Vehicle emissions of primary air pollutants from 2009 to 2019 and projection for the 14th Five-Year Plan period in Beijing, China

Breathing in danger: Understanding the multifaceted impact of air pollution on health impacts

Air pollution, a pervasive environmental threat that spans urban and rural landscapes alike, poses significant risks to human health, exacerbating respiratory conditions, triggering cardiovascular problems, and contributing to a myriad of other health complications across diverse populations worldwide. This article delves into the multifarious impacts of air pollution, utilizing cutting-edge research methodologies and big data analytics to offer a comprehensive overview. It highlights the emergence of new pollutants, their sources, and characteristics, thereby broadening our understanding of contemporary air quality challenges. The detrimental health effects of air pollution are examined thoroughly, emphasizing both short-term and long-term impacts. Particularly vulnerable populations are identified, underscoring the need for targeted health risk assessments and interventions. The article presents an in-depth analysis of the global disease burden attributable to air pollution, offering a comparative perspective that illuminates the varying impacts across different regions. Furthermore, it addresses the economic ramifications of air pollution, quantifying health and economic losses, and discusses the implications for public policy and health care systems. Innovative air pollution intervention measures are explored, including case studies demonstrating their effectiveness. The paper also brings to light recent discoveries and insights in the field, setting the stage for future research directions. It calls for international cooperation in tackling air pollution and underscores the crucial role of public awareness and education in mitigating its impacts. This comprehensive exploration serves not only as a scientific discourse but also as a clarion call for action against the invisible but insidious threat of air pollution, making it a vital read for researchers, policymakers, and the general public.

Enhancement of gaseous chlorobenzene biodegradation and power generation in a microbial fuel cell by bifunctional Acinetobacter sp. HY-99C

The efficient biodegradation of volatile chlorinated hydrocarbons using microbial fuel cells (MFCs) offers a feasible approach for purifying waste gas and alleviating energy crises. However, power generation is limited by poor pollutant biodegradation and slow electron transfer. The bifunctional bacterium Acinetobacter sp. HY-99C was screened and used to improve the performance of a conventional MFC. The inoculation of strain HY-99C into the conventional MFC promoted the formation of a compact biofilm with high metabolic activity and an enriched bifunctional genus (Acinetobacter), which resulted in the accelerated decomposition of chlorinated aromatic compounds into biodegradable organic acids. This led to efficient chlorobenzene removal and power generation from the MFC, with a chlorobenzene elimination capacity of 70.8 g m-3 h-1 and power density of 89.6 mW m-2, which are improved over those of previously reported MFCs. This study provides novel insights into enhancing pollutant removal and power generation in MFCs.

Proposal of policies based on temporal-spatial dynamic characteristics and co-benefits of CO2 and air pollutants from vehicles in Shanghai, China

In megacities, vehicle emissions face urgent challenges related to air pollution and CO2 control. To achieve the refinement of vehicle control policies for the co-control of air pollutants and CO2, this study established a vehicle emission inventory with high spatial and temporal resolution based on the hourly traffic flow in Shanghai and analyzed the spatial and temporal distribution characteristics of the real-time vehicle emissions. Meanwhile, a policy evaluation framework was constructed by combining pollutant emission predictions with quantitative co-control effect assessments. The results indicated that spatio-temporal variations in different air pollutants and CO2 could mainly be attributed to primary contributing vehicle types. The pollutants (CO2, CO and VOCs) primarily contributed by private cars exhibited a bimodal pattern in 24-h time series and their spatial distribution was concentrated in the urban city center. The spatial distribution of NOx and PM primarily contributed by heavy trucks was still obvious on non-urban center areas. Furthermore, the results of synergistic effect analysis revealed that the alternative energy replacement scenario demonstrated the most significant potential for the co-control. Based on temporal-spatial and co-benefit analysis, the precise control policy of vehicle emissions can be established through time-, region-, and model-control. This study provides references and research methods for the formulation of the vehicle refinement control policies in worldwide megacities.

Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown Beijing, China

This study combined the real-time monitoring and investigation of traffic flows to comprehensively analyze the road traffic flow and vehicle structure in downtown Beijing. A dynamic emission inventory of motor vehicle air pollutants in downtown Beijing in 2021 was established, and the impact of these emissions on air quality was simulated and quantified, and different emission reduction control scenarios were proposed to evaluate their environmental improvement effects and explore measures to mitigate the impact of pollution emissions. The results show that the high traffic flow and the structure of the motor vehicle emissions in downtown Beijing are the main causes of severe motor vehicle pollution. Monitoring data shows that traffic flow in central Beijing is dominated by small passenger vehicles, while the vehicle mix is better than in other regions, with 72.0% of vehicles meeting "National V" or higher emission standards. However, to achieve higher air quality goals, further reducing vehicle emissions is necessary. Based on dynamic traffic flow, the average daily emissions of nitrogen oxides (NOX), particulate matters(PM2.5) and volatile organic compounds(VOC) from motor vehicles in central Beijing are 17.7 tons, 0.6 tons and 14.0 tons, respectively, accounting for 23.0% of the city's average daily motor vehicle emissions. If a zero-emission zone for motor vehicles were implemented in central Beijing, the annual average emission level of pollutants will be reduced by 10.4% to 21.0%. The designation of ultra-low emission zones for motor vehicles could be effective in improving the air quality in the center of Beijing.

Application of the extended value-belief-norm (VBN) theory to understand consumers' intention to use autonomous delivery vehicles (ADVs)

Emissions from transportation fuel vehicles are polluting the environment more than ever before. Currently, autonomous delivery vehicles (ADVs) are welcomed by logistics service providers and lots of consumers in general for their significant contribution in reducing environmental pollution and increasing delivery efficiency. However, there is a lack of in-depth research on consumers' willingness to adopt ADVs, despite the fact that ADVs are innovative delivery method in the field of last-mile delivery. The purpose of the study is to expand the existing knowledge of consumers' adoption behaviors by developing and testing the extended Value-Belief-Norm (VBN) theory in autonomous delivery literature. In particular, the study adds subjective norms and COVID-19 risk into the original VBN model as a theoretical framework to gain a comprehensive understanding of the consumer decision-making processes with respect to their intentions to use ADVs. Structural equation modeling is conducted using data from a web-based survey of 561 consumers through an online sample platform. The results of the study demonstrated that both subjective norms and COVID-19 risk are all related with consumers' intention to use ADVs. The casual chain hypotheses of the extend VBN theory mentioned in our study are all supported. The results of the study make significant theoretical and managerial contributions to the field of last-mile delivery and the adoption behaviors of emerging technologies.

Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities

Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin₁₂-bin₁₆ contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.

High spatiotemporal resolution vehicular emission inventory in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020, China

One comprehensive emission inventory of CO, HC, NO_X, PM₁₀, PM_2.5, BC, CH₄, CO₂ and N₂O with high spatial resolution (0.01° × 0.01°) for 58 cities in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020 are developed by using COPERT model and ArcGIS methodology. The results show that vehicular emissions of CO, HC, NO_X, PM₁₀, PM_2.5, BC and CH₄ have begun to decrease or slow their growth rates in recent years due to the implementation of measures to control vehicular emissions. However, vehicular emissions of CO₂ increase rapidly due to little fuel economy improvement. Besides, the usage of selective catalytic reduction (SCR) systems by heavy duty truck (HDT) is the main factor impacting the growth trend of vehicular N₂O emissions since 2017. By 2020, vehicular emissions of CO, HC, NO_X, PM₁₀, PM_2.5, BC, CO₂, CH₄ and N₂O are estimated at about 1.65 Mt, 0.35 Mt, 1.39 Mt, 87.44 kt, 55.06 kt, 15.57 kt, 527.71 Mt, 36.20 kt and 8.56 kt, respectively. Therein, China III, IV, IV and IV passenger cars (PCs) are the predominated models for vehicular emissions of CO, HC, CH₄ and CO₂, accounting for 19.59-28.26 % of the total vehicular emission of corresponding pollutant. Nevertheless, the major contributors of vehicular emissions of NO_X, PM₁₀, PM_2.5, BC and N₂O are China III (29.64 %), III (18.03 %), III (22.81 %), III (42.16 %) and V (22.28 %) HDTs, respectively. The gridded vehicular emissions vary significantly, with emissions of CO, HC, CH₄ and CO₂ being mainly concentrated in central urban areas of cities (e.g., Beijing, Tangshan, Zhengzhou, Tianjin, Qingdao, Jinan). Nevertheless, the grids with high vehicular emissions of NO_X, PM₁₀, PM_2.5, BC and N₂O are mainly distributed along the expressway and the suburban roads of cities (e.g., Linyi, Tangshan, Jining, Weifang, Shijiazhuang, Tianjin, Baoding). Finally, multi-year uncertainties of vehicular emission inventory are discussed.

Synergistic Effects of SO2 and NH3 Coexistence on SOA Formation from Gasoline Evaporative Emissions

Vehicular evaporative emissions make an increasing contribution to anthropogenic sources of volatile organic compounds (VOCs), thus contributing to secondary organic aerosol (SOA) formation. However, few studies have been conducted on SOA formation from vehicle evaporative VOCs under complex pollution conditions with the coexistence of NO_x, SO₂, and NH₃. In this study, the synergistic effects of SO₂ and NH₃ on SOA formation from gasoline evaporative VOCs with NO_x were examined using a 30 m³ smog chamber with the aid of a series of mass spectrometers. Compared with the systems involving SO₂ or NH₃ alone, SO₂ and NH₃ coexistence had a greater promotion effect on SOA formation, which was larger than the cumulative effect of the two promotions alone. Meanwhile, contrasting effects of SO₂ on the oxidation state (OSc) of SOA in the presence or absence of NH₃ were observed, and SO₂ could further increase the OSc with the coexistence of NH₃. The latter was attributed to the synergistic effects of SO₂ and NH₃ coexistence on SOA formation, wherein N-S-O adducts can be formed from the reaction of SO₂ with N-heterocycles generated in the presence of NH₃. Our study contributes to the understanding of SOA formation from vehicle evaporative VOCs under highly complex pollution conditions and its atmospheric implications.

Driving factors of NOX emission reduction in China's power industry: based on LMDI decomposition model

Under the policy background of "joint prevention and control" of global greenhouse gas emission reduction and regional air pollutants, the power industry, as an important target industry of energy conservation and emission reduction policies, has become an effective choice to release dual pressures. In this paper, the "bottom-up" emission factor method was used to measure the emission of CO₂ and NO_X from 2011 to 2019. Then, the contributions of six factors to NO_X emission reduction in China's power industry were identified using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition methods. The research results show that (1) there is a significant synergistic emission reduction effect between CO₂ emission reduction and NO_X emission reduction; (2) the factor that inhibits the growth of NO_X emissions reduction in the power industry is economic development factor; and (3) the main factors that promote the reduction of NO_X emission from the power industry are synergy effect, energy intensity, power generation intensity, and power production structure factors. Several suggestions are proposed, which are the power industry should adjust its structure, improve energy intensity, focus on applying low-nitrogen combustion technology, and improve the air pollutant emission information disclosure system to reduce NO_X emissions.

How does vehicle emission control policy affect air pollution emissions? Evidence from Hainan Province, China

Vehicular emissions have become important sources of air pollution in China. Regarding the environmental impacts of vehicle emission control policies (VECPs), changes in air pollutants and CO₂ emissions have attracted more attention. Hainan is the first province in China declared to ban the sale of fuel-powered cars by 2030, aiming to accelerate cutting down the local air pollution emissions. However, there is no previous study examining how these VECPs would affect air pollutants in Hainan. Further, research on whether the controls would lead to a real carbon reduction is limited. Therefore, this paper quantitatively assesses the emission changes of primary air pollutants (including NO_x, CO, VOCs, PM_2.5, PM₁₀, and PM_TSP) and greenhouse gases (CO₂, CH₄, and N₂O) in the transportation sector with regard to different VECPs in Hainan. The results reveal that (1) VECPs would lead to significant increases in vehicular population by 21 %-65 % in 2025-2050. Specifically, light-duty cars and buses with 4-stroke engines (LD4Cs) is the largest contributor and banning sales of fuel-powered vehicles would lead to a larger increase of 1914.6 thousand (64 %) in 2030; (2) for air pollutant emissions, the policy scenario would bring notable reduction effects, decreasing by 1.0 %-16.0 % and 16.7 %-38.7 % in 2030 and 2050 (PM excluding), respectively, suggesting VECPs play important roles in alleviating environmental pollution; (3) conversely, for CO₂ emissions, the policy scenario would cause increases of 0.8 Mt. (17.8 %) and 0.3 Mt. (6.1 %) in 2035 and 2050, respectively, indicating promoting new energy vehicles (NEVs) would increase carbon emissions. Meanwhile, it suggests that CO₂ emission in the transportation sector of Hainan peaked in 2020. This research highlights that VECPs would be a double-edged sword, leading to air pollutants reductions but not necessarily decline CO₂ emissions. This fact would further accelerate mechanism and technological innovation in transport to alleviate air pollution and carbon emissions simultaneously.

Multi-pollutant emission characteristics of non-road construction equipment based on real-world measurement

Non-road construction equipment (NRCE) has become a crucial contributor to urban air pollution. However, the current research on NRCE is still in its infancy, and the understanding of its pollutant emissions is not yet clear. In this study, multi-pollutant (CO, HC, NOx, PM_2.5, and BC) and CO₂ emissions from 12 excavators and 9 loaders under real-world conditions are investigated by using a synchronous platform based on portable emission measurement system (SP-PEMS). We find the instantaneous emission rates of multi-pollutant present significant variability under different operation modes, and pollutant emissions are significantly high under cold start. Generally, multi-pollutant emission factors (EFs) have been all effectively reduced with the tightening of emission standards except for CO and NOx. The BC and PM_2.5 emissions are significantly affected by engine types, and those emitted by electronically-controlled fuel injection (EI) engines are at lower concentration levels compared with mechanical fuel injection (MI) engines. The mass ratios of BC/PM_2.5 for EI engines are 2.05 times that for MI engines on average. Through comparison, we find the multi-pollutant EFs of NRCE reported by different studies and the Guide vary greatly, and those recommended by the Guide may be overestimated or underestimated to varying degrees. Finally, we recommend the multi-pollutant EFs of NRCE under different emission standards by combining the results of various studies, and which will provide scientific support for the accurately establish of emission inventory.

Multi-type emission factors quantification of black carbon from agricultural machinery based on the whole tillage processes in China

Black carbon (BC), as one of the short-lived climate pollutants, is becoming more prominent contribution from non-road mobile source, especially for agricultural machinery (AM) in China. However, the understanding of BC emissions from AM is still not clear, and the BC emission factors (EFs) are also limited. In this study, we conducted real-world measurements on twenty AM to investigate the instantaneous BC emission characteristics and quantify BC EFs under the whole tillage processes. We find the instantaneous BC emissions and fuel consumptions are obvious differences and present good synchronization under different tillage processes. Multi-type (CO₂-, fuel-, distance-, time-, and area-based) EFs of BC are developed, which are significantly affected by different tillage processes and emission standards of the used AM. While AM conducting rotary tillage, ploughing, harvest corn and harvest wheat on the same area of land, total BC emissions by using the China III emission standard AM will be reduced by 56%, 36%, 88%, and 87% than those by using China II emission standard AM, respectively. Furthermore, for corn and wheat production under the whole tillage processes, BC EFs are 16.90 (6.03-39.12) g/hm² and 18.18 (5.91-38.69) g/hm², CO₂ EFs are 112.64 (72.07-195.98) g/hm² and 103.72 (71.47-167.02) g/hm², respectively. We estimate the BC and CO₂ emissions from wheat and corn productions based on the average area-based EFs. The large fluctuation ranges of BC and CO₂ emissions in different tillage processes and the whole processes can reflect that the use of AM in China is uneven. It also indicates that there is a large space for BC and CO₂ emission reduction and optimization. Therefore, more attention should be paid to the control of BC and CO₂ emissions from AM. We believe that the recommended multi-type EFs are applicable for the quantification of BC emissions from AM in China and other countries.

Recent progress in performance optimization of Cu-SSZ-13 catalyst for selective catalytic reduction of NOx

Nitrogen oxides (NO_x), which are the major gaseous pollutants emitted by mobile sources, especially diesel engines, contribute to many environmental issues and harm human health. Selective catalytic reduction of NO_x with NH₃ (NH₃-SCR) is proved to be one of the most efficient techniques for reducing NO_x emission. Recently, Cu-SSZ-13 catalyst has been recognized as a promising candidate for NH₃-SCR catalyst for reducing diesel engine NO_x emissions due to its wide active temperature window and excellent hydrothermal stability. Despite being commercialized as an advanced selective catalytic reduction catalyst, Cu-SSZ-13 catalyst still confronts the challenges of low-temperature activity and hydrothermal aging to meet the increasing demands on catalytic performance and lifetime. Therefore, numerous studies have been dedicated to the improvement of NH₃-SCR performance for Cu-SSZ-13 catalyst. In this review, the recent progress in NH₃-SCR performance optimization of Cu-SSZ-13 catalysts is summarized following three aspects: 1) modifying the Cu active sites; 2) introducing the heteroatoms or metal oxides; 3) regulating the morphology. Meanwhile, future perspectives and opportunities of Cu-SSZ-13 catalysts in reducing diesel engine NO_x emissions are discussed.

Exposure to Traffic Density during Pregnancy and Birth Weight in a National Cohort, 2000-2017

The variation on birth weight is associated with several outcomes early on in life and low birth weight (LBW) increases the risk of morbidity and mortality. Some environmental exposures during pregnancy, such as particulate matters and other traffic-related pollutants can have a significant effect on pregnant women and fetuses. The aim of this study is to estimate the effect of exposure to traffic density during pregnancy over birth weight in Spain, from 2000–2017. This was a retrospective, cross-sectional study using the information from Spain Birth Registry Statistics database. The traffic density was measured using the Annual average daily traffic. Multivariate linear regression models using birth weight and traffic density were performed, as well as a logistic regression model to estimated Odds ratios for LBW and GAM models to evaluate the non-linear effect. Our findings showed that increases in traffic density were associated with reduction of birth weight and increases of LBW risk. Moreover, exposure to high and very-high traffic-density during pregnancy were associated with reduction of birth weight and increase on LBW risk comparing with exposure to low number of cars trespassing the neighborhoods. The results of this study agree with previous literature and highlights the need of effective policies for reducing traffic density in residential neighborhoods of cities and towns.

Multi-Scenario Simulation and Prediction of Regional Habitat Quality Based on a System Dynamic and Patch-Generating Land-Use Simulation Coupling Model—A Case Study of Jilin Province

Effectively evaluating and predicting the change trend in regional habitat quality and its response to land-use change is of great significance for promoting regional high-quality and sustainable development. In this study, Jilin Province is taken as an example, and the SD–PLUS coupling model and the habitat quality module of the InVEST model are used to simulate the habitat quality of Jilin Province in 2030. In addition, the population and urbanization rates under the SSPs path are taken as the scenario framework, and the habitat quality changes from 1995 to 2030 are discussed. The results showed that the kappa coefficient of the simulation results was 0.93, and the FoM coefficient was 0.102. The simulation effect was good. The land-use simulation results under the four scenarios were quite different, and the change areas were mainly concentrated in the northwest, southeast, and central urban areas of Jilin Province. From 1995 to 2015, the habitat quality showed spatial distribution characteristics of “high in the southeast and low in the northwest”, and the habitat quality continued to deteriorate. By 2030, the ecological priority scenario (S3) is expected to have the maximum average value of habitat quality. Under this scenario, the scale of ecological land, such as forest, increases, and the scale of construction land is controlled. The minimum habitat quality appeared in the situation of rapid expansion (S2), and the increase in low-quality habitat areas was highly consistent with the expansion trend in urban construction land. In the coordinated development scenario, the growth rate of construction land reached 52.26%, but the average value of habitat quality decreased by only 0.0002, which basically found the balance point between economic development and ecological protection. S4 had a high reference value for the future development of Jilin Province.