High contribution of vehicle emissions to fine particulate pollutions in Lanzhou, Northwest China based on high-resolution online data source appointment

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.

Impact of aerosol-boundary layer interactions on PM2.5 pollution during cold air pool events in a semi-arid urban basin

Global emission reductions still must address winter fine particulate matter (PM2.5) pollution in urban basins with enclosed terrains and frequent cold air pool (CAP) events when the temperatures within the basin are colder than above it. The effects of urban basin aerosol-boundary layer interactions on PM2.5 pollution during CAP events remain unclear. Intensive boundary layer observations in January 2021 and numerical models were used to investigate this issue in the semi-arid urban Lanzhou Basin of China. The results showed that CAPs formed because of the synoptic weather system that exacerbated the warming over the basin. The CAPs in this experiment were characterized by stronger temperature inversion (TI) layers in the vertical direction and lower relative humidity, lower wind speed, and weaker turbulence at the bottom of the basin compared to other conditions. The strong TI layers below the top of the basin inhibited the vertical dispersion of pollutants in the basin and concentrated the PM2.5 within a height of 0.3 km from the bottom of the basin. During CAP events, the proportion of elemental carbon in PM2.5 increased, whereas that of secondary inorganic species decreased. Aerosol absorption increased faster than scattering during CAP events. Therefore, the mean single scattering albedo decreased from 0.85 during non-CAP periods to 0.81 during CAP events. Radiosonde-sounding observations and numerical simulations indicated that aerosols accumulating in the lower basin heated the atmosphere during the daytime and facilitated boundary layer development via the "stove effect" (absorption aerosol heats lower atmosphere to promote boundary layer development). No significant "dome effect" (absorption aerosol heats the upper boundary layer to suppress boundary layer development) occurred during the two CAP events. These findings provide a theoretical basis for scientifically-guided PM2.5 pollution control in winter in isolated urban basins.

Study on PM diffusion and distribution of trackless rubber-tyred vehicle under different driving conditions in underground coal mining environment

Particulate matter (PM) is one of the most harmful exhaust pollutants to human health. In this study, the PM diffusion and distribution emitted by trackless rubber-tyred vehicle under different driving conditions in coal mine were analyzed with numerical simulations and field measurements. The results show that when the vehicle velocity was constant, the PM concentration of the trackless rubber-tyred vehicle decreased with increasing distance from the exhaust pipe orifice. In addition, the proportion of PM with a concentration below 10 mg/m3 was the highest owing to the influences of diffusion and airflow dilution. However, when the diffusion distance is less than 3 m, the PM concentration far exceeds the occupational exposure limit (10 mg/m3). In this case, underground personnel should stay away from the area near and along the exhaust pipe as far as possible. With increasing vehicle velocity, the PM concentration gradient at a diffusion distance of 0-6 m showed the most significant slope. Besides, the concentration fluctuation of PM was the largest and relatively high when the diffusion distance was 5-15 m. Therefore, the area 15 m from the exhaust gas pipe opening of the trackless rubber-tyred vehicle should be controlled. In addition, the relative errors between the measured and numerical simulation results were mostly less than 10%, which proved that the numerical simulation results were reliable.

Influence of vehicle and pavement characteristics on dust resuspension from soil pavement of open-pit mine

It is essential to explore the distribution characteristics of dust concentration distribution near the surface of soil pavement in open-pit mines to develop effective dust control measures. Therefore, in this study, the dust resuspension process of soil pavement was analyzed by building the dust resuspension experimental system of open-pit mine, and the change rules of dust concentration under different factors were investigated. The results showed that under the action of wheel rolling, the dust moved around the wheel along the vertical direction, and the diffusion trajectory in the horizontal direction was approximately parabolic. After re-suspension of the open-pit mine soil pavement, the area of high dust concentration behind the wheel is roughly triangular. The relationship between the average dust concentration (Total dust, Respirable dust and PM2.5) and the vehicle speed and weight were fit to a power function, while the relationship with silt content and water content were quadratic. Vehicle speed and water content had significant effect on the total dust, respirable dust (RESP) and PM2.5 average concentration, while vehicle weight and silt content had little effect on the respirable dust and PM2.5 average concentration. When the water content of mine soil pavement reached 3 %, the average dust concentration could be reduced to <10 mg/m³, and the vehicle speed should be reduced as much as possible under the mine production permitting conditions.

Wintertime aerosol properties of urban desert region of western India: Implications in regional climate assessment

This study assessed the inter-relation between physiochemical and optical characteristics of aerosols measured at a desert-urban region affected by anthropogenic sources and desert dust during October 2020 to January 2021. Based on horizontal visibility and measured PM_2.5 concentration, clear (37 %), light (33 %) and high (31 %) pollution periods were identified. Elemental and organic carbon (50 ± 15 μgm^-3_; 31 %) and secondary inorganics (53 ± 21 μgm^-3; 33 %) dominated the PM_2.5 mass (160 ± 4 μgm^-3) during high pollution period with low dust (14 ± 7 μgm^-3; 8 %) content. Interestingly, the clear pollution period was also influenced by carbonaceous fraction (19 ± 8 μgm^-3; 32 %) and secondary inorganics (19 ± 5 μgm^-3; 32 %), but the PM_2.5 concentrations (59 ± 9 μgm^-3) were ∼ one-third as compared to high pollution period. High scattering coefficients were observed which were comparable to highly polluted Indian city like Delhi. An exponential increase in non-absorbing material was observed and showed clear influence on light absorption capacity of EC and dust due to coating/mixing. High absorption Ångström exponent (AAE) >0.6 was observed for the ratio of non-absorbing to light absorbing components (LAC) in the range of 1-2.5 and EC/PM_2.5 fraction of 7-14 %. While further increase in non-absorbing to absorbing components ratio > 4 and low amount of EC (<4 %) tend to decrease AAE below 0.4. Higher mass absorption cross-section (>30 m²g^-1 of EC) was observed when 4-10 % EC fraction of PM_2.5 associated with 1.5-3.5 times non-absorbing components to total absorbing components. Likewise, absorption enhanced by three to five folds compared to uncoated EC for low EC fraction (3-6 %) in PM_2.5, but high non-absorbing to absorbing component ratio (>2.5). Interestingly, absorption was minimally amplified for nominal coating fraction associated with significant core materials or vice-versa. These findings have implications not only in regional climate assessment but also for other regions with comparable geography and source-mixes.

"Urban Respiration" Revealed by Atmospheric O2 Measurements in an Industrial Metropolis

Urban regions, which "inhale" O₂ from the air and "exhale" CO₂ and atmospheric pollutants, including harmful gases and fine particles, are the largest sinks of atmospheric O₂, yet long-term O₂ measurements in urban regions are currently lacking. In this study, we report continuous measurements of atmospheric O₂ in downtown Lanzhou, an industrial metropolis in northwestern China. We found declines in atmospheric O₂ associated with deteriorated air quality and robust anticorrelations between O₂ and gaseous oxides. By combining O₂ and pollutants measurements with a Lagrangian atmospheric transport model, we quantitatively break down "urban respiration" (ΔO_2URB) into human respiration (ΔO_2RES) and fossil fuel combustion (ΔO_2FF). We found increased ΔO_2FF contribution (from 66.92% to 72.50%) and decreased ΔO_2RES contribution (from 33.08 to 27.50%) as O₂ declines and pollutants accumulate. Further attribution of ΔO_2FF reveals intracity transport of atmospheric pollutants from industrial sectors and suggests transportation sectors as the major O₂ sink in downtown Lanzhou. The varying relationships between O₂ and pollutants under different conditions unfold the dynamics of urban respiration and provide insights into the O₂ and energy consumption, pollutant emission, and intracity atmospheric transport processes.

Potential influence of fine aerosol chemistry on the optical properties in a semi-arid region

The current understanding regarding the potential influence of aerosol chemistry on the optical properties does not satisfy accurate evaluation of aerosol radiative effects and precise determination of aerosol sources. We conducted a comprehensive study of the potential influence of aerosol chemistry on the optical properties in a semi-arid region based on various observations. Organic matter was the main contributor to the scattering coefficients followed by secondary inorganic aerosols in all seasons. We further related aerosol absorption to elemental carbon, organic matter, and mineral dust. Results showed that organic matter and mineral dust contributed to >40% of the aerosol absorption in the ultraviolet wavelengths. Therefore, it is necessary to consider the absorption of organic matter and mineral dust in addition to that of elemental carbon. We further investigated the potential influence of chemical composition, especially of organic matter and mineral dust on the optical parameters. Mineral dust contributed to higher absorption efficiency and lower scattering efficiency in winter. The absorption Ångström exponent (AAE) was mostly sensitive to organic matter and mineral dust in winter and spring, respectively; it was relatively high (i.e., 1.68) in winter and moderate (i.e., 1.42) in spring. Unlike in the other seasons, mineral dust contributed to higher mass absorption efficiency in winter. This work reveals the complexity of the relationship between aerosol chemistry and optical properties, and especially the influence of organic matter and mineral dust on aerosol absorption. The results are highly important regarding both regional air pollution and climate.

The role of source emissions in sulfate formation pathways based on chemical thermodynamics and kinetics model

Sulfate is a major PM_2.5 constituent and poses a significant threat to ecosystems and human health, which has attracted lots of attention to the sulfate formation mechanism. In recent years, there has been great scientific interest in the multiphase oxidation of SO₂ in aqueous aerosol particles. Many factors are involved in the reaction process, including precursor SO₂, oxidants/catalysts, and aerosol acidity, which are three channels closely related to the source emission. The conjoint analysis of source emissions and sulfate aqueous formation can provide a scientific basis for designing effective strategies, though the related research is extremely limited. Here, we applied an improved solute strength-dependent chemical Thermodynamics & Kinetics model (for aqueous pathway contribution) and the Partial Target Transformation-Positive matrix factor model (for source apportionment) to explore the role of source emission in sulfate aqueous formation. The results indicated H₂O₂ aqueous oxidation was the dominant pathway (65.9 %), and secondary nitrate source may grow together with sulfate formation from H₂O₂ pathway. H₂O₂ and TMI pathways were related to higher SOR (sulfur oxidation rate). TMI pathway was significant in summer (54.6 %) and increased with secondary sources and vehicle exhaust. NO₂ pathway was more significant at low secondary source and high coal combustion (higher contribution of NO₂ pathway appeared in winter, 24.7 %). While high formation rate of the O₃ pathway always occurred at low source levels. Coal combustion and vehicle exhaust showed obvious effects on sulfate aqueous formation. Notably, aerosol acidity is a significant factor related to sources and plays a key role in sulfate formation. The result also suggested aerosol pH may be more important than the amounts of substances involved in the oxidation reaction. The findings in this work can provide useful information for better understanding sulfate aqueous formation and offer a scientific basis for designing strategies for air pollution control and sulfate mitigation.

Environmental behavior, human health effect, and pollution control of heavy metal(loid)s toward full life cycle processes

Heavy metal(loid)s (HMs) have caused serious environmental pollution and health risks. Although the past few years have witnessed the achievements of studies on environmental behavior of HMs, the related toxicity mechanisms, and pollution control, their relationship remains a mystery. Researchers generally focused on one topic independently without comprehensive considerations due to the knowledge gap between environmental science and human health. Indeed, the full life cycle control of HMs is crucial and should be reconsidered with the combination of the occurrence, transport, and fate of HMs in the environment. Therefore, we started by reviewing the environmental behaviors of HMs which are affected by a variety of natural factors as well as their physicochemical properties. Furthermore, the related toxicity mechanisms were discussed according to exposure route, toxicity mechanism, and adverse consequences. In addition, the current state-of-the-art of available technologies for pollution control of HMs wastewater and solid wastes were summarized. Finally, based on the research trend, we proposed that advanced in-operando characterizations will help us better understand the fundamental reaction mechanisms, and big data analysis approaches will aid in establishing the prediction model for risk management.

Changes in physical and chemical properties of urban atmospheric aerosols and ozone during the COVID-19 lockdown in a semi-arid region

The synergistic response of urban atmospheric aerosols and ozone (O₃) to reduction of anthropogenic emissions is complicated and still needs further study. Thus, the changes in physical and chemical properties of urban atmospheric aerosols and O₃ during the Coronavirus Disease 2019 (COVID-19) lockdown were investigated at three urban sites and one rural site in Lanzhou with semi-arid climate. Fine particulate matter (PM_2.5) decreased at four sites by ∼ 20% while O₃ increased by >100% at two urban sites during the COVID-19 lockdown. Both primary emissions and secondary formation of PM_2.5 decreased during the lockdown. Significant increase in both sulfur and nitrogen oxidation ratios was found in the afternoon, which accounted for 48.7% of the total sulfate and 40.4% of the total nitrate, respectively. The positive matrix factorization source apportionment revealed increased contribution of secondary formation and decreased contribution of vehicle emissions. Aerosol scattering and absorption decreased by 33.6% and 45.3%, resulting in an increase in visibility by 30% and single scattering albedo (SSA) at 520 nm slightly increased by 0.02. The enhanced O₃ production was explained by increased volatile organic compounds to nitrogen oxides ratio, decreased aerosol, as well as increased SSA. The primary emissions of secondary aerosol precursors significantly decreased while Ox (i.e., NO₂ and O₃) exhibited little change. Consequently, Ox to CO ratio, PM_2.5 to elemental carbon (EC) ratio, secondary inorganic aerosols to EC ratio, and secondary organic carbon to EC ratio increased, confirming enhanced secondary aerosol production efficiency during the lockdown. Positive feedback among O₃ concentration, secondary aerosol formation, and SSA was revealed to further promote O₃ production and secondary aerosol formation. These results provide scientific guidance for collaborative management of O₃ and particulate matter pollution for cities with semi-arid climate.

Chemical characteristics and regional transport of submicron particulate matter at a suburban site near Lanzhou, China

Lanzhou, which is a valley city on the Loess Plateau, frequently suffered from aerosol pollution in recent years, especially in winter. However, the lack of understanding of factors governing aerosol pollution limits the implementation of effective emission policies in and around Lanzhou. To help solve this problem, an intensive field campaign was conducted at the SACOL site, which is a suburban site near Lanzhou, in winter 2018. The chemical characteristics and sources of submicron particulate matter (PM₁) were investigated, and the influence of the topography around Lanzhou on aerosol pollution was examined. In the present study, the average PM₁ mass concentration reached 25.6 ± 12.8 μg m^-3, with 41.0% organics, 16.1% sulfate, 19.7% nitrate, 10.7% ammonium, 3.1% chloride, and 9.4% black carbon (BC). Three organic aerosol (OA) factors were identified with the positive matrix factorization (PMF) algorithm, including a biomass burning OA (BBOA, 13.6%), a coal combustion OA (CCOA, 34.2%), and an oxygenated OA (OOA, 52.2%). The significant relationships between organics, BC, and chloride and wind pattern suggested that the SACOL site was strongly influenced by regionally transported aerosols. Further analysis suggested that these aerosol regional transport events were caused by topography. Due to the limitation of the valley, aerosols accumulated in the valley. These accumulated aerosols were then transported to the SACOL site along the valley by prevailing winds. Our study highlights enhanced aerosol regional transport in valleys, which provides a new perspective for future studies on aerosol pollution in basins and valleys.

Forecast of Electric Vehicle Sales in the World and China Based on PCA-GRNN

Since electric vehicles (EVs) could reduce the growing concerns on environmental pollution issues and relieve the social dependency of fossil fuels, the EVs market is fast increased in recent years. However, a large growth in the number of EVs will bring a great challenge to the present traffic system; thus, an acceptable model is necessary to forecast the sales of EVs in order to better plan the appropriate supply of necessary facilities (e.g., charging stations and sockets in car parks) as well as the electricity required on the road. In this study, we propose a model to predict the sales volume and increase rate of EVs in the world and China, using both statistics and machine learning methods by combining principle component analysis and a general regression neural network, based on the previous 11 years of sales data of EVs. The results indicate that a continuing growth in the sales of EVs will appear in both the world and China in the coming eight years, but the sales increase rate is slowly and continuously deceasing because of the persistent growth of the basic sales volume. The results also indicate that the increase rate of sales of EVs in China is higher than that of the world, and the proportion of sales of EVs in China will increase gradually and will be above 50% in 2025. In this case, large accessory facilities for EVs are required in China in the coming few years.