Chemical characterisation of PM2.5 emitted from motor vehicles powered by diesel, gasoline, natural gas and methanol fuel

Single particle mass spectral signatures from on-road and non-road vehicle exhaust particles and their application in refined source apportionment using deep learning

With advances in vehicle emission control technology, updating source profiles to meet the current requirements of source apportionment has become increasingly crucial. In this study, on-road and non-road vehicle particles were collected, and then the chemical compositions of individual particles were analyzed using single particle aerosol mass spectrometry. The data were grouped using an adaptive resonance theory neural network to identify signatures and establish a mass spectral database of mobile sources. In addition, a deep learning-based model (DeepAerosolClassifier) for classifying aerosol particles was established. The objective of this model was to accomplish source apportionment. During the training process, the model achieved an accuracy of 98.49 % for the validation set and an accuracy of 93.36 % for the testing set. Regarding the model interpretation, ideal spectra were generated using the model, verifying its accurate recognition of the characteristic patterns in the mass spectra. In a practical application, the model performed hourly source apportionment at three specific field monitoring sites. The effectiveness of the model in field measurement was validated by combining traffic flow and spatial information with the model results. Compared with other machine learning methods, our model achieved highly automated source apportionment while eliminating the need for feature selection, and it enables end-to-end operation. Thus, in the future, it can be applied in refined and online source apportionment of particulate matter.

Assessing emission-driven changes in health risk of source-specific PM2.5-bound heavy metals by adjusting meteorological covariates

Heavy metals (HMs) in PM2.5 gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM2.5-bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM2.5 reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020). Sources of PM2.5-bound HMs were identified, with significant contributions from vehicular emissions (on average, 33.4 %), coal combustion (26.3 %), biomass burning (14.1 %), dust (11.7 %), industrial boilers (9.7 %), and shipping emission and sea salt (4.7 %). The source-specific emission-driven health risk can be enlarged or dwarfed by the changing meteorological conditions over time, demonstrating that the actual risks from these source emissions for a given time period may be higher or smaller than those estimated by traditional assessments. Meteorology contributed on average 56.1 % to the interannual changes in source-specific carcinogenic risk of HMs from 2018 to 2019, and 5.6 % from 2019 to 2020. For the source-specific noncarcinogenic risk changes, the contributions were 38.3 % and 46.4 % for the respective periods. Meteorology exerts a more profound impact on daily risk (short-term trends) than on annual risk (long-term trends). Such meteorological impacts differ among emission sources in both sign and magnitude. Reduced health risks of HMs were largely from targeted regulatory measures on sources. Therefore, the meteorological covariates should be considered to better evaluate the health benefits attributable to pollution control measures in health risk assessment frameworks.

Particulate matter emissions from light-duty gasoline vehicles under different ambient temperatures: Physical properties and chemical compositions

Fine particulate matter (PM2.5) from vehicle exhaust is typically emitted at breathing height and thus imposes severe adverse effects on human health and air quality. However, there is currently limited knowledge on the characteristics of PM2.5 in exhaust, specifically its chemical components, at different ambient temperatures. Particulate emissions from typical light-duty gasoline vehicles (LDGVs) were investigated on a chassis dynamometer according to the Worldwide Harmonized Light-Duty Test Cycle at ambient temperatures of 38 °C, 28 °C, 15 °C, 5 °C and - 7 °C. The results showed a significant increase in particulate mass (PM) and particle number (PN) emissions with decreasing ambient temperature, particularly during cold starts below 5 °C. The particle size distributions exhibited distinct bimodal patterns, with accumulation-mode (AM) particles (60-125 nm) dominating the gasoline direct injection (GDI) distribution and nucleation-mode (NM) particles (8-12 nm) dominating the port fuel injection (PFI) distribution. AM particles were more temperature-sensitive than NM particles. Lower temperatures produced higher emissions of elements, carbonaceous components, and large-ring polycyclic aromatic hydrocarbons, while water-soluble ions showed an opposite trend. The total toxic equivalent, primarily influenced by benzo[a]pyrene, was significantly higher at -7 °C. The penalty distribution of LDGV PM and PN, defined by comparing the emissions at the various temperatures to those at regulated temperatures (23-30 °C), exhibited notable temporal heterogeneity (winter > autumn > spring > summer) and spatial heterogeneity (northern China > southern China). These findings are essential for establishing more stringent vehicle emission standards and improving emission models in cold environments.

Source-specific light absorption and radiative effects decreases and indications due to the lockdown

The 'extreme' emission abatement during the lockdown (from the end of 2019 to the early 2020) provided an experimental period to investigate the corresponding source-specific effects of aerosol. In this study, the variations of source-specific light absorption (babs) and direct radiative effect (DRE) were obtained during and after the lockdown period by using the artificial neural network (ANN) and source apportionment environmental receptor model. The results showed that the babs decreased for all sources during the two periods. The most reductions were observed with ∼90% for traffic-related emissions (during the lockdown) and ∼85% for coal combustion (after the lockdown), respectively. Heightened babs (370 nm) values were obtained for coal and biomass burning during the lockdown, which was attributed to the enhanced atmospheric oxidization capacity. Nevertheless, the variations of babs (880 nm) after the lockdown was mainly due to the weakening of oxidation and reduced emissions of secondary precursors. The present study indicated that the large-scale emission reduction can promote both reductions of babs (370 nm) and DRE (34-68%) during the lockdown. The primary emissions decrease (e.g., Traffic emission) may enhance atmosphere oxidation, increase the ultraviolet wavelength light absorption and DRE efficiencies. The source-specific emission reduction may be contributed to various radiation effects, which is beneficial for the adopting of control strategies.

The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin city, China

PM2.5 pollution events are often happened in urban agglomeration locates in mountain-basin regions due to the complex terra and intensive emissions. Source apportionment is essential for identifying the pollution sources and important for developing local mitigation strategies, however, it is influenced by regional transport. To understand how the regional transport influences the atmospheric environment of a basin, we connected the PM2.5 source contributions estimated by observation-based receptor source apportionment and the regional contributions estimated by a tagging technology in the comprehensive air quality model with extensions (CAMx) via an artificial neural network (ANNs). The result shows that the PM2.5 in Xi'an was from biomass burning, coal combustion, traffic related emissions, mineral dust, industrial emissions, secondary nitrate and sulfate. 48.8 % of the PM2.5 in study period was from Xi'an, then followed by the outside area of Guanzhong basin (28.2 %), Xianyang (14.6 %) and Weinan (5.8 %). Baoji and Tongchuan contributed trivial amount. The sensitivity analysis showed that the transported PM2.5 would lead to divergent results of source contributions at Xi'an. The transported PM2.5 from the outside has great a potential to alter the source contributions implying a large uncertainty of the source apportionment introduced when long-range transported pollutants arrived. It suggests that a full comprehension on the impacts of regional transport can lower the uncertainty of the local PM2.5 source apportionment and reginal collaborative actions can be of great use for pollution mitigation.

Spatial and temporal analysis of influential factors on motor vehicle carbon monoxide emissions in China considering emissions trading scheme

The number of cars is increasing every year and the environmental aspects of transport are becoming a hot topic. The spatial and temporal patterns of motor vehicle carbon monoxide (CO) emissions are still unclear due to the unbalanced economic development and heterogeneous geographic conditions of China. With the objective of realizing a reduction in motor vehicle CO emissions, his study explores the transport carbon emission reduction pathways of China from motor vehicle CO emission. Firstly, the entropy method is adopted to comprehensively evaluate the CO emissions from motor vehicles in each province; secondly, the development of a Geographically and Temporally Weighted Regression (GTWR) model facilitates the examination of the spatiotemporal dynamics pertaining to the influencing factors of motor vehicle CO emissions within each province.; finally, the characteristics of motor vehicle CO emissions in ETS pilot areas and non-ETS pilot areas are compared. The results show that: (1) After the completion of the six ETS pilot areas in 2011, the CO emission from motor vehicles is reduced by 18% compared with 2010.(2)The entropy method shows that the largest CO emissions from motor vehicles are from Beijing, Shanghai, Guangdong and other provinces with high economic levels.(3) The results of the GTWR model show that the positive effects of economic level, population size, road mileage intensity and motor vehicle intensity on motor vehicle CO emissions are decreasing year by year. The negative effect of metro line intensity on CO emission decreases year by year. This study can help decision makers to identify the high emission areas, understand the influencing factors, and formulate emission reduction measures to achieve the purpose of carbon emission reduction in transport.

Chemical characteristics of fine tire wear particles generated on a tire simulator

Tire wear is one of the major sources of traffic-related particle emissions, however, laboratory data on the components of tire wear particles (TWPs) is scarce. In this study, ten brands of tires, including two types and four-speed grades, were chosen for wear tests using a tire simulator in a closed chamber. The chemical components of PM2.5 were characterized in detail, including inorganic elements, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and polycyclic aromatic hydrocarbons (PAHs). Inorganic elements, WSIs, OC, and EC accounted for 8.7 ± 2.1%, 3.1 ± 0.7%, 44.0 ± 0.9%, and 9.6 ± 2.3% of the mass of PM2.5, respectively. The OC/EC ratio ranged from 2.8 to 7.6. The inorganic elements were dominated by Si and Zn. The primary ions were SO42- and NO3-, and TWPs were proven to be acidic by applying an ionic balance. The total PAHs content was 113 ± 45.0 μg g-1, with pyrene being dominant. In addition, the relationship between the chemical components and tire parameters was analyzed. Inorganic elements and WSIs in TWPs were more abundant in all-season tires than those in winter tires, whereas the content of PAHs was the opposite. The mass fractions of OC, Si, and Al in the TWPs all showed increasing trends with increasing tire speed grade, but the PAHs levels showed a decreasing trend. Ultimately, to provide more data for further research, a TWPs source profile was constructed considering the tire weighting factor.

A comparative study of life-years lost attributable to air particulate matter in Asia-Pacific and European countries

Air particulate matter (PM) and its harmful effects on human health are of great concern globally due to all-cause and cause-specific mortality impacts across different population groups. While Europe has made significant progress in reducing particulate air pollution-related mortality through innovative technologies and policies, many countries in Asia-Pacific region still rely on high-polluting technologies and have yet to implement effective policies to address this issue, resulting in higher levels of mortality due to air pollution in the region. This study has three aims related to quantifying life-years lost (LYL) attributable to PM, and further separated into ambient PM and household air pollution (HAP): (1) to investigate LYL by causes of death; (2) to compare LYL between Asia-Pacific (APAC) and Europe; and (3) to assess LYL across different socio-demographic index (SDI) countries. The data used come from the Institute for Health Metrics and Evaluation (IHME) and Health Effects Institute (HEI). Our results show that average LYL due to PM in APAC was greater than in Europe, with some Pacific island countries particularly affected by the exposure to HAP. Three quarters of LYL came from premature deaths by ischemic heart disease and stroke, in both continents. There were significant differences between SDI groups for causes of death due to ambient PM and HAP. Our findings call for urgent improvement of clean air to reduce indoor and outdoor air pollution-related mortality in the APAC region.

Heterogeneous characteristics and absorption enhancement of refractory black carbon in an urban city of China

In this study, field measurement was conducted using an integrated online monitoring system to characterize heterogeneous properties and light absorption of refractory black carbon (rBC). rBC particles are mainly from the incomplete combustion of carbonaceous fuels. With the data collected from a single particle soot photometer, thickly coated (BC_kc) and thinly coated (BC_nc) particles are characterized with their lag times. With different responses to the precipitation, a dramatical decline of 83 % in the number concentration of BC_kc is shown after rainfall, while that of BC_nc decreases by 39 %. There is a contrast in core size distribution that BC_kc is always with larger particle sizes but has smaller core mass median diameters (MMD) than BC_nc. The mean rBC-containing particle mass absorption cross-section (MAC) is 6.70 ± 1.52 m² g^-1, while the corresponding rBC core is 4.90 ± 1.02 m² g^-1. Interestingly, there are wide variations in the core MAC values which range by 57 % from 3.79 to 5.95 m² g^-1, which are also closely related to those of the whole rBC-containing particles with a Pearson correlation of 0.58 (p < 0.01). Errors would be made if we eliminate the discrepancies and set the core MAC as a constant when calculating absorption enhancement (E_abs). In this study, the mean E_abs is 1.37 ± 0.11 while the source apportionment shows that there are five contributors of E_abs including secondary aging (37 %), coal combustion (26 %), fugitive dust (15 %), biomass burning (13 %) and traffic-related emissions (9 %). Secondary aging is found to be the highest contributor due to the liquid phase reactions in formations of secondary inorganic aerosol. Our study characterizes property diversities and provides insights into the sources impacting the light absorption of rBC and will be helpful for controlling it in the future.

Pre- and postnatal particulate matter exposure and blood pressure in children and adolescents: A systematic review and meta-analysis

BACKGROUND

Early life is a susceptible period of air pollution-related adverse health effects. Hypertension in children might be life-threatening without prevention or treatment. Nevertheless, the causative association between environmental factors and childhood hypertension was limited. In the light of particulate matter (PM) as an environmental risk factor for cardiovascular diseases, this study investigated the association of pre- and postnatal PM exposure with blood pressure (BP) and hypertension among children and adolescents.

METHOD

Four electronic databases were searched for related epidemiological studies published up to September 13, 2022. Stata 14.0 was applied to examine the heterogeneity among the studies and evaluate the combined effect sizes per 10 μg/m³ increase of PM by selecting the corresponding models. Besides, subgroup analysis, sensitivity analysis, and publication bias test were also conducted.

RESULTS

Prenatal PM_2.5 exposure was correlated with increased diastolic blood pressure (DBP) in offspring [1.14 mmHg (95% CI: 0.12, 2.17)]. For short-term postnatal exposure effects, PM_2.5 (7-day average) was significantly associated with systolic blood pressure (SBP) [0.20 mmHg (95% CI: 0.16, 0.23)] and DBP [0.49 mmHg (95% CI: 0.45, 0.53)]; and also, PM₁₀ (7-day average) was significantly associated with SBP [0.14 mmHg (95% CI: 0.12, 0.16)]. For long-term postnatal exposure effects, positive associations were manifested in SBP with PM_2.5 [β = 0.44, 95% CI: 0.40, 0.48] and PM₁₀ [β = 0.35, 95% CI: 0.19, 0.51]; DBP with PM₁ [β = 0.45, 95% CI: 0.42, 0.49], PM_2.5 [β = 0.31, 95% CI: 0.27, 0.35] and PM₁₀ [β = 0.32, 95% CI: 0.19, 0.45]; and hypertension with PM₁ [OR = 1.43, 95% CI: 1.40, 1.46], PM_2.5 [OR = 1.65, 95% CI: 1.29, 2.11] and PM₁₀ [OR = 1.26, 95% CI: 1.09, 1.45].

CONCLUSION

Both prenatal and postnatal exposure to PM can increase BP, contributing to a higher prevalence of hypertension in children and adolescents.

Real-world emission for in-use non-road construction machinery in Wuhan, China

Non-road construction machinery (NRCM) emissions pollutants significantly impact air quality. Six typical NRCM (2 excavators, 3 loaders, and 1 forklift) are analyzed based on a portable emission measurement system (PEMS) in Wuhan to estimate the real-world emission characteristics and chemical composition of PM_2.5 of NRCM. The results show that the fuel-based average emission factors (EFs) of carbon monoxide (CO), hydrocarbon (HC), nitrogen oxides (NO_x), and particulate matter (PM) are 19.4 ~ 35.7 g kg^-1 fuel, 2.9 ~ 7.9 g kg^-1 fuel, 57.5 ~ 95.3 g kg^-1 fuel, and 1.8 ~ 2.6 g kg^-1 fuel for the tested NRCM. The high NO_x EF implies that the regulation of NO_x emission in Wuhan should be strengthened. In addition, the PM_2.5 chemical composition profiles for NRCM show that the PM_2.5 emitted from NRCM is dominated by organic carbon and elemental carbon (56.11 ~ 73.85%), followed by water-soluble ions (WSIs, 1.47 ~ 3.46%), and elements (0.16 ~ 0.41%). The major WSIs species are Cl^-, Na⁺ and NO₃^-, and the major elements are Ca, Na, and K, which are important markers for PM_2.5 source analysis. The results of EFs and chemical composition emission characteristics of NRCM tailpipe pollutants obtained in the real-world can provide essential data support for accurately establish of emission inventory of non-road mobile sources in Wuhan.

Toxicological effects of fresh and aged gasoline exhaust particles in Hong Kong

Exhaust emissions from gasoline vehicles are one of the major contributors to aerosol particles observed in urban areas. It is well-known that these tiny particles are associated with air pollution, climate forcing, and adverse health effects. However, their toxicity and bioreactivity after atmospheric ageing are less constrained. The aim of the present study was to investigate the chemical and toxicological properties of fresh and aged particulate matter samples derived from gasoline exhaust emissions. Chemical analyses showed that both fresh and aged PM samples were rich in organic carbon, and the dominating chemical species were n-alkane and polycyclic aromatic hydrocarbons. Comparisons between fresh and aged samples revealed that the latter contained larger amounts of oxygenated compounds. In most cases, the bioreactivity induced by the aged PM samples was significantly higher than that induced by the fresh samples. Moderate to weak correlations were identified between chemical species and the levels of biomarkers in the fresh and aged PM samples. The results of the stepwise regression analysis suggested that n-alkane and alkenoic acid were major contributors to the increase in lactate dehydrogenase (LDH) levels in the fresh samples, while polycyclic aromatic hydrocarbons (PAHs) and monocarboxylic acid were the main factors responsible for such increase in the aged samples.

Specific size distributions of elemental and organic carbon, and polycyclic aromatic hydrocarbons emitted from petrol engine using two fuel grades

The most common commercial oils in the Chinese market are two petrol types with octane levels of 93 and 97. To determine the source spectrum of air pollutant emissions, we herein investigated the specific emission sizes of the total suspended particles (TSP), total carbon (TC), elemental carbon (EC), organic carbon (OC), and polycyclic aromatic hydrocarbons (PAHs) from a petrol engine fueled with 93# and 97# petrol in 2016 (based on Chinese national IV gasoline standard). We found that while 93# emitted a higher TSP content, 97# emitted greater TC, EC, OC, and PAHs. The highest carbon contents were found in the < 0.25 µm and 0.44-1.0 µm size fractions for the 93# and 97# petrol, respectively. OC content showed a significant positive correlation with EC, and EC2 (at 740 ℃) was the main carbon fragment in both petrol exhausts. The highest PAH content occurred in the 0.25-0.44 µm size-bin, differing from the results for TC, EC, and OC, and medium molecular weight (4 rings) PAHs were the primary component in the emissions. These results indicate that fuel composition and octane sensitivity have a prominent effect on the size distributions of TC (including EC, OC, and PAHs). Thus, more studies on the carbon content at specific emission sizes in petrol exhaust should be conducted to clarify the main factors impacting these variations.

Black carbon and elemental characterization of PM2.5 in dense traffic areas in two cities in Fiji, a Small Island Developing State

PM_2.5 characterizations are essential in understanding its impact on the health of the exposed population. Sampled PM_2.5 by Mani et al. (2020) was characterized to determine atmospheric metal concentration and inhalation health risk in Suva and Lautoka Cities, the only two cities in Fiji and one of the largest in the South Pacific Islands. Twenty-two elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Pb, S, Si, Sr, V, Zn) were analyzed using ICP-OES. Black Carbon (BC) sampling was also done at three different sites in Suva City, namely, Fiji National University Samabula Intersection site, Suva City Bus Station site and the Reservoir Road Community Settlement Site as well as at Lautoka City Bus Station. Mean BC concentrations over the sampling period were found to be 3.9 ± 2.9 (median = 3.3 μg/m³), 2.6 ± 2.7 μg/m³ (median = 1.7 μg/m³), 2.4 ± 2.3 μg/m³ (median = 1.7 μg/m³) and 4.0 ± 4.7 μg/m³ (median = 2.4 μg/m³) respectively. Health risk assessments (Carcinogenic Risk (CR) and Non-Carcinogenic Risk (HQ)) were also done to assess the risk of inhalation exposure in adults and children. The Hazard Index for children in Lautoka (HI = 1.03) was found to slightly exceed the safe level of 1. This study provides the first inventory of atmospheric particulate bound metal concentrations and diurnal BC profiles in Fiji and informs policy makers and scientists for further studies.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM_2.5 in typical industrial areas of North China, manual sampling and analysis of PM_2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM_2.5 was 53.4 ± 43.9 μg·m^-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO₃^- ion, at 14.6 ± 14.2 μg·m^-3, followed by organic carbon (OC), SO₄^2-, and NH₄⁺, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m^-3, respectively. The concentrations of OC, NO₃^-, and SO₄^2- were highest in winter and lowest in summer, whereas the NH₄⁺ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO₂ emission and conversion rates in winter, resulting in the SO₄^2- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m^-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m^-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM_2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM_2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Source apportionment of PM2.5 in Seoul, South Korea and Beijing, China using dispersion normalized PMF

East Asian countries experience severe air pollution owing to their rapid development and urbanization induced by substantial economic activities. South Korea and China are among the most polluted East Asian countries with high mass concentrations of PM_2.5. Although the occurrence of transboundary air pollution among neighboring countries has been recognized for a long time, studies involving simultaneous ground-based PM_2.5 monitoring and source apportionment in South Korea and China have not been conducted to date. This study performed simultaneous daily ground-based monitoring of PM_2.5 in Seoul and Beijing from January to December 2019. The mass concentrations of PM_2.5 and its major chemical components were analyzed simultaneously during 2019. Positive matrix factorization (PMF) as well as dispersion normalized PMF (DN-PMF) were utilized for the source apportionment of ambient PM_2.5 at the two sites. 23 h average ventilation coefficients were applied for daily PM_2.5 chemical constituents' data. Nine sources were identified at both sites. While secondary nitrate, secondary sulfate, mobile, oil combustion, biomass burning, soil, and aged sea salt were commonly found at both sites, industry/coal combustion and incinerator were identified only at Seoul and incinerator/industry and coal combustion were identified only at Beijing. Reduction of the meteorological influences were found in DN-PMF compare to C-PMF but the effects of DN on mobile source were reduced by averaging over the 23 h sampling period. The DN-PMF results showed that Secondary nitrate (Seoul: 25.5%; Beijing: 31.7%) and secondary sulfate (Seoul: 20.5%; Beijing: 17.6%) were most dominant contributors to PM_2.5 at both sites. Decreasing secondary sulfate contributions and increasing secondary nitrate contributions were observed at both sites.

Global association between atmospheric particulate matter and obesity: A systematic review and meta-analysis

BACKGROUND

Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. Although several studies have shown a link between particulate pollution and obesity, the conclusions are still inconsistent.

METHODS

We conducted a systematic review and meta-analysis to pool the effect of PM exposure on obesity. Five databases (including PubMed, Web of Science, Scopus, Embase, and Cochrane) were searched for relevant studies up to Jan 2022. Adjusted risk ratio (RR) with corresponding 95% confidence interval (CI) were retrieved from individual studies and pooled with random effect models by STATA software. Besides, we tested the stability of results by Egger's test, Begg's test, funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. The NTP-OHAT guidelines were followed to assess the risk of bias. Then the GRADE was used to evaluate the certainty of evidence.

RESULTS

26 studies were included in this meta-analysis. 19 studies have shown that PM_2.5 can increase the risk of obesity per 10 μg/m³ increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM₁₀ increase the risk of obesity per 10 μg/m³ increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM_2.5 increases the risk of obesity in children (RR: 1.06, 95% CI: 1.02-1.11). And we explored the source of heterogeneity by subgroup analysis, which suggested associations between PM and obesity tended to vary by region, age group, participants number, etc. The analysis results showed publication bias and other biases are well controlled, but most certainties of the evidence were low, and more research is required to reduce these uncertainties.

CONCLUSION

Exposure to PM_2.5 and PM₁₀ with per 10 μg/m³ increment could increase the risk of obesity in the global population.

Compositions, Sources, and Aging Processes of Aerosol Particles during Winter Hazes in an Inland Megacity of NW China

As one of the largest inland megacities in Northwest (NW) China, Xi’an has been facing serious regional haze frequently, especially during winter. The composition of aerosols in Xi’an is highly complex due to its unique basinal topography and unique meteorological conditions. In this study, we characterized the morphology, size, and composition of individual aerosol particles collected during regional haze events at an urban site in Xi’an using Transmission Electron Microscopy (TEM) coupled with Energy-Dispersive X-ray Spectrometry (EDX). Six types of particles were identified based on their morphology and chemical composition, including organic (41.88%), sulfate (32.36%), soot (8.33%), mineral (7.91%), K-rich (5.13%), and fly ash particles (4.49%). These results demonstrate that the organic particles made a larger contribution to haze formation than the secondary inorganic particles during the sampling period. Size distribution and dominance suggest that organic and sulfate particles exert major control on the variation trends of particle size in haze. The coating thickness of organic-cored particles was about 369 nm and that of sulfate-cored particles was about 322 nm, implying that the organic particles were more aged than the sulfate particles. The results presented in this study provide further insights into understanding haze particle formation.

Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method

Our study implies the importance of exhaust and non-exhaust emissions in a highway road tunnel, which is crucial to assess their impacts on air quality, human health, climate and developing functional methods for controlling. The total suspended particulates (TSP) and road dust (RD) samples were collected by PUF samplers and manually sweeping, respectively. Campaigns were performed in the summer and winter of 2014 in a highway road tunnel in Bolu, Turkey. Chemical analyses were presented to characterize the contents of organic carbon (OC) fractions (OC1,2,3,4), elemental carbon (EC) fractions (EC1,2,3,4,5,6), polycyclic aromatic hydrocarbons (PAHs) and metals (Al, Ba, Ca, Cu, Mg, Mn, Pb, Sr, Cr and Fe) in the collected TSP and RD samples. Positive matrix factorization (PMF) and orthogonal (Deming) regression analysis were applied to find out the exhaust and non-exhaust vehicle emissions of metal and carbonaceous species in the tunnel. The results showed that the identified source profiles included resuspended road dust (43%), non-exhaust emissions (37%), diesel exhaust emissions (13%), and gasoline exhaust emissions (7%). The relationship between emission markers of metal species and EC carbon fractions was supported by correlation studies. Among these EC fractions, EC4 and EC2 were the most abundant fractions in aerosol and RD samples, respectively and so they highly represented the diesel and non-exhaust emissions. Besides, the EC1 fraction was the indicator of gasoline-fueled emissions. Lower EC1 and higher soot-EC contribution obtained in tunnel aerosol (AS) samples showed the dominance of diesel-fueled vehicles in the tunnel. The data represented herein would help to identify the characteristic of vehicle emissions.

Spatial Distribution of Primary and Secondary PM2.5 Concentrations Emitted by Vehicles in the Guanzhong Plain, China

With the rapid increase of the vehicle population in the Guanzhong Plain (GZP), the fine particulate matter (PM2.5) emitted by vehicles has an impact on regional air quality and public health. The spatial distribution of primary and secondary PM2.5 concentrations from vehicles in GZP in January and July 2017 was simulated in this study by using the Weather Research and Forecasting (WRF) model and the California Puff (CALPUFF) air quality model. The contributions of vehicle-related emission sources to total PM2.5 concentrations were also calculated. The results show that although the emissions of primary PM2.5, NOx, and SO2 in July were greater than those in January, the hourly average concentrations of primary and secondary PM2.5 in January were significantly higher than those in July. The highest concentrations of primary and total PM2.5 were mostly located in the urban areas of Xi’an and Xianyang in the central region of GZP. The contributions of exhaust emissions, secondary nitrates, brake wear, tire wear, and secondary sulfate to the total PM2.5 concentrations in GZP were 50.37%, 34.76%, 10.79%, 4.06%, and 0.04% in January and 71.91%, 11.14%, 11.89%, 5.03%, and 0.03% in July, respectively. These results will help us to further control PM2.5 pollution caused by vehicles.

Characteristics of PM10 Levels Monitored in Bangkok and Its Vicinity Areas, Thailand

The ambient air concentrations of PM10 were observed in Bangkok and its vicinity areas including Nonthaburi and Nakhon Pathom, Thailand. The selected study areas are located near heavy-traffic roads with a high concentration of traffic-related air pollution. The ambient air samples were collected in the winter season (October 2019 to February 2020). The highest average level of PM10 was found in Nonthaburi (66.63 µg/m3), followed by Bangkok (56.79 µg/m3) and Nakhon Pathom (40.18 µg/m3), respectively. The morphology of these particles is typically spherical and irregular shape particles. At the sampling site in Bangkok, these particles are primarily composed of C, O, and Si, and a certain amount of metals such as Fe, Cu, and Cr. Some trace amount of other elements such as Ca, Na, and S are present in minor concentration. The particles collected from Nakhon Pathom and Nonthaburi sampling sites contain the main abundant elements C, O, and Si, followed by Cu, Cr, S, Fe, Ca, and Na, respectively. These particles are an agglomeration of carbon particles resulting from the incomplete combustion of organic matter. Their origin may be associated with road dust, vehicle emission, and the erosion of building products. It can be noted that the levels and characteristics of PM10 are key factors in understanding the behavior of the particles in not only atmospheric visibility but also human health risks.

Chemical characterization of PM2.5 emitted from China IV and China V light-duty vehicles in China

This study reported the emission factors (EFs) and detailed chemical compositions of PM_2.5 collected from China IV and China V light-duty vehicles (LDVs) through dynamometer test. The China IV LDVs containing 4 gasoline vehicles (GVs) and 4 natural gas vehicles (NGVs) had port fuel injection (PFI) engines, while the China V LDVs included 2 GVs with PFI engines and 2 GVs with gasoline direct injection (GDI) engines. The average EFs of PM_2.5 were 1.90 ± 0.70 mg km^-1, 1.44 ± 0.29 mg km^-1, and 0.56 ± 0.05 mg km^-1 for China IV GVs, China IV NGVs, and China V GVs, respectively. PM_2.5 profiles of LDVs were characterized by abundant carbon species (60.59-68.58%) with low amounts of water soluble ions (WSIs, 6.96-16.37%) and elements (5.20-7.53%). In general, the EFs of PM_2.5 constituents including organic carbon (OC), elemental carbon (EC), WSIs, and elements were reduced obviously by strengthening emission standards from China IV to China V. While the contributions of most WSIs and elements to PM_2.5 increased as vehicle technology improved. Furthermore, the EFs of PM_2.5 components from China IV LDVs also decreased when shifting fuels from gasoline to natural gas. While the fractions of OC, WSIs and most elements in PM_2.5 increased due to the highest reduction rate of EC mass. For China V LDVs, GDI vehicles emitted less OC but more EC compared to PFI vehicles, and the EFs of most WSIs and elements also increased. Overall, GDI vehicles exhibited lower fractions OC and WSIs but higher contents of EC and elements in PM_2.5. Besides, PM_2.5 and its chemical species were heavily dependent on vehicle's driving patterns. The average EFs of PM_2.5 components under aggressive driving pattern increased significantly compared to those under moderate driving pattern.

Air pollutants and their degradation of a historic building in the largest metropolitan area in Latin America

Historic buildings that comprise the cultural heritage of humanity are in need of preservation on a worldwide scale in regard to degradation resultant from atmospheric pollutants. The Brazilian Public Market, located in the historic center of the mega city of São Paulo, is the object of this research, due to its representation of historical Brazilian architecture. The general objective of this manuscript is to analyze the influence of air pollutants on the degradation of the historic São Paulo Public Market in the city of São Paulo, Brazil. Methodologically, between May 2018 and April 2019, samples of sedimented dust were collected at five points on the side walls of the market's historic structure, for the analysis of accumulated ultrafine particles (UFPs) and nanoparticles (NPs). A total of 20 samples of particulate matter were collected using self-made passive samplers (SMPSs). Using SMPSs, 12 months of accumulation and deposition were used to sample the atmospheric PM1. The results demonstrate the presence of dangerous elements such as: As, Cd, Cr, Pb, Zn. Note that EDS coupled with microscopy techniques, points out the risks to human health, due to the presence of these dangerous elements that accumulate in the building's structure. The results show that 85% of the NPs sampled contained Pb, and 56% contained Pb and Ti, which are harmful to both historic buildings and human health. Air pollution enables the further deterioration of the São Paulo Public Market, which is in need of restoration.

PM2.5-Bound Heavy Metals in Southwestern China: Characterization, Sources, and Health Risks

The health risks of PM2.5-bound heavy metals have attracted extensive attention recently. In order to evaluate those deleterious effects on human health more accurately, and to propose proper measures to reduce health risks of air pollution, the conduction of a source-specific health risk assessment is necessary. Based on daily collected PM2.5 samples at different functional sites during winter 2019 in a megacity Chongqing, China, combining source apportionment results from PMF and health risk assessment from the U.S. EPA, the source-specific health risks from PM2.5-bound heavy metals were given. Six types of PM2.5 sources have been identified, coal burning (25.5%), motor vehicles (22.8%), industrial emissions (20.5%), biomass burning (15.9%), dust (7.8%), and ship emissions (7.5%). Results showed that the total hazard quotient (HQ) was 0.32 and the total carcinogenic risks (CR) were 2.09 × 10−6 for children and 8.36 × 10−6 for adults, implying certain risks for local residents. Industrial emissions related with Cr posed both the highest carcinogenic risk and noncarcinogenic risk (contributing 25% CR and 36% HQ). Coal combustion (associated with Cr, As, and Mn) contributed 15.46% CR and 20.64% HQ, while biomass burning and motor vehicles shared 19.99% and 19.05% of the total CR, respectively. This work indicated that health risks of air pollution sources were the combined effects of the source contribution and chemical components. In order to control the health risks of PM2.5 to the local residents, the priority of targeted emission sources should be adopted for industrial emissions, biomass burning, vehicle emissions, and coal combustion sources.

Real-World Vehicle Volatile Organic Compound Emissions and Their Source Profile in Chengdu Based on a Roadside and Tunnel Study

With the continuous progress of air pollution prevention and control in China, the study of the emission characteristics of vehicles has become increasingly important. An in situ experiment was performed in the Tianfu tunnel in Chengdu to determine the vehicle emissions of volatile organic compounds (VOCs). A total of 50 species of VOCs were quantified in the tunnel, with total concentrations in the range of 32.25–162.18 ppbv in the entrance and 52.90–233.92 ppbv in the exit, respectively. Alkanes were the most abundant group, followed by alkenes, aromatic hydrocarbons, oxygenated VOCs, alkynes and chlorocarbons. The general emission factors of the measured VOCs ranged from 141.71 mg veh−1 km−1 to 236.12 mg veh−1 km−1, and the average ± std was 177.31 ± 24.59 mg veh−1 km−1. The emission factors of diesel-fuelled vehicles, gasoline-fuelled vehicles and natural gas-fuelled vehicles were estimated based on linear regression analysis, with values of 272.39 ± 191.17 mg veh−1 km−1, 185.08 ± 12.85 mg veh−1 km−1 and 158.72 ± 3.21 mg veh−1 km−1, respectively. The results of roadside experiments indicate that the roadside ambience atmosphere contains many species characterized with vehicle emission features. Especially, there were fuel evaporation emission related substances, which were higher in content than tunnel samples.

Effects of Ignition Timing on Combustion Characteristics of a Gasoline Direct Injection Engine with Added Compressed Natural Gas under Partial Load Conditions

The gasoline/natural gas dual-fuel combustion mode has been found to have unique advantages in combustion. The ignition timing has a significant impact on the combustion characteristics of gasoline engines. Thus, here we study the combustion characteristics of gasoline/natural gas dual-fuel combustion mode to determine the details of their respective advantages under cooperative combustion. A direct-injection turbocharged gasoline engine was modified, and an engine experimental platform was built for the coordinated control of gasoline direct-injection and natural gas port injection. A low-speed and low-load operating point was selected, and the in-cylinder pressure, heat release rate, pressure rise rate, combustion temperature, ignition delay, and combustion duration under the coordinated combustion of gasoline and natural gas dual fuel at the ignition moment were studied through bench tests among other typical combustion parameters. The results show that with the increase of the ignition advance angle, the maximum cylinder pressure, heat release rate, pressure rise rate, and maximum combustion temperature increase. The ignition advance angle is 28°CA-BTDC, and PES40 has the best fuel synergy effect and the best power performance improvement. The effect of the advance of the ignition advance angle on the ignition delay and the combustion duration reaches the peak at 20°CA-BTDC–22°CA-BTDC, and the improvement of the two periods is more significant at PES60.

Morphology and composition of particles emitted from conventional and alternative fuel vehicles

Size, morphology, and composition of airborne particles strongly affect human health and visibility, precipitation, and the kinetic characteristics of particles. In this study, the morphology and chemical composition of particles emitted from conventional (diesel and gasoline) and alternative (CNG and methanol) fuel vehicles were characterized through scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The SEM images revealed that the size of primary particles (without agglomeration) was approximately 10 nm in the exhaust from all the tested vehicles. The particles emitted from gasoline vehicle (GV), CNG vehicle (CNGV), and methanol vehicle (MV) had the same median diameter, 62 nm, which was smaller than those from heavy diesel vehicle (HDV) and light diesel vehicle (LDV). Soot was observed in the HDV, LDV, and GV samples but not in the CNGV and MV. The fractal dimension, which was used to quantify the degree of irregularity of soot, was 1.752 ± 0.014, 1.789 ± 0.076, and 1.769 ± 0.006 in the exhaust from HDV, LDV, and GV samples, respectively. The particles discharged by all tested vehicles contained the elements C, O, Fe, and Na. The main element in the samples of HDV, LDV, and GV was C, while O was the main element in the samples of alternative fuel vehicles. The profiles of minor elements were more complex in the emissions of alternative fuel vehicles than those in the emissions of conventional fuel vehicles. The results improved our understanding of the morphology and elemental composition of particles emitted from vehicles powered by diesel, gasoline, CNG, and methanol.

Determination of trace elements in the nanometer, ultrafine, fine, and coarse particulate matters in an area affected by light vehicular emissions in the city of Rio de Janeiro

The objective of this work was to determine the trace element composition in the nanometric, ultrafine, fine, and coarse particulate matters (PM) found in the surrounding area of the UERJ Chemical Technology Applications Institute, using a MSP 120 MOUDI II cascade impactor. After acid extraction, the elements were analyzed via ICP-OES, and the results obtained were treated statistically. The average concentrations of the nanometric, ultrafine, fine, and coarse particles were 11.8, 8.2, 7.7, and 7.1 μg m^-3, respectively. The total average concentration of Cd, Ni, Pb, Cr, and Fe complied with the air quality standards recommended by US EPA and WHO. When compared with other locations, the PM fractions found in this study were 1.1 to 346 times greater. Through the calculation of Pearson's correlation coefficient, a high correlation was observed between most of the trace elements studied, especially in the ultrafine, fine, and coarse fractions, which suggests that they are probably caused by the same sources of vehicular emissions. The enrichment factor was calculated to estimate the possible sources. Since Cd, Cu, Pb, and Mo are enriched by anthropic sources, they are probably influenced by vehicular emissions, in particular the wear on tires and brakes, and the burning of fossil fuel.

Revisiting the impact of vehicle emissions and other contributors to air pollution in urban built-up areas: A dynamic spatial econometric analysis

Whether vehicle emissions are the primary source of PM_2.5 in urban China remains controversial, which may be attributable to the insufficient consideration of the spatial autocorrelation and the spatial spillover effects of PM_2.5. We employ data from built-up areas of 285 prefecture-level cities in China spanned 2001-2016 and dynamic spatial panel data analysis to resolve this controversy. Our results show that the direct and indirect effects of vehicles on PM_2.5 concentration (annual mean and spatial variation within the city) in urban China are not significant in the short- and long-term. Alternatively, SO₂ emission directly increases the mean and spatial variation of PM_2.5 within the city in the short- and long-term. Short-term direct and indirect positive association and long-term indirect positive association are found relative to economic growth and PM_2.5. Population density increases PM_2.5 directly and indirectly in the short-term and yet, directly decreases and indirectly increases PM_2.5 in the long-term. In the short- and long-term, the spatial spillover effect of secondary industry increases PM_2.5, and industry also directly increases the spatial variation of PM_2.5 within the city. Although real estate investment directly increases PM_2.5 in the long-term, the spatial spillover effect of investment reduces PM_2.5 in the short- and long-term. Our results show that other factors, rather than vehicle emissions, are the major contributors to PM_2.5 in urban China. Furthermore, the Environmental Kuznets Curve hypothesis does not apply to the relationship between economic growth and PM_2.5 proliferation in urban China. When tackling air pollution, owing to the significant spatial spillover of PM_2.5 that is driven by multiple contributing factors, short- and long-term inter-regional coordination is required to achieve an effective positive outcome.

Chemical characterization of PM2.5 emissions and atmospheric metallic element concentrations in PM2.5 emitted from mobile source gasoline-fueled vehicles

Fine particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5), particularly from the in-use gasoline-fueled vehicles, is a leading air quality pollutant and the chemical composition of PM_2.5 is vital to the practical issues of climate change, health effects, and pollution control policies, inter alia. These atmospheric fine particulate matters (PM_2.5) emitted from the exhausts of mobile source gasoline-fueled vehicles constitute substantial risks to human health through inhalation, and most importantly, affect urban air quality. Therefore, in order to explicitly determine the inhalation risks of PM_2.5 which could potentially contain a significant amount of chemicals and metallic elements (MEs) concentration, we investigated the chemical composition (comprising of carbonaceous species and metallic elements) of PM_2.5 emissions from mobile source gasoline-fueled vehicles. To further examine the chemical composition and metallic elements concentration in PM_2.5 from the exhausts of mobile source gasoline-fueled vehicles, we systematically investigated PM_2.5 emission samples collected from the exhausts of fifteen (15) mobile source gasoline-fueled vehicles. Our study has equally also determined the chemical compositions based on carbonaceous species (organic carbon - OC and elemental carbon - EC). Furthermore, the concentrations of PM_2.5 and metallic elements (Ca, Al, Zn, K, Ca, Fe, Mg and Cr) in PM_2.5 were analyzed with the help of Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The details of the tested gasoline-fueled vehicles cover the model years, consisting of the vehicles registered from 2000 to 2017 from several vehicle manufacturers (or brands) with various running mileages ranging from 123.4 to 575,844 km (average 123,105 km). Our results established that elemental carbon (EC) and organic carbon (OC) were the most significant concentrations of carbonaceous species. The concentration of metallic elements in PM_2.5 and chemical characterization were studied by their relationship with atmospheric PM_2.5 and the results showed that the metallic elements concentration in PM_2.5 were in descending order as follows: Ca > Al > Zn > K > Fe > Mg > Cr. These results will help us to further understand how PM_2.5 emissions from the exhausts of in-use gasoline-fueled vehicles contribute to both chemical and atmospheric metallic elements concentration in the ambient air.

Size-segregated carbonaceous aerosols emission from typical vehicles and potential depositions in the human respiratory system

Particles emitted from five typical types of vehicles (including light-duty gasoline vehicles, LDG; heavy-duty gasoline vehicles, HDG; diesel buses, BUS; light-duty diesel vehicles, LDD and heavy-duty diesel vehicles, HDD) were collected with a dilution sampling system and an electrical low-pressure impactor (ELPI+, with particle sizes covering fourteen stages from 6 nm to 10 μm) on dynamometer benches. The mass concentrations and emission factors (EF) for organic carbon (OC) and elemental carbon (EC) were obtained with a DRI Model 2001 thermal/optical carbon analyzer. A respiratory deposition model was used to calculate the deposition fluxes of size-segregated carbonaceous aerosols in human respiratory system. Results indicated that the OC produced from LDG mainly existed in the size range of 2.5-10 μm, while EC from HDG enriched in 0.94-2.5 μm. For diesel vehicles, both OC and EC concentrations peaked at 0.094-0.25 μm. The OC/EC ratios for PM_2.5 varied from different types of vehicles, from 0.61 to 8.35. The primary emissions from LDD and HDD exhibited high OC/EC ratios (>3), suggesting that using OC/EC higher than 2 to indicate the formation of secondary organic aerosol (SOA) was not universal. The emission factors for OC and EC of LDG (HDG) in PM₁₀ were 1.78 (3.14) mg km^-1 and 0.88 (4.32) mg km^-1, respectively. The OC2 and OC3 were the main section (over 60%) of OC emitted from all the five types of vehicles. EC1 was the most abundant EC fraction of LDG (76.9%), while EC2 dominated for other types of vehicles (more than 62%). About 60% of the OC in ultrafine particles could be deposited in the alveoli. Diesel EC mainly could be deposited in the alveolar region. It is necessary to control the emission of ultrafine particles and diesel EC.

Characterization and Quantification of Ultrafine Particles and Carbonaceous Components from Occupational Exposures to Diesel Particulate Matter in Selected Workplaces

Questions still exist regarding which indicator better estimates worker's exposure to diesel particulate matter (DPM) and, especially for ultrafine particles (UFP), how exposure levels and the characteristics of the particles vary in workplaces with different exposure conditions. This study aimed to quantify and characterize DPM exposures in three workplaces with different exposure levels: an underground mine, a subway tunnel, and a truck repair workshop. The same sampling strategy was used and included measurements of the particle number concentration (PNC), mass concentration, size distribution, transmission electron microscopy (TEM), and the characterization of carbonaceous fractions. The highest geometric means (GMs) of PNC and elemental carbon (EC) were measured in the mine [134 000 (geometric standard deviation, GSD = 1.5) particles cm-3 and 125 (GSD = 2.1) µg m-3], followed by the tunnel [32 800 (GSD = 1.7) particles cm-3 and 24.7 (GSD = 2.4) µg m-3], and the truck workshop [22 700 (GSD = 1.3) particles cm-3 and 2.7 (GSD = 2.4) µg m-3]. This gradient of exposure was also observed for total carbon (TC) and particulate matter. The TC/EC ratio was 1.4 in the mine, 2.5 in the tunnel and 8.7 in the workshop, indicating important organic carbon interference in the non-mining workplaces. EC and PNC were strongly correlated in the tunnel (r = 0.85; P < 0.01) and the workshop (r = 0.91; P < 0.001), but a moderate correlation was observed in the mine (r = 0.57; P < 0.05). Results from TEM showed individual carbon spheres between 10 and 56.5 nm organized in agglomerates, while results from the size distribution profiles showed bimodal distributions with a larger accumulation mode in the mine (93 nm) compared with the tunnel (39 nm) and the truck workshop (34 nm). In conclusion, the composition of the carbonaceous fraction varies according to the workplace, and can interfere with DPM estimation when TC is used as indicator. Also, the dominance of particles <100 nm in all workplaces, the high levels of PNC measured and the good correlation with EC suggest that UFP exposures should receive more attention on occupational routine measurements and regulations.

PM2.5-inducible long non-coding RNA (NONHSAT247851.1) is a positive regulator of inflammation through its interaction with raf-1 in HUVECs

Several studies have demonstrated that PM_2.5 inhalation is associated with an increased risk of cerebrovascular disease (CVD), in which inflammation plays an important role. The mechanisms of this disease are not fully understood to date. Long non-coding RNAs (lncRNAs) are involved in many pathophysiological processes, such as immune responses; however, their functions associated with inflammation are largely unexplored. High-throughput sequencing assay and obtained numerous lncRNAs that altered the expression in response to PM_2.5 treatment in HUVECs. NONHSAT247851.1 was also identified, which was significantly up-regulated to control the expression of immune response genes. Mechanistically, the results indicated that NONHSAT247851.1 knockdown reduced the expression of IL1β. In study, we investigated NONHSAT247851.1 as a promoter in regulating immune response genes via binding with raf-1 to regulate the phosphorylation level of p65 protein in HUVECs. The data collected suggests that NONHSAT247851.1 regulates inflammation via interaction with raf-1 to control the inflammatory expression in PM_2.5 exposure.