-varying PM with invasive breast cancer risk (n = 3,524 cases; 70% African American and Latino females), adjusting for sociodemographics and lifestyle factors. Subgroup analyses were conducted for race and ethnicity, hormone receptor status, and breast cancer risk factors. Satellite-based PM2.5 was associated with a statistically significant increased incidence of breast cancer (hazard ratio [HR] per 10 μg/m3, 1.28 [95% CI, 1.08 to 1.51]). We found no evidence of heterogeneity in associations by race and ethnicity and hormone receptor status. Family history of breast cancer showed evidence of heterogeneity in PM2.5-associations (Pheterogeneity = .046). In a meta-analysis of the MEC and 10 other prospective cohorts, breast cancer incidence increased in association with exposure to PM2.5 (HR per 10 μg/m3 increase, 1.05 [95% CI, 1.00 to 1.10]; P = .064). Findings from this large multiethnic cohort with long-term air pollutant exposure and published prospective cohort studies support PM2.5 as a risk factor for breast cancer. As about half of breast cancer cannot be explained by established breast cancer risk factors and incidence is continuing to increase, particularly in low- and middle-income countries, our results highlight that breast cancer prevention should include not only individual-level behavior-centered approaches but also population-wide policies and regulations to curb PM2.5 exposure.

Comparative Life Cycle Assessment and Carbon Footprint of Typical Hydrogen Energy Products

To compare the environmental impact and carbon footprint of gray hydrogen, blue hydrogen, and green hydrogen, inventories were obtained through literature research. Some inventories that were not available in China were obtained through foreign inventories combined with localized power conversion. The localized end-point destructive life cycle impact assessment method was used to calculate the environmental impact potential of the raw material acquisition, transportation, and hydrogen production stages of five hydrogen products. The carbon footprint was calculated, and the sensitivity analysis and uncertainty analysis were carried out and compared with the ReCiPe method. The results showed that： ① The environmental impact from large to small was： gray hydrogen （coal） （1 203 mPt·kg-1） &gt; blue hydrogen （coal） （876 mPt·kg-1） &gt; gray hydrogen （gas） （492 mPt·kg-1） &gt; green hydrogen （323 mPt·kg-1） &gt; blue hydrogen （gas） （252 mPt·kg-1）. The environmental impacts of gray hydrogen and blue hydrogen were mainly concentrated in climate change, fine particulate matter formation, and fossil fuels. The environmental impacts of green hydrogen were mainly concentrated in climate change, fine particulate matter formation, fossil fuels, and mineral resources. ② The carbon footprint from large to small was： gray hydrogen （coal） （23.79 kg·kg-1, measured by CO2eq, the same below） &gt; blue hydrogen （coal） （11.07 kg·kg-1） &gt; gray hydrogen （gas） （10.97 kg·kg-1） &gt; blue hydrogen （gas） （3.47 kg·kg-1） &gt; green hydrogen （1.97 kg·kg-1）. Direct carbon emissions in the production process of gray hydrogen and blue hydrogen accounted for the largest proportion, whereas that of green hydrogen accounted for a large proportion of power input. ③ Measures to reduce environmental impact and carbon emissions include reducing direct emissions of pollutants and greenhouse gases, reducing power consumption, and strengthening raw material substitution and reduction.

Increased Stillbirth Rates and Exposure to Environmental Risk Factors for Stillbirth in Counties with Higher Social Vulnerability: United States, 2015-2018.

Exposure to unfavorable environmental conditions during pregnancy, such as extreme heat and air pollution, has been linked to increased risk of stillbirth, defined as fetal mortality at or after 20 weeks' gestation, however no studies have examined its association with social vulnerability. We examined associations between county-level stillbirth rates, environmental risk factors for stillbirth, and social vulnerability in the United States. This ecologic study linked county-level data from three nationwide datasets on stillbirths (National Vital Statistics System), environmental conditions (North American Land Data Assimilation System and Environmental Protection Agency), and social vulnerability (Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index). Poisson and negative binomial models were fit to the variables and produced rate ratios to estimate associations among stillbirth rates, environmental risk factors, and social vulnerability. Social vulnerability was positively associated withn stillbirth rates, annual average number of extreme heat days, and ambient concentration of particulate matter ≤ 2.5μm in diameter (PM2.5). The average number of days that ozone and PM2.5 each exceeded regulatory standards were not associated with stillbirth rates or social vulnerability. A positive association between average annual PM2.5 concentration and stillbirth rates was detected; no other significant associations between environmental risk factors and stillbirth rates were observed. We found evidence of associations between social vulnerability and stillbirth rates, and between social vulnerability and environmental risk factors for stillbirth at the county level. Further research could inform understanding of how social vulnerability impacts the relationship between environmental exposures and stillbirth risk.

Spatiotemporal Characterization and Driving Factors of Fine Particulate Matter and Its Chemical Components in the Huaihe River Basin

According to the data sets of fine particulate matter （PM2.5） and its components in 35 cities in the Huaihe River Basin from 2015 to 2021, the temporal and spatial distribution patterns of pollutants were analyzed. The influence of meteorological factors on PM2.5 concentrations was examined using a random forest model. The original series of PM2.5, sulfate （SO42-）, nitrate （NO3-）, ammonium salt （NH4+）, organic matter （OM）, and black carbon （BC） were rebuilt using KZ （Kolmogorov-Zurbenko） filtering and multiple linear regression （MLR） to quantify the effects of meteorological conditions. The results demonstrated that from 2015 to 2021, the declining rates of PM2.5, SO42-, NO3-, NH4+, OM, and BC in the Huaihe River Basin were 4.71, 0.99, 1.05, 0.77, 1.01, and 0.19 μg·（m3·a）-1, respectively. The high mass concentrations of PM2.5 and its components were concentrated in the central and western regions of the HRB, whereas those in coastal and southern cities were lower. The variance contributions of the short-term, seasonal, and long-term components of PM2.5 to the original PM2.5 sequences in 35 cities were 51.6%, 35.9%, and 7.0%, respectively. The PM2.5 in coastal cities were more affected by the short-term components. The meteorological conditions were unfavorable for PM2.5 reduction in the HRB from 2015 to 2018, whereas the meteorological conditions supported the PM2.5 decrease from 2019 to 2021. From 2015 to 2021, the contribution rates of meteorological conditions to the long-term component reductions of PM2.5, SO42-, NO3-, NH4+, OM, and BC were 28.3%, 29.1%, 31.0%, 29.3%, 27.8%, and 28.6%, respectively. The contribution rates of meteorological conditions to the long-term PM2.5 reduction were 43.4%, 25.6%, 25.5%, and 20.6% in the HRB cities in Anhui, Shandong, Jiangsu, and Henan Provinces, respectively. With the decrease in PM2.5 concentration in the HRB, the sulfur oxidation rate （SOR） increased significantly, while the nitrogen oxide oxidation rate （NOR） changed little.

Evolution Characteristics and Typical Pollution Episodes of PM2.5 and O3 Complex Pollution in Bozhou City from 2017 to 2022

In China, atmospheric pollution exhibits a complex pattern, with simultaneous exceedances of fine particulate matter （PM2.5） and ozone （O3） levels becoming evident. To understand the complex pollution characteristics and evolution patterns of PM2.5 and O3 in Bozhou City, various methods such as weather classification, analysis of typical pollution processes, and investigation of precursor sources were employed to explore the pollution and variations of PM2.5 and O3 in Bozhou City from 2017 to 2022 and subsequently analyze their causes and precursor sources. The results indicated that： ① PM2.5-O3 complex pollution in Bozhou City mostly occurred under high-pressure weather conditions, with daytime high temperatures and low humidity promoting the formation of O3 pollution, whereas nighttime high humidity and atmospheric oxidative conditions promoted the generation of secondary components such as nitrates and ammonium salts in PM2.5. ② During the pollution process, PM2.5 in Bozhou City mainly originated from biomass burning, secondary generation, traffic pollution, coal combustion, and dust sources. Volatile organic compounds （VOCs） primarily emerged from plant sources, traffic pollution, oil and gas evaporation, solvent use, fossil fuel combustion, residential emissions, and industrial emissions. Biomass burning and traffic pollution made significant contributions to the pollution process. ③ Analysis of air mass trajectories and regional pollution situations indicated that the overlay of northern and southern air masses, along with local generation, were the main causes of the PM2.5-O3 complex pollution in Bozhou from October 18th to 27th, 2022.

A Deep Learning Framework for Satellite-Derived Surface PM2.5 Estimation: Enhancing Spatial Analysis in the United States

Abstract Monitoring fine particulate matter (PM2.5) is crucial for evaluating air quality and its effects on public health. However, the limited distribution of monitoring stations presents a challenge in accurately assessing air pollution, especially in areas distant from these stations. To address this challenge, our study introduces a two-step deep learning approach for estimating daily gap-free surface PM2.5 concentrations across the contiguous United States (CONUS) from 2018 to 2022, with a spatial resolution of 4 km. In the first phase, we employ a Depthwise-Partial Convolutional Neural Network (DW-PCNN) to fill gaps between surface PM2.5 stations, utilizing Aerosol Optical Depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the second phase, we integrate the PM2.5 grids imputed by the DW-PCNN with meteorological and anthropogenic variables into a Deep Convolutional Neural Network (Deep-CNN) to further enhance the accuracy of our estimation. This enables us to estimate gap-free surface PM2.5 concentrations accurately, evidenced by a Pearson’s correlation coefficient (R) of 0.92 and an Index of Agreement (IOA) of 0.96 in ten-fold cross-validation. We also introduce a grid-based method for calculating PM2.5 Design Values (DV), providing a continuous spatial representation of PM2.5 DV that enhances the traditional station-based approach. Our grid-based DV representations offer a comprehensive perspective on air quality, facilitating more detailed analysis. Furthermore, our model's ability to provide spatiotemporally consistent, gap-free PM2.5 data addresses the issue of missing values, supporting health impact research, policy formulation, and the accuracy of environmental assessments.

Application End Evaluation of Electrostatic Precipitation for Control PM and NOx Emissions from Small-Scale Combustions

Electrostatic precipitators (ESPs) have shown promise in reducing particulate matter (PM) emissions, but their potential for simultaneous NOx reduction in small-scale combustion systems remains underexplored. This study focuses on using non-thermal plasma generated in a corona discharge to reduce PM and NOx emissions from small-scale combustion. ESP was specifically designed for a commercially available 15 kW boiler with wood pellet combustion and used with both positive and negative discharge polarity to control emissions without any chemical additives. ESP performance was evaluated across a range of specific input energies (SIE) in terms of particle mass and number concentrations and NOx concentrations obtained by continuous gas analysis. ESP ensured the reduction in PM concentrations from 48 mg/m3 to the magnitude of PM content in the ambient air. The highest precipitation efficiency was observed for particles in the 20–200 nm range. Concurrently, NOx emissions were reduced by up to 78%, from 178 mg/m3 to 39 mg/m3. These results were achieved at specific input energies of 36 for positive and 48 J/L for negative corona, which is significantly lower than those reported for many existing separate PM and NOx control systems. This study demonstrates the potential of ESPs as a compact, energy-efficient solution for simultaneous PM and NOx removal in small-scale combustion systems, offering promising implications for improving air pollution control technologies for small-scale combustion systems.

Association of specific PM2.5 chemical constituents and ozone exposure with pregnancy outcomes in women undergoing assisted reproductive technology treatment in central China

The associations of air pollutants exposure with assisted reproductive technology (ART) pregnancy outcomes are mixed, and the effects of specific components of fine particulate matter (PM2.5) and ozone (O3) are not well understood. We conducted a retrospective longitudinal study to explore the association of PM2.5 constituents and O3 exposure with three ART outcomes among women undergoing ART treatment. The exposure window was segmented into five periods corresponding to the cycle of ovarian stimulation and oocyte retrieval procedure. Generalized linear mixed model (GLMM) was applied to explore the relationships between PM2.5 constituents, O3, Normalized Vegetation Index (NDVI) exposure and three ART outcomes. The combined effect of PM2.5 constituents was evaluated by the quantile g (qg)-computation. We also explored the modifying effect of different covariate. Elevated exposure level of PM2.5 (OR = 0.915, 95% CI: 0.859, 0.974) and its constituents (BC: 0.905, 95% CI: 0.840, 0.975; OM: 0.910, 95% CI: 0.848, 0.976; NO3−: 0.909, 95% CI: 0.850, 0.972, SO42−: 0.905, 95% CI: 0.846, 0.968, and NH4+: 0.902, 95% CI: 0.842, 0.966) exposure throughout the year before oocyte retrieval (period 1) was correlated with a reduced odds ratio (OR) of live birth with statistical significance. Similarly, for each interquartile range (IQR) increase in O3 exposure during periods 2 (85 days prior to oocyte retrieval), 3 (30 days prior to oocyte retrieval), 4 (oocyte retrieval to embryo transfer) and 5 (embryo transfer to hCG test) was significantly related to a decreased OR of live birth. Especially, participants who underwent fresh embryo transfer cycles and received two cleavage-stage embryo transfer, and were younger than 30 years old, showed a higher susceptibility to particulate matter. Findings from this study suggest that PM2.5 constituents and O3 exposure may have adverse effects on the ART outcomes, highlighting the importance of identifying critical exposure periods for various air pollutants and the need for meticulous management of particulate matter.

Revitalizing subterranean spaces: a comprehensive study on enhancing air quality in underground shopping malls for sustainable urban living

Cities worldwide are increasingly turning to underground spaces to address the challenges posed by high population density. These subterranean areas are now utilized for various purposes such as offices, shopping malls, subway terminals, and underground sidewalks. However, the semi-closed nature of most underground spaces presents difficulties in ensuring a comfortable environment due to the lack of natural ventilation. This study focuses on a representative underground shopping mall in South Korea, utilizing preliminary surveys and long-term sensor monitoring to identify existing problems. The aging ventilation system was retrofitted to enhance and assess indoor air quality. As a result, concentrations of carbon dioxide, total volatile organic compounds, and radon were reduced by over 33, 74, and 98%, respectively, while particulate matter with a diameter of 2.5 μm or less (PM2.5) concentrations remained the same as before. This not only contributed to maintaining proper indoor air quality, but also led to a reduction in total energy consumption. The goal of this project is to improve air quality in facilities located in underground spaces, such as underground shopping malls, where indoor air quality management is challenging, thereby creating a safe and healthy environment for users and enhancing the overall functionality of the facility.

Simultaneous comparison of the chemical composition and attributable source of PM2.5 during 2014–2018 in major metropolitan cities in South Korea: impacts of policy interventions

Abstract Ambient fine particulate matter (PM2.5) is one of the most concerning pollutants, characterized by its diverse chemical composition. Although various studies have revealed PM2.5 chemical components, there is limited knowledge on how to reduce PM2.5 concentrations through administrative policies focusing on source management. We compared PM2.5 compositional characteristics and performed source apportionment using the positive matrix factorization in four metropolitan cities (Seoul, Daejeon, Gwangju, and Ulsan) in South Korea from 2014 to 2018. The annual average of PM2.5 concentrations exceeded the annual national ambient air quality standard of 15 μg m−3 in all areas while secondary inorganic aerosols constituted the largest fraction of PM2.5. This implies that secondary formation from gaseous precursors in the atmosphere was the main factor contributing to ambient PM2.5. However, the concentrations of PM2.5 constituents varied significantly across cities, suggesting that PM2.5 is a heterogeneous pollutant considerably influenced by region-specific conditions. In line with the chemical composition, secondary nitrate, secondary sulfate, and mobile-related sources were found to be significant contributors of PM2.5. Additionally, the extent of contribution from each source varied across the study regions. We also evaluated the impacts of policy interventions by comparing the PM2.5 composition and source apportionment before and after the policies for improving air quality. Intensive programs focused on the vehicle sector in Seoul led to a considerable decrease in the concentrations of carbonaceous compounds and mobile-related sources. In addition, strengthened regulations on coal-fired power plants (CFPPs) since 2016 have influenced the contributions of coal combustion sources in two cities adjacent to the west coastal area, where approximately half of the CFPPs of the country are densely distributed. Overall, the study’s findings indicate that region-specific PM2.5 chemical constituents and source contributions should be considered for establishing PM2.5-related policies, considering the high heterogeneity of PM2.5.