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Predicting spatial explicit information of soil nutrients is critical for sustainable soil management and food security under climate change and human disturbance in agricultural land. Digital soil mapping (DSM) techniques can utilize soil-landscape information from remote sensing data to predict the spatial pattern of soil nutrients, and it is important to explore the effects of remote sensing data types on DSM. This research utilized Landsat 8 (LT), Sentinel 2 (ST), and WorldView-2 (WV) remote sensing data and employed partial least squares regression (PLSR), random forest (RF), and support vector machine (SVM) algorithms to characterize the spatial pattern of soil total nitrogen (TN) in smallholder farm settings in Yellow River Basin, China. The overall relationships between TN and spectral indices from LT and ST were stronger than those from WV. Multiple red edge band-based spectral indices from ST and WV were relevant variables for TN, while there were no red band-based spectral indices from ST and WV identified as relevant variables for TN. Soil moisture and vegetation were major driving forces of soil TN spatial distribution in this area. The research also concluded that farmlands of crop rotation had relatively higher TN concentration compared with farmlands of monoculture. The soil prediction models based on WV achieved relatively lower model performance compared with those based on ST and LT. The effects of remote sensing data spectral resolution and spectral range on enhancing soil prediction model performance are higher than the effects of remote sensing data spatial resolution. Soil prediction models based on ST can provide location-specific soil maps, achieve fair model performance, and have low cost. This research suggests DSM research utilizing ST has relatively high prediction accuracy, and can produce soil maps that are fit for the spatial explicit soil management for smallholder farms.

In-depth exploration of the potential links between instantaneous black carbon (BC) emissions and driving parameters from real-world diesel trucks (DTs) is a key step toward development of a highly flexible vehicle emissions estimation system. In this study, we conducted real-world measurements on 22 DTs with mainstream types and emission standards, and obtained instantaneous data of BC emissions and vehicle driving. Since vehicle specific power (VSP) is an excellent surrogate for engine load, we characterize the instantaneous BC emissions and VSP distributions, and then establish links between VSP and fuel consumption, VSP and BC emission rates, VSP and BC emission factors (EFs), respectively. We find that BC emission rates of China V light-duty DTs installed with diesel particulate filter (DPF) are significantly lower (2 to 3 orders of magnitude) than those with China III and China IV. Frequent acceleration and deceleration of vehicles maybe the main reason leads to high BC emissions. The distribution of VSP is mainly concentrated in the ranges of -30 to 35 kW/t in the scope of this study. We find that VSP and BC EFs did not show a consistent pattern for all tested DTs, and BC EFs present obvious fluctuations with the VSP variation. The average fuel-based BC EFs vary by factors of 2.27-8.25 from the lowest to highest EFs. Through a fitting of the third-order polynomial function, we finally quantify and provide fitting formulas of BC EFs and VSP under more detailed categorization. Our results can provide important data support for accurate quantification of BC EFs, and even emission inventory calculations.

Black carbon (BC), as one of the short-lived climate pollutants, is becoming more prominent contribution from non-road mobile source, especially for agricultural machinery (AM) in China. However, the understanding of BC emissions from AM is still not clear, and the BC emission factors (EFs) are also limited. In this study, we conducted real-world measurements on twenty AM to investigate the instantaneous BC emission characteristics and quantify BC EFs under the whole tillage processes. We find the instantaneous BC emissions and fuel consumptions are obvious differences and present good synchronization under different tillage processes. Multi-type (CO

Non-road construction equipment (NRCE) has become a vital contributor to urban air pollutants with the rapid urbanization in China. Black carbon (BC), as a key pollutant emitted from NRCE (mainly diesel-fueled), has attracted considerable concerns due to adverse impacts on climate change, visibility, and human health. However, the understanding of its emissions is still unclear based on limited research results. In this study, we conducted real-world measurements on BC emissions from 12 excavators and 9 loaders to characterize the variation and quantify fuel-based emission factors (EFs) by using a synchronous platform based on PEMS (SP-PEMS). We analyzed the impacts of key factors (operation mode, emission standard, and engine rated power) on BC emission comprehensively. High BC emission in working mode may be mainly owing to the increase of fuel consumption and the deterioration of air-fuel ratio. With more stringent emission standards, BC EFs of all tested NRCE present significant decreasing trends. Interestingly, NRCE with high rated power generally exhibits lower BC emissions. Through comparison, we find BC EFs in this study are generally higher than elemental carbon (EC) EFs reported in previous studies, which will lead BC emissions from NRCE to be underestimated while EC EFs are used instead of BC EFs. Furthermore, BC EFs of NRCE with Stage III are significantly higher (1–3 orders of magnitude) than those of on-road diesel trucks with the current mainstream emission standards of China IV and China V, which reinforces the urgency and importance of controlling BC emissions from NRCE in China. Finally, we recommend BC EFs of excavators and loaders under different emission standards and operation modes, and which preliminarily fills the gap in localized BC EFs of typical NRCE to relieve the urgent needs for emission inventory calculation.

Emissions of carbonyl compounds from agricultural machines cannot be ignored. Carbonyl compounds can cause the formation of ozone (O

Heavy metals in agricultural soils not only affect the food security and soil security, but also endanger the human health through the food chain. Based on the incorporation of index analysis, positive matrix factorization (PMF), self-organizing map (SOM), and geostatistical methods, this research performed the assessment of source apportionment and ecological and health risks of soil heavy metals in Hulan River Watershed, Northeastern China. According to the Pollution Load Index (PLI), 83.08% of the soil samples were slightly or mildly polluted, and 1.54% of the soil samples were severely polluted. The ecological risk index (EI) showed that about 80.77% and 60.77% of the soil samples were beyond the low risk level for Hg and Cd, respectively. In this research, the non-carcinogenic and carcinogenic risk indices for children were higher than adult males and adult females. Four potential sources were revealed based on the PMF and SOM analysis including atmospheric deposition and industrial emission; transportation source; agricultural source; and a combination of agricultural, industrial, and natural sources. Considerable and high ecological risk from Hg existed in the area close to the coal steam-electric plant, and considerable and high ecological risk from Cd existed in the Hulan River estuary area. The eastern part of the study area experienced higher non-carcinogenic and carcinogenic risks for adults and children than the western part of the study area. The source apportionment and ecological and health risk mapping provide important role in reducing pollution sources. Zonal pollution control and soil restoration measures should be performed in the areas with high ecological and health risks.

Modeling studies have highlighted that accurate simulations of radiative effect of black carbon (BC) require knowledge about the particle size and mixing state of freshly emitted BC from combustion sources. However, the information is absent in China due to lack of available measurements. In this study, we present the particle size and mixing state of fresh BC emitted from diesel vehicles (DV), brick kilns (BK), residential crop residue burnings (CR), and residential firewood burnings (FW) in September-October 2014 at North China Plain by field measurement. The mass median diameters of BC cores (whole particles including cores and coatings) above the limit of measurement (i.e.,70 nm) from these sources are ∼155 (∼194), ∼230 (∼306), ∼250 (∼438) and ∼273 (∼426) nm, respectively, and corresponding size ratios (i.e., mixing state) are ∼1.25, ∼1.33, ∼1.75, and ∼1.56, respectively. Compared with the values commonly used in model based on the laboratory experiments and the field measurements in developed countries, larger particle sizes and higher mixing sate of freshly emitted BC in China may enhance their light absorption and cloud condensation nuclei activities during atmospheric transport. The available data could be used to improve future model development on radiative effect of BC in China.

Medium-flow atmospheric samplers were used to collect particulate (PM2.5) and gaseous samples from the indoor kitchen of each of 35 randomly selected rural houses in North China while a meal was being cooked. The concentrations of 16 polycyclic aromatic hydrocarbons (PAHs) and 9 nitro-PAHs (NPAHs) in the samples were quantified by high-performance liquid chromatography (HPLC). This study provided the real PAH and NPAH pollution characteristics and carcinogenic risk produced by cooking in rural indoor kitchens in North China. The mean PAH and NPAH concentrations in air in the indoor kitchens during cooking periods were 4049.1 and 1741.6 ng/m3, respectively. The PAH and NPAH concentrations were lower in the particulate phase than the gaseous phase. The mean PAH and NPAH concentrations were much higher for cooking using coal than for cooking using liquefied petroleum gas (LPG) or electricity. The PAH and NPAH benzo[a]pyrene toxic equivalent (TEQBaP) concentrations for cooking using coal were 1823.3 and 2760.9 ng/m3, respectively. Lower PAH and NPAH concentrations were found in kitchens with than without range hoods. Range hoods decreased the PAH and NPAH TEQBaP concentrations by 68.8% and 61.9%, respectively. Appropriate fuel and ventilation choice will improve air pollution in indoor kitchens during cooking. The results provide important evidence for changing cooking habits and developing policies for cooking in rural China.

Diesel vehicle is an important source of black carbon (BC). A portable emission measurement system including a photo-acoustic extinctiometer and SEMTECH-LDV was used to measure the real-world emissions of 14 light-duty and heavy-duty diesel trucks (LDDTs and HDDTs, meeting the China IV and China V standards) in Beijing. BC emission factors and the BC/PM2.5 ratio were obtained, and the effects of the vehicle type, emission standard and driving cycle on emissions were analyzed. The tightening of emission standards and the advancement of vehicle technology have reduced BC emissions from the China II standard to the China V standard. The emission reductions of BC are lower than those of other components of PM2.5 from the China II standard to the China IV standard but higher from the China IV standard to the China V standard. The BC and PM2.5 had the same main sources for the HDDTs and China IV LDDTs but had different sources for the China V LDDTs having diesel particulate filters. The BC/PM2.5 ratios of LDDTs, and HDDTs decreased from the China IV standard to the China V standard by 97.2% and 38.2%, respectively. The BC/PM2.5 ratio for China V LDDTs was 10 to 20 times lower than that for other diesel vehicles. The BC emissions tested under the highway driving cycle were 39.4% ± 16.7% lower than those under the no-highway driving cycle, but the BC/PM2.5 ratios had the opposite tendency. More China V and China VI heavy-duty diesel vehicles equipped with diesel particulate filters need to be tested to obtain more accurate BC/PM2.5 data and to improve the readiness of emission inventory calculations. The findings of this study help clarify the BC emission characteristics of diesel vehicles on actual roads and provide scientific basis for the formulation of emission control strategies for diesel vehicles in China.

Biofuel stoves are an important source of black carbon (BC) emissions, which have adverse effects on the environment and human health, especially in rural areas. However, there have been only limited studies of BC emissions from residential biofuel stoves based on real-time measurements. In this study, a photo-acoustic extinctiometer (PAX)-based real-time measurement system was employed to monitor the emission characteristics of corncobs, corn stalks, cotton stalks and poplar branches in simple or improved stoves (with a total of 16 units) in Hebei Province, China. The real-time and phased emissions of BC, fine particulate matter (PM2.5), carbon monoxide (CO) and carbon dioxide (CO2) were assessed, and the effects of stove type and fuel on emissions were analyzed. Under the same conditions, polar branches were associated with the highest BC emission factors (EFs) of up to 2.64 ± 0.42 g kg−1, while the EFs for improved stoves were higher than those for simple stoves. During the ignition phase, BC emissions were found to be low, while the later addition of fuel dramatically increased emissions, followed by a gradual decrease until the next fuel addition. The phased results show that the flaming phase had the highest BC emission rate, the fuel addition phase was associated with the highest BC EF. The BC emission rates and EFs for the ignition, fuel addition, flaming and smoldering phases ranged from 0.0014–0.014, 0.11–6.32, 0.18–2.24 and 0.03–0.32 mg s−1, and from 0.04–0.18, 0.38–9.53, 0.45–3.55 and 0.12–1.01 g kg−1, respectively. This study assessed the BC emissions from residential biofuel stoves using a larger sample size than in prior work. The results increase our understanding of the BC emissions process, which is helpful in terms of improving the accuracy of BC EF estimations. The real-time measurement process described herein is also expected to provide new approaches to minimizing BC emissions.

The concentrations and characteristics of 16 polycyclic aromatic hydrocarbons (PAHs) in 48 oil samples randomly collected from 30 catering services that employ six cooking methods were quantified via high-performance liquid chromatography (HPLC). These 16 PAHs were detected in almost all of the samples. The levels of Σ16PAHs, Σ4PAHs, benzo[a]pyrene (BaP), and total BaP equivalents (ΣBaPeq) for the six cooking methods exceeded the legal limit. The concentrations of Σ4PAHs were approximately 9.5 to 16.4 times the legal limit proposed by the European Commission (Off J Eur Union 215:4-8, 2011), and the level of BaP exceeded the national standard in China by 4.7- to 10.6-fold, particularly in oil from fried foods. Low molecular weight PAHs (LMW PAHs) were predominant in fried food oil from different catering services and accounted for 94.8 % of these oils, and the ΣBaPeq of the high molecular weight PAHs (HMW PAHs) was 11.5-fold higher than that of the LMW PAHs. The concentrations of Σ16PAHs (3751.9-7585.8 μg/kg), Σ4PAHs (144.6-195.7 μg/kg), BaP (79.7-135.8 μg/kg), and ΣBaPeq (231.0-265.4 μg/kg) were highest in the samples from fast food restaurants/buffets (FB), followed by those from fried food stalls (FS) and then cooking restaurants/cafeterias (RC). The results of this study suggest that the government should strengthen control and supervision of PAH contamination in food and edible oils.

With the increasingly strict supervision of road mobile sources and the ongoing progress in research, the relative contribution of non-road mobile sources to the total emissions has grown in prominence. Therefore, accurately estimating the emissions from non-road mobile sources is essential to developing effective policies for improving air quality. Hence, this study established an inventory of nine air pollutants, viz., CO, NOx, HC, PM2.5, PM10, BC, OC, VOCs, and SO2, emitted by four types of non-road mobile sources, viz., construction machinery, agricultural machinery, vessels, and diesel locomotives, in China for the period 1990–2017. These emissions increased continually from 1990 till 2014, after which they decreased before increasing again during 2017. With the exception of SO2, which primarily originated from vessels, agricultural machinery accounted for the largest proportion of emissions for all of the pollutants, contributing 67.7% (1472.5 Gg) and 46.1% (2170.4 Gg) of the total CO and NOx from non-road mobile sources, respectively. Additionally, the spatial distribution of the investigated pollutants revealed high concentrations on the North China Plain and in the Southeast China coastal area. Our findings demonstrate the necessity of improving the registration system for non-road mobile sources as well as the urgency of obtaining accurate emission factors for them by further researching their emission characteristics.

The polycyclic aromatic hydrocarbon (PAH) and nitro-polycyclic aromatic hydrocarbon (NPAH) emissions from 16 gasoline passenger cars, encompassing five emission standards and two driving conditions, were tested using a portable emission measurement system (PEMS) in Beijing under on-road conditions. In total, 16 PAHs and 9 NPAHs were quantified in both the gaseous and particulate phases by high-performance liquid chromatography (HPLC). The results indicated that lower PAH and NPAH emissions were observed with improved emission standards, especially for China 3 to China 5 vehicles (P 0.05). Higher emission factors (EFs) were detected on nonhighway roads than on highway roads due to incomplete combustion. Although most PAHs and NPAHs were in the gas-phase, the TEQ

To mitigate NOx and other emissions from diesel vehicles, China I, China II, China III and China IV emissions standards for new vehicles have been implemented nationwide. However, recent on-road measurements using a portable emission measurement system (PEMS) have revealed no significant reductions in the NOx emissions factors of diesel trucks due to the change from China II emissions standards to the more stringent China III standards. Thus, it is important to understand the effect of the China IV emissions standard on NOx emissions. In this study, nine China III and nine China IV diesel trucks of three sizes (light-duty diesel trucks (LDDTs), medium-duty diesel trucks (MDDTs) and heavy-duty diesel trucks (HDDTs)) were tested on real roads in Beijing using a PEMS. Compared to the tested China III diesel trucks, the China IV diesel trucks showed significant reductions of the average NOx emissions factors in terms of both distance travelled and fuel consumption. However, the driving conditions had an important impact on the reduction. Under non-highway driving (NHD), several of the tested China IV diesel trucks experienced no reduction or an increase in NOx emissions compared to their China III counterparts. The NOx emissions factors of the 18 tested diesel trucks under NHD were on average 1.5-times greater than those under highway driving (HD), and the effects on NOx emissions removal from China III to China IV diesel trucks were greater under HD than under NHD. In addition, no significant reduction of NOx based on fuel consumption for China IV diesel trucks was observed for MDDTs and HDDTs compared to the test results for similar China II vehicles reported in a previous study. To reduce NOx emissions in China, additional control measures of vehicular NOx emissions should be formulated.

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

This paper estimates the energy consumption and CO2 emissions from China’s urban passenger transportation sector up to year 2030. A “bottom-up” methodology is developed to estimate the emissions based upon passenger travel behaviors in cities, which is notably different from popular existing approaches that calculate emissions from vehicular population. This methodology enables policy analysts to (1) quantify how different urban development strategies and patterns would affect about CO2 emissions; (2) directly link behavioral changes with urban development patterns and policies; and (3) analyze and understand the sensitivities of the urban passenger transportation sector in responding to both national- and city-level policies for carbon mitigation, thus helping the policy evaluation and development. Detailed information regarding urban passenger travels are collected in grouped Chinese cities of six categories. With the newly developed methodology, total carbon emissions from China’s urban passenger transportation sector under three scenarios are considered. The results showed that mode choice changes are the most sensitive to policies. Promoting public transportation and limiting car usage can contribute 21% of the total energy reduction of China’s transportation sector in 2030. Enhancing the above by optimizing street network and urban form, this contribution can be doubled in size.

This paper, which focuses on diesel trucks, is the third in a series of three papers published in Atmospheric Environment to understand vehicle emissions in China by conducting on-board emission measurements. Diesel trucks are a significant source of emissions in ambient air, especially for NOx. Recently, China announces an aggressive target to reduce national NOx emissions by 10% from 2010 to 2015 in the “Twelfth Five-Year Plan (2011–2015)” and diesel vehicles are identified as a key target for NOx control. However, the understanding of the real-world emissions of diesel trucks is limited. In this study, we measured HC, CO, NOx, and PM 2.5 emissions from 175 diesel trucks of different sizes and technologies in five Chinese cities during 2007 and 2011, and generated emission factors on the basis of the measurements. The results show that the HC, CO, and PM 2.5 emission factors have been reduced significantly as the emission standards become more stringent from Euro 0 to Euro IV, but the NOx emission factors change differently. Euro II trucks have 3–6% higher NOx emission levels than Euro I technologies and Euro III trucks fail to show a reduction as regulated by the standards. More stringent NOx requirements (e.g. Euro IV) for diesel vehicles need to be enforced. The comparison with the emission factors used in recent emission inventory studies shows that these inventories may have overestimated or underestimated diesel emissions for the years after 2006. This study emphasizes the importance of conducting local measurement research to improve the accuracy of the estimates of mobile emissions in China.

Vehicle-use intensity (kilometers traveled per vehicle per year or VKT) is important because it directly affects simulation results for vehicle fuel use and emissions, but the poor understanding of VKT in China could significantly affect the accuracy of estimation of total fuel use and CO2 emissions, and thus impair precise evaluation of the effects of associated energy and environmental policies. As an important component of our work on the Fuel Economy and Environmental Impacts (FEEI) model, we collected VKT survey data in China from available sources and conducted additional surveys during 2004 and 2010, from which we derived VKT values and VKT-age functions by vehicle type for China. We also projected the future VKT for China by examining the relationship of vehicle use to per-capita GDP in 20 other countries worldwide. The purpose of this work is to achieve a better understanding of vehicle-use intensity in China and to generate reliable VKT input (current and future VKT levels) for the FEEI model. The VKT results obtained from this work could also benefit other work in the field associated with vehicle energy use and emissions.

One of the principal ways to reduce transport-related energy use is to reduce fuel-consumption rates of motor vehicles (usually measured in liters of fuel per 100 km). Since 2004, China has implemented policies to improve vehicle technologies and lower the fuel-consumption rates of individual vehicles. Policy evaluation requires accurate and adequate information on vehicle fuel-consumption rates. However, such information, especially for Chinese vehicles under real-world operating conditions, is rarely available from official sources in China. For each vehicle type we first review the vehicle technologies and fuel-economy policies currently in place in China and their impacts. We then derive real-world (or on-road) fuel-consumption rates on the basis of information collected from various sources. We estimate that the real-world fuel-consumption rates of vehicles in China sold in 2009 are 9 L/100 km for light-duty passenger vehicles, 11.4 L/100 km for light-duty trucks, 22 L/100 km for inter-city transport buses, 40 L/100 km for urban transit buses, and 24.9 L/100 km for heavy-duty trucks. These results aid in understanding the levels of fuel consumption of existing Chinese vehicle fleets and the effectiveness of policies in reducing on-road fuel consumption, which can help in designing and evaluating future vehicle energy-efficiency policies.

This paper is the second in a series of three papers aimed at understanding the emissions of vehicles in China by conducting on-board emission measurements. This paper focuses on light-duty gasoline vehicles. In this study, we measured 57 light-duty gasoline vehicles (LDGVs) in three Chinese mega-cites (Beijing, Guangzhou, and Shenzhen), covering Euro 0 through Euro IV technologies, and generated CO, HC, and NOx emission factors and deterioration rates for each vehicle technology. The results show that the vehicle emission standards have played a significant role in reducing vehicle emission levels in China. The vehicle emission factors are reduced by 47–81%, 53–64%, 46–71%, and 78–82% for each phase from Euro I to Euro IV. Euro 0 vehicles have a considerably high emission level, which is hundreds of times larger than that of Euro IV vehicles. Three old taxis and four other Euro I and Euro II LDGVs are also identified as super emitters with equivalent emission levels to Euro 0 vehicles. Of the measured fleet, 23% super emitters were estimated to contribute 50–80% to total emissions. Besides vehicle emission standards, measures for restricting super emitters are equally important to reduce vehicle emissions. This study is intended to improve the understanding of the vehicle emission levels in China, but some key issues such as emission deterioration rates are yet to be addressed with the presence of a sufficient amount of vehicle emission measurements.

Recently, China has implemented many policy measures to control the oil demand of on-road vehicles. In 2010, China started to report the fuel consumption rates of light-duty vehicles tested in laboratory and to require new vehicles to show the rates on window labels. In this study, we examined the differences between the test and real-world fuel consumption of Chinese passenger cars by using the data reported by real-world drivers on the internet voluntarily. The sales-weighted average fuel consumption of new cars in China in 2009 was 7.80 L/100 km in laboratory and 9.02 L/100 km in real-world, representing a difference of 15.5%. For the 153 individual car models examined, the real-world fuel consumption rates were −8 to 60% different from the test values. The simulation results of the International Vehicle Emission model show that the real-world driving cycles in 22 selected Chinese cities could result in −8 to 34% of changes in fuel consumption compared to the laboratory driving cycle. Further government effort on fuel consumption estimates adjustment, local driving cycle development, and real-world data accumulation through communication with the public is needed to improve the accuracy of the labeling policy.

We propose a method to simulate vehicle emissions in Chinese cities of different sizes and development stages. Twenty two cities are examined in this study. The target year is 2007. Among the cities, the vehicle emission factors were remarkably different (the highest is 50–90% higher than the lowest) owing to their distinct local features and vehicle technology levels, and the major contributors to total vehicle emissions were also different. A substantial increase in vehicle emissions is foreseeable unless stronger measures are implemented because the benefit of current policies can be quickly offset by the vehicle growth. Major efforts should be focused on all cities, especially developing cities where the requirements are lenient. This work aims a better understanding of vehicle emissions in all types of Chinese cities. The proposed method could benefit national emission inventory studies in improving accuracy and help in designing national and local policies for vehicle emission control.

As stricter standards for diesel vehicles are implemented in China, and the use of diesel trucks is forbidden in urban areas, determining the contribution of light-duty gasoline vehicles (LDGVs) to on-road PM2.5 emissions in cities is important. Additionally, in terms of particle number and size, particulates emitted from LDGVs have a greater health impact than particulates emitted from diesel vehicles. In this work, we measured PM2.5 emissions from 20 LDGVs in Beijing, using an improved combined on-board emission measurement system. We compared these measurements with those reported in previous studies, and estimated the contribution of LDGVs to on-road PM2.5 emissions in Beijing. The results show that the PM2.5 emission factors for LDGVs, complying with European Emission Standards Euro-0 through Euro-4 were: 117.4 ± 142, 24.1 ± 20.4, 4.85 ± 7.86, 0.99 ± 1.32, 0.17 ± 0.15 mg/km, respectively. Our results show a significant decline in emissions with improving vehicle technology. However, this trend is not reflected in recent emission inventory studies. The daytime contributions of LDGVs to PM2.5 emissions on highways, arterials, residential roads, and within urban areas of Beijing were 44%, 62%, 57%, and 57%, respectively. The contribution of LDGVs to PM2.5 emissions varied both for different road types and for different times.

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions (CO, NMHC, NOx, and PM2.5) for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

To guarantee good traffic and air quality during the 16th Asian Games in Guangzhou, China, the government carried out two traffic control Drills before the Games and adopted traffic control measures during the Games. Vehicle activities before and during the first and second Drills, and during the Games, were surveyed. Based on the data under investigation, the impacts of control measures on traffic volumes and driving characteristics were analyzed during the first and second Drills, and the Games. The emission reduction of traffic control measures was also evaluated during the three stages using the MOBILE-China model. The results show that there were significant effects of implementing temporary traffic control measures on transportation activity and vehicular emissions. During the first and second Drills, and the Games, the average traffic volumes in monitored roads decreased, and the average speed of vehicles increased significantly The co-effects of traffic flow reduction, traffic congestion improvement, and the banning of high-emitting vehicles helped to greatly reduce the estimated emissions from motor vehicles in Guangzhou during the first and second Drills, and the Games. Estimated vehicular emissions were reduced by 38-52% during the first Drill and 28-36% for the second Drill. During the Asian Games, vehicular emissions of carbon monoxide (CO), hydrocarbon (HC), oxides of nitrogen (NO), and particulate matter with an aerodynamic diameter10 microm (PM10) reduced by an estimated 42%, 46%, 26%, and 30%, respectively, compared with those before the Games. Both the banning of high-emitting vehicles and the travel restrictions imposed by use of odd-even licenses had significant effects on the reduction of vehicular emissions of CO, HC, NOx, and PM10.Motor vehicles have become the most prevalent source of emissions and subsequently air pollution within Chinese cities. Understanding the impacts that different control measures have on vehicular emissions is very important in order to be able to control vehicle emissions. The results of this study will be very helpful for the further control of vehicle emissions in Guangzhou in the future. In addition, the effects of temporary transportation control measures will provide important awareness to other cities that will be hosting large-scale activities similar to the Asian Games.

We propose a new link-based, bottom-up vehicle emission inventory method for Chinese cities using available on-road emission measurement data and activity survey data. This study uses Beijing as a case study and focuses on CO, HC, and NOx emissions from hot-stabilized activities of light-duty vehicles. The target year is 2004. The total quantity of emissions, emission intensity, temporal distribution of emissions by hour, and spatial distribution of emissions at 1 km x 1 km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total emissions from light-duty vehicles in the Beijing urban area in 2004 were 1141 Mg of CO per day, 48 Mg of HC per day, and 32 Mg of NOx per day. Pollutant emissions from mobile sources show temporal and spatial variation trends that are consistent with the characteristics of people's activities. The inventory developed in this study reflects the influences of vehicle driving patterns in traffic on vehicle emissions on a road link basis, and it could be used to evaluate the impacts of traffic-related emission control measures in China.

On-board emission measurements were performed on 49 light-duty gasoline vehicles in seven cities of China. Vehicle-specific power mode distribution and emission characteristics were analyzed based on the data collected. The results of our study show that there were significant differences in different types of roads. The emission factors and fuel consumption rates on arterial roads and residential roads were approximately 1.4-2 times those on freeways. The carbon monoxide, hydrocarbon, and nitrogen oxides emission factors of Euro II vehicles were on average 86.2, 88.2, and 64.5% lower than those of carburetor vehicles, respectively. The new vehicle emission standards implemented in China had played an important role in reducing individual vehicle emissions. More comprehensive measures need to be considered to reduce the total amount of emissions from vehicles.