City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region

Models for predicting vehicle emissions: A comprehensive review

Air pollution is a primary concern, causing around 7 million premature deaths annually, with traffic-related sources contributing 23 %-45 % of emissions. While several studies have surveyed vehicle emission models, they are either outdated or focus on specific data-driven models. This paper systematically reviews vehicle emission prediction models, comparing traditional approaches with data-driven emission models. The traditional emission models can be divided into average-speed, modal, and other models, noting their reliance on empirical assumptions and parameters that may not be universally applicable. In contrast, we delve into data-driven models utilizing dynamometer and on-road test data for time-series and spatial-temporal predictions. The application of these models is discussed across various scenarios, highlighting the progress and gap. We observed that traditional models, primarily estimating total traffic emissions in study regions, lack micro-level detail crucial for tailored decisions. The direct link between road emission model accuracy and input data quality poses challenges in disaggregating on-road vehicle emission inventories. Due to unique transportation instruments, traffic fleet components, and patterns, exploring the effects of emission-reduction policies in specific cities or regions is urgent. Vehicle characteristics, environmental conditions, traffic scenarios, and prediction scales are common effect factors, while instantaneous driving profiles prove effective in model calibration. In data-driven models, ANN outperforms in estimating emissions and performance of low-power diesel engines with errors not exceeding 5 %. However, no single data-driven method performed excellently in predicting all pollutants. Besides, integrated methods utilizing LSTM, GRU, and RNN outperform individual models. To enhance prediction accuracy considering the inherent connectivity of road networks and spatiotemporal variation patterns of vehicle emissions, GCN is an emerging approach for capturing spatial-temporal relationships based on remote sensing data. Moreover, limited data-driven studies have been performed to forecast particle matter emissions, the main contributors to urban pollution, calling for more attention for future research.

Carbon mitigation and health effects of fleet electrification in China's Yangtze River Delta

Fleet electrification is one of the most promising strategies to mitigate carbon emissions and improve air quality. This study provides a comprehensive analysis of the currently unclear CO2 mitigation and human health benefits from electric vehicle (EV) adoption and energy decarbonization in the Yangtze River Delta (YRD) region by integrating fleet modeling, emission projection, air quality modeling and health risk assessment. Based on future socioeconomic trajectories, we project that the total vehicle stock in the YRD region will peak at 107-117 million around 2045-2050. The transition to EVs combined with largely renewable energy in the YRD region can potentially reduce CO2 emissions by 870 Tg in 2060 and brings along substantial health co-benefits with ∼360 avoided premature deaths per million from reduced PM2.5 and O3 concentrations. This study further explores the NO2-attributable burden from road transportation and reveals that fleet electrification could yield greater NO2-attributable health benefits than those from reduced PM2.5 and O3, especially in traffic-dense urban areas. Those findings indicate that China's near-term energy development plans (35% renewable energy) have created the conditions for large-scale EV adoption. Our results imply that the benefits of EVs exhibit substantial spatial heterogeneity, underscoring the importance of region-specific EV incentive policies, and hint that policymakers should prioritize densely populated megacities to maximize the potential for public health gains.

Temporal-spatial dynamic characteristics of vehicle emissions on intercity roads in Guangdong Province based on vehicle identity detection data

Estimating intercity vehicle emissions precisely would benefit collaborative control in multiple cities. Considering the variability of emissions caused by vehicles, roads, and traffic, the 24-hour change characteristics of air pollutants (CO, HC, NO_X, PM_2.5) on the intercity road network of Guangdong Province by vehicle categories and road links were revealed based on vehicle identity detection data in real-life traffic for each hour in July 2018. The results showed that the spatial diversity of emissions caused by the unbalanced economy was obvious. The vehicle emissions in the Pearl River Delta region (PRD) with a higher economic level were approximately 1-2 times those in the non-Pearl River Delta region (non-PRD). Provincial roads with high loads became potential sources of high emissions. Therefore, emission control policies must emphasize the PRD and key roads by travel guidance to achieve greater reduction. Gasoline passenger cars with a large proportion of traffic dominated morning and evening peaks in the 24-hour period and were the dominant contributors to CO and HC emissions, contributing more than 50% in the daytime (7:00-23:00) and higher than 26% at night (0:00-6:00). Diesel trucks made up 10% of traffic, but were the dominant player at night, contributed 50%-90% to NO_X and PM_2.5 emissions, with a marked 24-hour change rule of more than 80% at night (23:00-5:00) and less than 60% during daytime. Therefore, targeted control measures by time-section should be set up on collaborative control. These findings provide time-varying decision support for variable vehicle emission control on a large scale.

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.

Transmission paths and source areas of near-surface ozone pollution in the Yangtze River delta region, China from 2015 to 2021

Near-ground ozone in the Yangtze River Delta (YRD) region has become one of the main air pollutants that threaten the health of residents. However, to date, the transport behavior and source areas of ozone in the YRD region have not been systematically analyzed. In this study, by combining the ozone observational record with a HYSPLIT (hybrid single-particle Lagrangian integrated trajectory) model, we tried to reveal the spatiotemporal regularity of the airflow transport trajectory of ozone. Spatially, high ozone concentrations mainly clustered in industrial cities and resource-based cities. Temporally, the center of the ozone pollution shifted westward of Nanjing from 2015 to 2021. With the passage of time, the influence of meteorological elements on the ozone concentration in the YRD region gradually weakened. Marine atmosphere had the most significant impact on the transmission path of ozone in Shanghai, of which the trajectory frequency in 2021 accounted for 64.21% of the total frequency. The transmission trajectory of ozone in summer was different from that in other seasons, and its transmission trajectory was mainly composed of four medium-distance transmission paths: North China-Bohai Sea, East China Sea-West Pacific Ocean, Philippine Sea, and South China Sea-South China. The contribution source areas mainly shifted to the southeast, and the emission of pollutants from the Shandong Peninsula, the Korean Peninsula-Japan, and the Philippine Sea-Taiwan area increased the impact of ozone pollution in the Shanghai area from 2019 to 2021. This study identified the regional transport path of ozone in the YRD region and provided a scientific reference for the joint prevention and control of ozone pollution in this area.

Co-effect assessment on regional air quality: A perspective of policies and measures with greenhouse gas reduction potential

Clean air policies have achieved remarkable air quality improvement in China for the last decade. However, as more importance was attached to climate issues and further improvement of air quality, policies with greenhouse gas (GHG) reduction potential were supposed to play a significant role. Here, we designed a conventional legislation pathway scenario (CLP) and an enhanced greenhouse gas reduction scenario (EGR), to estimate the co-effects of policies effective in GHG reduction on air pollutant control and air quality improvement in the Yangtze River Delta (YRD) region from 2014 to 2020, adopting a measure-specific evaluation method and an integrated WRF-CAMx model simulation. Results showed that: 1) With the implementation of enhanced measures with GHG reduction potential, emissions of SO₂, NO_x, PM_2.5, PM₁₀, VOC_s and NH₃ decreased by 16.4 %, 21.6 %, 18.6 %, 16.5 %, 23.9 % and 15.4 % in EGR scenario respectively, compared with CLP scenario. And the annual mean simulated concentrations of PM_2.5, SO₂ and NO₂ of the YRD decreased by 11.2 %, 15.4 % and 20.6 %, respectively. 2) The average 8-h maxima (MDA8) concentration of O₃ presented a slightly increasing trend under the impacts of measures with GHG reduction potential, which might be on account of the unbalanced control of NO_x and VOC_s, the two major precursors of O₃. 3) Based on the source apportionment analysis, major partition of total ozone in the four receptors in YRD was from regional transportation, rather than local formation. And the major sectors contributing to ozone were industry and transportation sector. This study quantitatively assessed the co-benefits of GHG-control-effective policies and specific measures on air quality improvement, which would help to provide implications for future policy-making to achieve air pollution and climate change co-control.

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.

Scenarios of demographic distributional aspects of health co-benefits from decarbonising urban transport

BACKGROUND

There is limited knowledge on the distribution of the health co-benefits of reduced air pollutants and carbon emissions in the transport sector across populations.

METHODS

This Article describes a health impact assessment used to estimate the health co-benefits of alternative land passenger transport scenarios for the city of Beijing, China, testing the effect of five transport-based scenarios from 2020 to 2050 on health outcomes. New potential scenarios range from implementing a green transport infrastructure, to scenarios primarily based on the electrification of vehicle fleets and a deep decarbonisation scenario with near zero carbon emissions by 2050. The health co-benefits are disaggregated by age and sex and estimated in monetary terms.

FINDINGS

The results show that all the alternative mitigation scenarios result in reduced PM_2·5 and CO₂ emissions compared to a business-as-usual scenario during 2020-50. The near zero scenario achieves the largest health co-benefits and economic benefits annually relative to the sole mitigation strategy, preventing 300 (95% CI 229-450) deaths, with health co-benefits and CO₂ cost-saving an equivalent of 0·01% (0·00-0·03%) of Beijing's Gross domestic product in 2015 by 2050. Given Beijing's ageing population and higher mortality rate, individuals aged 50 years and older experience the greatest benefit from the mitigation scenarios. Regarding sex, the greatest health benefits occur in men.

INTERPRETATION

This assessment provides estimates of the demographic distribution of benefits from the effects of combinations of green transport and decarbonising vehicles in transport futures. The results show that there are substantial positive health outcomes from decarbonising transport in Beijing. Policies aimed at encouraging active travel and use of public transport, increasing the safety of active travel, improving public transport infrastructure, and decarbonising vehicles lead to differential benefits. In addition, disaggregation by age and sex shows that the health impacts related to transport pollution disproportionately influence different age cohorts and genders.

FUNDING

National Natural Science Foundation of China and FRIEND Project (through the National Research Foundation of Korea, funded by the Ministry of Science and ICT).

Variation of spatio-temporal distribution of on-road vehicle emissions based on real-time RFID data

High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on real-time traffic data from 820 RFID detectors covering 454 roads, and the differences in spatio-temporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM_2.5, PM₁₀, and NOx were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars (LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NOx emissions were different. Diesel and natural gas buses were major contributors of daytime NOx emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks (HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NOx contributor in both inner and outer districts, and its three NOx emission peak hours were found, which are different to the peak hours of total NOx emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.

Prediction of Emission Reduction Potential from Road Diesel Vehicles in the Beijing–Tianjin–Hebei (BTH) Region, China

China has started to focus on the reduction in pollutants from diesel vehicles with high emission intensities in recent years. Therefore, it is essential and valuable to conduct a deep and detailed exploration of the reduction potential from diesel vehicles and compare the abatement effect from different control measures in upcoming decades. This study attempted to estimate the present emissions of four conventional pollutants from diesel vehicles by applying the Computer Program to Calculate Emissions from Road Transport (COPERT) model, and to predict the future emission trends under different scenarios during 2019–2030, taking the Beijing–Tianjin–Hebei (BTH) region as the case study area. In addition, we analyzed the emission reduction potential of diesel vehicles and compared the reduction effects from different control measures. The results showed that the CO and NOX emissions from diesel vehicles in this region could increase by 104.8% and 83.9%, respectively, given no any additional control measures adopted over the next decade. The largest emission reduction effect could be achieved under the comprehensive scenario, which means that vehicular diesel emissions in 2030 could decrease by 74.8–94.0% compared to values in 2018. The effect of emission reduction under the emission standards’ upgrade scenario could cause a gradual increase and achieve a 19.8–82.6% reduction for the four pollutants in 2030. Furthermore, the new energy vehicle promotion scenario could achieve a considerable reduction effect. It could also offer better emission reduction effects under the highway to railway scenario for Tianjin and Hebei provinces. The old vehicle elimination scenario could have a considerable reduction effect, but only in the short term. Furthermore, emission reductions could be mainly influenced by heavy diesel trucks. These results can provide scientific support to formulate effective reduction measures to diesel vehicles for policy makers.

Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region

Accurate and updated aerosol optical properties (AOPs) are of vital importance to climatology and environment-related studies for assessing the radiative impact of natural and anthropogenic aerosols. We comprehensively studied the columnar AOP observations between January 2019 and July 2020 from a ground-based remote sensing instrument located at a rural site operated by Central China Comprehensive Experimental Sites in the center of the Yangtze River Delta (YRD) region. In order to further study the aerosol type, two threshold-based aerosol classification methods were used to investigate the potential categories of aerosol particles under different aerosol loadings. Based on AOP observation and classification results, the potential relationships between the above-mentioned results and meteorological factors (i.e., humidity) and long-range transportation processes were analyzed. According to the results, obvious variation in aerosol optical depth (AOD) during the daytime, as well as throughout the year, was revealed. Investigation into AOD, single-scattering albedo (SSA), and absorption aerosol optical depth (AAOD) revealed the dominance of fine-mode aerosols with low absorptivity. According to the results of the two aerosol classification methods, the dominant aerosol types were continental (accounting for 43.9%, method A) and non-absorbing aerosols (62.5%, method B). Longer term columnar AOP observations using remote sensing alongside other techniques in the rural areas in East China are still needed for accurate parameterization in the future.

Air quality improvement via modal shift: Assessment of rail-water-port integrated system planning in Shenzhen, China

The escalating concerns regarding air pollution problems surrounding port cities have attracted much research attention. The Port of Shenzhen is one of the busiest container ports worldwide, only third to Shanghai and Singapore globally. However, 70% of the freight transportation demand is satisfied via on-road trucks, leading to serious traffic congestion, road accidents and air pollution issues in the city of Shenzhen. This study aims to assess the environmental benefits of modal shift of port-connecting freight transportation by increasing the use of rail and waterborne systems in Shenzhen. To evaluate the environmental benefits of the multimodal transportation strategy in 2025, we employed traffic datasets with a high spatial resolution and a transportation demand model to establish emission inventories and applied them in air quality simulations. Our results indicate that the implementation of multimodal transportation systems could notably reduce the truck volume along major freight corridors, except for roads adjacent to the planned inland ports. The freight traffic activities along the major freight corridors are reduced by nearly 70% over the original freight volume, resulting in a drastic reduction in the emission intensity. Under the most progressive policy-enhanced strategy (PPP) scenario, the total well-to-wheel (WTW) NO_X, fine particulate matter (PM_2.5) and CO₂ emissions could be reduced by 8881 t, 104.8 t and 688 × 10³ t, respectively. The NO₂ concentration in traffic-intensive areas could be reduced by 5 μg/m³, and the 8-h maximum O₃ concentration could be reduced by 0.34 μg/m³ on the average (up to 1.1 μg/m³ in certain areas). Our research indicates that a shift from traditional road transport to cleaner railway and waterway transport could deliver transportation and environmental benefits to port cities.

Atmospheric characteristics and population exposure assessment of black carbon at a regional representative site in the Yangtze River Delta region, China based on the five-year monitoring

To investigate the multi-year atmospheric characteristic and population exposure level of black carbon (BC) in the Yangtze River Delta (YRD) region, China, about five years of ambient BC measurement was performed at Dianshan Lake (DSL) regional Supersite from February 2014 to February 2019. BC concentration at DSL was 1.39 ± 1.15 μg m^-3, which was at low to medium level compared to other areas in the world, and annual BC level was decreased by an average of 45.4% from 2014 to 2018. The absorption Ångström exponent (AAE) value was 1.30 ± 0.173, indicating the predominant contribution of liquid fuel sources such as traffic exhaust to BC. Meanwhile, AAE and BC values both showed the winter-high and summer-low temporal patterns, which highlighted the increasing contribution from solid fuels to BC in winter. Moreover, diurnal characteristics of BC, AAE, carbon monoxide and nitrogen oxide demonstrated the dominance of traffic sources for BC. The average estimated daily intakes (EDIs) of BC through inhalation for 17 population age subgroups were 0.0177-0.0811 μg kg^-1 day^-1, which the highest EDIs for male and female were both observed in infants (9 months ~ < 1 year). Male generally taken higher exposure level of BC compared to female. This work could improve the insights for atmospheric characteristic and population exposure level of BC, and potentially facilitate the development of abatement policies of BC in YRD region, China.

Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China

According to the traffic flow variation from January 2019 to August 2020, emissions of primary air pollutants from highway vehicles were calculated based on the emission factor method, which integrated the actual structure of on-road vehicles. The characteristics of on-highway traffic flow and pollution emissions were compared during various progression stages of coronavirus disease (COVID-19). The results showed that the average daily traffic volume decreased by 38.2% in 2020, with a decrease of 62% during the strict lockdown due to the impact of COVID-19. The daily emissions of primary atmospheric pollutants decreased by 29.2% in 2020 compared to the same period in 2019. As for the structure of on-highway vehicle types, the small and medium-sized passenger vehicles predominated, which accounted for 76.3% of traffic, while trucks and large passenger vehicles accounted for 19.7% and 4.0%, but contributed 58.4% and 33.9% of nitrogen oxide (NO_x) emissions, respectively. According to the simulation results of the ADMS model, the average concentrations of NO_x were reduced by 12.0 µg/m³ compared with the same period in 2019. As for the implication for future pollution control, it is necessary to further optimize the structure of on-highway and the road traffic vehicle types and increase the proportions of new-energy vehicles and vehicles with high emission standards.

Scenario analysis of vehicular emission abatement procedures in Xi'an, China

Vehicular emissions contribute significantly to air pollution, and the number of vehicles in use is continuing to rise. Policymakers thus need to formulate vehicular emission reduction policies to improve urban air-quality. This study used different vehicle control scenarios to predict the associated potential of mitigating carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxide (NO_x), particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀) in Xi'an China, in 2020 and 2025. One business-as-usual scenario and six control scenarios were established, and vehicular emission inventory was developed according to each scenario. The results revealed that eliminating high-emission vehicles and optimizing after-treatment devices would effectively reduce vehicular emissions. In addition, increasing the number of alternative fuel vehicles, restraining vehicle use, and restraining the growth of the vehicle population would all have certain effects on CO and VOCs emissions, but the effects would not be significant for NOx, PM_2.5, and PM₁₀. The results also indicated that if all control measures were stringently applied together, emissions of CO, VOCs, NO_x, PM_2.5, and PM₁₀ would be reduced by 51.66%, 51.58%, 30.19%,71.12%, and 71.81% in 2020, and 53.55%, 51.44%, 19.09%, 54.88%, and 55.51%, in 2025, respectively.

Health benefits of on-road transportation pollution control programs in China

China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM2.5) and O3 based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998-2015 would have been 2-3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM2.5 and O3 in 2015 would have been higher by 11.7 μg/m3 and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM2.5 and O3 in different regions, to sustain improvement in air quality and public health given continuing swift growth in China's vehicle population.

Multi-Criteria Decision Making Process in Metropolitan Transport Means Selection Based on the Sharing Mobility Idea

The article presents the idea of modeling the decision-making process in the field of the metropolitan areas transport system. Due to the increasing process of metropolization and urbanization, which is predicted to be 68.4% worldwide and 83.7% in Europe in 2050, the issue will be even more sophisticated. The problem of depletion of transport network capacity as well as the implementation of modern technology solutions forces metropolitan committees to apply tools for metropolitan passenger transport system optimization. Significantly, the policy and regulations on sustainable urban mobility management are based on the mobility demand predictions and understanding of the travel decision-making process of citizens. The scientific purpose of this article is to build a mathematical model, as a tool supporting the multi-criteria decision-making process regarding the choice of means of transport in a developing metropolis. The issue raised in this article considers the most important research areas of the metropolitan transport means selection, which includes transport safety, qualitative, financial, and ecological aspects. The model was implemented in Silesian Metropolis in Poland with a particular emphasis on sharing mobility transport means users. As a result, a ranking of sharing transport means was developed, which is a piece of significant information for planners and future investors in the development of the metropolitan transport system.

A WRF-Chem model-based future vehicle emission control policy simulation and assessment for the Beijing-Tianjin-Hebei region, China

Using 2025 as the target year, we quantitatively assessed the reduction potentials of emissions of primary pollutants (including CO, HC, NO_x, PM_2.5 and PM₁₀) under different vehicle control policies and the impacts of vehicle emission control policies in the BTH region on the regional PM_2.5 concentration in winter and the surface ozone (O₃) concentration in summer. Comparing the different scenarios, we found that (1) vehicle control policies will bring significant reductions in the emissions of primary pollutants. Among the individual policies, upgrading new vehicle emission standards and fuel quality in Beijing, Tianjin, and Hebei will be the most effective policy, with emission reductions of primary pollutants of 26.3%-54.7%, 38.0%-70.3% and 46.0%-81.6% in 2025, respectively; (2) for PM_2.5 in winter, the Combined Scenario (CS) will lead to a reduction of 0.5-3.9 μg m^-3 (3.5%-11.6%) for the monthly average PM_2.5 concentrations in most areas. The monthly nitrate and ammonium concentrations would reduce by 5.8% and 5.3%, respectively, in the whole BTH region, indicating that vehicle emission control policies may play an important role in the reduction of PM_2.5 concentrations in winter, especially for nitrate aerosols; and (3) for O₃ concentrations in summer, vehicle emission control policies will lead to significant decreases. Under the CS scenario, the maximum reduction of monthly average O₃ concentrations in the summer is approximately 3.6 ppb (5.9%). Most areas in the BTH region have a decrease of 15 ppb (7.5%) in peak values compared to the base scenario. However, in some VOC-sensitive areas in the BTH region, such as the southern urban areas, significant reductions in NO_x may lead to increases in ozone concentrations. Our results highlight that season- and location-specific vehicle emission control measures are needed to alleviate ambient PM_2.5 and O₃ pollution effectively in this region due to the complex meteorological conditions and atmospheric chemical reactions.

Vehicle emission and atmospheric pollution in China: problems, progress, and prospects

China has been the largest vehicle market in the world since 2009. The stalemate between the rapid development of the vehicle industry and delayed vehicle emission control has become increasingly prominent. Vehicle emission has become a significant source of air pollution in China's cities. Understanding the current barriers in the vehicle industry is necessary for the development of effective and sustainable measures and policy to manage vehicle-induced air pollution. This review provides insight into the circumstances and causes of vehicle-induced air pollution and outlines recent progress in policy-makers' long-term strategies and regulations. The development of an integrated mechanism of social participation, technical revolution, and regulatory innovation in vehicles, fuel, and roads is suggested to break the stalemate between air pollution and the automobile boom in China; the implications of this review extend to other countries facing the similar atmospheric pollution problems.

Real-World Measurement of Hybrid Buses’ Fuel Consumption and Pollutant Emissions in a Metropolitan Urban Road Network

This study investigates pollutant emissions and fuel consumption of six Euro VI hybrid-diesel public transport buses operating on different scheduled routes in a metropolitan urban road network. Portable emission measurement systems (PEMS) are used in measurements and results are compared to those obtained from a paired number of Euro V conventional buses of the same body type used as control over the same routes. The selected routes vary from urban to highway driving and the experimentation was conducted over the first half of 2015. The available emissions data correspond to a wide range of driving, operating, and ambient conditions. Fuel consumption, distance- and energy-based emission levels are derived and presented in a comparative manner. The effect of different factors, including speed, ambient temperature, and road grade on fuel consumption and emissions performance is investigated. Mean fuel consumption of hybrid buses was found 6.1% lower than conventional ones, from 20% lower up to 16% higher, over six routes tested in total. The mean route difference between the two technologies was not statistically significant. Air conditioning decreased consumption benefits of the hybrid buses. Decrease of the mean route speed from 15 km h−1 tο 8 km h−1 increased the hybrid buses consumption by 63%. Nitrogen oxides (NOx) emissions of the Euro VI hybrid buses were 93 ± 5% lower than conventional Euro V ones. Nitrous oxide (N2O) emissions from hybrid Euro VI buses made up 5.9% of total greenhouse gas emissions and largely offset carbon dioxide (CO2) benefits. The results suggest that hybrid urban buses need to be assessed under realistic operation and environmental conditions to assess their true environmental and fuel consumption benefits.

Characteristics of the pollutant emissions in a tunnel of Shanghai on a weekday

Tunnel displays a typical semi-closed environment, and multitudes of the pollutants tend to accumulate. The samples of gaseous pollutants and particulate matter (PM) were collected from the Xiangyin tunnel at Shanghai to investigate the characteristics of the pollutant emissions. The results indicated that both gaseous pollutants and PM exhibited much higher concentrations during the rush hours in the morning and at night due to vehicle emission. Two peaks of the PM concentration were observed in the scope of 0.7-1.1 and 3.3-4.7 μm, accounting for 14.6% and 20.3% of the total concentrations, respectively. Organic matter (OM), EC, and many water-soluble ions were markedly higher at the rush hours in the morning than those at night, implicating comprehensive effects of vehicle types and traffic volume. The particle number concentrations exhibited two peaks at Aitken mode (25 nm and 100 nm) and accumulation mode (600 nm), while the particle volume concentration displayed high values at the accumulation mode (100-500 nm) and coarse mode (2.5-4.0 μm). The peak around 100 nm was detected in the morning rush hours, but it diminished with the decrease of the traffic volume. Individual-particle analysis revealed that main particles in the tunnel were Fe-rich particles, K-rich particles, mineral particles, Ca-S rich particles and Al-Si particles. The particles collected at the rush hours displayed marked different morphologies, element concentrations and particle sizes compared to the ones collected at the non-rush period. The data presented herein could shed a light on the feature of vehicle emissions.

Assessing the Future Vehicle Fleet Electrification: The Impacts on Regional and Urban Air Quality

There have been significant advancements in electric vehicles (EVs) in recent years. However, the different changing patterns in emissions at upstream and on-road stages and complex atmospheric chemistry of pollutants lead to uncertainty in the air quality benefits from fleet electrification. This study considers the Yangtze River Delta (YRD) region in China to investigate whether EVs can improve future air quality. The Community Multiscale Air Quality model enhanced by the two-dimensional volatility basis set module is applied to simulate the temporally, spatially, and chemically resolved changes in PM_2.5 concentrations and the changes of other pollutants from fleet electrification. A probable scenario (Scenario EV1) with 20% of private light-duty passenger vehicles and 80% of commercial passenger vehicles (e.g., taxis and buses) electrified can reduce average PM_2.5 concentrations by 0.4 to 1.1 μg m^-3 during four representative months for all urban areas of YRD in 2030. The seasonal distinctions of the air quality impacts with respect to concentration reductions in key aerosol components are also identified. For example, the PM_2.5 reduction in January is mainly attributed to the nitrate reduction, whereas the secondary organic aerosol reduction is another essential contributor in August. EVs can also effectively assist in mitigating NO₂ concentrations, which would gain greater reductions for traffic-dense urban areas (e.g., Shanghai). This paper reveals that the fleet electrification in the YRD region could generally play a positive role in improving regional and urban air quality.