Non-road mobile machinery (NRMM) is a major contributor to air pollution and carbon emissions in megacities such as Beijing. Traditional emission inventories primarily rely on static registration data and lack mechanisms to reflect real-world activity, which often leads to systematic overestimation. This study develops an activity-level correction method for construction machinery based on extensive on-site and telephone surveys covering 2584 units. The method adjusts utilization rates and operating hours by machinery type and year of manufacture, producing a refined 2024 emission inventory for Beijing. After correction, the number of active machines decreased by 34.8%, revealing a substantial amount of inactive equipment in the registry. Excavators and forklifts showed the highest usage intensity (1210 h yr−1 and 1187 h yr−1) and dominated emissions, together contributing over 57% of total CO2 and pollutant emissions. The updated inventory estimated annual emissions of 7791.7 t CO, 1533.0 t VOCs, 5413.9 t NOx, 421.6 t PM2.5, and 1732.3 kt CO2, which were significantly lower and more realistic than values based on uncorrected data. A synergistic reduction assessment of four major mitigation measures showed that phasing out old machinery and promoting electrification achieved the strongest combined reductions in both CO2 and air pollutants, whereas emission-standard upgrades mainly reduced air pollutants with limited carbon-reduction benefits. This study provides a scientific basis for dynamic and data-driven management of non-road machinery and offers policy guidance for integrated pollutant and carbon control in urban environments.

Abstract Concrete supply chain transportation is a concentrated but often hidden source of urban freight emissions in megacities. This study develops a segment-resolved bottom-up NOx emission inventory for Beijing’s concrete supply chain in 2024, covering aggregate, cement, rail-to-truck transfer, and ready-mixed concrete delivery activities, and couples it with a logistic technology-diffusion model and Monte Carlo uncertainty analysis to evaluate clean-transition pathways through 2035. Results show that NOx emissions from concrete supply chain transportation reached 4994.7 tonnes in 2024, equivalent to approximately 20.0% of Beijing’s total on-road vehicle NOx emissions. Emissions were highly concentrated in aggregate inter-regional road transportation (58.5%) and concrete local road transportation (31.9%), while China V heavy-duty diesel trucks were the dominant fleet contributor. Under business as usual (BAU), natural fleet turnover reduces NOx emissions by 49.9% by 2035. Road-to-rail modal shift (RTR) and vehicle electrification transition (VET) achieve larger reductions of 60.5% and 76.3%, respectively, and the combined policy (CP) scenario reaches an 87.8% reduction. Uncertainty analysis confirms the robust ranking of policy effectiveness despite variability in activity levels, emission factors, and technology adoption. These findings show that deep mitigation requires matching policies to logistics functions: rail substitution for long-distance bulk haulage, electrification for short-haul urban delivery, and clean feeder transport to avoid end point pollution transfer.

Remote sensing equipment (RSE) plays an essential role in monitoring vehicle emissions but requires comprehensive evaluation to verify reliability. In this study, the performance of seven different RSE models in Beijing was assessed by comparing their measurements with those of portable emission measurement systems (PEMS) and steady-state condition testing (SCT). Large variations were observed among the RSE models for CO (16 %-363 %), NO (2 %-354 %), and HC (10 %-725 %) emissions. Comparisons between RSE and PEMS revealed even more significant discrepancies for CO (20 %-6773 %), NO (15 %-2818 %), and HC (13 %-5477 %), with maximum deviations occurring at vehicle speeds between 20 and 60 km/h, reflecting the impacts of vehicle operation on emission measurements. The correlation between RSE and SCT was satisfactory for CO and NO (R-2 values of 0.64-0.76) but poor for HC (R-2 = 0.16-0.22), primarily due to differences in measurement principles. Strengthening management, enhancing certification and accreditation, and regular consistency checks of RSE with SCT and PEMS are recommended for improved reliability in law enforcement applications.

Oil-fired construction machinery (OCM) is a major source of urban air pollutants and CO2 emissions, and electrification is a crucial pathway for improving air quality and achieving China's dual carbon goals; however, its feasibility has not been fully explored. This study uses data envelopment analysis and the analytic hierarchy process to establish a development potential index, covering technical efficiency, economic cost, application scenarios, and charging time and range, with an empirical analysis conducted in Beijing. The findings indicated the high feasibility of replacing OCM with electric alternatives, especially within the low-power range. Based on 2023 registered coding data, it is projected that by 2030, electrification could reduce regional average concentrations of CO, NOx, PM2.5 and VOCs by 12.2 % to 56.4 % and reduce CO2 by 11.7 % to 56.9 %. Owing to economic considerations, small- and medium-sized machinery are particularly feasible for electrification. Key recommendations include prioritizing the electrification of forklifts, lifting platforms, and small-sized machinery in high-emission areas, particularly in central urban districts. Policies such as carbon taxes, carbon markets, and performance grading systems are suggested to incentivize electrification, along with expanding high-emission restriction zones and improving energy infrastructure to support widespread electrification.

Heavy-duty diesel trucks (HDDTs) contributed significantly to on-road air pollution. This study measured the traffic flow of HDDTs on seven national highways in Beijing-Tianjin-Hebei (BTH) region to estimate air pollutants of HDDTs from 2016 to 2020. The emission factors are corrected by the International Vehicle Emissions (IVE) model, traffic flow, and road length. Compared with 2016, traffic flow in 2019 increased by 41

Gasoline vehicles (GVs) have become one of the main emission sources of NOx and volatile organic compounds (VOCs) in Beijing, and determining the pollutant emission levels of in-use GVs is crucial. In this study, we assessed the emission levels, exceedance rates, and factors influencing primary air pollutants (NO, CO, and hydrocarbons (HCs) from GVs, including 7.46 million GVs in Beijing from 2019 to 2023. We predicted the variation in the exceedance rate after implementing the standard b-limit and assessed the social stability risk. In general, the emissions of GVs in Beijing were relatively low. According to the simple driving mode conditions, the CO, HC and NO concentrations in the top 50% of the cumulative probability distributions of emissions were 0.04%, 10.3 ppm and 77.0 ppm, respectively, which account for only 1/10 similar to 1/8 of the standard a-limit values. However, we found that the pollutant concentrations corresponding to the top 10% and 90% of the cumulative probability distributions significantly differed. For example, the NO concentrations in the top 10% were 220 times greater than those in the top 90%, namely, approximately 36.5% greater than the standard limit. The greater risk of exceeding the standards was related to the occurrence of carbon deposits on the valves and cylinder heads of engines, of which medium-duty trucks (MDTs) exhibited the highest rate of exceeding the standards (34.5%) due to vehicle deterioration under high-intensity use. GVs exhibited the highest exceedance rate among all the vehicle types, at 38.7%, whereas China VI vehicles exhibited an exceedance rate of only 0.2%. If the more stringent standard b-limit were implemented, the number of vehicles exceeding the standard would increase, and the exceedance rate of GVs under the standard b-limit would be slightly greater than that under the a-limit. Overall, the exceedance rate showed a decreasing trend with increasing emission stage, with the proportion of the exceedance rate at the different emission stages also varying.

China's rapid urbanization has driven extensive construction activities, leading to the widespread deployment of fuel-powered construction machinery and substantial greenhouse gas (GHG) emissions. We combined surveys on machinery units, operational hours, and load factors to quantify GHG emissions (CO2, CH4, and N2O) from construction machinery in China from 2013 to 2022. Emissions projections were modeled using the low emissions analysis platform (LEAP) under baseline, market-driven, policy-guided, and regulatory-driven scenarios, with parameters including machinery stock, electrification rate, and fuel consumption per hour. The results indicate that from 2013 to 2022, the number of machinery units increased significantly, driving parallel growth in CO2 and N2O emissions, whereas CH4 emissions demonstrated consistent annual decreases because of emission intensity. CO2 equivalent (CO2 eq) emissions increased by 17 % from 2013 to 2021 and then decreased by 2.6 % to 7.3 × 107 t CO2 eq in 2022, with CO2 accounting for 98 %-99 % of total GHG emissions and N2O and CH4 accounting for 1.2 % and 0.1 %, respectively. The primary emission sources were China Stage Ⅲ machinery (69 %), excavators (64 %), and high-power equipment (> 130 kW, contributing 30 %-90 %). Spatially, East China accounted for 47 % of national emissions in 2022, followed by Central China (18 %), which is related mainly to the advanced economic development and infrastructure construction demands. The scenario analysis showed that reducing machinery numbers, enhancing electrification, and improving fuel efficiency could yield substantial mitigation benefits, with the regulatory-driven scenario achieving up to 97 % GHG reduction potential.

To understand the smoke level and NOx emission characteristics of in-use construction machinery in Beijing, we selected 905 construction machines in Beijing from August 2022 to April 2023 to monitor the emission level of smoke and NOx. The exhaust smoke level and excessive emission situation of different machinery types were identified, and their NOx emission levels were monitored according to the free acceleration method. We investigated the correlation of NOx and smoke emission, and proposed suggestions for controlling pollution discharge from construction machinery in the future. The results show that the exhaust smoke level was 0-2.62 m-1, followed a log-normal distribution (μ = -1.73, δ = 1.09, R2 = 0.99), with a 5.64% exceedance rate. Differences were observed among machinery types, with low-power engine forklifts showing higher smoke levels. The NOx emission range was 71-1516 ppm, followed a normal distribution (μ = 565.54, δ = 309.51, R2 = 0.83). Differences among machinery types were relatively small. Engine rated net power had the most significant impact on NOx emissions. Thus, NOx emissions from construction machinery need further attention. Furthermore, we found a weak negative correlation (p < 0.05) between the emission level of smoke and NOx, that is the synergic emission reduction effect is poor, emphasizing the need for NOx emission limits. In the future, the oversight in Beijing should prioritize phasing out China Ⅰ and China Ⅱ machinery, and monitor emissions from high-power engine China Ⅲ machinery.

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

Coordinated control of both carbon dioxide (CO2) and air pollutants from the urban transport sector will deliver the greatest benefit to climate and health. To calculate and assess the synergistic control effect on CO2 and air pollutants from various transport types in Beijing from 2021 to 2050, we built a quantitative analysis model based on the Long-range Energy Alternatives Planning framework. Results showed that passenger transport was the dominant contributor to CO2 and major air pollutants (fine particles, carbon monoxide, volatile organic compounds) emitted from the transport sector in 2021 in Beijing. An exception is for nitric oxide which was mostly from freight transport. Clean energy alternatives for road vehicles and aviation, and electrification of railways offer the best synergistic emission reduction potential for both CO2 and air pollutants, and are also the most important measure to realize carbon neutrality in transportation. A change in transport mode (e.g. from road to rail) and the early elimination of aging vehicles would lead to a greater synergistic effect than that achieved by improving fuel economy in the short-term, except for co-benefits for fine particles and CO2 for which the fine particle emission reduction was much lower than that of CO2. In general, the adoption of clean energy for motor vehicles and aviation (e.g., electric vehicles, hydrogen fuel cell vehicles, and bio-fuels), is the best way for Beijing to quickly pass the carbon peak and achieve neutrality in the transport sector and improve air quality in the future.

Over the past decade, the emission standards and fuel standards in Beijing have been upgraded twice, and the vehicle structure has been improved by accelerating the elimination of 2.95 million old vehicles. Through the formulation and implementation of these policies, the emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NOx), and fine particulate matter (PM2.5) in 2019 were 147.9, 25.3, 43.4, and 0.91 kton in Beijing, respectively. The emission factor method was adopted to better understand the emissions characteristics of primary air pollutants from combustion engine vehicles and to improve pollution control. In combination with the air quality improvement goals and the status of social and economic development during the 14th Five-Year Plan period in Beijing, different vehicle pollution control scenarios were established, and emissions reductions were projected. The results show that the emissions of four air pollutants (CO, VOCs, NOx, and PM2.5) from vehicles in Beijing decreased by an average of 68% in 2019, compared to their levels in 2009. The contribution of NOx emissions from diesel vehicles increased from 35% in 2009 to 56% in 2019, which indicated that clean and energy-saving diesel vehicle fleets should be further improved. Electric vehicle adoption could be an important measure to reduce pollutant emissions. With the further upgrading of vehicle structure and the adoption of electric vehicles, it is expected that the total emissions of the four vehicle pollutants can be reduced by 20%-41% by the end of the 14th Five-Year Plan period.

京津冀区域化石能源消费和工业产品产量大,二氧化碳(CO2)和大气污染物协同减排面临较大挑战.本研究采用排放因子法,核算了2011—2017年京津冀区域CO2排放总量,识别其排放特征和影响因素.基于情景分析法,结合减排协同率、线性回归分析方法对京津冀区域内CO2和主要大气污染物(SO2、NOx)协同减排情况进行量化评估,提出未来协同控制对策和建议.研究结果表明:(1)2011—2017年京津冀区域CO2排放总量呈现先上升后下降的趋势,2013年达到最大值(17.7亿t),此后受产业结构和能源结构调整带动,CO2排放量下降,2017年降至16.0亿t,较2013年下降了9.60％.(2)2011—2017年间京津冀区域SO2与CO2排放协同性较好,说明降低煤炭、燃油消耗对区域内SO2和CO2协同减排效果较为显著;NOx与CO2排放协同性相对较差,还需要进一步降低交通、工业等领域油品消耗.(3)河北省能源消费以煤、油为主,工业生产量大,减排潜力较北京市、天津市更大,需持续优化产业结构并降低化石燃料消费总量.(4)对于未来京津冀区域大气污染物和CO2协同控制,建议因地适宜、分阶段制定减排目标,合理设置减排力度,动态调整协同减排政策.

A general feature in the diurnal cycle of atmospheric ammonia (NH3) concentrations is a morning spike that typically occurs around 07:00 to 10:00 (LST). Current hypotheses to explain this morning's NH3 increase remain elusive, and there is still no consensus whether traffic emissions are among the major sources of urban NH3. Here, we confirmed that the NH3 morning pulse in urban Beijing is a universal feature, with an annual occurrence frequency of 73.0% and a rapid growth rate (>20%) in winter. The stable nitrogen isotopic composition of NH3 (δ15N-NH3) in winter also exhibited a significant diurnal variation with an obvious morning peak at 07:00 to 10:00 (-18.6‰, mass-weighted mean), higher than other times of the day (-26.3‰). This diurnal pattern suggests that a large fraction of NH3 in the morning originated from nonagricultural sources, for example, power plants, vehicles, and coal combustion that tend to have higher δ15N-NH3 emission signatures relative to agricultural emissions. In particular, the contribution from vehicular emissions increased from 18% (00:00 to 07:00) to 40% (07:00 to 10:00), while the contribution of fertilizer sources to NH3 was reduced from 15.8% at 00:00 to 07:00 to 5.2% at 07:00 to 10:00. We concluded that NH3 concentrations in winter mornings in urban Beijing were indeed enhanced by vehicle emissions, which should be considered in air pollution regulations.

The incineration of sacrificial offerings is a significant widely practiced custom that is also a kind of neglected air pollution source in China. Our results showed that the emission factors of particulate matter, SO2, CO, NOx, and VOCs emitted from the incineration of sacrificial offerings with purification systems were reduced by 95%, 19%, 9%, 82%, and 42%, respectively, compared with those without a purification system, revealing a significant effect of the flue gas purification system on reducing particulate matter and gaseous pollutants. The emission level of air pollutants from the incineration of sacrificial offerings remained stable before 2013 and then showed a remarkable decrease after the implementation of China´s Air Pollution Prevention Action Plan in 2013. The emissions of TSP (total suspended particulate), PM10, PM2.5, and NOx in 2009 were 8222, 6106, 5656 and 15,878 ton, respectively, obviously higher than 3434, 2551, 2305 and 8579 ton in 2019. Such trend was affected by both the quantity of incineration and the installation rate of purification systems after the Emission Standard of Air Pollutants for Crematory (GB 13801-2015) issued in China. Distinct spatial distribution of atmospheric pollutants from incineration of sacrificial offerings was found with higher in the east and south of China than the west and north of China, which is proportional to the regional economy and population. The maximum ground-level concentration typically occurred at 0.12-0.2 km from the pollution source, posing potential health risks to people entering and exiting funeral and burial sites and nearby residents.

Non-road construction equipment (NRCE) has become a crucial contributor to urban air pollution. However, the current research on NRCE is still in its infancy, and the understanding of its pollutant emissions is not yet clear. In this study, multi-pollutant (CO, HC, NOx, PM2.5, and BC) and CO2 emissions from 12 excavators and 9 loaders under real-world conditions are investigated by using a synchronous platform based on portable emission measurement system (SP-PEMS). We find the instantaneous emission rates of multi-pollutant present significant variability under different operation modes, and pollutant emissions are significantly high under cold start. Generally, multi-pollutant emission factors (EFs) have been all effectively reduced with the tightening of emission standards except for CO and NOx. The BC and PM2.5 emissions are significantly affected by engine types, and those emitted by electronically-controlled fuel injection (EI) engines are at lower concentration levels compared with mechanical fuel injection (MI) engines. The mass ratios of BC/PM2.5 for EI engines are 2.05 times that for MI engines on average. Through comparison, we find the multi-pollutant EFs of NRCE reported by different studies and the Guide vary greatly, and those recommended by the Guide may be overestimated or underestimated to varying degrees. Finally, we recommend the multi-pollutant EFs of NRCE under different emission standards by combining the results of various studies, and which will provide scientific support for the accurately establish of emission inventory.

Non-road mobile machinery (NRMM), mainly construction machinery, has a high emission intensity of air pollutants, significantly impacting urban air quality. Most previous estimates of NRMM emissions have employed a top-down approach mainly based on estimates of energy consumption, leading to large uncertainties. This study uses the information code registration data specified in the latest regulations to establish a bottom-up method for emission accounting to more precisely identify the characteristics of air pollutant emissions from construction machinery in Beijing in 2020. Moreover, the study evaluates the effectiveness of the implementation of the corresponding control measures in conjunction with the current situation of pollution control of NRMM in Beijing. The results show the following: (1) Based on the information code registration data, there are 37,000-based fuel construction machines, with excavators accounting for the largest proportion (56%), loaders and forklifts also accounting for large proportions (19% and 15%, respectively), representing the main types of construction machinery. (2) Information code registration data better reflect the actual situation of construction machinery emissions than the top-down method; the emissions of the main air pollutants NOx, PM2.5, and VOCs amount to 12,000 tons, 600 tons, and 1000 tons, respectively, which are overestimated to some extent by the top-down method. (3) Loaders and excavators have a large contribution to emissions, accounting for 80-91% of these three pollutants emissions; there is a large quantity of machinery classified into the China III standard, accounting for 64-68% of these pollutants emissions; the designation of low emission zones banning the use of high-emission machinery plays a positive role in pollution reduction, but high-emission machinery is still used in these regions, which requires further attention. (4) In the future, the scope of these regions banning high-emission machinery and the types of controlled machinery should be further expanded, and the supervision and enforcement should be strengthened, Furthermore, the structural adjustment and energy conservation of construction machinery should be promoted, and measures such as electrification should be implemented for part of the light construction machinery to continue to reduce pollutant emissions.

Based on the current air pollution control and CO2 emission reduction policies, this study analyzed the energy structure, number of motor vehicles and nonroad mobile machinery, energy consumption and pollutant emissions in Beijing. Furthermore, the diesel consumption characteristics and challenges for emission reduction in key fields were investigated, such as medium- and heavy-duty diesel trucks, long-distance passenger and tourist diesel vehicles, and nonroad machinery, which are areas with difficult-to-reduce diesel consumption. Control targets and measures for total diesel consumption were also proposed. The results indicated that the higher diesel consumption per unit area in Beijing is related to the larger passenger car and freight truck populations. In recent decades, the number of diesel vehicles has increased, the vehicle type structure has been optimized, the proportion of vehicles with high emission standards has increased, and the absolute pollutant emissions have decreased. Among these, nitrogen oxides (NOx), fine particulate matter (PM2.5) and volatile organic compound (VOC) emissions of different models decreased by 39.5%, 75.3% and 42.8%, respectively, while carbon dioxide (CO2) emissions from diesel combustion decreased by 32%. Moreover, medium and large passenger vehicles, medium- and heavy-duty trucks and construction machinery are the main contributors to diesel consumption. These vehicle types are also difficult to control and reduce, and their replacement by new-energy vehicles is relatively limited. The main control measures for diesel consumption are as follows. First, a green transportation mode can be adopted for goods that can be converted from roads to railways. Second, fuel consumption reduction for nonroad mobile machinery can be realized by tightening fuel consumption limits, setting appropriate maximum retirement life, establishing low- or ultralow-emission zones, and establishing demonstration plots for electric vehicle (EV) substitution for mobile machinery. To improve the air quality and take the lead in carbon neutrality in the future, Beijing must further accelerate the energy structure adjustment and the development of new-energy vehicles in the transportation sector. Carbon neutralization is an important opportunity for diesel consumption reduction, and the synergistic control of atmospheric pollution and carbon emissions from diesel combustion must be strengthened.

The cremation workshop is affected by factors such as equipment workload and personnel operation standardization, and the concentration of particulate matter is usually high, which is easy to cause health risks to exposed people. The study collected PM2.5 samples from cremation workshops of 20 crematoriums in the Beijing-Tianjin-Hebei region, and the health risk assessment model recommended by the USEPA was used to evaluate Exposure risk of PM2.5 heavy metal elements in crematorium to human health. The results of the study show that the PM2.5 concentration level in the cremation workshop is relatively high, with an average concentration of 470 mu g.m(-3), which is 6.3 times the national secondary standard for ambient air quality. The metal elements in PM2.5 chemical components account for a relatively large proportion, with an average mass concentration of 131.2 mu g.m(-3), accounting for 22% of the PM2.5 concentration, and an average total mass concentration of 8 water-soluble ions (Ca2+, NO3-, SO42+, NH4+, Cl-, K+, Na+ , Mg2+) of 26.9 mu g.m(-3), accounting for 4.5%.In general, the non-carcinogenic and carcinogenic risks of heavy metals in the PM2.5 of the cremation workshop to the exposed people are within the acceptable range, but there are still some heavy metal elements that are not carcinogenic and carcinogenic. Poor air-tightness, personnel operation level and workshop ventilation conditions are related to factors. The non-carcinogenic risk levels from high to low are Mn>Cr>Sb>Co>Pb>Ni>Zn>Cu. The values of Mn, Cr, and Sb are greater than the non-carcinogenic risk threshold 1. The carcinogenic risk is relatively obvious. In addition, the carcinogenic risk value of Cr also exceeds the acceptable threshold of carcinogenic risk (1 x 10(-6)-1 x 10(-4) ) requires attention.

Road traffic constitutes a major source of air pollutants in urban Beijing, which are responsible for substantial premature mortality. A series of policies and regulations has led to appreciable traffic emission reductions in recent decades. To shed light on long-term (2014-2020) roadside air pollution and assess the efficacy of traffic control measures and their effects on public health, this study quantitatively evaluated changes in the concentrations of six key air pollutants (PM2.5, PM10, NO2, SO2, CO and O3) measured at 5 roadside and 12 urban background monitoring stations in Beijing. We found that the annual mean concentrations of these air pollutants were remarkably reduced by 47%-71% from 2014 to 2020, while the concurrent ozone concentration increased by 17.4%. In addition, we observed reductions in the roadside increments in PM2.5, NO2, SO2 and CO of 54.8%, 29.8%, 20.6%, and 59.1%, respectively, indicating the high effectiveness of new vehicle standard (China V and VI) implementation in Beijing. The premature deaths due to traffic emissions were estimated to be 8379 and 1908 cases in 2014 and 2020, respectively. The impact of NO2 from road traffic relative to PM2.5 on premature mortality was comparable to that of traffic-related PM2.5 emissions. The public health effect of SO2 originating from traffic was markedly lower than that of PM2.5. The results indicated that a reduction in traffic-related NO2 could likely yield the greatest benefits for public health.

通过对京津冀地区20家火葬场火化车间挥发性有机物(Volatile Organic Compounds,VOCs)现场采样和实验室分析,探究其环境VOCs浓度水平及化学组分特征,并采用最大增量反应活性(Maximum Incremental Reactivity,MIR)计算了不同组分的臭氧生成潜势(Ozone Formation Potential,OFP),最后利用美国EPA推荐的暴露风险评价模型对11种VOCs组分的非致癌和致癌风险进行了评价.结果表明:①火化车间VOCs浓度为147～3926μg·m-3,平均浓度为993μg·m-3,超过了国家室内空气质量标准中总挥发性有机化合物(Total Volatile Organic Compounds,TVOC)限值.在化学组分中,烯烃、苯及苯系物和烷烃占比较大,分别贡献了 32.6％、25.5％和18.2％.②烯烃对臭氧生成潜势OFP的贡献率最高,达到61.8％,其次是苯及苯系物和烷烃,分别贡献了 25.6％和6.3％,三者OFP贡献之和达93.6％,是火化车间VOCs组分中臭氧生成潜势的关键活性组分.③非致癌风险方面,苯的危害指数(Hazard Index,HI)值为1.4,对暴露人群具有明显的非致癌风险;致癌风险方面,苯、甲苯和二氯甲烷的风险值(R)均超过了致癌风险阈值,需采取措施进行重点控制,以确保区域内人员身体健康.