[Environmental Benefits of Pollution and Carbon Reduction by Bus Fleet Electrification in Zhengzhou].

Electrification of bus fleets is an effective approach to reducing transportation-related pollution and carbon emissions. Evaluating the impact of electrification on existing bus fleets can provide valuable insights for promoting full electrification of public transportation in large cities. Utilizing the fuel life cycle method, we analyzed the CO2 and pollutant emissions of Zhengzhou's bus fleet before and after electrification and evaluated emissions under different electrification scenarios. Our results indicated that after electrification, the fuel life cycle CO2 and PM2.5 emissions increased by 32.6% and 42.6%, respectively, whereas CO, NOx, and VOC emissions decreased by 28%, 34%, and 25%, respectively. Optimizing the power generation structure is a critical factor in reducing CO2 and PM2.5 emissions during the electrification process. The best scenario for comprehensive electrification and power generation structure optimization could result in a 38.7% reduction in CO2, as well as reductions of 80.1% in CO, 84.4% in NOx, 92.2% in VOC, and 30.2% in PM2.5. Prioritizing electrification on long-distance routes is recommended during the replacement process. Additionally, replacing plug-in hybrid natural gas vehicles with pure electric vehicles has both advantages and disadvantages in terms of emission reduction. Achieving pollution reduction and carbon synergies requires advancing fleet replacement and power structure adjustments simultaneously.

Emissions from international airport and its impact on air quality: A case study of beijing daxing international airport (PKX), China.

The Beijing Daxing International Airport is a newly opened airport, and a comprehensive emission inventory of air pollution sources has not yet been established. The lack of basic inventory data will cause difficulties in controlling the air quality (AQ) in and around the airport. Based on actual flight data, we established a comprehensive emission inventory (carbon monoxide (CO), nitrogen oxides (NOX), hydrocarbons (HC), sulfur dioxide (SO2), particulate matter (PM), and carbon dioxide (CO2)) at Beijing Daxing International Airport. Furthermore, we evaluated the impact of airport emissions on the AQ of the surrounding areas using the ADMS-Airport model. The results showed that Beijing Daxing International Airport emitted 1.15 E+03, 1.76 E+03, 1.38 E+02, 1.16 E+02, 3.53 E+01, and 3.75 E+05 t of CO, NOX, HC, SO2, PM, and CO2, respectively, from July 1, 2020, to June 30, 2021. Engine exhaust emissions (landing and takeoff [LTO] cycles) dominated all airport pollutant emissions except for PM from the power plant. Among all aircraft types, B738 emitted the most CO2, as it accounted for almost half of all the flights. The AQ simulations showed that the air pollutant diffusion range was concentrated within 15 km of the airport and the surrounding areas. The contribution of airport emissions to NOX concentrations was most apparent under the most unfavorable meteorological conditions. Based on the average pollutant concentration during the study period, the Gu'an Li Hu Primary School station was the most affected. In particular, NOX concentrations at this station were approximately 50% higher in winter than in summer. Currently, the airport's contribution to pollution in the surrounding areas is insignificant. However, with the continuous increase in the number of flights at the airport, its impact on the AQ in the surrounding areas must be addressed in the future.

[Railway Emission Trends in China Based on Fuel Life Cycle Analysis].

Railway transportation is one of the main modes of modern transportation. Under the dual constraints of air quality improvement and carbon neutrality achievement, clarifying the emission trend of CO2 and pollutants in railway transportation is of great significance for pollution and carbon reduction in the transport sector. In this study, the CO2 and pollutant emission characteristics of Chinese railways from 2001 to 2018 were analyzed based on the fuel life cycle method. Then, railway emission trends from 2019-2030 were assessed combined with scenario analysis. The results showed that with the advancement of railway electrification, the use of new diesel locomotives, and the continuous upgrading of fuel standards, the total CO2 and pollutant emissions in the fuel life cycle of railway transportation showed an upward and downward trend, respectively. In 2018, the total emissions of CO2, NOx, CO, BC, and SOx from railway transportation were 3780.29×104t, 11.98×104t, 3.94×104t, 0.20×104t, and 3.08×104t, respectively. Accelerating the improvement of power structure and reducing unit energy consumption were the best single control strategies to reduce railway emissions of CO2, SOx, NOx, BC, and CO, respectively. Under the comprehensive scenario of actively responding to railway pollution and carbon reduction, the emission reduction rates of CO2, NOx, CO, BC, and SOx could reach 35%, 37%, 39%, 32%, and 45%, respectively. The stagnation of power structure reform or the railway electrification process will lead to a significant increase in total emissions of railway transportation. Therefore, the pollution and carbon reduction of railway transportation requires continuous attention.

[Evolution and Characteristics of Full-process Vehicular VOCs Emissions in Tianjin from 2000 to 2020].

Vehicle emissions are an important source of anthropogenic volatile organic compound (VOCs) emissions in urban areas and are commonly quantified using vehicle emission inventories. However, most previous studies on vehicle emission inventories have incomplete emission factors and emission processes or insufficient consideration of meteorological parameters. Based on the localized full-process emission factors attained from tested data and previous studies, a method to develop a monthly vehicular VOC emission inventory of full process for the long-term was established, which covered exhaust and evaporative emissions (including running loss, diurnal breathing loss, hot soak loss, and refueling emission). Then, the method was used to develop a full-process vehicular VOC emission inventory in Tianjin from 2000 to 2020. The results showed that the total vehicular VOC emissions in Tianjin rose slowly and then gradually decreased. In 2020, the total emissions were 21400 tons. The light-duty passenger vehicles were the dominant contributors and covered 75.00% of the total emissions. Unlike the continuous decline in exhaust emissions, evaporative emissions showed an inverted U-shaped trend with an increasing contribution to total emissions yearly, accounting for 31.69% in 2020. Monthly emissions were affected by both vehicle activity and emission factors. VOC emissions were high in autumn and winter and low in spring and summer. During the COVID-19 epidemic in 2020, vehicle activity was limited by closure and control, making VOC emissions significantly lower than those during the same period in previous years. The method and data in this study can provide technical reference and a decision-making basis for air pollution prevention and control.

[Chemical Component of Particulate Matters and VOCs Characteristics During Vehicle Brake Processes].

Six sets of brake systems were tested using a brake dynamometer, and the brake wear particles (BWPs) and volatile organic compounds (VOCs) were collected during the braking process. In total, 39 elements, 12 water-soluble ions, 7 carbon components, and 18 polycyclic aromatic hydrocarbons (PAHs) in BWPs were extracted and detected, and 74 VOCs in gas samples were analyzed. The average mass fractions of 12 inorganic elements (i.e., Sb, Mg, Cu, Zn, Ti, Ca, Si, Zr, K, Ba, Al, and Fe) with higher contents in PM2.5 and PM10 were 43.4% and 40.3%, respectively, and the average mass fraction of Fe was the highest, accounting for 16.6% and 13.1% of PM2.5 and PM10, respectively. The average mass fractions of the 12 water-soluble ions in PM2.5 and PM10 were 16.5% and 12.6%, respectively, and NO3-, SO42-, and Ca2+ were the ions with high contents. The average mass fraction of total carbon (TC) in PM2.5 and PM10 were 21.9% and 18.1%, respectively, and the average mass fraction of organic carbon (OC) was approximately five times that of elemental carbon (EC). There were six types of PAHs with a detection rate greater than 50%, among which naphthalene (Nap) was the most abundant. The average mass concentration of 74 VOCs was 316.04 µg·m-3, of which the aromatic hydrocarbon had the highest mass concentration. The compositions of BWPs and VOCs emitted by the six sets of brake systems were quite different, which was mainly determined by the brand and raw materials of the brake pads.

[Mobile Source Emission Inventory with High Spatiotemporal Resolution in Tianjin in 2017].

Mobile source emissions have become a major contributor to air pollution in urban areas. Most of the previous studies focus on the emissions from a single source such as on-road mobile source (vehicles) or non-road mobile source (construction machinery, agricultural machinery, ships, railway diesel locomotives, aircraft), but few studies investigate the mobile source emissions as a whole. In this study, we introduced a method for developing mobile source emission inventory with high spatiotemporal resolution, and applied this method in Tianjin in 2017 to analyze the emission compositions and spatiotemporal characteristics there. The results showed that the CO, VOCs, NOx, and PM10 emissions from the mobile sources were 183.03, 64.18, 149.85, and 8.36 thousand tons, respectively. The on-road mobile source was the main contributor to CO and VOCs emissions, accounting for 85.38% and 86.60%, respectively. The non-road mobile source was the main contributor to NOx and PM10 emissions, accounting for 57.32% and 66.95%, respectively. According to the temporal distributions, the mobile source emissions were lowest in February for all pollutants. Moreover, they were highest in October for CO and VOCs and in August for NOx and PM10. Holidays (such as Spring Festival and National Day) have a significant impact on the temporal distribution of the mobile source emissions. According to the spatial distributions, the CO and VOCs emissions were concentrated in urban areas and roads with heavy traffic flow (highways and national highways), and the NOx and PM10 were concentrated in urban areas and port areas. The spatial distributions of different pollutants were determined by the location of their major contributors. This study can provide the required data for fine air pollution control and air quality simulation in Tianjin. Moreover, this method can be applied to the other areas where a mobile source emission inventory needs to be developed.

[Vehicle Emission Inventory and Scenario Analysis in Liaoning from 2000 to 2030].

Vehicle emissions have become a major source of air pollution in urban cities. The vehicle emission inventory of the Liaoning province from 2000 to 2030 was established based on the COPERT model and ArcGIS, and the temporal and spatial distribution characteristics of six pollutants (CO, NMVOC, NOx, PM10, SO2, and CO2) were analyzed. Taking 2016 as the base year, eight scenarios of control measures were designed based on scenario analysis, and the effects of different scenarios on emission reduction were assessed. Results showed that during 2000-2016, CO, NMVOC, NOx, and PM10 emissions at first exhibited increasing trends, after which they decreased. Emissions of SO2 exhibited fluctuating trends, while the emissions of CO2 showed a continuous increase. Passenger cars and motorcycles were the main contributors of CO and NMVOC emissions. Heavy-duty trucks and buses were the main sources of NOx and PM10 emissions. Passenger cars were the major contributors to SO2 and CO2 emissions. Vehicle emissions were significantly higher in the central and southern in Liaoning Province. At the city level, vehicle emissions were mainly concentrated in Shenyang and Dalian. The scenario analysis showed that the implementation of stricter vehicle emission standards can enhance the emission reduction effect. Moreover, accelerating the implementation of new emission standards was beneficial to reduce emissions. The integrated scenario would achieve the maximum emission reduction, with reduction rates of CO, NMVOC, NOx, PM10, CO2, and SO2 at 30.7%, 14.3%, 81.7%, 29.4%, 12.3%, and 12.1%, respectively.

[Pollution Characteristics and Emission Factors of VOCs from Vehicle Emissions in the Tianjin Tunnel].

The pollution characteristics and emission factors (EFs) of the volatile organic compounds (VOCs) of vehicles were investigated using the tunnel test method on weekdays and weekends in the Wujinglu Tunnel in Tianjin, China. Gas samples in the tunnel were collected with 3.2 L stainless steel canisters and 99 VOCs species were analyzed by gas chromatography-mass spectrometry (GC-MS). The concentration levels, variation characteristics, and EFs of the VOCs were analyzed. The ozone formation potentials (OFPs) and secondary organic aerosol formation potentials (SOAFPs) of the VOCs in the tunnel were calculated. Moreover, a comparison of the study results with current literature was conducted. The total concentrations of VOCs at the inlet and midpoint are (190.85±51.15) µg·m-3 and (257.44±62.02) µg·m-3, respectively. The total EFs are (45.12±10.97) mg·(km·veh)-1 and the EFs for alkanes, alkenes, alkynes, aromatics, halocarbons, and oxygenated volatile organic compounds (OVOCs) are (22.79±7.15), (5.04±1.20), (0.78±0.34), (9.86±2.81), (0.26±0.17), and (6.25±2.27) mg·(km·veh)-1, respectively. They are notably smaller than the values obtained in a previous test in 2009. Isopentane, toluene, ethylene, methyl tert-butyl ether (MTBE), and ethane were the top five species among the VOC EFs. The ratios of methyl tert-butyl ether/benzene (MTBE/B) and methyl tert-butyl ether/toluene (MTBE/T) are 1.07 and 0.77, respectively. This implies that the contribution of evaporative emissions from vehicles to VOCs emissions cannot be ignored. The OFPs and SOAFPs in the tunnel are (145.50±37.85) and (43.87±12.75) mg·(km·veh)-1, respectively. Compared with the test in 2009, the OFPs and SOAFPs are 94.23% and 90.88% smaller, respectively. The sharp decrease of the OFPs and SOAFPs is closely related to stricter emission standards and the upgrade of oil products.

[Association Between Fine Particulate Matter and Asthma Hospital Outpatient Visits in Hangzhou].

To study the short-term effects of air pollution on asthma visits and differences in susceptibility to various groups of people, data for asthma visits from January 1, 2013 to December 31, 2015 were obtained from a Hangzhou hospital. Considering the nonlinear relationships among concentration of air pollutants, respiratory hospital outpatient visits and meteorological factors, Generalized Additive Models (GAM) and stratification analysis were used to explore the lag effects and differences in people stratifications. The natural cubic spline function was used for smoothing the average temperature, the average relative humidity and the long-term trend, using dummy variables to control the effect of the day of the week and of holidays. Correlation of PM2.5, NO2 and SO2 daily mean concentrations were significant (under 0.01) in Spearman correlation analysis, while the correlations of daily mean temperature and 3 pollutants were significantly negative. The lag effects of PM2.5 concentration on outpatient visits of asthma peaked at 3-5 days. The relative risk of asthma reached maximum at lag day 5 as 1.0056 (95% CI:1.0021-1.0091), with per 10 µg·m-3 increment of PM2.5 concentration. The relative risk of asthma outpatient visits of all groups of patients were statistically significant (P<0.05). The relative risk of asthma outpatient visits of males and young and middle-aged group were statistically significant at lag days 3-5, and for females and the elderly, were statistically significant at lag day 5. With the introduction of the effects of NO2, the relative risk of asthma outpatient visits increased at lag 5 day in co-pollutant models. The authors concluded that the increase of PM2.5 may be related to the increase of asthma hospital outpatient visits within 3-5 days in Hangzhou, and the effects on male group and elderly group were more definite.

[Characteristics of Particulate and Inorganic Elements of Motor Vehicles Based on a Tunnel Environment].

Respirable particulate matter(PM2.5)samples were collected at different locations (inside and outside the tunnel) at the Zhang Zizhong Tunnel in Tianjin in September 2015. Seventeen inorganic elements were measured, and the sources were analyzed by the PCA receptor model. The results show that the daily average concentration of PM2.5 inside and outside the tunnel is (94.79±62.78) µg·m-3 and (83.92±61.60) µg·m-3, respectively. The concentration during the working day is higher than on a non-working day, and, to a certain extent, PM2.5 concentration in the tunnel during peak periods is correlated with the vehicle flow, which indicates that PM2.5 concentration is affected by motor vehicle pollution seriously. In the tunnel, the concentrations of Si, Fe, Al, Ca, and Mg are higher, the mass fraction reach 98.48% of all analyzed elements and these elements are less affected by vehicles. Fe and trace heavy metals (Zn, Cu, and Pb) are related closely to motor vehicle pollution. From the Wilcoxon Signed-Rank test, there are significant differences in Ba, Cu, Zn, Mo, Sn, and Sb inside and outside the tunnel. Enrichment factors inside and outside the tunnel show that the enrichment factor ratios of Co, Mn, Cr, Ca, Mg, Ba, Fe, Mo, and V are less than 5, which are mainly from the crust. In addition, the enrichment factor ratios of Cu, Zn, Pb, Sn, Sb, and Cd are greater than 5, which are affected largely by anthropogenic sources. The factor analysis indicates that the main pollution sources in the tunnel are the mixed sources of wear and the combustion of fuel, the dust, and the combustion of diesel vehicles. In addition, in order to analyze the source of motor vehicle pollution further, a factor analysis indicates that the main pollution sources are tire wear and exhaust emission, brake wear and exhaust emissions, and diesel emissions.

[Emission Characteristics of Vehicle Exhaust in Artery and Collector Roads in Nanjing Based on Real-time Traffic Data].

The vehicle emissions were estimated by the Urban High Temporal-Spatial Resolution Vehicle Emission Inventory Model and Decision Support System (hereinafter referred to as the HTSVE system) with the real-time data including traffic flow, average speed and fleet compositions obtained from Radio Frequency Identification (RFID) and emission factors based on COPERT. The study focused on the characteristics of vehicle emissions by means of non-parametric test and cluster analysis with ArcGIS in artery roads and collector roads in Nanjing, 2014. The result showed that the proportion of passenger cars reached up to 80%, and China 3 and China 4 accounted for over 90% while China 3 contributed most. The daily average emissions in special periods including morning, noon and evening were affected by both road types and weekend effect. The artery and collector roads were classified as 5 clusters. Each type had similar emission rates distribution and was affected by spatial position to support traffic management.

[Characteristics and Health Risk Assessment of Metallic Elements in PM2.5 Fraction of Road Dust].

In order to analyze and compare the pollution characteristics and risks to human health of metallic elements in the PM2.5 fraction of urban road dust (RD) and park road dust (PRD), particles smaller than 2.5 µm were suspended to filters by a re-suspension system and concentrations of Na, Mg, Al, Fe, Cu, Mn, Ni, Sb, Zn, Cd, and Pb were quantified. Results showed that the average concentrations of Cu and Sb in RD were 626 mg·kg-1 and 23 mg·kg-1, significantly higher than that in PRD (274 mg·kg-1 and 11 mg·kg-1). This indicated that the elemental composition of RD was influenced by non-exhaust emissions. The geoaccumulation Index (Igeo) of each detected element showed that samples were strongly to extremely contaminated by Cd (4 < Igeo < 5), moderately to strongly contaminated by Cu, Sb, Zn, and Pb (2 < Igeo < 4), and uncontaminated to moderately contaminated by Ni and Mn (Igeo < 1). The hazard index (HI) values of Sb, Pb, Cu, Ni, Zn, and Cd were less than 1 and the incremental lifetime cancer risk (ILCR) values of Ni and Cd were less than 10-6, indicating that these elements of RD and PRD are not associated with any cancer risks or non-cancer health risks.

[Characteristics of Particulate Matter and Carbonaceous Species in Ambient Air at Different Air Quality Levels].

This study describes the characteristics of particulate matter and carbonaceous species at different air quality levels. The concentrations of PM10, PM2.5, PM1, and carbonaceous species in PM2.5 were monitored on-line in Langfang City on March 1-22, 2016. The PM10, PM2.5, and PM1 concentrations were 204.1 µg·m-3, 107.9 µg·m-3, and 87.8 µg·m-3, respectively. Diurnal variations in particulate matter concentrations showed a bimodal distribution. In general, the mass concentrations of particulate matter and carbonaceous species (OC, EC, SOC, and POC) and the ratios of PM1/PM10 and PM2.5/PM10 were lower on better air quality periods. However, the mass concentration of PM10 was the highest on moderately polluted times. The ratios of PM1/PM10 and PM2.5/PM10 reached minimum values on moderately polluted times.The mass concentration of OC was slightly lower in moderately polluted periods than slightly polluted times; it was significantly lower in moderately polluted periods compared to severely polluted time periods. Hourly concentrations of OC and EC were lower between the hours of 13:00 and 23:00 compared to slightly polluted and severely polluted periods. The proportion of PM2.5 and PM1 decreased in moderately polluted time periods, consistent with the corresponding primary pollutants. Besides, the value of OC/EC was larger than 2.0. The concentrations of SOC and POC estimated using the minimum OC/EC ratio were 12.2 µg·m-3 and 5.0 µg·m-3, respectively.

[Development of a Non-Road Mobile Source Emissions Inventory for Tianjin].

Based on the collected data of activity level in 2015, a non-road mobile source emissions inventory for Tianjin was developed following the recommended method from the Compilation Guide for a Vehicle Emissions Inventory (trial edition) released by the Ministry of Environmental Protection. In 2015, the emissions of CO, hydrocarbons (HC), nitrogen oxides (NOx), particulate matter (PM) and SO2 from non-road mobile sources in Tianjin were 6.15×103 t, 2.45×103 t, 2.90×104 t, 1.45×103 t, and 1.37×104 t, respectively. Marine sources were identified as the largest non-road mobile source contributor accounting for 73.66% of total emissions, followed by non-road mobile machinery (21.66%). Emissions from civil aircraft and locomotives were relatively lower. Generally, emissions from non-road mobile sources increase from March (spring) to November and decrease from the beginning and the end of the year (winter). Emissions are mainly distributed in suburban districts where there is flourishing agriculture, downtown areas with dense populations, urban construction areas, ports, railway lines, and airports. Uncertainty in the inventory results is mainly due to the lack of key data, such as local emission factors and actual activity levels.

Long-term exposure to urban air pollution and lung cancer mortality: A 12-year cohort study in Northern China.

Cohort evidence that links long-term exposures to air pollution and mortality comes largely from the United States and European countries. We investigated the relationship between long-term exposures to particulate matter <10µm in diameter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and mortality of lung cancer in Northern China. A cohort of 39,054 participants were followed during 1998-2009. Annual average concentrations for PM10, NO2, and SO2 were determined based on data collected from central monitoring stations. Lung cancer deaths (n=140) were obtained from death certificates, and hazard ratios (HRs) were estimated using Cox proportional hazards models, adjusting for age, gender, BMI, education, marital status, smoking status, passive smoking, occupation, alcohol consumption, etc. Each 10mg/m(3) increase in PM10 concentrations was associated with a 3.4%-6.0% increase in lung cancer mortality in the time-varying exposure model and a 4.0%-13.6% increase in the baseline exposure model. In multi-pollutant models, the magnitude of associations was attenuated, most strongly for PM10. The association was different in men and women, also varying across age categories and different smoking status. Substantial differences exist in the risk estimates for participants based on assignment method for air pollution exposure.

[Water-soluble Inorganic Ions in the Road Ambient Atmospheric Particles of Tianjin].

Atmospheric particles, especially water-soluble inorganic ions are hazardous to human body. Motor vehicle exhaust is the greatest contributor to atmosphere pollution in Tianjin. In order to explore the emission characteristics of different road types, PM2.5 and PM10 from four types of roads were sampled and analyzed by water-soluble ions component analysis and Pearson correlation analysis during the period of April to May, 2015 to discover the ratio of PM2.5 to PM10 and the major pollutants. The results showed that water-soluble inorganic ions mainly existed in fine particles varying with different road types, which mainly came from secondary pollution. The quantities of secondary ions in PM2.5 were twice as high as that in PM10, which were the key components of the water-soluble inorganic ions. This was probably due to the increase of automobiles and their emissions, as well as the transmission and spreading of pollutants in the surroundings. Furthermore, water-soluble inorganic ions might exist in the forms of NaNO3, NH4Cl, NH4NO3, (NH4)2SO4, KCl, KNO3, K2SO4, MgCl2, CaCl2, etc. K+, Mg2+, Na+and Ca2+ showed high homology and the contributors of PM2.5 and PM10 were mainly the mixture of combustion and secondary pollutants, then followed by the mixture of re-suspended dust and traffic source.