In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) ...concentrations data of air pollutants including particulate matter (PM2.5 and PM10) and gaseous pollutants (SO2, NO2, CO, and O3) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) μg m−3 for PM2.5, 107.8 (91.1, 85.7) μg m−3 for PM10, 54.8 (56.2, 57.2) μg m−3 for O3_8 h, 39.6 (33.3, 33.4) μg m−3 for NO2, 34.1 (26, 21.9) μg m−3 for SO2, 1.2 (1.1, 1.1) mg m−3 for CO, and 0.60 (0.59, 0.58) for PM2.5/PM10, respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM2.5, PM10, NO2, and SO2 standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM2.5, PM10, O3_8 h, NO2, SO2, CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O3 (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NOx controls were more beneficial than SO2 controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards.
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•Air pollution in China were characterized with three-year observed data.•Population-weighted-average concentrations in provinces, mega-city clusters and regions were calculated.•The complex air pollution caused by PM and O3 is an emerging problem in Chinese mega-city clusters.•Spatial distributions of annual average air pollutants in China were conducted.
Benzothiazole (BT) and its derivates are commonly used as vulcanization accelerators in rubber production. Information on the occurrence of BTs in road dust (RD) and on human exposure to these ...compounds is very limited. BT and its six derivates in tire wear particles (TWPs) and RD were determined in this study. Samples were extracted using solid-liquid extraction, purified by a HLB SPE column, and determined by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). All seven BTs were found in 17 TWPs samples from different tire brands. The mass fractions of all seven BTs (∑BTs) in TWPs ranged from 46.93 to 215 μg/g with an average concentration of 99.32 μg/g. Benzothiazole and 2-hydroxybenzothiazole (2-OH-BT) were the two major compounds, accounting for 56%–89% of the total. The seven BTs were also found in all 36 sets of RD samples (each set included one sample of TSP (particles < 75 μm in diameter), PM10 (particles < 10 μm in diameter) and PM2.5 (particles < 2.5 μm in diameter)) fractions of RD. The median ∑BTs concentration was highest in PM2.5 (26.62 μg/g), followed by PM10 (22.03 μg/g), and TSP (0.68 μg/g). Of the seven BTs, BT, 2-aminobenzothiazole (2-NH2-BT), 2-mercaptobenzothiazole (MBT), and 2-(methylthio)benzothiazole (MTBT) were distributed in PM2.5 and 2-OH-BT was distributed in PM2.5-10 of RD. Based on the mass fractions of BTs in the TSP, PM10, and PM2.5 fractions of RD, human exposure via ingestion, inhalation and dermal absorption were evaluated. Ingestion was found to be the main exposure pathway in humans, and daily intake of BTs in PM2.5 was highest, followed by PM10 and TSP, respectively. Children may suffer more health risks than adults when exposed to RD.
•BTs levels in tire debris of 17 major-brands from 8 countries were determined.•BTs levels in TSP, PM10 and PM2.5 fractions of road dust were investigated for the first time.•BT and 2-OH-BT were the major compounds in both tire and road dust samples.•BTs were more distributed in inhalable particles in road dust.•BTs daily intake was estimated via ingestion, inhalation and dermal absorption.
This study aims to quantify exhaust/non-exhaust emissions and the uncertainties associated with them by combining innovative motorway tunnel sampling and source apportionment modelling. Analytical ...techniques ICP-AES and GC–MS were used to identify the metallic and organic composition of PM10, respectively. Good correlation was observed between Fe, Cu, Mn, Ni, Pb and Sb and change in traffic volume. The concentration of polycyclic aromatic hydrocarbons and other organics varies significantly at the entrance and exit site of the tunnel, with fluoranthene, pyrene, benzoapyrene, chrysene and benzothiazole having the highest incremented concentrations. The application of Principal Component Analysis and Multiple Linear Regression Analysis helped to identify the emission sources for 82% of the total PM10 mass inside the tunnel. Identified sources include resuspension (27%), diesel exhaust emissions (21%), petrol exhaust emissions (12%), brake wear emissions (11%) and road surface wear (11%). This study shows that major health related chemical species of PM10 originate from non-exhaust sources, further signifying the need for legislation to reduce these emissions.
•Identifies major sources of traffic emissions by using a real world motorway tunnel.•Major non-exhaust sources include resuspension, brake wear and road surface wear.•Several toxic metals (e.g. Fe, Cu, Mn, Ni, Pb, Sb) and PAHs show high incremented levels.•Diesel (21%) & petrol (12%) exhaust emissions also contribute as major sources of PM10.•A number of toxic chemical species of PM10 originate from non-exhaust sources.
•Speed correction curves are introduced to improve the simulation of vehicle emission factors.•A multi-year emission inventory is developed in a typical middle-sized city based on detailed data.•The ...comparison of emissions is made between the middle-sized city and the megacities.•Four possible emission control policies are evaluated and discussed for middle-sized cities.
Vehicle emissions are regarded as an important contributor to urban air pollution in China and most previous studies focused on megacities. However, the vehicle pollution in middle-sized cities becomes more severe due to the increasing vehicle population (VP) and lagged control policy. This study takes Langfang, a typical middle-sized city bordered by two megacities (Beijing and Tianjin), as the target domain to investigate vehicle emissions. The speed correction curves (SCC) are introduced to improve the vehicle emission factors (EF) simulation in official technical guidelines on emission inventory (GEI). A multi-year vehicle emission inventory (from 2011 to 2025) is developed in Langfang. From 2011 to 2017, the total vehicle emissions in Langfang decrease for carbon monoxide (CO), but increase for volatile organic compounds (VOCs), nitrogen oxides (NOx), and inhalable particles (PM10), respectively. From 2018 to 2025, the emissions would increase more rapidly in Langfang than in Beijing and Tianjin, indicating the middle-sized cities may become a significant contributor to air pollution in China. Four possible control policies, including VP constrained (VPC), public transportation promotion (PTP), new energy vehicles promotion (NEP), and freight transportation structure optimization (FTO) are evaluated. The most significant emissions reductions are observed under the FTO for CO, NOx, and PM10, and under the VPC for VOCs. The spatial distributions of vehicle emissions show a high order of heterogeneity, indicating that local conditions should be considered in policy formulation in addition to national consistency. More comprehensive policies should be implemented to mitigate the vehicle pollution in middle-sized cities.
The establishment of a non-road construction machinery emission inventory forms the basis for the analysis of pollutant emission characteristics and for the formulation of control policy. We analyzed ...and investigated data on populations, emission factors, and activity levels for the construction machinery in Tianjin to estimate an emission inventory. Finally, a variety of emission reduction scenarios were used to simulate emission reductions and propose the most effective control policy. The results show that total emissions of CO, HC, NOx, PM
10
, and PM
2.5
from non-road construction machinery in Tianjin of 2018 reached 4180.78, 951.44, 5833.85, 383.92, and 365.70 t, respectively. Forklifts, excavators, and loaders were the three most important emission sources in Tianjin. There are clear differences in the emissions of different districts. Large machinery emissions were mainly distributed across the Binhai New Area, which includes high volumes of port machinery and tractors in Tianjin Port. Based on various emission reduction scenarios, the effect of emission reductions is estimated. The IAD affected the reduction of CO and HC emissions with RR values of 17.6% and 17.3%, respectively, while EMO affected the mitigation of PM
10
and PM
2.5
emissions and RR values by 18.0% and 18.4%, respectively. The emission reduction control policy for non-road construction machinery is proposed, including the accelerated updating of non-road machinery emission standards; integrating diesel engine research and development institutions to accelerate the development of vehicle after-treatment technology; and establishing a cooperation mechanism for scientific research institutes, government departments, and enterprises in the control of non-road mobile machinery emissions.
Knowledge of the relationship between air quality and impact factors is very important for air pollution control and urban environment management. Relationships between winter air pollutant ...concentrations and local meteorological parameters, synoptic-scale circulations and precipitation were investigated based on observed pollutant concentrations, high-resolution meteorological data from the Weather Research and Forecast model and gridded reanalysis data. Artificial neural network (ANN) model was developed using a combination of numerical model derived meteorological variables and variables indicating emission and circulation type variations for estimating daily SO
2
, NO
2
, and PM
10
concentrations over urban Lanzhou, Northwestern China. Results indicated that the developed ANN model can satisfactorily reproduce the pollution level and their day-to-day variations, with correlation coefficients between the modeled and the observed daily SO
2
, NO
2
, and PM
10
ranging from 0.71 to 0.83. The effect of four factors, i.e., synoptic-scale circulation type, local meteorological condition, pollutant emission variation, and wet removal process, on the day-to-day variations of SO
2
, NO
2
, and PM
10
was quantified for winters of 2002–2007. Overall, local meteorological condition is the main factor causing the day-to-day variations of pollutant concentrations, followed by synoptic-scale circulation type, emission variation, and wet removal process. With limited data, this work provides a simple and effective method to identify the main factors causing air pollution, which could be widely used in other urban areas and regions for urban planning or air quality management purposes.
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•Machine learning is used to build vehicle CO2 and NOX transient models.•The models are trained on multiple vehicles and verified by a separate vehicle.•The input features of the ...models are more comprehensive than MOVES.•For CO2 and NOX, how different model inputs affect the model results is analyzed.•Different models are constructed according to different pollutants.
The transient simulation of CO2 and NOX from motor vehicles has essential applications in evaluating vehicular greenhouse gas emissions and pollutant emissions. However, accurately estimating vehicular transient emissions is challenging due to the heterogeneity between different vehicles and the continuous upgrading of vehicle exhaust purification technology. To accurately characterize the transient emissions of motor vehicles, a Super-learner model is used to build CO2 and NOx transient emission models. The actual onboard test data of 9 China VI N2 vehicles were used to train the model, and the test data of another China VI N2 vehicle were selected for further robustness verification. There were significant differences in the emissions between the vehicles, but the constructed transient model could capture the common law of transient emissions from China VI N2 vehicles. The R2 values of CO2 and NOx emission in the test data of the validation vehicle were 0.71 and 0.82, respectively. In addition, to further prove the model's robustness, the training data were synchronously modelled based on the Moves-method. The Super-learner model has a smaller RMSE on the validation set than the model based on the Moves-method, indicating that the Super-learner model has more transient simulation advantages. The marginal contributions of the model characteristics to the model results were analysed by SHapley Additive exPlanation (SHAP) value interpretation, and the marginal contributions of different pollutant characteristic parameters varied. Therefore, when establishing transient models of different pollutants, the selection of the model parameters demands considering the generation and purification process of different pollutants. The present work provides novel insights into the parameter selection, construction, and interpretation of the transient vehicle emission model.
•A UV-mutated species, Bacillus subtilis 38, is a good sorbent for multi-metals (Cd, Cr, Hg and Pb).•B38 mixed with NovoGro exhibited a synergetic effect on the immobilization of heavy metals in ...soil.•DTPA, M3 and BCR were suitable for predicting metal bioavailability for specific classes of plant.•The NovoGro could enhance the proliferation of both exotic B38 and native microbes.•It's a practical strategy for the remediation of actual farmland polluted by multi-heavy metals.
Bacillus subtilis 38 (B38) is a mutant species of Bacillus subtilis acquired by UV irradiation with high cadmium tolerance. This study revealed that B38 was a good biosorbent for the adsorption of multiple heavy metals (cadmium, chromium, mercury, and lead). Simultaneous application of B38 and NovoGro (SNB) exhibited a synergetic effect on the immobilization of heavy metals in soil. The heavy metal concentrations in the edible part of the tested plants (lettuce, radish, and soybean) under SNB treatment decreased by 55.4–97.9% compared to the control. Three single extraction methods, diethylenetriaminepentaacetic acid (DTPA), Mehlich 3 (M3), and the first step of the Community Bureau of Reference method (BCR1), showed good predictive capacities for metal bioavailability to leafy, rhizome, and leguminous plant, respectively. The polymerase chain reaction–denaturing gradient gel electrophoresis (PCR–DGGE) profiles revealed that NovoGro could enhance the proliferation of both exotic B38 and native microbes. Finally, the technology was checked in the field, the reduction in heavy metal concentrations in the edible part of radish was in the range between 30.8% and 96.0% after bioremediation by SNB treatment. This study provides a practical strategy for the remediation of farmland contaminated by multiple heavy metals.
To determine the size distribution and source identification of PM-bound heavy metals in roadside environments, four different particle size (<0.2 μm, 0.2–0.5 μm, 0.5–1.0 μm and 1.0–2.5 μm) samples ...were collected and analyzed from four different types of roads during the summer of 2015 in Tianjin. The results showed that the concentrations of PM-bound heavy metal from the roadside environment sampling sites were 597 ± 251 ng/m3 (BD), 546 ± 316 ng/m3 (FK), 518 ± 310 ng/m3 (JY) and 640 ± 237 ng/m3 (WH). There were differences in the concentrations of the heavy metal elements in the four different particle size fractions. The concentrations of Cu, Zn, Cd, Sn and Pb were the highest in the larger particle size fraction (0.5–2.5 μm). Cd, Cu, Zn and Pb were the elements that indicated emissions from tire wear and brake pad wear. The concentrations of Cr, Co and Ni were the highest in the smallest particle size fraction (<0.5 μm), indicating that motor vehicle exhaust was their main source. The correlation analysis results showed that there are differences in the concentration, distribution and correlation of different PM-bound heavy metals in different particle size fractions. The PCA results show that the accumulative interpretation variances of PM0.2, PM0.2–0.5, PM0.5–1.0 and PM1.0–2.5 reached 80.29%, 79.56%, 79.57% and 71.42%, respectively. Vehicle exhaust was the primary source of PM-bound heavy metal collected from the roadside sampling sites, while brake pad wear and tire wear were the second most common sources of the heavy metal.
Fine particulate matter ≤2.5 μm (PM2.5) air pollution is regarded as one of the prominent risk factors that contributes to morbidity and mortality globally, among which cardiovascular disease (CVD) ...has been strongly associated with PM2.5 exposure and is a leading cause of death. Atherosclerosis (AS), the common pathological basis of many CVDs, is a progressive syndrome characterized by the accumulation of lipids and fibrous plaque in the arteries. Recent epidemiological and toxicological studies suggest that PM2.5 may also contribute to the development of AS, even at levels below the current air quality standards. In this paper, the complete pathological process of atherosclerotic plaque from occurrence to rupture leading to CVD was elaborated. Then, the growing epidemiological evidence linking PM2.5 to AS in humans was reviewed and summarized. Furthermore, the potential mechanisms of PM2.5‐mediated AS were discussed, including oxidative stress, inflammation, endothelial dysfunction, abnormal lipid metabolism, disturbance of the autonomic nervous system, and abnormal coagulation function. This paper aimed to provide a comprehensive view of the effect of PM2.5 on the occurrence and development of AS for better prevention and mitigation of adverse health impacts due to PM2.5 air pollution.
Atherosclerotic cardiovascular disease (CVDs) has been strongly associated with PM2.5 exposure. The promoting effect of PM2.5 on arteriosclerosis runs through the whole development process from lesion initiation to plaque rupture. The main mechanisms are oxidative stress, inflammation, endothelial dysfunction, abnormal lipid metabolism, disturbance of the autonomic nervous system and abnormal coagulation function.
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