Effects of fuel and driving conditions on particle number emissions of China-VI gasoline vehicles: based on corrections to test results.

The increasing number of vehicles are emitting a large amount of particles into the atmosphere, causing serious harm to the ecological environment and human health. This study conducted the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) to investigate the emission characteristics of particle number (PN) of China-VI gasoline vehicles with different gasoline. The gasoline with lower aromatic hydrocarbons and olefins reduced particulate matter (PM) and PN emissions by 24% and 52% respectively. The average PN emission rate of the four vehicles during the first 300 s (the cold start period) was 7.2 times that of the 300 s-1800s. Additionally, because the particle transmission time and instrument response time, the test results of instantaneous emissions of PN were not synchronized with vehicle specific power (VSP). By calculating the Spearman correlation coefficient between pre-average vehicle specific power (PAVSP) and the test results of PN instantaneous emissions, the delay time was determined as 10s. After the PN emissions results were corrected, the PN emissions were found to be more related to VSP. By analyzing the influence of driving status on emission, this study found that vehicles in acceleration mode increased PN emissions by 76% compared to those in constant speed mode.

The effect of multiple factors on water-soluble inorganic ions in diesel particulate matter emissions.

The water-soluble inorganic ions (WSII) in diesel particulate matter (DPM) have a significant impact on ambient air quality and human health. In this study, the 12 groups of bench tests were conducted to analyze the emission characteristics of two diesel engines, taking into account the influence of engine parameters, test cycle, fuel types, and after-treatment measures. Compared to conventional diesel, a blend of diesel with 5 % biodiesel resulted in a reduction of the WSII emission factors by 23.7-48.0 %. The emission factors of WSII decreased by 8.4 % after installing selective catalytic reduction (SCR). Dummy variable regression analysis was used to analyze the relationship between WSII and influencing factors. The emission factors of Na+, K+, and Ca2+ were mostly affected by the engine, potentially due to the use of coolants and lubricants containing metal oxides in the engine. The emission factors of NO3- were mainly affected by the test cycle. Techniques for order preference by similarity to ideal solution (TOPSIS) were used to analyze the priority of emission reduction technologies. The results indicated that SCR, biodiesel, and low-sulfur diesel could effectively reduce WSII. This study aims to explore the influence of multiple factors on WSII, providing valuable insights for future research on WSII in DPM.

Emissions of air pollutants from non-road construction machinery in Beijing from 2015 to 2019.

Construction machinery (CM) is considered to be a significant source of air pollution. The estimation of emissions from CM is essential for policy-makers to control air pollution and reduce carbon emissions. In this study, air pollutant emissions from CM with four emissions standards (Beijing I-IV) in Beijing from 2015 to 2019 were estimated by combining data from the Non-road Mobile Source Emissions Inventory Compiled Technical Guidelines, Motor Vehicle Emission Simulator (MOVES) and actual measurements. Taking an example for 2019, emissions of hydrocarbons (HCs), carbon monoxide (CO), nitrogen oxides (NOx), particulate matter (PM) and carbon dioxide (CO2) were estimated to be 4.80 Gg, 16.51 Gg, 27.77 Gg, 1.35 Gg and 5.09 Tg, respectively, representing annual mean decreases of 13.2%, 13.1%, 10.8%, 15.2% and 3.5%, respectively, over the five-year period. Tongzhou, Shunyi and Changping Districts contributed 53-67% of total CM emissions in 2019. Among the ten types of CM considered, loaders were the largest contributors to total emissions, accounting for 41-54% of total CM emissions in Beijing from 2015 to 2019. Machinery with a mean power above 75 kW accounted for the largest share (67-78%) of total CM emissions in Beijing from 2015 to 2019. Our results contribute to the limited data of estimated CM emissions and can help develop control strategies to improve air quality and alleviate climate change.

Integrated effects of SCR, velocity, and Air-fuel Ratio on gaseous pollutants and CO2 emissions from China V and VI heavy-duty diesel vehicles.

Vehicle exhaust, an important source of air pollution, is affected by many factors, including driving conditions, combustion efficiencies, and the usage of emission control devices. In this study, the Portable Emission Measurement System (PEMS) was used to test the emissions from China V and China VI heavy-duty diesel vehicles to evaluate the integrated effects of Selective Catalytic Reduction (SCR), velocity, and air-fuel ratio on carbon dioxide (CO2) and nitrogen oxide (NOx) emissions. Our results reveal that the average distance-based CO2 and CO emission factors at high velocities (50-90 km/h) are 25% and 61% lower than those at low velocities (less than 50 km/h). The use of SCR increases CO2 emissions in the range of 70-90 km/h (an average increase of 10.9%). In addition, SCR leads to a 55% NOx emission reduction at low velocities and 89% at high velocities, with an overall average reduction of 84%. We also find that SCR leads to a significant reduction in the correlation between NOx emissions and air-fuel ratio (0.76 vs 0.47 for China V truck; 0.72 vs 0.05 for China VI truck), but it does not cause a drastic reduction in the correlation coefficients between CO2 emissions and air-fuel ratio, which can be used to detect whether SCR is working effectively.

Energy consumption and pollutant emission of diesel-fired combustion from 2009 to 2018 in Beijing, China.

Diesel-fired combustion is one of the main sources of air pollution in the world. In this study, to better understand the energy consumption and main air pollutant emissions of diesel-fired combustion, a practical investigation and historical data analyses were conducted to determine the variations and driving forces of diesel consumption, the distribution of diesel consumption, and the contribution of emissions among various industries. Based on the results of this study, future control measures can be proposed for diesel-fired combustion. The results show that economic development led to an increase in the total volume of passengers and freight transportation, and the number of diesel vehicles increased from 0.16 million in 2009 to 0.25 million in 2018. However, diesel consumption in Beijing decreased from 2.4 Mt in 2009 to 1.8 Mt in 2018 due to the dominant driving forces, such as structural optimization of the diesel vehicle fleet and stricter limit standards for single-vehicle fuel consumption. The use of diesel vehicles in the logistics and transportation industries and the use of diesel-fired machinery in the construction industry were the two main sources of diesel consumption, accounting for 55% and 23% of the total, respectively. The main air pollutant emissions from diesel-fired combustion from 2009 to 2018 first increased and then decreased, while the NOX emissions peaked at 74,800 tons in 2014, which was affected by the structural optimization of the vehicle fleet and the elimination of old diesel trucks. The emissions finally decreased to 54,000 tons in 2018, which was approximately 89% of the amount in 2009. However, the continuously increasing contribution of diesel combustion to the total emissions requires more attention. The electrification of diesel vehicles and the structural upgrading of diesel vehicles have played important roles in mitigating the emissions of diesel combustion. Our study suggests that consumption control targets should be set, reduction plans for key industries such as the logistics and transportation, construction, and tourism industries should be developed, and low-emission zones should be created to promote the elimination and updating of low-emission diesel vehicles and machinery.

Traffic-related organic and inorganic air pollution and risk of development of childhood asthma: A meta-analysis.

The effect of early childhood exposure to traffic-related air pollution (TRAP) on the development of asthma remains unclear. The aim of this study was to clarify potential associations between TRAP (fine particulate matter, PM2.5; nitrogen dioxide, NO2; Benzene and total volatile organic pollutants, TVOCs) and childhood asthma by integrating the results from previous studies. Elsevier, LISTA (EBSCO) and Web of Science databases were searched for relevant studies. Adjusted odds ratio (OR) with corresponding 95% confidence interval (CI) for the association between traffic-related air pollutants and health effects were recovered from individual studies and summary effect estimates (meta-OR) were generated in Review Manager 5.3. Twenty-seven studies were included in the meta-analysis and the results showed that TRAP increased the risk of asthma among children: PM2.5 (meta-OR = 1.07, 95% CI:1.00-1.13), NO2 (meta-OR = 1.11, 95% CI:1.06-1.17), Benzene (meta-OR: 1.21, 95% CI:1.13-1.29) and TVOC (meta-OR:1.06, 95% CI: 1.03-1.10). Sensitivity analyses supported these findings. In addition, regional analysis showed that ORs of inorganic TRAP (PM2.5 and NO2) on the risk of childhood asthma were significantly higher in Asia than those in Europe and North America. Subsequent research should focus on the association between organic pollutants in TRAP and childhood asthma. Furthermore, the disentanglement between TRAP and other pollutant sources may be investigated in future studies.

Air pollution in China: Status and spatiotemporal variations.

In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) concentrations data of air pollutants including particulate matter (PM2.5 and PM10) and gaseous pollutants (SO2, NO2, CO, and O3) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) µg m-3 for PM2.5, 107.8 (91.1, 85.7) µg m-3 for PM10, 54.8 (56.2, 57.2) µg m-3 for O3_8 h, 39.6 (33.3, 33.4) µg m-3 for NO2, 34.1 (26, 21.9) µg m-3 for SO2, 1.2 (1.1, 1.1) mg m-3 for CO, and 0.60 (0.59, 0.58) for PM2.5/PM10, respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM2.5, PM10, NO2, and SO2 standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM2.5, PM10, O3_8 h, NO2, SO2, CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O3 (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NOx controls were more beneficial than SO2 controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards.

Health burden attributable to ambient PM2.5 in China.

In China, over 1.3 billion people have high health risks associated with exposure to ambient fine particulate matter (PM2.5) that exceeds the World Health Organization (WHO) Air Quality Guidelines (AQG). The PM2.5 mass concentrations from 1382 national air quality monitoring stations in 367 cities, between January 2014 and December 2016, were analyzed to estimate the health burden attributable to ambient PM2.5 across China. The integrated exposure-response model was applied to estimate the relative risks of disease-specific mortality. Disease-specific mortality baselines in province-level administrative units were adjusted by the national mortality baseline to better reveal the spatial inequality of the health burden associated with PM2.5. Our study suggested that PM2.5 in 2015 contributed as much as 40.3% to total stroke deaths, 33.1% to acute lower respiratory infection (ALRI, <5yr) deaths, 26.8% to ischemic heart disease (IHD) deaths, 23.9% to lung cancer (LC) deaths, 18.7% to chronic obstructive pulmonary disease (COPD) deaths, 30.2% to total deaths combining IHD, stroke, COPD, and LC, 15.5% to all cause deaths. The population weighted average (PWA) attributable mortality rates (10-5 y-1) were 112.0 in current year analysis, and 124.3 in 10-year time lag analysis. The Mortality attributable to PM2.5 in 10-year time lag analysis (1.7 million) was 12% higher than the current year analysis (1.5 million). Our study also estimated site-specific annual PM2.5 concentrations in scenarios of achieving WHO interim targets (ITs) and AQG. The mortality benefits will be 24.0%, 44.8%, 70.8%, and 85.2% of the total current mortalities (1.5 million) when the PWA PM2.5 concentrations in China meets the WHO IT-1, IT-2, IT-3, and AQG, respectively. We expect air quality modeling and cost-benefits analysis of emission reduction scenarios and corresponding health benefits in meeting the site-specific annual PM2.5 concentrations (WHO IT-1, IT-2, IT-3, and AQG) this study raised.

[Spatial Distribution and Source of Perfluorinated Compounds in Urban Soil from Part of Cities in Anhui Province, China].

In order to explore the spatial distribution and source of perfluorinated compounds (PFCs),eleven mixed urban soil samples were collected from 7 cities in Anhui Province in 2013.Fifteen individual PFCs were detected by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS),and principal components analysis was used to trace the different sources of PFCs in urban soil.The results showed that the total concentration of PFCs (ΣPFCs) ranged from 1.15 to 5.98 ng·g-1 dry weight (dw),with an average concentration of 2.69 ng·g-1.perfluorooctane sulfonate (PFOS) with a concentration range of n.d.-3.56 ng·g-1 and an average concentration of 0.96 ng·g-1 was the dominant PFC contaminant,followed by perfluorooctane acid (PFOA) with a concentration range of n.d.-2.89 ng·g-1 and an average concentration of 0.64 ng·g-1.The highest ΣPFCs concentration in all selected mixed urban soil samples was from Chuzhou City with the value of 5.89 ng·g-1,followed by Jingxian County of Xuancheng City (4.04 ng·g-1).Interestingly,the PFOS concentration was as high as 3.56 ng·g-1 in Jingxian County,accounting for 88.1% of the total PFCs concentration,which might be influenced by paper industry in this area.Comparing to other soil samples in China,ΣPFCs concentration of urban soil from Anhui Province was at middle level.Over 60% of ΣPFCs in urban soil of Anhui province could be attributed to the four principal components,represented by PFOA,perfluorobutane sulfonate,perfluorododecanoic acid,perfluorobutane acid and PFOS.

Individual and population intake fractions of diesel particulate matter (DPM) in bus stop microenvironments.

Diesel particulate matter (DPM) is associated with adverse human health effects. This study aims to investigate the relationship between DPM exposure and emissions by estimating the individual intake fraction (iFi) and population intake fraction (iFp) of DPM. Daily average concentrations of particulate matter at two bus stops during rush hours were measured, and then they were apportioned to DPM due to heavy-duty diesel bus emissions using Chemical Mass Balance Model. The DPM emissions of diesel buses for different driving conditions (idling, creeping and traveling) were estimated on the basis of field observations and published emission factors. The median iFi of DPM was 0.67 and 1.39 per million for commuters standing at the bus stop and pedestrians/cyclists passing through the bus stop during rush hours, respectively. The median iFp of DPM was 94 per million. Estimations of iFi and iFp of DPM are potentially significant for exposure assessment and risk management.

Investigation of speciated VOC in gasoline vehicular exhaust under ECE and EUDC test cycles.

The emission factors and compositions of volatile organic compounds (VOC) in exhaust gas from in-use gasoline passenger cars were characterized using a chassis dynamometer. Three passenger cars were tested at the ECE and the EUDC drive cycles to represent both urban and suburban driving scenarios. Exhaust gas was collected in Summa canisters and analyzed by gas chromatography-mass spectrometry (GC-MS). Common gaseous emissions (CH(4), NOx, CO, and CO(2)) were measured by an on-board monitoring system. The VOC emission factors of different cars ranged from 0.10 to 0.25 g km(-1) at the ECE cycle, and 0.01-0.02 g km(-1) at the EUDC cycle. A total of 57 individual VOC were detected in the exhaust gas, and the weight percentages were very consistent among the three cars. Ethylene (11.80 wt.%), toluene (11.27 wt.%), and benzene (8.83 wt.%) were the most abundant VOC in exhaust gas. Aromatics (38.32%) dominated the low speed conditions (ECE), while alkanes (37.34%) were the major compounds at the high speed condition (EUDC). The total amount of alkenes did not change much between those two cycles, while ethylene is abundant in the ECE and EUDC cycles. Ozone formation potential (OFP) was calculated to estimate the ozone yield from VOC emissions by gasoline cars and the results showed that OFP of VOC emission at the ECE cycle was about ten times higher than that at the EUDC cycle.

An evaluation of improvements in the air quality of Beijing arising from the use of new vehicle emission standards.

An innovative approach of mean emission by vehicle type was used in this paper to assess the impact of new vehicle emission standards in Beijing, China during the period of 2000-2005. It was found that CO and NO(x) emissions decreased by 48% and 23%, respectively, from Type O (before 2000) to Type I (year 2000) vehicles. The reductions from Type O to Type II (year 2002) vehicles were 85% and 73% for CO and NO(x), respectively. When all three types of vehicles (Types O, I and II) are combined, the annual per vehicle CO emissions decreased from 586 kg per vehicle per year in 2000 to 324 kg per vehicle per year in 2005, while that of NO(x) decreased from 66.9 to 43.4 kg per vehicle per year, which was mainly resulted from the impact of stringent new vehicle emission standards implemented in years 2000 and 2002. However, the vehicle population increased by 70% during the same time period, which offset the impact of cleaner vehicles. Thus, the total vehicle emission decreased little for CO (885,000 tons in 2000, 837,000 tons in 2005) and even increased slightly for NO(x) (101,000 and 112,000 tons in 2000 and 2005, respectively). The ambient concentrations of CO decreased significantly throughout 2000-2005, the same trend was not observed for NO(2). Correlation analysis (grey correlation and Pearson correlation) between the annual vehicle emissions and annual concentrations of CO, the annual NO(x) emission and annual NO(2) concentration indicated that the implementation of new vehicle emission standards was associated with the abatement of ambient CO and NO(2) concentrations in Beijing.