Mass Concentrations Of PM2 Research Articles

Interpreting hourly mass concentrations of PM2.5 chemical components with an optimal deep-learning model

PM2.5 constitutes a complex and diverse mixture that significantly impacts the environment, human health, and climate change. However, existing observation and numerical simulation techniques have limitations, such as a lack of data, high acquisition costs, and multiple uncertainties. These limitations hinder the acquisition of comprehensive information on PM2.5 chemical composition and effectively implement refined air pollution protection and control strategies. In this study, we developed an optimal deep learning model to acquire hourly mass concentrations of key PM2.5 chemical components without complex chemical analysis. The model was trained using a randomly partitioned multivariate dataset arranged in chronological order, including atmospheric state indicators, which previous studies did not consider. Our results showed that the correlation coefficients of key chemical components were no less than 0.96, and the root mean square errors ranged from 0.20 to 2.11 µg/m3 for the entire process (training and testing combined). The model accurately captured the temporal characteristics of key chemical components, outperforming typical machine-learning models, previous studies, and global reanalysis datasets (such as Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service ReAnalysis (CAMSRA)). We also quantified the feature importance using the random forest model, which showed that PM2.5, PM1, visibility, and temperature were the most influential variables for key chemical components. In conclusion, this study presents a practical approach to accurately obtain chemical composition information that can contribute to filling missing data, improved air pollution monitoring and source identification. This approach has the potential to enhance air pollution control strategies and promote public health and environmental sustainability.

Source apportionment and health risk assessment of PM10 bound carbonaceous and elemental species in the central Himalayas

In this extensive investigation, the sources and health risk assessment of carbonaceous aerosols, as well as the elemental compositions (Ca, Al, Fe, S, K, Mg, Pd, B, Mo, Zn, Ag, Nb, Ga, Cl, Ti, Zr, Na, Cr, Cu, Mn, Cs, P, Y, Sb, Ni, Sn, F, Sr, Br, Pm, U, Pb, Th, Br, Rb, and V) of PM10, were conducted throughout January-December 2021 in Nainital, a central Himalayan region of India. The average annual mass concentration of PM10 was determined to be 64±6 µg m-3. Carbonaceous aerosols (CAs), comprising OC, EC, WSOC, and SOC, exhibited annual averages of 9.3±0.8 µg m-3, 4.9±0.5 µg m-3, 1.5±0.2 µg m-3, 2.7±0.2 µg m-3, and 2.97±0.45 µg m-3, respectively. The elemental composition featured major contributors such as Ca, Al, Fe, S, and K, alongside trace levels of various elements (Mg, Pd, B, Mo, Zn, Ag, Nb, Ga, Cl, Ti, Zr, Na, and Cr). Positive Matrix Factorization (PMF) identified six primary contributors to PM10, each with varying percentage contributions: crustal/soil/road dust, soil re-suspension, combustion, vehicular emissions, industrial emissions, and biomass burning. The health risk assessment revealed elevated Hazard Quotient (HQ) values for Cr and Mn in children, indicating a non-carcinogenic health risk. Adults exposed to high Cr levels may face potential carcinogenic risks, while elements like Al, Pb, Cu, Zn, and Ni pose no health hazards, aligning with USEPA guidelines.

Hemolytic Properties of Fine Particulate Matter (PM2.5) in In Vitro Systems.

Epidemiological studies have suggested that inhalation exposure to particulate matter (PM) air pollution, especially fine particles (i.e., PM2.5 (PM with an aerodynamic diameter of 2.5 microns or less)), is causally associated with cardiovascular health risks. To explore the toxicological mechanisms behind the observed adverse health effects, the hemolytic activity of PM2.5 samples collected during different pollution levels in Beijing was evaluated. The results demonstrated that the hemolysis of PM2.5 ranged from 1.98% to 7.75% and demonstrated a clear dose-response relationship. The exposure toxicity index (TI) is proposed to represent the toxicity potential of PM2.5, which is calculated by the hemolysis percentage of erythrocytes (red blood cells, RBC) multiplied by the mass concentration of PM2.5. In a pollution episode, as the mass concentration increases, TI first increases and then decreases, that is, TI (low pollution levels) < TI (heavy pollution levels) < TI (medium pollution levels). In order to verify the feasibility of the hemolysis method for PM toxicity detection, the hemolytic properties of PM2.5 were compared with the plasmid scission assay (PSA). The hemolysis results had a significant positive correlation with the DNA damage percentages, indicating that the hemolysis assay is feasible for the detection of PM2.5 toxicity, thus providing more corroborating information regarding the risk to human cardiovascular health.

The composition of the bacterial communities collected from the PM10 samples inside the Seoul subway and railway station

Health implications of indoor air quality (IAQ) have drawn more attention since the COVID epidemic. There are many different kinds of studies done on how IAQ affects people’s well-being. There hasn’t been much research that looks at the microbiological composition of the aerosol in subway transit systems. In this work, for the first time, we examined the aerosol bacterial abundance, diversity, and composition in the microbiome of the Seoul subway and train stations using DNA isolated from the PM10 samples from each station (three subway and two KTX stations). The average PM10 mass concentration collected on the respective platform was 41.862 µg/m3, with the highest average value of 45.95 µg/m3 and the lowest of 39.25 µg/m3. The bacterial microbiomes mainly constituted bacterial species of soil and environmental origin (e.g., Acinetobacter, Brevundimonas, Lysinibacillus, Clostridiodes) with fewer from human sources (Flaviflexus, Staphylococcus). This study highlights the relationship between microbiome diversity and PM10 mass concentration contributed by outdoor air and commuters in South Korea’s subway and train stations. This study gives insights into the microbiome diversity, the source, and the susceptibility of public transports in disease spreading.

Assessment of Air Pollution by Aerosols over a Coal Open-Mine Influenced Region in Southwestern Romania

The mining activity in open-pit coal sites exerts a high pressure over the surrounding environment and on the health of people working and living nearby. Using data form a total of six field campaigns, this study aimed to capture the level of exploitation activities in the residential area close to the coal open-mine in terms of mass concentrations and total carbon fractions (TC) of ambient PM10, PM2.5 samples. Sampling campaigns were performed between spring of 2018 and spring of 2020, covered both working (full time, part-time) and non-working days at the coal exploitation, and captured also the seasonal variations of different fractions of PM and of their carbonaceous fraction. Fine fraction was also analyzed based on the aerosol Angstrom exponent, determined from measurements of the aerosol scattering coefficient at 450 nm, 550 nm and 700 nm by a nephelometer. The mass concentrations of PM and TC showed significant variations from full time working days to non-working days. The air quality (AQ) level is determined by the air quality index (AQI) specific for PM10. In situ measurements clearly indicated that AQIlocal gives better image on the level of air pollution than the AQIestim from AQ monitoring stations in the region, closest to the Matasari site. Insights into the morphology and composition of particles were obtained by scanning electron microscopy (SEM) and energy dispersive X-ray (EDX/EDS) and Fourier transform infrared spectroscopy (FTIR) analyses. Major elements that were identified C, O, Si, Ca, K, S, Cu, Ni, Fe, Mg, Ti have both crustal and anthropogenic origin, in various proportions.

Assessment of particulate matter and particle path trajectory analysis using a HYSPLIT model over Dire Dawa, Ethiopia

This work deals with the assessment of particulate matter (PM1, PM2.5, and PM10) over Dire Dawa during the month of May 2021. In the study, purple sensor (PS) and gravimetric methods (GM) were used. The purple sensor was to provide real-time measurements of PM1.0, PM2.5, and PM10 particulates. The GM instruments were constructed using wood with 1 m height (distance to ground), with flat board on top of which filter papers were placed to collect particulate matter. The difference in filter paper weight before and after sampling was used to calculate the particle masses. By dividing the weight gain of the filter by the amount of air measured, the concentrations of suspended particulate matter in the defined size range were estimated. The mean value of PM10 indicated a good status whereas the mean value of PM2.5 revealed a moderate condition as far as pollution is concerned. The purple sensor detected relatively higher values for PM10 measurement as compared to GM method during the study period. According to the calculated results of the ratio of mass concentration of PM1.0 to PM10, coarse particles were dominant whereas in the ratio of PM2.5 to PM10 both coarse and fine mode particles were equally present during the sampling period. The spatial distribution showed variations depending on the locations where the sampling filter papers were placed. The HYSPLIT backward trajectory analysis indicated various air masses and transport channels during different seasons. The predominant pathways were from both urban and desert origins.

OCCURRENCE OF PM0.1 AND PM2.5 AT HIGH POLLUTING EVENT DAYS IN HANOI AND HEALTH IMPLICATION

High levels of fine (PM2.5) and ultrafine (PM0.1) particles in the atmosphere can cause adverse effects on the environment and human health. This study aims at determining the mass concentrations of PM and health risks on pollution event days (episodes) in Hanoi. Semi-daily samples (daytime and night-time) of PM2.5 and PM0.1 were collected at Hanoi University of Science and Technology, in December 2021. The daily PM2.5 concentrations were in the range of 42 – 204 µg/m3 (average of 123 µg/m3). Those of PM0.1 varied from 9 to 30 µg/m3 (average of 22 µg/m3). There is negligible change on daytime and night-time PM0.1 concentrations, whereas those levels of PM2.5 were remarkably different. PM2.5 daytime concentrations were in the range of 39 – 205 µg/m3 with an average of 107 µg/m3. The level ranges of night-time were slightly wider which varied from 39 to 230 µg/m3 (average of 132 µg/m3). A prolonged episode of PM2.5 (which is defined by the criterion of PM2.5 &gt; 50 µg/m3) was found with an intensity of 26 days in December. During the pollution episode, the Monte Carlo simulation showed that respirable doses were the highest for the adult (above 21 years) for chronic effects, whereas the highest doses for acute were observed in the children (0-3 years), which has implications in the adverse health effects for sensitive groups. The sensitive analysis finds the concentration of PM to be the most influencing factor in inhalation dose estimation.

Characteristics of PM2.5 in Long Binh Industry Park, Bien Hoa City, Vietnam: Mass Concentrations, Chemical Composition, Source Apportionment, and Health Risk Assessment

This study aimed to assess the concentration, source, chemical properties, and health risks associated with PM2.5 in Long Binh ward, Bien Hoa city, Dong Nai province, where there is a large distribution of industrial zones. PM2.5 samples were collected using a high-volume sampler during both the dry and rainy seasons. The mass concentration of PM2.5 was determined by Mettler Toledo XS205, and the chemical properties of eleven heavy metal elements were analyzed using inductively coupled plasma mass spectrometry (ICP-MS; iCAP-RQ, Thermo Science, US). The migration trajectory of PM2.5 was determined using the HYSPLIT model. The results showed that the PM2.5 concentration exceeded the WHO recommended value, while only the PM2.5 concentration in the dry season exceeded the national standard gia (QCVN 05:2013/BTNMT). Industry, road and non-road transportation activities were identified as the main sources of PM2.5. The heavy metal element Cr was found to be the most significant contributor to the chemical composition of fine particles. The health risk assessment revealed that the HI values were lower than 1 in both seasons, indicating a low risk of chronic adverse health effects. However, the TRC values exceeded the recommended threshold for cancer risk in both the rainy season (10-4 ± 6,6 x 10-5) and dry seasons (7,9 x 10-4 ± 5,6 x 10-4).

A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions.

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.

Estimation of PM2.5 and PM10 Mass Concentrations in Beijing Using Gaofen-1 Data at 100 m Resolution

Due to the advantage of high spatial coverage, using satellite-retrieved aerosol optical depth (AOD) data to estimate PM2.5 and PM10 mass concentrations is a current research priority. Statistical models are the common method of PM estimation currently, which do not require the knowledge of complex chemical and physical interactions. However, the statistical models rely on station data, which results in less accurate PM estimation concentrations in areas where station data are missing. Hence, a new hybrid model, with low dependency on on-site data, was proposed for PM2.5 and PM10 mass concentration estimation. The Gaofen-1 satellite and MODIS data were employed to estimate PM2.5 and PM10 concentrations with 100 m spatial resolution in Beijing, China. Then, the estimated PM2.5/10 mass concentration data in 2020 were employed to conduct a spatio-temporal analysis for the investigation of the particulate matter characteristic in Beijing. The estimation result of PM2.5 was validated by the ground stations with R2 ranging from 0.91 to 0.98 and the root mean square error (RMSE) ranging from 4.51 μg/m3 to 17.04 μg/m3, and that for PM10 was validated by the ground stations with R2 ranging from 0.85 to 0.98 and the RMSE ranging from 6.98 µg/m3 to 29.00 µg/m3. The results showed that the hybrid model has a good performance in PM2.5/10 estimation and can improve the coverage of the results without sacrificing the effectiveness of the model, providing more detailed spatial information for urban-scale studies.

Assessment of the contribution of residential waste burning to ambient PM10 concentrations in Hungary and Romania

Abstract. The illegal burning of solid waste in residential stoves is an existing practice, but until now it has been completely disregarded as an emission source of atmospheric pollutants in many developed countries, including those in eastern Europe. Various types of solid waste (plastics, treated wood, plyboards, tyre, rag) serve as an auxiliary fuel in many households, in particular during the heating season. In this work, for the first time ever in atmospheric pollution studies, specific tracer compounds identified previously in controlled test burnings of different waste types in the laboratory were detected and quantified in ambient PM10 samples collected in five Hungarian and four Romanian settlements. Using the identified tracers and their experimentally determined relative emission factors, the potential contribution of illegal waste burning emissions to ambient PM10 mass concentrations was assessed. Our findings implied that the burning of polyethylene terephthalate (PET)-containing waste (food and beverage packaging, clothes) was predominant at all the locations, especially in north-eastern Hungary and Romania. There is substantial evidence that the burning of scrap furniture is also common in big cities in Hungary and Romania. Back-of-the-envelope calculations based on the relative emission factors of individual tracers suggested that the contribution of solid waste burning particulate emissions to ambient PM10 mass concentrations may be as high as a few percent. This finding, when considering the extreme health hazards associated with particulate emissions from waste burning, is a matter of serious public health concern.

КАЧЕСТВО ВОЗДУХА В МОСКВЕ ВО ВРЕМЯ КАРАНТИНА COVID-19 В СРАВНЕНИИ С ДРУГИМИ РЕГИОНАМИ МИРА

An analysis of the changes in the carbon monoxide (CO) and particulate matter (PM10) mass concentrations in the atmosphere near highways and residential areas over Moscow during the spring lockdown in 2020 against of the mass concentrations in the previous years (2015-2019) is presented. In the lockdown period, a decrease in the CO mass concentrations was about 40% near highways and only 10% in residential areas. A decrease in the PM10 mass concentrations by about 10% was found during that period. The closeness of lockdown effects in Moscow and other megacities is shown by the comparison of trends in the traffic intensity and pollutant mass concentrations. The special importance of motor vehicles as a source of carbon monoxide emissions in the analyzed megacities is demonstrated.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India.

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region(NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban siteof Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81µgm-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10were entrenched to the receptor models to comprehend the possible sourcesof PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Wintertime investigation of PM10 concentrations, sources, and relationship with different meteorological parameters

Meteorological factors play a crucial role in affecting air quality in the urban environment. Peshawar is the capital city of the Khyber Pakhtunkhwa province in Pakistan and is a pollution hotspot. Sources of PM10 and the influence of meteorological factors on PM10 in this megacity have yet to be studied. The current study aims to investigate PM10 mass concentration levels and composition, identify PM10 sources, and quantify links between PM10 and various meteorological parameters like temperature, relative humidity (RH), wind speed (WS), and rainfall (RF) during the winter months from December 2017 to February 2018. PM10 mass concentrations vary from 180 – 1071 µg m−3, with a mean value of 586 ± 217 µg m−3. The highest concentration is observed in December, followed by January and February. The average values of the mass concentration of carbonaceous species (i.e., total carbon, organic carbon, and elemental carbon) are 102.41, 91.56, and 6.72 μgm−3, respectively. Water-soluble ions adhere to the following concentration order: Ca2+ > Na+ > K+ > NH4+ > Mg2+. Twenty-four elements (Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Co, Zn, Ga, Ge, As, Se, Kr, Ag, Pb, Cu, and Cd) are detected in the current study by PIXE analysis. Five sources based on Positive Matrix Factorization (PMF) modeling include industrial emissions, soil and re-suspended dust, household combustion, metallurgic industries, and vehicular emission. A positive relationship of PM10 with temperature and relative humidity is observed (r = 0.46 and r = 0.56, respectively). A negative correlation of PM10 is recorded with WS (r = − 0.27) and RF (r = − 0.46). This study’s results motivate routine air quality monitoring owing to the high levels of pollution in this region. For this purpose, the establishment of air monitoring stations is highly suggested for both PM and meteorology. Air quality standards and legislation need to be revised and implemented. Moreover, the development of effective control strategies for air pollution is highly suggested.

The Diwali festival: short-term high effect of fireworks emissions on particulates and their associated empirically calculated health risk assessment at Bhubaneswar city.

This article elucidates the role of the short-term combustion of firecrackers and sparklers as a significant source of atmospheric pollutants that deteriorate ambient air quality and increase health risks during the popular Diwali festival. The study was conducted at Bhubaneswar during the festive celebration in early November 2021 (4th Nov) and late October 2022 (24th Oct) to assess the level of particulates (PM2.5 and PM10 mass concentration) and the relative health risks associated with them. PM2.5 (113.83µg/m3) and PM10 (204.32µg/m3) showed significant rises on D-day at all seven different sites that exceeded the NAAQS in 2021. From 2021 to 2022, an overall decrease in PM2.5 (41%) and PM10 (36%) was observed. On D-day, the total concentration of quantified metals in PM2.5 and PM10 were found to be 4.83µg/m3 5.97µg/m3 (2021) and 5.08µg/m3 5.18µg/m3 (2022) respectively. The AQI during both years (2021-2022) was found to be high for PM2.5 (unhealthy) and PM10 (moderate), but it was markedly goodfor all other pollutants on the scale. The overall population in the study area were under a significant health risk was observed in the overall population as PM surpassed the threshold concentration amid the festivities for consecutive years, with PM2.5 being more potent than PM10. The total excess health risk in 2022 was found to be decreased lower by ~ 88% from 2021 on D-day. But, metal exposure (through inhalation) in children were more compared to the adults for both the years. However, the exposure risk of both children and adults were high in the year 2022 with inhalation of metals like K, Al, Ba, Fe and Ca found in higher concentration and directly emitted from the firecrackers.

Investigating Indoor Air Pollution Sources and Student’s Exposure Within School Classrooms: Using a Low‐Cost Sensor and Source Apportionment Approach

Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low‐cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low‐cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM2.5 and PM10 mass concentrations of 14.4 and 51.0 μg/m3, respectively. During school hours, when students were present, all classrooms had average PM2.5 concentrations greater than 8.1 μg m−3 and average PM10 concentrations greater than 13.1 μg m−3. Notably, the English studies classroom exceeded the 24‐h WHO ambient PM10 guideline (45 μg m−3). Employing the non‐negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM1 observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM2.5, and 19%–40% of PM10, respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. Thereby, it allows for air quality management in locations crucial for the public health and educational outcomes of children.

CHARACTERIZATION OF AIR POLLUTION BY PARTICULATE MATTERS EMITTED FROM CEMENT INDUSTRY LOCATED IN SAGAMU, NIGERIA

Air pollution in urban areas is a major concern to the general public and generally becoming a serious problem around the world. The effect of these pollutants on public health, animals and plants are devastating. This study examined environmental pollution caused by Lafarge Cement Plc, Sagamu at some terrestrial locations within the catchment area of the production. Particulate matters (PM2.5 and PM10) depositions were recorded for all the sampling locations. The Settling properties for particulate matters, optical properties and air quality index (AQI) for all referenced points were calculated from the measured data. The results show that the average AQI of Sagamu were found to be heavily polluted and therefore classified as hazardous for residence with AQI values of 186-699. The mass concentration of PM10 was highest at Abeokuta routes with a measurement of 349.2958µg/m3 and ≤ 308.6125 µg/m3 for other locations, this assertion was further corroborated by decreased visibility experienced at Abeokuta route.

Size-classified aerosol-bound heavy metals and their effects on human health risks in industrial and remote areas in Japan

Airborne aerosols were collected in six size classes (PM<0.1, PM0.1–0.5, PM0.5–1, PM1–2.5, PM2.5–10 and PM>10) to investigate aerosol health risks in remote and industrial areas in Japan. We focused on heavy metals and their water-dispersed fractions. The average concentration of heavy metals was 18 ± 25–86 ± 48 ngm−3 for PM<0.1, 46 ± 19–154 ± 80 for PM0.5–1 ngm−3, 98 ± 49–422 ± 186 ngm−3 for PM1–2.5, 321 ± 305–1288 ± 727 ngm−3 for PM2.5–10 and 65 ± 52–914 ± 339 ngm−3 or PM>10, and these concentrations were higher in industrial areas. Heavy metals emitted from domestic anthropogenic sources were added to the long-range transport component of the aerosols. The water-dispersed fraction of heavy metals contained 3.3–40.1% of the total heavy metals in each size class. The relative contribution of Zn and other species (As, Cd, Cr, Ni, Pb, Mn, V and Cu) increased in the water-dispersed fraction. Smaller particles contained greater proportions of the water-dispersed heavy metal fraction. Carcinogenic risk (CR) and the hazard index (HI) were estimated for each size class. The CR of carcinogens was at acceptable levels (<1 ×10−6) for five particle size fractions. The HI values for carcinogens and noncarcinogens were also below acceptable levels (<1) for the same five size fractions. The estimated CR and HI values were dominated by contributions from the inhalation process.

Oxidation potential of PM2.5 in a mechanical processing plant and its association with metal composition

Oxidative potential (OP) of particles is an emerging indicator of health that reflects their ability to induce oxidative stress and cause adverse health effects. It offers us a useful tool to evaluate the health effects of particles released by different industrial processes. We measured the OPv (volume normalized OP characterizes overall oxidative burden) and OPm (mass normalized OP characterizes intrinsic toxicity) of PM2.5 from a casting workshop, a machining workshop, a meeting room of a machining processing plant, and outdoors using dithiothreitol (DTT) assay. The observed variations were substantial and varied greatly, underscoring the diverse toxicological profiles of particulates from distinct sources. Overall, PM2.5 mass concentration and OPv were highest in the casting workshop (PM2.5: 669.26 ± 402.62 μg/m3, OPv: 69.55 ± 128.35 nmol/(min·m3)), followed by the machining workshop (PM2.5 = 85.51 ± 41.89 μg/m3, OPv = :5.38 ± 2.68 nmol/(min·m3)), outdoor (PM2.5: 30.77 ± 13.34 μg/m3, OPv: 1.83 ± 0.92 nmol/(min·m3)), and meeting room (PM2.5: 26.97 ± 12.03 μg/m3, OPv: 1.86 ± 1 nmol/(min·m3)). However, localized variances influenced by PM's intrinsic toxicity (OPm) reordered these rankings. For example, PM2.5 mass concentration at the spheroidizing/pouring zone in the casting workshop was the highest, but the OPv was not due to the low intrinsic toxicity of the particles. Spearman's correlation analysis implied that the OPv was significantly correlated with the concentration of transition metals Mn (ρ = 0.47, P < 0.01), Fe (ρ = 0.503, P < 0.01), and Zn (ρ = 0.507, P < 0.01) in addition to PM2.5 mass concentration (ρ = 0.879, P<0.01), and the OPm was significantly correlated with the mass fraction of Zn (ρ = 0.34, P < 0.05) and Al (ρ = 0.333, P < 0.05). Besides, environmental factors (wind speed, temperature relative humidity, CO2) did not contribute to the oxidation potential. Higher oxidation potential (OPv) means higher health risks, our findings underscore the imperative to consider both PM mass concentration and intrinsic toxicity for future air pollution control efforts.

Significant influence of nitrate on light absorption enhancement of refractory black carbon in the winter of 2022 in Beijing

The mixing state of refractory black carbon (rBC) aerosols is regarded as a major uncertainty in climate-forcing assessments. This study measured the size distribution and mixing state of rBC using a single-particle soot photometer in the winter of 2022 at an urban site in Beijing. During the campaign, the mean mass concentration of rBC was 0.79 ± 0.63 μg m−3, much lower than that observed in Beijing in the winter of 2013. The number and mass median diameter of the rBC cores were 97 and 200 nm, respectively. The average relative coating thicknesses (RCT) of rBC-containing particles was 1.45 ± 0.27 and average light absorption enhancement (Eabs) was 1.43 ± 0.22. Similar to Eabs, RCT and secondary inorganic aerosols (SIA), especially nitrate, increased with increasing relative humidity. This suggests that higher SIA mass fraction in aerosol with a higher relative humidity in the environment results in a thicker coating and black carbon ageing, thus enhancing light absorption. RCT and Eabs increased rapidly with the increase of PM1 loading but increased slowly when the PM1 mass concentration exceeded 60 μg m−3. This indicates that a further increase in the NR-PM1 species at high PM loading does not increase the thickness of the coatings; therefore, there is no further increase in Eabs. The effects of the chemical composition of the Eabs obtained using the Lindeman, Merenda, and Gold method showed that nitrate plays a prominent role in the enhancement of light absorption, followed by SOA. The rBC mass concentration exhibited clear day-low and night-high patterns which were influenced by the synergetic effects of the boundary layer and emissions. RCT and Eabs presented similar diurnal variations, peaking in the afternoon, which was consistent with the pattern of SIA. This suggests that the SIA produced via photochemical reactions supports the ageing of black carbon-containing particles, leading to light-absorption enhancement. The back-trajectory analysis showed the highest values of rBC mass concentration, RCT, and Eabs appeared in the S cluster suggested that the rBC-containing particles transported from south Beijing were more aged with a thicker coating. While the rBC-containing particles from northern and northwestern Beijing had lower RCT and Eabs values.