On-road Vehicle Emission Inventory and Its Characteristics Analysis in Northeast China: A Case Study of Changchun,China

Chengkang Gao,Qiao Ba,Kaihui Song,Qingjiang Xu,Yuhong Xing,Weiwei Chen,Zhenbo Yu,Hongming Na,Sen Wang

1 School of Metallurgy,Northeastern University,Shenyang 110819,China

2 Department of Geographical Sciences,University of Maryland,College Park 20742,MD,USA

3 Northeast Institute of Geography and Agroecology,Chinese Academy Sciences,Changchun 130000,China

4 Heilongjiang Provincial Environmental Science Research Institute,Harbin 150000,China

Keywords Northeast China Transport emissions Emission inventory Spatial distribution

Abstract The transportation sector in Northeast China is facing challenges of fuel combustion and vehicle maintenance,like many high latitude areas,for the cold weather, long-lasting snow and associated slippery roads. The high reliance on vehicles rather than bicycles reinforced the challenges, resulting in inefficient fuel burning and high emissions from mobility. To better understand transportation emissions from cold areas and inform emission control strategies,this study analyzed the temporal and spatial dynamics of transport emissions in 2016, taking Changchun city as a typical city representing northeast China. Based on field investigation and national motor emission guideline, this study established a 1km×1km spatial highresolution emission inventory for atmospheric pollutants in Changchun City and analyzed emission responsibility from different types of vehicles. The results showed that the annual emissions of atmospheric pollutants CO, HC, NOx, PM2.5, and PM10 from road movement sources in 2016 in Changchun were 137,700 tons, 29,000 tons, 40,900 tons, 2200 tons and 2400 tons,respectively. Small passenger vehicles had the highest contribution rates to CO and HC emissions,which were 47.8%and 57.9%respectively. Heavy trucks had the highest contribution rates to NOx and PM which were 41.5% and 43.85%, respectively. Small passenger cars and heavy-duty trucks are the focus of future road source air pollution control. On the spatial level,the emission intensity of atmospheric pollutants from road movement sources in Changchun showed a trend of decreasing from city center to urban edge, especially concentrated in the square areas enclosed by the eastern urban expressway,southern urban expressway,western urban expressway and northern urban expressway.

1 Introduction

The increasing purchasing power and rapid urbanization in China have been driving increasing demands of vehicles for residents, leading China to the largest automobile production and sale country around the world for nine consecutive years since 2017 (MEE,2018). In 2016, the estimated registered motor vehicles in China reached 310 million (MPS, 2018), with a high annual growth rate averaged 28.3% between 2010 and 2016(MEE,2018). Mo-tor vehicles are reported as significant contributors to urban air pollution in China,not only contributed to a large amount of primary emissions but also the secondary particulate matter (PM) formation(Guo et al.,2014;Huang et al.,2014;Qian et al.,2016). It is reported that mobile sources contributed 13.5-41.0%of the fine particulate concentration in 15 major cities including Beijing, Tianjin, and Shanghai. Furthermore,the contribution rate can even reach over 50%in extremely severe events(MEP,2017). These cities have high population density, resulting in great health risk on the public (Gong et al., 2012; Chan et al., 2008; Xie et al.,2016). Meanwhile,people’s increasing purchase power will allow the growth rate of motor vehicles to continue maintaining at a high level, given the improvement of road construction and urbanization in the third-tier and fourth-tier cities in North-east China.

Quantitative analysis of transportation emission is of great guiding significance for environmental impact assessment and air pollution prevention. Many studies established local emission inventory of atmospheric pollutants based on activity level, and examined vehicle emissions by model simulation. With further analyses of emission influencing factors and emission characteristics, prior studies evaluated the feasibility of the policy recommendations or socioeconomic influences after policy implementation (Fontaras et al., 2014; Kousouliou et al.,2013;Rhys-Tyler et al.,2011;Mohammadiha et al.,2018;Weiss et al.,2012). Studies about vehicle emissions typically focused on cities or metropolitan areas. Hao et al.(2001)analyzed temporal and spatial dynamics of vehicle emissions in Beijing using mathematical discrete model,and applied the model to explore emissions from road transportation in big cities of Beijing, Guangzhou, and Shanghai. Huang et al. (2017) compared emission factors of light gasoline vehicles which were obtained from the chassis dynamometer and tunnel measurement,and concluded that the emission factors of the actual operating vehicles were underestimated mainly due to the high emissions of old vehicles. Wang et al. (2003) established vehicle emission inventory in Shanghai with IVE model, analyzed the emission characteristics of motor vehicles and the emission sharing rates of different models,found that the cold-start emission accounts for 20%of the total emission. Wu et al. (2011)assessed the implementation effect of vehicle emission control measures in Guangzhou by using the Mobile-China model;In addition,other authors used COPERT model to estimate the emission of air pollutants of on-road vehicles in China from 1999 to 2011, and examined the correlation between vehicle emissions and GDP (Lang et al., 2014). There are mainly three aspects that improved the accuracy of results: the increasingly mature and di-verse research methods of motor vehicle emissions, from emission factor model based on the average speed of development to which based on the instantaneous velocity, traffic data acquisition methods’ development from fixed-point monitoring to large data statistical analysis which is based on modern means. From the research area,the research of the emission characteristics of motor vehicles mainly concentrate on the areas of Beijing-Tianjin-Hebei,Yangtze River Delta and Pearl River Delta where have the more developed economy and the larger amount of motor vehicles. However,there are relatively few studies on the emission characteristics of motor vehicles in Northeast China. Improvement in reasonable assessment of the emission characteristics and associated environmental implications will inform the local policy programs of motor pollution control.

Northeast China has been a typical region for vehicle exhaust analysis for its high emission intensity and characterized dynamics. On the one hand,the seasonal weather is characterized by a distinct cold winter,when snow-covered roads and the high load of air conditioner inside of vehicles increased emissions from unitary mileage driving. On the other hand,the difficulty in commuting increased people’s tendency of driving and thus caused a heavier load of traffic. The two reasons emphasized the importance of detailed analysis in Northeast China area. Changchun city is selected as the study area,given it is the capital of Jilin Province and a major city in Northeast China ratified by the State Council,embracing nearly all characteristics in Northeast China.

This study combines the merits of both top-down and bottom-up research methods and calculates the emission inventory of road mobile sources in Changchun in 2016 based on the Technical Guidelines for Compiling Road Vehicle Air Pollutant Emission Inventory(hereinafter referred to as the Guidelines). Based on the data of road network density and road traffic flow,we analyzed the emission features and sources in 1km×1km spatial resolution in Changchun urban area. Uncertainty analysis was conducted in support of robust evidence to inform policy-making in Changchun.

2 Methods

2.1 Vehicle emission factor acquisition

Vehicle emission factor is an important parameter for calculating emission inventory. The Guideline provides a comprehensive benchmark emission factor of different fuels and different vehicle types following various emission standards, based on a nationwide emission test of vehicles under typical urban traffic conditions, meteorological conditions, fuel quality and load coefficient in 2014. The emission factor requires adjustment to better represent the local emission in Northeast China,as shown in the technical roadmap in Fig.1. First,emission factors are calibrated by environmental conditions such as the monthly average temperature and relative humidity in Changchun,which are derived from the National Meteorological Information Center. The emission factors are then adjusted by operating conditions,mainly the average speed of various types of vehicles

The emission factor EFiis calculated by the following equation.

Fig.2 Classification of motor vehicles in Changchun.

Where, BEFi is the comprehensive benchmark emission factor of type i motor vehicles, in g/km.?iis the environmental correction factor of type i motor vehicles.λiis the deterioration correction factor of type i motor vehicles.θiis the other usage condition (such as load factor, oil quality, etc.) correction factor of type i motor vehicles.γiis the average velocity correction factor of type i motor vehicles.

The emission factor EFs should be calibrated by local environmental parameters, vehicle operating conditions, and fuel quality and deterioration degree to better estimate the emission level in Changchun. All the emission factors and the correction factors are provided by the Guidelines.

2.2 Vehicle emission inventory

Identifying the dominant contributors to vehicle emissions and presenting vehicle emission inventory help with controlling urban vehicle emissions by means of traffic planning, vehicle renewal and other methods. Given the unique weather and significant role transportation played in air pollution, it is necessary to establish a regional scale emission inventory in Northeast China to inform local policy program to improve the environmental quality.

On-road vehicle emissions are mainly composed by exhaust emissions and evaporation of hydrocarbons(HC),calculated by the following equation.

Where,E is the total vehicle emissions,E1is vehicle exhaust emissions and E2is HC evaporation.

Vehicle exhaust emissions from various road mobile sources are calculated by equation(3).

Where,EFi is per unit mileage pollutant content of type i motor vehicles,in g/km. Pi is the number of registered vehicles of type i motor vehicles. VKTiis annual average mileage of type i motor vehicles,in km/vehicle.

HC evaporation emissions are calculated as follows:

Where, EFaiis evaporative emission factor of type i vehicle when driving, in g/h. Viis the average running speed correction factor of type i vehicle, in km/h. EFbiis the comprehensive emission factor of type i vehicle when parking,in g/d and Pi is number of registered vehicles of type i vehicle.

EFi combines with the number of registered vehicles in Changchun and the annual average mileage provided by Guidelines. The majority types of vehicles in Changchun were covered in order to obtain a complete road mobile source emissions inventory, as shown in Fig. 2. In addition, each type of vehicles is classified into a third-level classification to analyze different types of vehicle technology, such as Mini passenger car(MiniPC),Heavy duty truck(HDT).

3 Data

3.1 Motor vehicle activity

3.1.1 Vehicle driving characteristics

Vehicle operating conditions are important determinants of vehicle emissions. Speed is one of the main characteristic parameters of operating conditions and key parameters that affect emission factors. Road attribute is another important factor affecting the vehicle operating condition (MEP, 2018). According to the functional properties and road characteristics of Changchun urban area,Chaoyang District and Erdao District are selected as representatives of commercial and residential districts; urban expressways, trunk roads and residential roads are selected as typical roads in each district in this research. Meanwhile, the test route is optimized according to the layout of urban road networks. For light-mini passenger cars, portable GPS was installed on the representative vehicles in Changchun and the vehicles run along the prescribed routes. The GPS records the speed of vehicles, the real-time location of the vehicles(including altitude, longitude, and latitude). The recorded information is transmitted to the server,with transmission time interval being 5-10 seconds,and then downloaded through the server. Two GPS devices are used in this study to improve the veracity and accuracy of records.Each district was tested on both weekdays and weekends from 7:00 to 20:00. The measured data represent the speed distribution of light-mini passenger cars in Changchun on marked with different blocks, road types, and time periods. Meanwhile,we use GPS to collect the driving characteristics data of 8 typical buses which running routes radiate from the center to the outskirts of the city,including typical roads such as trunk roads,sub-trunk roads, and residential roads. The selected buses can represent the average dynamic performance and driving characteristics of the buses in Changchun. For taxis, the portable GPS is installed in the randomly selected taxis in the urban area of Changchun to obtain records of two continuous days. For other types of vehicles, the operating conditions can be obtained through consulting relevant documents.

Fig.3 shows the average speed variation of the light-mini passenger cars in different urban functional areas.The diagram presents speed changes of urban expressways, main roads,and residential roads all in wave shape with one obvious peak and two troughs. The peak value appears at about 14:00, which is related to the lower traffic flow before off-duty,the trough value appears in 8:00～9:00 and 16:30～17:30,coinciding with rush hour.From the perspective of road types, the average speed curve of residential roads changed slightly, in which the first trough appeared at about 7:00, nearly 1 hour earlier than other road types. The average speeds of vehicles in commercial districts 41.69 km/h for urban expressways, 19.57 km/h for trunk roads, and 12.53 km/h for residential roads. They are 10.77%,31.88%and 40.48%respectively higher than those driving on the same type of roads in commercial districts. The traffic conditions in residential districts are better than those in commercialdistricts. In addition,the average speed of light-mini passenger cars is approximately 25.8 km/h,taking different urban functional areas,different roads,and different periods into consideration.

Similarly, we use the same method which is based on statistics and analysis of existing research results in Changchun and similar cities (Motrycz et al., 2016; China Automotive Industry Yearbook, 2016) to get the average speeds of medium passenger cars,large passenger cars,light-mini-duty trucks,medium-duty trucks and heavy-duty trucks,which are 49.7 km/h,25.8 km/h,27.3 km/h,49.7 km/h and 80.4 km/h,respectively.

3.1.2 Road traffic flow

Vehicle traffic flow on the road is important to represent the level of vehicle activity and associated spatial emission distribution. Besides,traffic flow,time,and different road types are also important factors for vehicle activity and emission patterns. The monitoring equipment is HT3000-E mobile high-definition capturing device,which is the most advanced over speed forensics product in the field of intelligent transportation in China. It has the functions of radar speed measurement, video monitoring, vehicle type identification, traffic flow statistics,and returns analyses of the hourly traffic flow.Because the vehicle identification function is difficult to use in the case of heavy traffic flow,the statistical analysis of vehicle types is done by video playback. Road traffic flow monitoring was carried out for 4 days with each typical road tested for 2 days to get hourly traffic flow records.

The traffic flow is featured with two obvious peaks appearing at the same time as the rush hours, as shown in Fig.4a～4c.

Among the three types of roads, urban expressways carry the heaviest traffic flow, about 5489 vehicles/h,followed by the arterial roads 3945 vehicles/h and residential roads 1122 vehicles/h. The light passenger cars on urban expressways contribute 90.4%of the total, followed by taxis (6.6%). There are no large passenger cars,buses, large-duty trucks and motorcycles, on urban expressways due to their unique functions. It is estimated that 71.1%of vehicles on arterial roads are light passenger cars,a lower proportion than those on urban expressways;in contrast, 16.7%of vehicles are taxis and 4.2%are buses,indicating that arterial roads serve important functions in public transportation. The proportion of motorcycles in residential road increased significantly than the other two types of road,reaching 12%in peak periods. Despite the high proportion,most of the motorcycles were electric motorcycles(operating concentrated around 12:00～17:00)thus had little emissions directly to the atmospheric environment.

3.1.3 Annual vehicle kilometer traveled(VKT)

The VKT data provided in the Guideline are based on the statistical results of the country,which are universally applicable. Light vehicle has the largest number,so we take the light motor vehicles as an example to evaluate the VKT provided by the‘Guideline’. Based on the data of cumulative mileage and registration year obtained from 198 questionnaires, the corresponding relationship between cumulative mileage and service life was analyzed,as shown in Fig. 5. It is found that the VKT of light vehicles and taxis in Changchun is 17061 km and 114 995 km, respectively. The deviations from the Guideline are 5.2% and 4.2%. Within a reasonable range, the VKT data provided by the Guideline can be used.

3.2 Motor vehicle technical level

3.2.1 Amount of motor vehicles

The Statistical Yearbook of Changchun provides the amount of motor vehicles in Changchun over the years(Changchun Statistical Bureau, 2018). Most of the registered vehicles are passenger cars, accounting for approximately 70% of the total amount of motor vehicles, followed by motorcycles, trucks and other vehicles.Passenger cars and trucks are mainly mini and light vehicles, accounting for 96% and 66% respectively. The amounts of motor vehicles with different fuels are also analyzed according to the fuel consumption statistics of motor vehicle in Changchun (Changchun Statistical Yearbook, 2016). It shows that the majority are gasoline vehicles(about 1,219,889 vehicles), followed by diesel vehicles(474,633 vehicles)and other fuel vehicles(4,946 vehicles). Among the gasoline vehicles, light passenger cars shared the largest proportion and amount to 876,240 vehicles, followed by the motorcycles totaling about 281,600 vehicles and other. Among the diesel vehicles,the number of light passenger cars and light-duty trucks ranked the top,71.6%and 14.5%respectively,and heavy-duty trucks only accounted for 7.7%. Other fuel vehicles are mainly taxis and buses; furthermore,80%of the buses in Changchun use clean energy,and most of the taxis use LNG(Changchun Statistical Bureau,2018). And State 0,I,II,III,IV account for 3.1%,7.5%,8.5%,26.4%,54.5%of all the vehicles respectively.

Fig.5 Relationship between accumulated annual mileage and service life of light motor vehicles.

3.2.2 Others factors

The annual average temperature in Changchun was 5.7 ?C. The annual average humidity in Changchun was 62.4%. It is recorded that the sulfur contents of gasoline and diesel oil for motor vehicles is lower than 10 ppm and 50 ppm respectively by the investigation of fuel quality in Changchun(Changchun Statistical Bureau,2018). This study developed emission inventory based on the year of 2016, with calibrations by deterioration coefficients of motor vehicles of 2016 and load factor of diesel vehicles 50%. All the data variables have their corresponding adjustment factors in Guideline,as shown in Appendix.

4 Results and discussions

4.1 Vehicle emission factors

The average emission factors are weighted by number of register vehicles in different emission control standards and the adjustment factors from the Guideline,as shown in Table 1.

4.2 Emissions from motor vehicles in Changchun

4.2.1 Vehicle exhaust emissions

According to the number of vehicles in Changchun in 2016, combined with the average driving mileage and emission factors of different pollutants, the vehicle emission inventory of Changchun in 2016 is established, as shown in Table 2.

Table 2 shows that CO emissions from four kinds of conventional pollutants of motor vehicles in Changchun account for 131.7 million tons. Gasoline vehicles are the main source of vehicle pollution, contributing 68.6%of the total air pollutants, followed by diesel vehicles and other fuel vehicles, which are 29.4% and 2.0% respectively. Meanwhile, gasoline vehicles contributed the most to CO and HC emissions, 86.43% and 82.31%respectively, due to the large number of gasoline vehicles, accounting for 71.7% of the total number of motor vehicles. Diesel vehicles share 28.0%of the total vehicles, contributed only 12% and 15%to CO and HC,buttheir contribution to NOx and PM emissions was as high as 83.3%. 54% and 89.68%, indicating that diesel vehicles are the main sources of NOx and PM for motor vehicles. It is agreed with the existing studies that NOx is an important precursor of tropospheric O3and secondary particulate matter. Therefore,special attention should be paid to the influence of diesel vehicles on haze weather and photochemical smog.

Table 1 Comprehensive emission factors for atmospheric pollutants of motor vehicles.

Table 2 Emissions of pollutants from vehicles in different fuels(in ton).

Fig.6 shows the emission contribution from different types of motor vehicles in Changchun. It shows that the light passenger cars are the largest contributors to CO and HC emissions of Changchun,accounting for 47.85%and 45.5% of the total counterpart emissions from road transportation, due to the majority registered vehicles are fueled by gasoline. Taxis are the second largest contributors to CO and HC emissions,accounting for about 16.9%and 13.3%respectively,followed by motorcycles which account for 14.5%and 17.2%respectively to the total CO and HC emissions. Although taxi only forms 0.91% of the total registered vehicles, its high annual average mileage, low speeds in urban areas, and the poor engine combustion conditions resulted in relatively large emissions of CO and HC. The emissions from motorcycles are mainly attributed to its relatively large quantity and relatively low emission control level. Heavy-duty trucks contributed 41.5%, 43.8% and 43.9%respectively to NOX,PM2.5and PM10,resulted from the large average annual mileage of heavy-duty trucks and the majority being diesel vehicles. The contribution rates of light-duty trucks to NOx and PM are 16.6% and 12.7%respectively. It is due to,the relatively large quantity,which accounts for about 4.78%of total registered motor vehicles.

Fig.6 Emission contribution from of different types of motor vehicles.

Fig.7 Contribution of different types of motor vehicles to HC evaporation.

4.2.2 Vehicle evaporative emissions

HC is the main pollutants of vehicle evaporation emissions. With the gradual improvement of exhaust treatment technology, the evaporative emission contribution rate to vehicle emissions is increasing (Rubin et al., 2006;Gentner et al., 2009). The HC evaporation emissions of mobile road source in Changchun are about 12,222t,accounting for 42% of the total vehicle HC emission, much higher than the level of 20% in Beijing (Song et al., 2007). The shares of different types of vehicle are shown in Fig.7, the HC evaporation emissions of light passenger cars are the largest,about 9,170t,accounting for 75%of the total evaporation emission. It is followed by motorcycles (14%),taxis(6%)and mini passenger cars(2%),which are mainly explained by the number of different types of vehicles,fuel types,vehicle evaporation emission control technology and other parameters.

NOx and PM emissions of diesel vehicles reached 83.54% and 89.68% of total NOx and PM emissions respectively,while CO and HC emissions of gasoline vehicles reached 86.43%and 89.76%of total CO and HC emissions respectively. It shows that diesel vehicles of Changchun are the main sources of PM and NOx,while gasoline vehicles are the main sources of CO and HC.

Table 3 Vehicle emission inventory in Changchun and other cities.

4.2.3 Comparative analysis of similar emission inventories

In this study, the vehicle emission inventory of Changchun is compared with the emission inventory of other cities,as shown in Table 3.

Due to the large difference in the quantity of vehicles in each region, the emission levels of pollutants in each region are also quite diverse. Therefore, the pollutant emissions are divided by the number of vehicles to obtain the pollutant emissions per million vehicles for comparison. The emission levels of CO and NOX in Changchun are relatively low compared with those in Yangtze River Delta,which is due to the lower proportion of MiniPC and HDT in Changchun. The emission levels of HC,PM2.5and PM10in Changchun are the highest in the research regions. The reason for the high emission levels of PM and HC is that the small temperature of Changchun in winter season leads to a long time for the engine to reach the working temperature. The wet and slippery roads during snow days bring down driving speed and combustion efficiency. And the poor economic environment in Changchun makes the proportion of old vehicles in the total amount of motor vehicles high.leading to a large amount of PM emissions and HC evaporation.

4.3 Spatial analysis of emissions from motor vehicles

Weight average method is applied to analyze the emissions generated from road networks on the resolution of 1 km by 1 km in Changchun. Based on the layout of road network,we calculated the ratio of road network length in each grid to the total road length in the study area. The total pollutant emissions are also assigned to the grid based on the weights of typical road traffic flow,as shown in Fig. 8(a)-(d).

We mapped the four major emissions from vehicles. The spatial characteristics of the four pollutants are consistent, showing a decreasing trend from the center to the edge of the city. The high-emission areas are concentrated in Chaoyang District,Erdao District and Greenpark District,and the emissions in square areas of the eastern, southern, western and northern urban expressway besieged city are relatively high only behind the center of the city. The high emission of vehicle pollutants is mainly distributed in urban areas, due to dense urban road network and large traffic volume. The low emission of pollutants in suburban areas is explained by the fact that most of the vehicles in suburban areas are medium and heavy-duty trucks. Despite the large contribution of medium and heavy-duty trucks to pollutant emission, the pollutant emission in suburban areas is far less than that in urban areas. In the urban center, light passenger cars and heavy-duty trucks bring more pollutant emissions, and should be the focus of air pollution control of mobile sources in Changchun in the future.

5 Conclusion

This study compiled the emission inventory of air pollutants from on-road mobile sources in Changchun in 2016,based on the Guideline,vehicle test,and research data. The emissions of CO,HC,NOx,PM2.5 and PM10 were 131,700 tons,29,000 tons,40,900 tons,2,200 tons and 2,400 tons,respectively.

Light passenger cars contributed 47.8% and 57.9% to CO and HC in Changchun, and heavy-duty trucks contributed 41.5%and 43.85%to NOx and PM respectively. Light passenger cars and heavy-duty trucks should be the focus of air pollution control of mobile sources in Changchun in the future.

Fig.8 Spatial distribution of vehicle emissions(CO,HC,NOX,and PM2.5)in Changchun.

HC evaporation emissions accounted for 42.1% of the total HC emissions, of which light passenger cars accounted for 75.0%of the total evaporation emissions. With the increasingly stringer emission standards, the contribution rate of evaporative emissions may gradually increase. It is necessary to strengthen the control of vehicle evaporative emissions from the technical and management levels, especially the management of light passenger cars.

The characteristics of spatial distribution of atmospheric pollutant emissions from on-road mobile sources in Changchun present a decreasing trend from the urban center to the urban fringe. The high-emission areas are concentrated in Chaoyang District, Erdao District and Greenpark District, and it concentrated the square areas of east,south,west and north urban expressway enclosure.

Acknowledgements

This work was supported by National Project of Key Research and Development Plan(2017YFC0212303-03),and the Based Research Projects of National Natural Science Foundation of China(41871212; 41601609), and the Based Research Projects of Northeastern University(N172504031).