PM10 mass concentration, chemical composition, and sources in the typical coal-dominated industrial city of Pingdingshan, China

Chronic exposure to PM10 induces anxiety-like behavior via exacerbating hippocampal oxidative stress

As one of the most environmental concerns, inhaled particulate matter (PM10) causes numerous health problems. However, the associations between anxiety behavior and toxicity caused by PM10 have rarely been reported so far. To investigate the changes of behavior after PM10 exposure and to identify the potential mechanisms of toxicity, PM10 samples (with doses of 15 mg/kg and 30 mg/kg) were intratracheally instilled into rats to simulate inhalation of polluted air by the lungs. After instillation for eight weeks, anxiety-like behavior was evaluated, levels of oxidative stress and morphological changes of hippocampus were measured. The behavioral results indicated that PM10 exposure induced obvious anxiety-like behavior in the open field and elevated plus maze tests. Both PM10 concentrations tested could increase whole blood viscosity and trigger hippocampal neuronal damage and oxidative stress by increasing superoxide dismutase (SOD) activities and malondialdehyde levels, and decreasing the expressions of antioxidant-related proteins (e.g., nuclear factor erythroid 2-related factor 2 (Nrf2), SOD1 and heme oxygenase 1). Furthermore, through collecting and analyzing questionnaires, the data showed that the participants experienced obvious anxiety-related emotions and negative somatic responses under heavily polluted environments, especially PM10 being the main pollutant. These results show that PM10 exposure induces anxiety-like behavior, which may be related to suppressing the Nrf2/Keap1-SOD1 pathway.

Association of ambient air pollution and pregnancy rate among women undergoing assisted reproduction technology in Fujian, China: A retrospective cohort study

BACKGROUND

Previous studies have reported the impact of ambient air pollutants on assisted reproduction. They concentrated on highly polluted environments and individual pollutants. It is unclear whether these effects continue at lower levels and as mixed effects. We aimed to study the influence of lower pollutant concentrations on pregnancy rates and identify vulnerable populations.

METHODS

We conducted a retrospective cohort study involving 9465 patients with infertility who received treatment from a local hospital between 2015 and 2021. Daily average levels of six pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) were collected from air quality monitoring stations. We employed generalized linear regression models (logistic, linear, and lasso), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) to assess the impact of pollutants on pregnancy rates. Additionally, stratified analyses were performed to identify potentially vulnerable populations.

RESULTS

Findings from the generalized linear models revealed a significant negative correlation between interquartile range increment exposure to PM2.5 (OR = 1.17, 95 % CI = 1.09-1.26), PM10 (OR = 1.18, 95 % CI = 1.11-1.26), NO2 (OR = 1.21, 95 % CI = 1.13-1.30), CO (OR = 1.02, 95 % CI = 1.00-1.03), SO2 (OR = 1.11, 95 % CI = 1.05-1.17) and pregnancy rate when considering the effects of individual pollutants. The WQS index exhibited a negative correlation with pregnancy rates and the number of oocytes retrieved (aOR = 1.20, 95 % CI = 1.08-1.34). BKMR analyses indicated an overall significant trend of decreasing pregnancy rates as pollutant concentrations increased across percentiles. Stratified analysis unveiled heightened sensitivity to pollutants among individuals aged ≥35 years.

CONCLUSIONS

By comparing results obtained from diverse models, we observed that exposure to lower levels of air pollutants led to decreased pregnancy rates. Notably, PM10, NO2, SO2, and CO emerged as the four most prominent pollutants in this context. Moreover, stratified analyses highlighted that individuals aged ≥35 years exhibited heightened susceptibility to pollutants.

TREM2 mitigates NLRP3-mediated neuroinflammation through the NF-κB and PI3k/Akt signaling pathways in juvenile rats exposed to ambient particulate matter

Ambient particulate matter (PM) is a global public and environmental problem. PM is closely associated with several neurological disorders that typically involve neuroinflammation. There have been few studies on the effect of PM on neuroinflammation to date. In this study, we used a juvenile rat model (PM exposure was conducted at a dose of 10 mg/kg body weight per day for 4 weeks) and a BV-2 cell model (PM exposure was conducted at concentrations of 50, 100, 150, and 200 μg/ml for 24 h) to investigate PM-induced neuroinflammation mediated by NLRP3 inflammasome activation and the role of TREM2 in this process. Our findings revealed that PM exposure reduced TREM2 protein and mRNA levels in the rat hippocampus and BV-2 cells. TREM2 overexpression attenuated PM-induced spatial learning and memory deficits in rats. Moreover, we observed that TREM2 overexpression in vivo and in vitro effectively mitigated the increase in NLRP3 and pro-Caspase1 protein expression, as well as the secretion of IL-1β and IL-18. Exposure to PM increased the expression of NF-κB and decreased the phosphorylation of PI3k/Akt in vivo and in vitro, and this process was effectively reversed by overexpressing TREM2. Our results indicated that PM exposure could reduce TREM2 expression and induce NLRP3 inflammasome-mediated neuroinflammation and that TREM2 could mitigate NLRP3 inflammasome-mediated neuroinflammation by regulating the NF-κB and PI3k/Akt signaling pathways. These findings shed light on PM-induced neuroinflammation mechanisms and potential intervention targets.

The dysfunctionality of hippocampal synapses may be directly related to PM-induced impairments in spatial learning and memory in juvenile rats

Epidemiological studies have demonstrated that exposure to air particulate matter (PM) increases the incidence of cardiovascular and respiratory diseases and exerts a significant neurotoxic effect on the nervous system, especially on the immature nervous system. Here, we selected PND28 rats to simulate the immature nervous system of young children and used neurobehavioral methods to examine how exposure to PM affected spatial learning and memory, as well as electrophysiology, molecular biology, and bioinformatics to study the morphology of hippocampus and the function of hippocampal synapses. We discovered that spatial learning and memory were impaired in rats exposed to PM. The morphology and structure of the hippocampus were altered in the PM group. In addition, after exposure to PM, the relative expression of synaptophysin (SYP) and postsynaptic density 95 (PSD95) proteins decreased dramatically in rats. Furthermore, PM exposure impaired long-term potentiation (LTP) in the hippocampal Schaffer-CA1 pathway. Interestingly, RNA sequencing and bioinformatics analysis revealed that the differentially expressed genes (DEGs) were rich in terms associated with synaptic function. Five hub genes (Agt, Camk2a, Grin2a, Snca, and Syngap1) that may play a significant role in the dysfunctionality of hippocampal synapses were identified. Our findings implied that exposure to PM impaired spatial learning and memory via exerting impacts on the dysfunctionality of hippocampal synapses in juvenile rats and that Agt, Camk2a, Grin2a, Snca, and Syngap1 may drive PM-caused synaptic dysfunction.

Chemical Composition and Toxicity of PM10 and PM0.1 Samples near Open-Pit Mines and Coal Power Stations

Particulate matter (PM) <10 μm in size represents an extremely heterogeneous and variable group of objects that can penetrate the human respiratory tract. The present study aimed to isolate samples of coarse and ultrafine PM at some distance from polluting industries (1−1.5 km from the border of open-cast mines). PM was collected from snow samples which allowed the accumulation of a relatively large amount of ultrafine particles (UFPs) (50−60 mg) from five objects: three open-cast mines, coal power plants, and control territories. The chemical composition of PM was examined using absorption spectroscopy, luminescence spectroscopy, high-performance liquid chromatography, X-ray diffraction (XRD), and X-ray fluorescence (XRF) analyses of solid particle material samples. Toxicity was assessed in human MRC-5 lung fibroblasts after 6 h of in vitro exposure to PM samples. The absorption spectra of all the samples contained a wide non-elementary absorption band with a maximum of 270 nm. This band is usually associated with the absorption of dissolved organic matter (DOM). The X-ray fluorescence spectra of all the studied samples showed intense lines of calcium and potassium and less intense lines of silicon, sulfur, chlorine, and titanium. The proliferation of MRC-5 cells that were exposed to PM0.1 samples was significantly (p < 0.01) lower than that of MRC-5 cells exposed to PM10 at the same concentration, except for PM samples obtained from the control point. PM0.1 samples—even those that were collected from control territories—showed increased genotoxicity (micronucleus, ‱) compared to PM10. The study findings suggest that UFPs deserve special attention as a biological agent, distinct from larger PMs.

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi, Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th-March 31st) and during the partial lockdown (April 1st-April 22nd) with "current" data obtained in 2020 and "historical" data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

Assessment of Emission Reduction and Meteorological Change in PM2.5 and Transport Flux in Typical Cities Cluster during 2013–2017

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM2.5 flux distribution. The results showed that the PM2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m3 and 1.1–3.6 μg/m3) and favorable in 2016 (contribution concentration −1.5 μg/m3 and −0.2 μg/m3). Further, the absolute value of the net flux’s intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures.

Temporal and spatial characteristics of PM2.5 transport fluxes of typical inland and coastal cities in China

Local pollution and the cross-boundary transmission of pollutants between cities have an inevitable impact on the atmosphere. Quantitative assessments of the contribution of transport to pollution in inland and coastal cities are necessary for the implementation of practical, regional, and joint emission control strategies. In this study, the Comprehensive Air Quality Model (CAMx), together with the Weather Research and Forecasting model (WRF), was used to simulate the contributions to pollution of different cities in 2016. The monthly inflow, outflow, and net flux from the ground to the extended layers served as the three main indicators for the analysis of the interactions of PM_2.5 transport between adjacent cities. Between inland and coastal cities, the magnitude of inflow and outflow are larger in the former than in the latter. The inflow flux in the inland cities (Beijing and Shijiazhuang) was 10.6 and 10.7 kt/day, respectively, while that in the coastal cities (Tianjin, Shanghai, Hefei, Nanjing, and Hangzhou) was 9.1, 3.3, 5.8, 4.4, and 3.7 kt/day, respectively. In terms of variation over the year, the strongest inflow in the BTH region occurred in April, followed by October, July, and January, while that in the coastal cities in YRD occurred in January, followed by October, April, and July. Therefore, based on the flux intensity calculations and the transport flux pathways, effective joint control measures can be provided with scientific support, and a better understanding of the evolutionary mechanism among inland and coastal cities can be acquired.

Particulate matter (PM10) enhances RNA virus infection through modulation of innate immune responses

Sensing of pathogens by specialized receptors is the hallmark of the innate immunity. Innate immune response also mounts a defense response against various allergens and pollutants including particulate matter present in the atmosphere. Air pollution has been included as the top threat to global health declared by WHO which aims to cover more than three billion people against health emergencies from 2019 to 2023. Particulate matter (PM), one of the major components of air pollution, is a significant risk factor for many human diseases and its adverse effects include morbidity and premature deaths throughout the world. Several clinical and epidemiological studies have identified a key link between the PM existence and the prevalence of respiratory and inflammatory disorders. However, the underlying molecular mechanism is not well understood. Here, we investigated the influence of air pollutant, PM10 (particles with aerodynamic diameter less than 10 μm) during RNA virus infections using Highly Pathogenic Avian Influenza (HPAI) - H5N1 virus. We thus characterized the transcriptomic profile of lung epithelial cell line, A549 treated with PM10 prior to H5N1infection, which is known to cause severe lung damage and respiratory disease. We found that PM10 enhances vulnerability (by cellular damage) and regulates virus infectivity to enhance overall pathogenic burden in the lung cells. Additionally, the transcriptomic profile highlights the connection of host factors related to various metabolic pathways and immune responses which were dysregulated during virus infection. Collectively, our findings suggest a strong link between the prevalence of respiratory illness and its association with the air quality.

Inorganic ion chemistry of local particulate matter in a populated city of North China at light, medium, and severe pollution levels

Twenty-six pairs of PM_2.5 and PM₁₀ samples were collected during haze episodes in Zhengzhou (113°28' E, 34°37' N), a highly populated city in North China. The samples were used to examine the inorganic ion chemistry of particulate matter (PM) of local origin at light (PM_2.5 < 60 μg m^-3 and PM₁₀ < 135 μg m^-3), medium (PM_2.5: 60-170 μg m^-3 and PM₁₀: 135-325 μg m^-3), and severe (PM_2.5 > 170 μg m^-3 and PM₁₀ > 325 μg m^-3) pollution levels. At the light and severe pollution levels, the increase of PM₁₀ was accounted for by the increase of PM_2.5, and the variation of PM_10-2.5 was small. In contrast, the increase of PM₁₀ at the medium pollution level was caused by the increase in both PM_2.5 and PM_10-2.5. Sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), and chloride in the form of ammonium chloride (Cl^-_S) accounted for 47.8% and 60.3% of the PM_2.5 mass at the light and severe levels, respectively. These values indicate a large contribution of secondary inorganic species to the PM_2.5 growth. As the pollution level changed from light to medium, the contribution of SO₄^2- to the growth of PM_2.5 decreased from 49.0% to 15.1%, while those of NO₃^- and Cl^-_S increased from 25.1% and 0.6% to 32.5% and 2.8%, respectively, indicating the substantial production of nitrate and chloride. At the severe level, the contribution of SO₄^2- was 30.1%, while those of NO₃^- and Cl^-_S were 5.9% and 0.5%, respectively, suggesting a hindering effect of sulfate on the production of nitrate and chloride. These results indicate that the production of secondary species with the increase of PM_2.5 was dominated by sulfate-associated conversions at the light and severe pollution levels and was substantially influenced by nitrate- and chloride-associated conversions at the medium pollution level. The estimation of carbonate presence in the PM indicates that part of the carbonate in coarse particles (PM_10-2.5) of crustal origin enhanced sulfate production via heterogeneous surface reactions. Quantification of the contribution of primary and secondary species to PM_2.5 showed that it was dominated by both primary and secondary particles at the light pollution level, and it was mainly composed of secondary species at the severe pollution level.

Sources of particulate matter in China: Insights from source apportionment studies published in 1987-2017

Particulate matter (PM) in the atmosphere has adverse effects on human health, ecosystems, and visibility. It also plays an important role in meteorology and climate change. A good understanding of its sources is essential for effective emission controls to reduce PM and to protect public health. In this study, a total of 239 PM source apportionment studies in China published during 1987-2017 were reviewed. The documents studied include peer-reviewed papers in international and Chinese journals, as well as degree dissertations. The methods applied in these studies were summarized and the main sources in various regions of China were identified. The trends of source contributions at two major cities with abundant studies over long-time periods were analyzed. The most frequently used methods for PM source apportionment in China are receptor models, including chemical mass balance (CMB), positive matrix factorization (PMF), and principle component analysis (PCA). Dust, fossil fuel combustion, transportation, biomass burning, industrial emission, secondary inorganic aerosol (SIA) and secondary organic aerosol (SOA) are the main source categories of fine PM identified in China. Even though the sources of PM vary among seven different geographical areas of China, SIA, industrial, and dust emissions are generally found to be the top three source categories in 2007-2016. A number of studies investigated the sources of SIA and SOA in China using air quality models and indicated that fossil fuel combustion and industrial emissions were the most important sources of SIA (total contributing 63.5%-88.1% of SO₄^2-, and 47.3%-70% NO₃^-), and agriculture emissions were the dominant source of NH₄⁺ (contributing 53.9%-90%). Biogenic emissions were the most important source of SOA in China in summer, while residential and industrial emissions were important in winter. Long-term changes of PM sources at two megacities of Beijing and Nanjing indicated that the contributions of fossil fuel and industrial sources have been declining after stricter emission controls in recent years. In general, dust and industrial contributions decreased and transportation contributions increased after 2000. PM_2.5 emissions are predicted to decline in most regions during 2005-2030, even though the energy consumptions except biomass burning are predicted to continue to increase. Industrial, residential, and biomass burning sources will become more important in the future in the businuess-as-usual senarios. This review provides valuable information about main sources of PM and their trends in China. A few recommendations are suggested to further improve our understanding the sources and to develop effective PM control strategies in various regions of China.

Atmospheric ambient trace element concentrations of PM10 at urban and sub-urban sites: source apportionment and health risk estimation

In this study, PM₁₀ concentrations and elemental (Al, Fe, Sc, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Ag, Cd, Sn, Sb, Ba, Pb, and Bi) contents of particles were determined in Düzce, Turkey. The particulate matter samplings were carried out in the winter and summer seasons simultaneously in both urban and sub-urban sampling sites. The average PM₁₀ concentration measured in the winter season was 86.4 and 27.3 μg/m³, respectively, in the urban and sub-urban sampling sites, while it was measured as 53.2 and 34.7 μg/m³ in the summer season. According to the results, it was observed that the PM₁₀ levels and the element concentrations reached higher levels, especially at the urban sampling site, in the winter season. The positive matrix factorization model (PMF) was applied to the data set for source apportionment. Analysis with the PMF model revealed six factors for both the urban (coal combustion, traffic, oil combustion, industry, biomass combustion, and soil) and sub-urban (industry, oil combustion, traffic, road dust, soil resuspension, domestic heating) sampling sites. Loadings of grouped elements on these factors showed that the major sources of the elements in the atmosphere of Düzce were traffic, fossil fuel combustion, and metal industry-related emissions.

Chemical composition and source apportionment of PM10 at an urban background site in a high-altitude Latin American megacity (Bogota, Colombia)

Bogota registers frequent episodes of poor air quality from high PM₁₀ concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM₁₀ source contribution. A characterization of the chemical composition and the source apportionment of PM₁₀ at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO₄^2-, Cl^-, NO₃^-, NH₄⁺), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM₁₀ components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM₁₀, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM₁₀) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM₁₀ source, accounting for ∼50% of the PM₁₀. The results provided novel data about PM₁₀ chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.

Determination of airborne trace elements in an urban area using lichens as biomonitor

The amounts of elements emitted from industrial, domestic, and vehicle sources in Düzce through the analyses of lichens, which are bioindicators of air pollution, were determined in this research. Concentrations of Al, Fe, Cr, Mn, Co, Ni, Cu, Zn, As, V, Cd, Hg, and Pb in the lichens that were collected from 40 different points were analyzed using an inductively coupled plasma (ICP-MS) device. The highest concentration values were detected for Fe and Al, while the lowest concentration values were detected for Cd and Hg. Distribution maps of elements were created using geographic information systems. The distribution maps showed how the concentrations of elements for Düzce have changed across the city. According to our results, the elements sourced from traffic and combustion, such as Cr, Co, Ni, Cu, As, and V, have the highest concentrations in the city center near the traffic.

Characterization and morphological analysis of individual aerosol of PM10 in urban area of Lucknow, India

Airborne particulate matters were collected during the period of October 2015 to September 2016 in Lucknow at different sampling sites. The annual mean concentration of particulate matter was found to be relatively higher than the limits prescribed by National ambient air quality standards (NAAQS), United State Environmental Protection Agency (USEPA) and World Health Organization (WHO). Particulate matters were studied for morphological analysis, elemental composition and functional group variability with the help of Scanning Electron Microscope-Energy Dispersive Spectroscopy (SEM-EDS) followed by Fourier Transform Infrared spectroscopy (FTIR). Morphological characteristics viz. particle count, aspect ratio, circulatory, roundness, equivalent spherical diameter (ESD) and surface area revealed that the particles were perfectly spherical to irregular in shape. Based on the morphology and elemental composition, four clusters of a particulates namely organic particle with inorganic inclusion, soot, tar balls and aluminosilicates were found. FTIR spectra revealed the presence of sulfate, bisulfate, particulate water, silicate, ammonium, aliphatic carbon, aliphatic alcohol, carbonyl and organic nitrates.