City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region

JES-00981; No of Pages 13 J O U RN A L OF E N V I RO N ME N TA L S CI EN CE S X X (2 0 1 6 ) XX X–XXX

Available online at www.sciencedirect.com

ScienceDirect www.elsevier.com/locate/jes

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Shaojun Zhang1 , Ye Wu2,3,⁎, Bin Zhao4 , Xiaomeng Wu2 , Jiawei Shu2 , Jiming Hao2,3

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1. University of Michigan, Department of Mechanical Engineering, Ann Arbor, MI 48109, USA 2. Tsinghua University, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing 100084, China 3. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China 4. Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California 90095, USA

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City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region

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AR TIC LE I NFO

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Article history:

The Yangtze River Delta (YRD) region is one of the most prosperous and densely populated 19

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Received 13 January 2016

regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve 20

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Revised 30 May 2016

air quality. Our assessment has revealed that mitigating vehicle emissions of NOx would be 21

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Accepted 1 June 2016

more difficult than reducing the emissions of other major vehicular pollutants (e.g., CO, HC 22

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Available online xxxx

and PM2.5) in the YRD region. Even in Shanghai, where the emission control implemented are 23

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Keywords:

emissions from 2000 to 2010. Emission–reduction targets for HC, NOx and PM2.5 are determined 25

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Vehicle

using a response surface modeling tool for better air quality. We design city-specific emission 26

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Emission control

control strategies for three vehicle-populated cities in the YRD region: Shanghai and Nanjing 27

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Scenario

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Yangtze River Delta

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more stringent than in Jiangsu and Zhejiang, we observed little to no reduction in NOx 24

and Wuxi in Jiangsu. Our results indicate that even if stringent emission control consisting of 28 the Euro 6/VI standards, the limitation of vehicle population and usage, and the scrappage of 29

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older vehicles is applied, Nanjing and Wuxi will not be able to meet the NOx emissions target 30

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by 2020. Therefore, additional control measures are proposed for Nanjing and Wuxi to further 31 © 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. 33

Introduction

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China has undergone extraordinary economic growth over the past three decades. However, this growth has been accompanied by a surge in energy consumption and serious air pollution (NBSC, 2014; Xing et al., 2011a; Wang and Hao, 2012). For example, extremely high pollution levels of major pollutants (e.g., fine particulate matter less than 2.5 μm in diameter, PM2.5, and nitrogen dioxide, NO2) were recently observed over the coastal

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mitigate NOx emissions from heavy-duty diesel vehicles. Published by Elsevier B.V.

areas of East China both in situ and from space (Wang et al., 2011a; Cheng et al., 2013; Richter et al., 2005), and these high pollutant levels have negatively influenced public health, climate and agriculture (Shindell et al., 2011; Tong et al., 2012, 2015). For many megacities in these areas (e.g., Beijing, Shanghai, and Guangzhou), the air pollution patterns have clearly shifted from coal-based pollution to a mixture of coal- and vehicle-based pollution, and on-road vehicles are considered to be one of the most important sources of airborne PM2.5 (Wu et al., 2011; China

⁎ Corresponding author. E-mail: [email protected] (Ye Wu).

http://dx.doi.org/10.1016/j.jes.2016.06.038 1001-0742/© 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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1.1. Trends in vehicle population, annual mileage and fleet 138 configuration 139 During 2000–2010, the total vehicle population in the YRD increased from 8.7 million to 27.4 million, primarily because of the surge in light-duty passenger vehicles (LDPVs) (see Fig. S1) (NBSC, 2014). Previous studies have reported that the Gompertz function is a reasonable model for relating the LDPV ownership rate to economic development (Wu et al., 2012b). Therefore, we predict the future trends in the LDPV populations of Nanjing and Wuxi using city-specific fitted Gompertz functions (see Fig. S2) based on the historic census data for these cities. Notably, Shanghai has a significantly lower LDPV ownership rate than other cities in China's three developed regions (see Table S2) due to its long history of restricting LDPV purchase (i.e., license control policies), which began in 1994 (Hao et al., 2011). For other vehicle classifications, we predicted their future populations based on historical trends and several relevant policies. For example, a substantial surge in truck stocks in the YRD region occurred in approximately 2010 because of a package of economic stimulation measures that began in late 2008. After 2011, the role of those policies in the truck market became less significant, and the shift from light-duty and medium-duty trucks (i.e., LDTs and MDTs) to heavy-duty trucks (HDTs) is clearly observed. In addition, use restrictions for motorcycles have been adopted in several cities (e.g., Nanjing and Wuxi) within the YRD region since 2000, leading to a decline in the motorcycle population since 2007. The projected total vehicle population of Shanghai, Nanjing and Wuxi was predicted to increase to 3.6 million, 2.4 million, and 1.9 million, respectively, under the business-as-usual (BAU) and moderate scenarios (see Fig. 1, and refer to Table 3 for the definition of scenarios). In particular, the share of LDPVs is projected to increase to 73% in Shanghai, 82% in Wuxi and 88% in Nanjing, whereas the motorcycle population is projected to decline. In this study, we estimate the annual vehicle kilometers traveled (VKT) for each fleet in the YRD based on previous surveys in China (Zhang et al., 2013, 2014a) and recently collected vehicle mileage data from Nanjing. Table 1 provides the estimated fleet-average annual VKT for major vehicle categories and their definitions in 2000, 2010 and 2020. Taking the LDPV fleet as an example, their fleet-average annual VKT is observed to have decreased and this decrease is primarily

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are usually more vague and less stringent than those actually adopted in more motorized cities (e.g., Beijing, Shanghai). In this study, we first evaluate the historic trends in total vehicle emissions of the YRD region and highlight the many difficulties from historical and international perspectives. Second, stringent reduction targets for vehicular emissions of HC, NOx and PM2.5 are proposed. We investigate the local features of these three representative cities (e.g., Shanghai, Nanjing and Wuxi) and design city-specific plans for emission control strategies and measures through 2020. This paper provides policy-makers with a prospective understanding of future vehicle emission controls in China for improving urban air quality, which can only be achieved through great effort.

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Daily, 2015). Furthermore, recent studies have indicated that vehicular emissions of nitrogen oxides (NOx) and hydrocarbons (HC) play a role in the formation of secondary inorganic and organic aerosols during episodes of severe haze, which might be underestimated by existing atmospheric models (He et al., 2014; Guo et al., 2014; Robinson et al., 2007; Gordon et al., 2014). In response to regional and urban air pollution, China's Central Government has released a series of policies and regulations to reduce urban air pollution. For instance, China's government set a 10% mitigation target for national anthropogenic NOx emissions during the period of the “Twelfth Five Year Plan” (12th FYP, i.e., 2011–2015) (Wu et al., 2012a). In 2012, China's State Council approved the National Ambient Air Quality Standard (NAAQS) Amendment (MEP and AQSIQ, 2012). This legislation tightened the concentration limits for nitrogen dioxide (NO2) and inhalable particulate matter with diameters less than 10 μm (PM10) and also added limits on annual and 24-hr average PM2.5 concentrations and the 8-hr average ozone (O3) concentration, as recommended by the World Health Organization's interim targets (see the Grade II limits for regular areas in Table S1). In 2013, China's State Council released its Action Plan for Air Pollution and Control for improving overall air quality across the nation and reducing the number of severely polluted days by 2017 (State Council, 2013). Additionally, certain megacities, such as Beijing and Shanghai, also published city-level Clean Air Action Plans 2013–2017, which contain stringent and comprehensive emission control measures to be implemented in the near future (Beijing Municipal Government, 2013; Shanghai Municipal Government, 2013; Zhang et al., 2014a). More recently, PM2.5 source apportionment studies in nine major cities have revealed that on-road vehicle emissions have become the most significant local source of ambient PM2.5 concentrations in five cities (Beijing, Shanghai, Guangzhou, Shenzhen and Hangzhou), where the total vehicle population has exceeded 2.5 million (MEP, 2015). Therefore, for municipal policy makers, the priority of controlling vehicles to improve air quality has become increasingly significant, particularly in relatively more motorized cities in East China. The Yangtze River Delta (YRD) region, geographically consisting of Shanghai Municipality, Jiangsu Province and Zhejiang Province, is one of the most prosperous regions in China and is also one of the most densely populated sectors adjacent to metropolitan areas worldwide. Although its geographical area constitutes only 2.2% of China's total area, the YRD region in 2013 contained 12% of the resident population and 15% of the vehicle stock (not including motorcycles and rural vehicles), contributing 20% of China's gross domestic product (GDP) (NBSC, 2014). However, the YRD region is currently facing great challenges to the improvement of air quality and must accelerate its future vehicle emission control policies and practices to maintain its social development and urbanization. It should be noted that most studies regarding future vehicle emission trends in China primarily focused emission inventories (more about CO2) at the national or provincial levels, and lacked clear associations with the improvement of air quality (Zhang et al., 2014a; Huo et al., 2012, 2014; Saikawa et al., 2011). In reality, due to the highly spatial heterogeneity in China, the emission control requirements at a broader level (e.g., the national level required by Ministry of Environmental Protection)

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Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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Historical

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Fig. 1 – Historic trends and future projections of registered vehicle populations in (a) Shanghai, (b) Nanjing and (c) Wuxi under the designed BAU and moderate scenarios from 2000 to 2020. Taxis and public busses are included in the LDPV and MDPV & HDPV categories in this figure. BAU: business-as-usual; LDPV: light-duty passenger vehicle.

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Light-duty passenger vehicle (LDPV) Medium-duty passenger vehicle (MDPV) d Heavy-duty passenger vehicle (HDPV) d Light-duty truck (LDT) d Medium-duty truck (MDT) d Heavy-duty truck (HDT) d Public bus Taxi Motorcycle

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We estimate the historic trends in fleet-average emission factors and total vehicle emissions of major air pollutants (CO, HC, NOx and PM2.5) using the following two equations (Zhang et al., 2014a), respectively:

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VPF f ;i;p  VKT f ;i  EF f ;i; j;p

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Table 1 – Estimated fleet-average annual VKT by vehicle category in the YRD from 2000 to 2020. Vehicle classification (abbreviation)

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1.2. Assessment of the trends in vehicle emissions in the YRD 211 region 212

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attributed to the increasing share of privately owned cars in the total LDPV fleet. We estimated that the decreasing trend will continue, with a fleet-average annual VKT of the LDPV

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fleet in the YRD of approximately 16,000 km in 2020. Notably, aggressive traffic management controls have been implemented in several cities to ease traffic pressure and mitigate vehicle emissions. For example, restrictions on car use that permit driving on only four weekdays per week have continued as a long-term policy in Beijing since October 2008 (Zhang et al., 2014a, 2014d). Therefore, the vehicle-use intensity for LDPVs in the YRD region, particularly in congested urban areas, might be lowered if similar driving restrictions for LDPVs are adopted within the YRD region. In terms of fleet configuration, vehicle population allocation by fuel type and emission standard category for each vehicle classification (see Table S3) are investigated and estimated based on statistical data and previous studies (NBSC, 2014; Zhang et al., 2014a; Wu et al., 2012b). The YRD region has gradually tightened emission standards for all vehicle classifications since 2000 (see Table S4), with Shanghai tending to implement emission standards earlier than the national requirements and the schedules of the provinces of Jiangsu and Zhejiang. Furthermore, it is worth noting that substantial alternative fuels and advanced vehicle technologies began penetrating the vehicle market in this region circa 2010 due to the availability of abundant fuel (e.g., natural gas), mature technologies and economic policies. For example, the population of compressed natural gas (CNG) busses in Nanjing and Wuxi was ~ 10% of the total public bus fleet by 2010 (~ 600 CNG busses in Nanjing and ~400 CNG busses in Wuxi).

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Registered vehicle population (×106)

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Registered vehicle population (×106)

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Description

PC ≤ 9 a 9 < PC ≤ 20 PC > 20 GVW < 4500 kg b 4500 ≤ GVW < 12,000 kg GVW ≥ 12,000 kg

Fleet-average annual VKT (km) 2000

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20,000 26,000 60,000 25,000 35,000 52,000 71,000 123,000 5000

16,000 27,000 60,000 23,000 46,000 55,000 71,000 123,000 5000

Passenger capacity. Gross vehicle weight. c Estimations under the BAU and moderate scenarios (defined previously) for three typical cities. d Heavy-duty diesel vehicle (the abbreviation HDDV used in this paper) fleets include diesel-powered MDPVs, HDPVs, LDTs, MDTs, HDTs and public busses. b

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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It should be noted that emission reduction targets for major air pollutants within China are not clear or lack associations with air quality in most previous studies (Zhang et al., 2014a; Huo et al., 2014), which is an issue of most concerns to policy-makers. Considering that the YRD region has a very high population density, even if vehicle emission factors could be reduced to a certain low level (e.g., comparable to that in developed countries), air pollution risks may still remain. In this study, targets for mitigating vehicle emissions are proposed according to both the official emission abatement objectives (e.g., mainly focused on NOx) during the 12th FYP (e.g., 2011 to 2015) (MEP, 2012) and the limits on key pollutants (i.e., PM2.5 and O3) in the newly revised NAAQs. Shanghai, Jiangsu and Zhejiang are supposed to reduce total anthropogenic NOx emissions by 17.5%, 17.5% and 18%, respectively, during the 12th FYP, an objective that is more rigorous than the national reduction target (i.e., 10%).

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Table 2 – Estimated mitigation targets for primary vehicle emissions to improve air quality.

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where EFf, j, p (g/km) is the fleet-average emission factor of pollutant j for vehicle fleet f in province p (i.e., Jiangsu, Shanghai and Zhejiang), VPFf, j, p is the vehicle population fraction of emission category i for vehicle fleet f in province or city p; VKTf, i (km) is the average annual VKT of vehicle fleet f and emission standard category i, as summarized in Table 1; Ej, p (ton) is the total emission of pollutant j for province p; VPf, p is the population of vehicle fleet f in province p; and VKTf, p (km) is the fleet-average annual VKT for vehicle fleet f in province p. The EMBEV model is used to derive the emission factors for different vehicle categories in this study. This model was developed based on a number of vehicle emission measurements for gasoline LDPVs (Zhang et al., 2014a), diesel cars (Hu et al., 2012), heavy-duty diesel vehicles (HDDVs) (Wu et al., 2012a, 2015), motorcycles (Zhou et al., 2014) and alternative fuel vehicles (Zhang et al., 2014b). A detailed description of the EMBEV model together with a case study of Beijing is provided by Zhang et al. (2014a). Local features (e.g., environmental conditions and fuel quality) and fleet configuration (see Table S3) were taken into consideration in estimating fleet-average emission factors for the YRD region with the EMBEV model (Wu et al., 2016). In particular, there were significant mismatches between the vehicle emission standards with their required fuel specifications and the actual sulfur contents of the gasoline and diesel combusted (see Table S4). Influences on emission factors of high actual sulfur content have also been assessed based on the fuel quality correction matrix of the EMBEV model (Zhang et al., 2014a). Moreover, according to detailed vehicle specification data in Nanjing, an upsizing trend has been identified for diesel trucks, which may lead to an increase of approximately 10% in NOx emission factors from 2000 to 2010 compared the estimation without a consideration of the vehicle size change. The uncertainties in vehicle emissions of major air pollutants are characterized using a Monte Carlo stochastic simulation method with the Crystall Ball™ software package (Zhang et al., 2014a).

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With regard to the attainment of the NAAQs, we use the RSM technique, a real-time emission control/air quality response tool, to assess air quality benefits and determine emission reduction targets (Wang et al., 2011b). RSM applies advanced statistical techniques to characterize the relationships between air quality responses and emission changes for primary pollutants in a highly efficient manner. The RSM tool applied in this study was developed based on China's emission inventory in 2005 (Wang et al., 2011b; Xing et al., 2011b; US EPA, 2006) using the Community Multi-scale Air Quality model (CMAQ), which includes the YRD region at a 12 × 12-km spatial resolution, and the outputs have been validated through comparison with satellite observations and ground monitoring data. The RSM tool can calculate both the responses of O3 concentrations to changes in NOx and HC emissions (Xing et al., 2011b) and the responses of PM2.5 concentrations to changes in NOx, NH3, SO2, HC and primary PM2.5 emissions (Wang et al., 2011b). The emission ratios of primary pollutants in the future compared to 2005 levels are required as input data for the RSM tool. For SO2, whose emissions are primarily attributed to coal-fired sectors (e.g., power units, industrial and residential boilers), the estimated total emissions in the YRD in 2020 are 60% of those in 2005 because a continued decreasing trend in national SO2 emissions is forecasted because of a surge in operational flue gas desulfurization units. For NH3 that is dominantly contributed by the agricultural sector, we estimate similar levels of estimated emissions in 2020 and 2005 (Xing et al., 2011a). For vehicle-related pollutants, including NOx, HC and primary PM2.5, the required emission reduction ratios are optimized using the RSM tool to achieve better air quality in 2020. We assume that the relative emission reductions for on-road vehicles should be the same for other emission sources (e.g., power plants and industrial boilers). It should be noted that great uncertainties may remain in the present emission inventories for HC and NH3 as well as other pollutant species regarding distributed human activities (e.g., residential coal use in rural areas). Future research efforts are required to improve China's emission inventories, in particular about the distributional emission reductions among various sectors. For the urban area of Shanghai, to fully meet the limits by 2020, 75% of VOC, 65% of NOx, and 70% of primary PM2.5 will have to be reduced as compared to 2005 levels (see Table 2). Notably, mitigating NOx emissions from on-road vehicles is significantly more difficult than mitigating the vehicular emissions of other pollutants (e.g., HC and primary PM2.5)

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Percent of days meeting the new NAAQS

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NAAQS: National Ambient Air Quality Standard.

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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1.4. Designing emission control scenarios for three vehicle-populated cities in the YRD region

It should be noted that many vehicle control policies and measures are designed and enforced at the city level rather than a wider range (e.g., the provincial level), because they are necessarily integrated with other municipal policy interventions such as those associated with vehicle registration, traffic management and economic incentives. Therefore, emission control scenarios at the city level will be of more practical significance to municipal policy makers than those developed at a broader level. In this study, three cities with relatively high motorization levels—the municipality of Shanghai and the cities of Nanjing and Wuxi in Jiangsu Province—are selected for assessing the benefits of vehicle emission controls through 2020. Shanghai is the largest metropolis in the YRD region and is a leader among all cities in this region in controlling vehicle emissions (see Table S4). In addition to the early implementation of increasingly stringent emission standards, Shanghai was the first city in China to have adopted a license plate control policy to limit excessively rapid growth of vehicle population (1994) (see Table S2). Nanjing is the capital city of Jiangsu Province, and Wuxi is a medium-scale developed city in this province. By 2013, the ownership rates of LDPVs in Nanjing and Wuxi have both approached 150 vehicles per 1000 people. This indicates that they are undergoing a similar rapid motorization process of personal transportation. However, the various population

shares of freight trucks in total vehicle population (e.g., in 2013, 4% in Nanjing and 7% for Wuxi) would also result in various difficulties in mitigating emissions from heavy-duty diesel vehicles (HDDVs, see the footnote of Table 1) especially for NOx and PM2.5 emission control. In this study, future vehicle emission control packages primary consist of five components: (1) tightening new vehicle emission standards, (2) tightening fuel quality standards, (3) limiting new LDPV sales, (4) controlling vehicle-use intensity of LDPVs, (5) scrappage of older LDPVs, (6) and additional controls for HDDVs (see Table 3). The first two components cover all vehicle fleets including both LDPVs and HDDVs. The three components (3) to (5) focus on LDPVs and are highly associated with municipal traffic management and economic incentives. Furthermore, beyond those five control components above, additional controls for HDDVs would be generated, if necessary, since emission control measures actually conducted for HDDVs in China are less stringent compared with those for LDPVs. All of these emission control measures have been evaluated for effectiveness in Beijing, since most of China's cities follow all or part of the emission control strategies in Beijing, which are considered the most stringent in China (Wu et al., 2011; Zhang et al., 2014a). We generate three control scenarios (e.g., the BAU scenario, the moderate scenario and the strengthened scenario) according to the stringency for the three cities. Under the BAU scenario, no further emission control measures are adopted after 2010. Therefore, the future trends in emissions under the BAU scenario would depend on the combined influence of the penetration of new vehicles (e.g., Euro 4 gasoline LDPVs for Shanghai and Euro 3 gasoline LDPVs for Nanjing and Wuxi) and the natural scrappage of older vehicles. Under the moderate scenario, increasingly stringent emission standards will be implemented in the three cities, accompanied by the improvement in fuel quality required by emission standards (see Table S5). The implementation dates of more stringent emission standards are reasonably similar to their European counterparts and the recently released official projections for 2015–2020 (e.g., the Euro 6/VI emission standards are expected to begin in 2018). We further envision the emission factors for future vehicles as complying with more stringent emission standards based on recent measurement results and trends in future emission limits (see Table S6). Under the strengthened scenario, the future growth of the LDPV populations in Nanjing and Wuxi is estimated based on the historic trends in Shanghai instead of the estimates produced by the Gompertz function. Driving restrictions will also be implemented in Shanghai, Nanjing and Wuxi in which driving is allowed four weekdays per week. Under this scenario, the estimated annual fleet-average VKT of LDPVs would be reduced to approximately ~ 13,000 km in 2020 (Zhang et al., 2014a). Furthermore, LDPVs in the three cities with a vehicle age over 15 years will be phased out by 2020 under the strengthened scenario through the use of financial incentives. In addition, to further control of vehicle emissions for HDDVs (primarily NOx), we additionally include penetration of alternative fuel busses and scrappage and retrofit programs for diesel fleets (see Table 3).

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(Zhang et al., 2014a). Therefore, in this study, we set a relative relaxed goal of better air quality in 2020 that permits 10% of days to exceed the O3 concentration limit, thus enabling less strict reduction targets for NOx emissions (e.g., 30% or 25%). When 10% exceedance is allowed, two emission-reduction plans will be able to meet the relaxed target. In 2015, Zhao et al. (2015) updated the RSM technology for PM2.5 and key aerosol components. We have also tested the emission reduction trends from 2010 to 2020 in Shanghai can guarantee an attainment of the annual concentration limit of PM2.5 using the new RSM model (i.e., ERSM v1.0) (Zhao et al., 2015). Because of the lack of daily air quality data from other cities in the YRD, we assess the emission control scenarios for Nanjing and Wuxi (see the next section) based on the same reduction targets as those used for Shanghai in this study (note: real-time concentration data have been recently opened to the public, but historical records with detailed daily results are still not available). Wang et al. (2014b) reported various future emission control scenarios for China from 2005 to 2030, including a probable control scenario PC[1] and a further enhanced control scenario PC[2]. For on-road vehicles, the emission reductions suggested by Wang et al.'s (2014) scenarios PC[1] and PC[2] are both less stringent than the emission reduction targets determined in this study. Thus, this study can deliver detailed control packages if more stringent control targets for vehicle emissions are proposed. Besides, we acknowledge that relative emission reductions in the future may differ vastly across various sectors (Wang et al., 2014; Zhao et al., 2013, 2014) and efforts can be followed up to refine emission controls for other sectors on the city-level.

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Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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Table 3 – Emission control scenarios for the vehicle fleets in three cities in the YRD region, 2010–2020.

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Control scenarios

BAU Moderate

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Additional controls specifically for HDDVs

Fuel quality

Driving restriction for LDPVs

BAU b Tighten to the Euro 6/VI standards e Tighten to the Euro 6/VI standards e

BAU b Reducing sulfur content e Reduce sulfur content e

BAU c BAU c

Phasing out older LDPVs BAU d BAU d

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License control policies would only be implemented in Nanjing and Wuxi, since Shanghai has adopted its control policy of limiting new LDPVs since 1994. b No further implantation of more stringent standards for vehicle emissions and fuel quality later than 2010. c In 2020, annual VKT values of the LDPV fleet are estimated 16,000 km under the BAU and moderate scenarios and 13,000 km under the strengthened scenario. d Natural phasing out based on historical survival rates. e Future implementation schedule of more stringent standards are listed in Table S5, which are generated according to the most plausible progress in the YRD region. f Future annual increase rates of LDPVs in Nanjing and Wuxi are estimated comparable to that in Shanghai, where the license control policy has been implemented for more than two decades. g The proposed promotion plan includes battery electric busses and natural gas busses.

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Promote alternative fuel busses g, enforce scrappage and retrofit programs for older vehicles

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Additional controls for HDDVs

Stop driving one Phase out all License controls weekday per week c LDPVs with in Nanjing and Wuxi f vehicle age over 15 years by 2020

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License control for LDPVs

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2. Results

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2.1. Historic trends in total vehicle emissions in the YDR region

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The estimated total on-road vehicle emissions within the YRD region during 2010 were 3690 (2760–4830) kt of carbon monoxide (CO), 515 (398–704) kt of hydrocarbon (HC), 666 (504–842) kt of NOx and 41.0 (31.0–58.6) kt of PM2.5, at a 95% confidence level (95% CL) (see Fig. 2). For HC and CO emissions, motorcycles and LDPVs are major contributors among all vehicle categories, e.g., contributing 30% and 48% of the total HC vehicle emissions in 2010 (see Fig. S3). Regarding other emissions, HDDVs are major contributors, responsible for 74% of NOx and 87% of PM2.5 vehicle emissions in 2010. By retrospectively analyzing the data for decade during 2000– 2010, it appears that the upward trends in total vehicle emissions of HC and CO in the YRD region have effectively reversed relative to their peak values in approximately 2005, primarily attributed to strengthened vehicle emissions standards for gasoline LDPVs and driving restrictions on motorcycles. With regard to PM2.5 emissions, the improvement in engine combustion performance spurred by the increasingly stringent emission standards for HDDVs has played a crucial role in reducing vehicle PM2.5 emissions within the YRD region, which peaked at 43.0 kt in 2007. However, the significant increase in the HDT population during 2009–2010 offset the benefits of PM2.5 emission reduction from other control actions. For NOx, no rising inflection point of estimated vehicle emissions in the YRD region before 2010 is observed, primarily because of an unsatisfied

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improvement in real-world NOx emission factors for major diesel fleets (see Fig. S4) (Wu et al., 2012a). For area-specific emissions, the regional-average levels of HC, NOx and PM2.5 were 2.42 (1.87–3.30) ton/km2, 3.13 (2.37–3.95) ton/km2 and 0.19 (0.15–0.28) ton/km2, respectively, for the YRD region in 2010. Overall, a significantly higher intensity of vehicle emissions is observed in the YRD region compared to other developed countries or regions with similar land area (e.g., France, Germany and the United Kingdom in Europe (EEA, 2014); New York, California and Michigan in the U.S. (US EPA, 2015); for metropolitan areas in comparison with the municipality of Shanghai, we include the New York metropolitan area, the Los Angeles metropolitan area and the Greater London Area (GLA, 2010); see Fig. 3). For example, area-specific NOx emissions from on-road vehicles in the YRD region were 100%–200% higher than those of the international countries and regions (e.g., France, Germany, the United Kingdom, New York, California and Michigan), and the relative increment in the vehicular emissions of HC and PM2.5 were even greater, indicating a great environmental burden from the on-road transportation sector in the YRD region. As a city that leads in mitigating vehicle emissions within the YRD region, the peaks of estimated HC and CO vehicle emissions in Shanghai occurred in 2003, almost two years earlier than those in the entire YRD region. Because of the license control policy for LDPVs and the emission standards that were tightened earlier than in Jiangsu and Zhejiang (e.g., Euro 2 and Euro 4 standards, see Table S4), the total vehicle emissions of CO and HC were reduced in Shanghai by 36% and 44%, respectively, during 2000–2010. We also observed

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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a significantly decreasing trend in PM2.5 emissions from vehicles in Shanghai starting in 2007. However, the total vehicle emissions of NOx in Shanghai still exhibit a moderate but steady upward trend, with an annual increase rate of 2%. Furthermore, when we focused exclusively on the municipality of Shanghai in an effort to better understand the spatial heterogeneity of traffic density, we found that the estimated area-specific vehicle emissions for major precursor pollutants in Shanghai were significantly higher than those of international metropolitan areas (e.g., New York, Los Angeles, and London) (see Fig. 3). The only comparable case is NOx emissions in Shanghai and London (e.g., 17.8 ton/km2 vs. 15.1 ton/km2) due to the smaller scale and higher population density of the Greater London Area, which results in a higher traffic density. In addition, the light-duty diesel vehicles widely used in this European metropolitan area were estimated to account for 34% of the total NOx emissions from on-road vehicles in London (GLA, 2010; Carslaw et al., 2011). Therefore, international comparison reveals a great need for further lowering vehicle emission factors in Shanghai. Thus, by combining temporal and spatial dimensions and international comparisons, our work reveals that future vehicle emission control tasks for the YRD region will be confronted with substantial challenges. In particular, because current vehicle controls are insufficient to mitigate NOx emissions, more effective measures should be considered, with a special focus on real-world NOx emissions from HDDVs.

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Fig. 2 – Estimated trends in vehicle emissions of (a) CO, (b) HC, (c) NOx and (d) PM2.5 in the YRD region from 2000 to 2010. The intervals between 2.5 and 97.5 percentiles indicate the estimated uncertainty ranges of total vehicle emissions for those four primary air pollutants at the 95% confidence level using the Monte Carlo simulation method (see Fig. S5 for an example). YRD: Yangtze River Delta.

2.2. Scenario-based analysis of vehicle emissions in three cities 525 in the YRD 526 Fig. 4 presents the estimated trends of total vehicle emissions in three cities—Shanghai, Nanjing, and Wuxi—in the YRD from 2010 to 2020 under three control scenarios. Under the BAU scenario, in which no further stringent emission control measures are implemented after 2010, the total vehicle emissions of CO, HC and PM2.5 exhibit downward trends during 2010–2020 for all three cities. These positive estimates are largely based on the scrappage of older vehicles with higher emission factors, which is naturally accompanied by the penetration of newer vehicles. For example, the estimated total vehicle emissions of CO, HC and PM2.5 in Nanjing during 2020 will be mitigated by 24%, 29% and 26%, respectively, compared to their 2010 levels. Shanghai has implemented a license control policy for LDVs that will lead to a lower annual rate of increase in LDVs than in Nanjing and Wuxi. As a result, the estimated emission reductions of CO and HC in Shanghai under the BAU scenario could decrease by as much as 63% and 68%, respectively, from 2010 to 2020. However, the estimated decreasing trends in vehicle emissions of CO, HC and PM2.5 for all three cities are predicted to gradually slow and even stabilize by approximately 2020. Thus, if no more stringent measures are implemented by 2020, the emission-reduction benefits for HC, CO and PM2.5 will likely be almost completely offset by the penetration of new additional vehicles. For NOx,

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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fully implemented in 2016 and 2018, respectively. Under the moderate scenarios, the most significant differences relative to the BAU scenario are the mitigation of NOx vehicle emissions in all three cities. Compared to 2010 levels, the estimated total vehicle emissions of NOx will be reduced by 38%, 9% and 17% for Shanghai, Nanjing and Wuxi, respectively, representing further reductions of 30%–38% relative to the BAU scenario. A major portion of those NOx emission reductions will result from the lower emissions factors resulting from diesel trucks complying with more stringent emission standards. For example, selective catalyst reduction (SCR) systems might be more reliable for mitigating NOx emissions under high-speed and heavy-load operating conditions, which are more typical for long-distance freight trucks than urban transit busses (Carslaw et al., 2011). Similarly, the moderate scenario will also reduce PM2.5 vehicle emissions more substantially by approximately 40%–50% in the three cities because of the introduction of cleaner HDDVs using diesel particle filters (DPFs) when the supply of ultra-low sulfur diesel (i.e., 10 ppm sulfur) is sufficiently guaranteed in the YRD region by 2016. Furthermore, the relative vehicle emission reductions of CO and HC are lower than those of PM2.5. For example, compared to the BAU scenario, the moderate scenario can further reduce HC emissions by ~20% in Nanjing and Wuxi and ~10% in Shanghai by 2020 because future reductions in the emission factors of CO and HC for Euro 5 and Euro 6 gasoline LDPVs relative to Euro 4 vehicles might not be as significant as those of previous stages (Carslaw et al., 2011; Chen and Borken-Kleefeld, 2014). The strengthened scenario will further reduce the urban use intensity of LDPVs through license control policies, driving restrictions during weekdays, and accelerated scrappage of older LDPVs (see below). Therefore, the strengthened scenario primarily mitigates the vehicle emissions of CO and HC for the three cities relative to the moderate scenario because LDPVs are one of the major contributors of those two pollutant categories. For instance, the total vehicle emissions of HC under the strengthened scenario will be reduced by 69%, 62% and 66% in Shanghai, Nanjing and Wuxi, respectively, during 2010–2020. However, it should be noted that the strengthened measures that focus on LDPVs will play less

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the estimated vehicle emissions in Nanjing and Wuxi will continue their upward trends under the BAU scenario, with total increases of 30% to 35% during the decade of 2010–2020, primarily driven by the increase in diesel HDTs. In Shanghai, although NOx emissions were moderately mitigated from 2011 to 2015 because of a significant decrease in the HDT population in 2012, without more stringent controls, we still predict increased NOx emissions after 2015. The moderate scenario for the three cities requires more rigorous emission standards for new vehicles before 2020, such as the Euro V and Euro VI standards for HDDVs, which are to be

Area-specific emissions (ton/km2)

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Fig. 3 – Comparison of area-specific emissions of (a) HC, (b) NOx and (c) PM2.5 from on-road vehicles between the YRD and foreign regions. The error bars for the YRD region indicate estimated uncertainty ranges at a 95% confidence level using the Monte Carlo simulation method. For metropolitan areas, vehicle emission data for the New York Metropolitan Area (an area of 34 thousand km2 consisting of New York City plus surrounding counties in New York, Connecticut, and Pennsylvania) and the Los Angeles Metropolitan Area (an area of 13 thousand km2 including Los Angeles and Orange counties) are derived from the 2011 National Emission Inventory (NEI). For the Greater London Area (an area of 1.6 thousand km2 consisting of the 32 London boroughs and the city of London), emission data are provided by the London Atmospheric Emission Inventory 2010 database, which specifies tailpipe exhaust PM2.5 emissions (applied in this figure) but does not include estimated HC emissions. YRD: Yangtze River Delta.

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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Fig. 4 – Future trends in total vehicle emissions of HC, NOx and PM2.5 in (a) Shanghai, (b) Nanjing and (c) Wuxi under three emission-control scenarios from 2010 to 2020. Note: The future trends in CO emissions for the three cities highly resemble those estimated for HC emissions under the three emission-control scenarios.

significant roles in mitigating the vehicle emissions of NOx

603 Q10 NOX and PM2.5 compared to CO and HC.

2.3. City-specific vehicle emission control strategies

605

Under the strengthened scenario, our forecasting assessment indicates that only Shanghai will be able to (albeit barely) meet its NOx emission mitigation targets during the 12th FYP (i.e., required reductions of 17%–18%) because the registered truck population declined significantly in 2012 (see Table S7). In contrast, the NOx vehicle emissions in Nanjing and Wuxi under the strengthened scenario are estimated to slightly increase during the 12th FYP. Postponed Euro IV emissions standards for HDDVs and the surge in diesel trucks in 2010–2011 are major factors leading to unsatisfactory NOx mitigations for on-road vehicles. In particular, total vehicular NOx emissions in Wuxi are estimated to be increased by 6% even under the strengthened scenario, posing the most rigorous situation to control N-NOx emissions among the three cities.

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Furthermore, among the three investigated cities, only Shanghai is predicted to be able to attain the required vehicle emission reductions by 2020. Under both the moderate and strengthened scenarios, Shanghai mitigated vehicle emissions by ~80% of HC and PM2.5 and ~35% of NOx relative to the 2005 emission levels (see Table S8). In contrast, under the strengthened scenario, Nanjing and Wuxi will be able meet the reduction targets for HC and PM2.5 vehicle emissions but not NOx. As a result, our assessment indicates that traditional emission control measures, such as more stringent emission standards and traffic management and control strategies primarily concentrated on the LDPV fleet, will be insufficient to ensure better air quality as had been expected. Thus, NOx emission control for on-road vehicles will represent the most significant hurdle in the future, especially for HDDV fleets, and more dedicated and effective emission-control measures and strategies should be developed for diesel busses and trucks. To reduce vehicle NOx emissions in Nanjing and Wuxi by 25% relative to their 2005 levels by the year 2020, we propose additional emission control measures for HDDVs, as

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639

10

654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682

t4:1 t4:2

t4:4 t4:5

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Table 4 – Proposed NOx emission-control measures for HDDVs in Nanjing and Wuxi from 2015 to 2020 in additional to control measures included in their strengthened scenarios.

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t4:6

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In addition to historical evaluation and scenario analysis, uncertainty in total vehicle emissions is another issue of concern to policy-makers. Regarding the historical trends of major air pollutants, we estimated relative uncertainty ranges of total vehicle emissions in the YRD region during 2010 of −25%–+31% for CO, − 23%–+37% for HC, − 24%–+26% for NOx and − 23%–+42% for PM2.5, with 95% CL after 10,000 trials by Monte Carlo simulation (see Fig. S5). These values indicate highly skewed distributions for PM2.5 emissions but substantially less skewed distributions for NOx emissions, primarily because PM2.5 emission factors usually have more significant long-tail distributions due to the existing gross emitters (Zhang et al., 2014a; Wang et al., 2012; Zheng et al., 2015). At the city level, the uncertainty ranges were estimated to be slightly wider; for example, the relative uncertainty ranges were − 34%–+50% for CO, − 33%–+54% for HC, − 27%–+42% for NOx and − 30%–+57% for PM2.5 for vehicle emissions in Shanghai in 2010. Furthermore, in addition to quantitative uncertainty analysis, policy-makers should pay special attention to issues resulting in greater uncertainties in future vehicle PM2.5 and NOx emissions (see Table S6). First, we note the significant gap in diesel NOx emissions between off-cycle and regulatory conditions for pre-Euro VI HDDVs. Due to limited on-road measurement data specifically for NOx emissions for Euro VI HDDVs, we refer to recent studies of NOx emissions from HDDVs complying with the U.S. 2010 standard, which is considered to be comparable to the Euro VI standard (Bishop et al., 2013; Misra et al., 2013; Herner et al., 2013). In the U.S., the fleet-average NOx emission factors for most modern diesel trucks have been substantially reduced to below 5 g NOx/kg fuel (i.e., below ~1.3 g/km), which corresponds to a reduction of as much as 80% compared with model year 2004–2007 trucks (Bishop et al., 2013). Notably, some unfavorable operating

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HDDVs and the proposed strengthened scenario can by 2020 mitigate total vehicle NOx emissions by 25% in Nanjing and 28% in Wuxi relative to the 2005 levels (see Table S9 for the reductions in fleet-average NOx emission factors for public busses and HDTs).

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summarized in Table 4. For public busses, dedicated natural gas busses (NGBs) and battery electric busses (BEBs) are two major alternatives for further reducing on-road NOx emissions (Zhang et al., 2014a, 2014b; Wang et al., 2015). In contrast, for hybrid electric busses (HEBs), a series of unfavorable factors, such as a higher vehicle price, a lack of purchase subsidies and unsatisfactory energy efficiency in the real world (e.g., with the air conditioner in use), have led to the slow growth of these vehicles in China (Zhang et al., 2014b, 2014c). Thus, we do not consider hybrid diesel busses in the additional control measures for public busses. For diesel trucks without deNOx after-treatment devices, because the normal turnover duration of diesel trucks is longer than that of LDPVs, scrappage programs will phase out those diesel trucks complying with pre-Euro III standards registered before 2007 that are also known as yellow-labeled vehicles. Such scrappage programs for pre-Euro III diesel trucks have clearly been included in many provincial and municipal emission mitigation year plans during 2013 to 2017 (Beijing Municipal Government, 2013; Shanghai Municipal Government, 2013). However, our results indicate scrappage actions only limited for pre-Euro III diesel trucks will not be sufficient to meet the required reduction target of total vehicle NOx emissions for Nanjing and Wuxi. Therefore, we propose additional retrofit programs involving installing SCR systems and aggressive in-use compliance and enforcement programs that provide an appropriate focus on the massive penetration of diesel trucks in this city that occurred circa 2010. When comparing the proposed control packages for Nanjing and Wuxi, although the total numbers of diesel trucks are quite close in these two cities. The more challenging situation for mitigating NOx emissions is in Wuxi due to its higher share of truck population than Nanjing. Therefore, more HDDVs are involved in the retrofit plan by adding SCR systems (see Table 4). Technically, retrofitted vehicles must be inspected to ensure that they have the appropriate emission-control components, and special urban test cycle and PEMS test methods could be added to ensure that the SCR systems can achieve adequate catalyst light off temperatures under typical urban driving conditions. Finally, to improve the real-world NOx emissions control, manufacturers should participate in retrofit programs by re-flashing the computer chips of existing vehicles. We estimate that these additional NOx emission controls for

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City

Public busses

Nanjing Increase the population shares of dedicated NGBs and BEBs to above 50% and 30%, respectively a Wuxi Increase the population share of dedicated NGBs and BEBs to above 50% and 30%, respectively

Vehicle fleets HDPVs (non-public busses) Phase out all pre-Euro III HDPVs registered before 2007; Retrofit ~2900 Euro III diesel HDPVs by adding SCR systems b Phase out all pre-Euro III HDPVs registered before 2007; Retrofit ~3300 Euro III diesel HDPVs by adding SCR systems

Diesel trucks Phase out all pre-Euro III trucks registered before 2007; Retrofit ~25,000 Euro III diesel trucks by adding SCR systems c Phase out all pre-Euro III trucks registered before 2007; Retrofit ~34,000 Euro III diesel trucks by adding SCR systems

a

Phased-out older HDDVs will be replaced by new HDDVs complying with the Euro VI emission standard. NOx emission factors of retrofitted Euro III diesel trucks with additional SCR systems are assumed to be comparable to their Euro V counterparts. c Scrappage programs of pre-Euro III HDDVs have been a major task since the Action Plan on Prevention and Control of Air Pollution was issued by the State Council. Because of the substantial subsidies, all the pre-Euro III HDDVs are expected to be phased out no later than 2017. b

Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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The abatement of vehicle emissions has become one of the most important concerns for air pollution control in China. As one of the most densely vehicle-populated regions in China, the YRD region urgently needs effective vehicle emission-control strategies to improve urban air quality. We first conduct a historical assessment of the total vehicular emissions of major air pollutants and the relevant uncertainties using the highly localized EMBEV model. Our results show that NOx emissions from vehicles have been significantly increased during the past decade due to the unsatisfactory emission control for diesel vehicles, which is quite different with the trends of other pollutants. It is noted that area-specific emission density in the YRD region is significantly higher than other regions in other developed countries, posing challenging situations for further vehicle emission controls. Second, we design various emission control scenarios for three typical traffic-populated cities (i.e., Shanghai, Nanjing and Wuxi) in the YRD region. The comprehensive control package includes implementation of stringent standards for vehicle emissions and fuel quality, strict vehicle registration and traffic restrictions, aggressive scrappage for older vehicles and additional controls for HDDVs. According to the determined emission-reduction targets for primary vehicular pollutants (e.g., HC, NOx and PM2.5), our evaluation results indicate that Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020 without additional stringent controls specifically for HDDVs, such as scrappage of older freight trucks and busses, SCR retrofit programs and promotion of dedicated NGBs and BEBs. We also discuss major aspects of uncertainties with most recent information taken into account. This paper provides policy-makers with a very timely policy analysis regarding vehicle emission controls in Chinese cities in an effort to improve urban air quality in the near term and clearly informs on the significant difficulty in achieving the required mitigation in vehicular NOx emission, which will be achievable only with great efforts regarding HDDVs.

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This study was sponsored by the National Science & Technology Pillar Program of China (No. 2013BAC13B03) and the National Natural Science Foundation of China (Nos. 51322804 and 91544222). The authors thank Mr. Charles. N. Freed formerly of the U.S. EPA for his helpful advice with regard to improving this paper. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the sponsors.

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YRD region. In light of this issue, we are collecting detailed traffic flow data from local and highway administrations using intelligence traffic system technologies (e.g., floating car, vehicle-issued radio frequency identification, and highway rolling systems) for several cities to improve the resolution and accuracy of emission inventories.

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conditions, such as cold start and idling, remain challenging (Misra et al., 2013; Herner et al., 2013). Therefore, by accounting for congested traffic conditions and loose in-use compliance in China and acknowledging the substantial uncertainty in the future NOx emissions from diesel fleets, we predict that reduction rates of NOx emission factors for Euro VI diesel trucks and urban busses will be 65% and 50% compared with those of vehicles complying with Euro V standards. Second, on-road measurement studies have indicated that natural gas busses with stoichiometric spark-ignition engines and deNOx aftertreatment devices (e.g., three-way catalyst and SCR) will more reliably mitigate NOx emissions compared with other natural gas engine technologies, such as lean-burn engines (Zhang et al., 2014b; Yoon et al., 2013; Ligterink et al., 2013). However, because of the better fuel economy of lean-burn engines, stoichiometric spark-ignition engines currently play only a minor role in China's urban public bus fleet. Therefore, policymakers should carefully distinguish between various technologies and guarantee adequate real emission benefits by promoting natural gas. Furthermore, the dramatic decline in PM2.5 vehicular emissions will be dependent on the scrappage of older HDDVs, the future improvement of engine combustion performance and the application of DPF. Although DPFs have penetrated diesel fleets in the U.S. and Europe for years, the high sulfur content of diesel fuels is an important and unfavorable factor affecting its application in China. Indeed, the Chinese government has recently become determined to accelerate the lowering of the diesel sulfur content and to implementing more strict emission standards (Yue et al., 2015). Ultra-low sulfur diesel fuels are expected to be available throughout the entire nation in 2016, which would enable the application of DPFs for HDTs that are commonly used for long-distance transportation. In the near future, once fuel quality is no longer a major hurdle, stringent and effective programs regarding type-approval conformity, market supervision and in-use compliance for HDDVs via more effective methods (e.g., PEMS measurement, remote sensing, and online on-board diagnostics) will become increasingly essential for guaranteeing the benefits of stricter emission regulations. We acknowledge that there are other limitations of the methodology applied in this study. First, the scenarios could have been designed without the uncertainty in future vehicle emission programs in the YRD region; for this reason, we limited the time framework to extend only to 2020. For example, if Shanghai follows the moderate scenario from 2020 to 2030, we estimate that the total vehicle emissions for this city in 2030 would be reduced by 78% for CO, 84% for HC, 71% for NOx and 91% for PM2.5, indicating steady and substantial decreases in the emissions of major vehicle pollutants. This implies that future NOx emission intensity in Shanghai in 2030 would approach to the current level in the New York Metropolitan Area (see Figure 3), despite the substantial uncertainty in emission factors reported herein. Second, we established emission inventories based on the registered vehicle population and ignored the impacts of inter-city traffic demands. Therefore, this study might underestimate the actual vehicle emissions within the city boundary of Shanghai, which attracts a substantial long-distance traffic demand from other provinces, including those outside the

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Please cite this article as: Zhang, S., et al., City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region, J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.06.038

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