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Abstract: Objective: Air-borne particulates from different sources could have different physicochemical properties and inflammatory potentials. This study aims to characterize the chemical compositions and the toxicity of ambient particulate matter (PM) associated with traffic emissions. Methods: The concentrations of trace elements, organic carbon (OC), elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs) in PM2.5 and PM10 were measured in samples collected at sites in Beijing, China. Their toxic effects on the pulmonary system of rats were investigated. Biochemical parameters (LDH, T-AOC, TP) and inflammatory cytokine(IL-6, IL-1, TNF-a) levels were measured in the lungs of rats exposed to traffic-related PM. Oxidative damage was observed. PM samples were taken from a near road site and an off road site in summer time in 2006. Results: The concentrations of the USEPA priority pollutant PAHs in both PM10 and PM2.5 were higher (299.658 and 348.412) at the near road site than those (237.728 and 268.472) at the off road site. The similar trend was observed for the concentrations of trace elements in PM. Compared to coarse particles (PM10), fine particles (PM2.5) have a greater adsorption capacity to enrich toxic elements than inhalable particles. Decrease in antioxidant capacity and an increase in the amount of lipid peroxidation products in rat lung tissues was observed. Conclusion: The findings of the present study suggest that the differing inflammatory responses of PM collected from the two road sites might have been mediated by the differing physicochemical characteristics. [Copyright &y& Elsevier]

Abstract: Objection: To study the pollution of atmospheric particles at winter in Beijing and compare the lung toxicity which induced by particle samples from different sampling sites. Method: We collected samples from two sampling points during the winter for toxicity testing and chemical analysis. Wistar rats were administered with particles by intratracheal instillation. After exposure, biochemically index, esimmunity indexes, histopathology and DNA damage were detected in rat pulmonary cells. Result: The elements with enrichment factors (EF) larger than 10 were As, Cd, Cu, Zn, S and Pb in the four experiment groups. The priority control of the total concentration of polycyclic aromatic hydrocarbons (PAHs) in PM10 and PM2.5 of Near-traffic source was much higher than that of Far-traffic source, it demonstrated that near the traffic source of PAHs pollution was heavier than that of Far-traffic source, as it was close to main roads Beiyuan Road, motor vehicle emissions were much higher. The pathology of lung showed that the degree of inflammation was increased with the particle diameter minished, it was the same as the detection of biochemical parameters such as lactate dehydrogenase (LDH), Total antioxidant status(T-AOC) and total protein (TP) in BALF and inflammation cytokine(interleukin-1, interleukin-6 and tumor necrosis factor-alpha) in lung homogenate. The indexes of DNA damage including the content of DNA and Olive empennage of PM2.5 were significant higher than that of PM10 at the same surveillance point (P < 0.05), near-traffic particles were higher than the far-traffic particles at the same diameter, (P < 0.05). Conclusion: Near-traffic area particles had certain pollution at winter in Beijing. Meanwhile, atmospheric particulate matters on lung toxicity were related to the particles size and distance related sites which were exposed: smaller size, more toxicity; nearer from traffic, more toxicity. [Copyright &y& Elsevier]

We developed and tested an improved neural network to predict the average concentration of PM10 (particulate matter with diameter smaller than 10 μm) several hours in advance in summer in Beijing. A genetic algorithm optimization procedure for optimizing initial weights and thresholds of the neural network was also evaluated. This research was based upon the PM10 data from seven monitoring sites in Beijing urban region and meteorological observation data, which were recorded every 3 h during summer of 2002. Two neural network models were developed. Model I was built for predicting PM10 concentrations 3 h in advance while Model II for one day in advance. The predictions of both models were found to be consistent with observations. Percent errors in forecasting the numerical value were about 20%. This brings us to the conclusion that short-term fluctuations of PM10 concentrations in Beijing urban region in summer are to a large extent driven by meteorological conditions. Moreover, the predicted results of Model II were compared with the ones provided by the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. The mean relative errors of both models were 0.21 and 0.26, respectively. The performance of the neural network model was similar to numerical models, when applied to short-time prediction of PM10 concentration. [ABSTRACT FROM AUTHOR]

From 1990 to 2017, the number of vehicles in China increased sharply from 5 million to 310 million, and vehicle emissions became one of the major sources of air pollution. Among the main sources of PM 2.5 in Beijing, the contributions from vehicle sources increased from 5.6% (2000) to 31.1% (2012) to 45% (2017). In 2010, the CO, hydrocarbon (HC), NO x , and particulate matter (PM) emissions of yellow-label vehicles (YLVs) accounted for 46.1%, 47.9%, 63.1% and 86.1% of the total emissions from on-road vehicles. In recent years, China has been implementing a YLV scrappage subsidy policy to control air pollution, and this policy has cost several hundred billion yuan nationwide. However, China has not evaluated the costs and benefits of the policy. Many people question whether the YLV scrappage subsidy policy is worthwhile, but all the stakeholders involved complicate the process of accurately evaluating the true value of the policy. In this study, we evaluated and compared the costs and benefits of the policy in the Beijing-Tianjin-Hebei (BTH) region based on 1.362 million YLVs from 2008 to 2015. Because of the implementation of the policy, the PM 2.5 , PM 10 , NO x , CO and HC emissions in the BTH region decreased by 16.46, 18.12, 174.44, 669.11, and 91.64 kt, respectively, in 2008–2015. The results show that the policy played an important role in reducing pollutant emissions and improving environmental quality in the BTH region. The costs, benefits, and net benefits of the policy were 13.69, 34.03, and 20.34 billion yuan , respectively. The cost-benefit ratio in the BTH region was 1:2.49; at the city scale, Beijing ranked first (1:7.27), and the cost-benefit ratios of Tianjin and Hebei Province were 1:2.06 and 1:1.14, respectively. Of the 13 cities in the BTH region, Beijing had the highest net benefits, amounting to 16.43 billion yuan , while Handan City has the lowest net benefits, amounting to −0.58 billion yuan. The results may provide scientific support for the promotion of older vehicle and diesel vehicle scrappage subsidy policies, the development of cost-benefit analysis (CBA), and effective environmental decision-making in China. • Based on net number of scrappage YLVs, net benefits of the policy are calculated. • This paper estimates costs and benefits of the policy based on 1.27 million YLVs. • The costs, benefits, and net benefits are 13.69, 34.03, and 20.34 billion yuan. • The results help China promote vehicle scrappage subsidy policy on a large scale. • The results promote the development of the cost-benefit analysis in China. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5 ) has attracted increasing attention due to its impacts on air quality and human health. As an important source of PM 2.5 , diesel vehicles are often the focus of research. In this study, we characterized the carbonaceous composition of PM 2.5 that is emitted from on-road China III diesel trucks (DTs). Organic carbon (OC), elemental carbon (EC), and PM 2.5 emission characteristics were determined for 17 China III DTs, including 6 light-duty diesel trucks (LDDTs), 5 medium-duty diesel trucks (MDDTs), and 6 heavy-duty diesel trucks (HDDTs), based on real-world measurements in Beijing, China, using a portable emissions measurement system (PEMS). The average distance-based PM 2.5 emission factors (EFs) (g km −1 ) generally increased and the average CO 2 -based PM 2.5 EFs (g (kg of CO 2 ) −1 ) generally decreased with increased vehicle size from LDDTs to MDDTs to HDDTs. The effects of driving conditions on the EFs for carbonaceous PM 2.5 were analyzed. The results show that distance-based and CO 2 -based EFs strongly depend on driving conditions. Generally, greater amounts of PM 2.5 and OC are emitted from non-highway driving cycles, and greater amounts of EC are emitted from highway driving cycles for vehicles of the same size. For LDDTs, MDDTs, and HDDTs, no significant differences were observed between vehicles with different EC/OC ratios; therefore, the EC/OC ratio is not useful for distinguishing between the emissions generated by differently sized vehicles. The EC/OC, OC/PM 2.5 , and EC/PM 2.5 mass ratios are strongly dependent on driving conditions for vehicles of the same size. The results of this study provide EFs for the carbonaceous composition of PM 2.5 that are more appropriate for China; these results will be helpful for improving policies that are designed to control the carbonaceous composition of PM 2.5 emitted from on-road DTs in China. [ABSTRACT FROM AUTHOR]