Spatial-temporal Distribution Characteristics of Emission and Diffusion of Vehicular Pollutants:A Case Study of the Expressway Network in Jiangsu Province
程大千1, 邹庆1,2, 张甦3, 陈俊1, 周俐峻3
1. JSTI Energy Technology Development Co., Ltd., Nanjing Jiangsu 210017, China; 2. Jiangsu Transportation Industry Center for Monitoring Statistics of Energy Consumption and Emissions, Nanjing Jiangsu 210017, China; 3. Environmental Monitoring Center of Jiangsu Province, Nanjing Jiangsu 210036, China
Spatial-temporal Distribution Characteristics of Emission and Diffusion of Vehicular Pollutants:A Case Study of the Expressway Network in Jiangsu Province
CHENG Da-qian1, ZOU Qing1,2, ZHANG Su3, CHEN Jun1, ZHOU Li-jun3
1. JSTI Energy Technology Development Co., Ltd., Nanjing Jiangsu 210017, China; 2. Jiangsu Transportation Industry Center for Monitoring Statistics of Energy Consumption and Emissions, Nanjing Jiangsu 210017, China; 3. Environmental Monitoring Center of Jiangsu Province, Nanjing Jiangsu 210036, China
摘要To address the growing pollution problem of vehicle exhaust on expressways, a calculation method for the emission and diffusion of vehicular pollutants in expressway network of Jiangsu province was proposed based on the emission inventory of road vehicular pollutants and the CALINE-4 diffusion model. The characteristics of the spatial-temporal distribution were analyzed. The following conclusions can be drawn:(1) In the province's expressway network with various vehicle styles and structures, the largest contributor of CO and HC emissions was Coach Model I, contributing 41.26% and 44.32%, respectively; the largest contributor of NOx and PM2.5 emissions was Truck Model V, contributing 33.32% and 32.52%, respectively. (2) From the vehicle emission level, for Coach Model I, the contribution rate of the national stage I-III vehicle emission standards to the total CO and HC emissions reached 73.56% and 62.05%, respectively; for Truck Models IV and V, the contribution rate of the national stage III vehicle emission standard to the total NOx and PM2.5 emissions reached 58.73% and 63.25%, respectively. (3) Except for NOx, the diffusion concentration of vehicular pollutants (CO, PM2.5, and PM10) in each section of the predicted points was lower than the 1-hour average limiting value taken as Grade II on the basis of the Ambient Air Quality Standards (GB3095-2012), which is 10 mg/m3, 75 μg/m3, and 150 μg/m3. (4) From the temporal distribution, the amount of various pollutants showed a double-hump trend, which occurred at 9-10 a.m. and 2-3 p.m. The hourly diffusion concentration of various pollutants in all sections of the province was higher at night (10 p.m. to 4 a.m. the next day) than in the daytime. The proportion of sections exceeding the limit of NOx diffusion concentrations at night was as high as 75.2%, reaching the peak value at 2-3 a.m. (5) From the spatial distribution, the total CO and HC emissions in the North Network were less than that in the South Network, and the NOx, PM2.5, and PM10 emissions in the North Network were higher than those in the South Network, while the emission intensity of all kinds of pollutants in the North Network was significantly higher than that in the South Network. The 1-hour average NOx concentration in Northern Jiangsu was higher than that in Southern Jiangsu and Middle Jiangsu, with the maximum value of all periods of the day appearing in the section of "Duanzhai Hub-Xinyi Dong" and the minimum value mainly distributing in Middle Jiangsu.
Abstract：To address the growing pollution problem of vehicle exhaust on expressways, a calculation method for the emission and diffusion of vehicular pollutants in expressway network of Jiangsu province was proposed based on the emission inventory of road vehicular pollutants and the CALINE-4 diffusion model. The characteristics of the spatial-temporal distribution were analyzed. The following conclusions can be drawn:(1) In the province's expressway network with various vehicle styles and structures, the largest contributor of CO and HC emissions was Coach Model I, contributing 41.26% and 44.32%, respectively; the largest contributor of NOx and PM2.5 emissions was Truck Model V, contributing 33.32% and 32.52%, respectively. (2) From the vehicle emission level, for Coach Model I, the contribution rate of the national stage I-III vehicle emission standards to the total CO and HC emissions reached 73.56% and 62.05%, respectively; for Truck Models IV and V, the contribution rate of the national stage III vehicle emission standard to the total NOx and PM2.5 emissions reached 58.73% and 63.25%, respectively. (3) Except for NOx, the diffusion concentration of vehicular pollutants (CO, PM2.5, and PM10) in each section of the predicted points was lower than the 1-hour average limiting value taken as Grade II on the basis of the Ambient Air Quality Standards (GB3095-2012), which is 10 mg/m3, 75 μg/m3, and 150 μg/m3. (4) From the temporal distribution, the amount of various pollutants showed a double-hump trend, which occurred at 9-10 a.m. and 2-3 p.m. The hourly diffusion concentration of various pollutants in all sections of the province was higher at night (10 p.m. to 4 a.m. the next day) than in the daytime. The proportion of sections exceeding the limit of NOx diffusion concentrations at night was as high as 75.2%, reaching the peak value at 2-3 a.m. (5) From the spatial distribution, the total CO and HC emissions in the North Network were less than that in the South Network, and the NOx, PM2.5, and PM10 emissions in the North Network were higher than those in the South Network, while the emission intensity of all kinds of pollutants in the North Network was significantly higher than that in the South Network. The 1-hour average NOx concentration in Northern Jiangsu was higher than that in Southern Jiangsu and Middle Jiangsu, with the maximum value of all periods of the day appearing in the section of "Duanzhai Hub-Xinyi Dong" and the minimum value mainly distributing in Middle Jiangsu.
基金资助:Supported by the 2017 Jiangsu Provincial Transportation Science and Technology and Achievement Transformation Project (No. 2017G07)
通讯作者:
CHENG Da-qian
E-mail: cdq51@jsti.com
引用本文:
程大千, 邹庆, 张甦, 陈俊, 周俐峻. Spatial-temporal Distribution Characteristics of Emission and Diffusion of Vehicular Pollutants:A Case Study of the Expressway Network in Jiangsu Province[J]. Journal of Highway and Transportation Research and Development, 2020, 14(4): 99-110.
CHENG Da-qian, ZOU Qing, ZHANG Su, CHEN Jun, ZHOU Li-jun. Spatial-temporal Distribution Characteristics of Emission and Diffusion of Vehicular Pollutants:A Case Study of the Expressway Network in Jiangsu Province. Journal of Highway and Transportation Research and Development, 2020, 14(4): 99-110.
[1] HUO Hong, HE Ke-bin, WANG Qi-dong. A Review of Vehicle Emission Models[J]. Environmental Pollution & Control, 2006, 28(7):526-530. (in Chinese) [2] WANG Zheng. Research on Atmospheric Environmental Traffic Capacity for Expressway[D]. Xi'an:Chang'an University, 2013. (in Chinese) [3] DENG Shun-xi, CHEN Ai-xia, CAO Shen-cun. An Experimental Study of Emission Factors of Vehicular Pollutants in a Freeway Tunnel[J]. China Journal of Highway and Transport, 1995,12(S1):94-100. (in Chinese) [4] DENG Shun-xi, CHEN Ai-xia, CAO Shen-cun. A Methodology for the Determination of Emission Rates from Vehicular Pollutants on Highway in China[J]. Journal of Traffic and Transportation Engineering, 2001, 1(4):83-86. (in Chinese) [5] YU Yan-chun, YU Ming-yuan. Estimation and Forecast of For-hire Motor Vehicle Emission Volume[J]. Journal of Highway and Transportation Research and Development, 2008, 22(6):154-158. (in Chinese) [6] WANG Jian, TONG Ji-long, WEI Ying, et al. Analysis of Differences of Highway Line Source Strength in Atmospheric Evaluation[J]. Industrial Safety and Environmental Protection, 2014, 40(4):81-83. (in Chinese) [7] LI Hai-ping, ZHAO Ying, FU Yi-ming. Spatial Distribution of Air Pollutant Emissions from National Trunk Highway in Beijing-Tianjin-Hebei (BTH)[J]. Acta Scientiae Circumstantiae, 2016, 36(10):3515-3526. (in Chinese) [8] ZHANG Fan, CHENG Shui-yuan, WANG Ren-jie, et al. Study on Effect of Atmospheric Pollution from Motor Vehicles on National Trunk Highway of Beijing-Tianjin-Hebei Region[J]. Journal of Highway and Transportation Research and Development, 2017, 34(6):144-150. (in Chinese) [9] Ministry of Environmental Protection. Technical Guide for Compilation of Emission Inventory for Air Pollutants from Road Motor Vehicles (Trial)[R]. Beijing:Ministry of Environmental Protection,2015. (in Chinese) [10] WANG Xiao-ning, ZHANG Hong-zhi, FU Ya-jun. Research on Computing Method for Amount of Emission of Motor Vehicle Exhaust[J]. Technology of Highway and Transport, 2016, 32(1):130-133,139. (in Chinese) [11] HUANG Guan-tao. Evaluation of Traffic Emissions at Microscopic Level Based on MOVES[D]. Beijing:Beijing Jiaotong University, 2011. (in Chinese) [12] HUANG Wen-wei, QIANG Ming-ming, SUN Long-lin, et al. Emission Factor Measurement of Vehicles Based on MOVES[J]. Journal of Traffic and Transportation Engineering, 2017, 17(1):140-148. (in Chinese) [13] LI Li, ZHANG Jie, ZHAO Qiu-yue, et al. Vehicle Exhaust Emission Characteristics and Their Contributions in Jiangsu Province[J]. Environmental Science, 2018, 39(9):3976-3986. (in Chinese) [14] GAO Cheng-kang, XU Qing-jiang, XING Yu-hong, et al. Emission Inventory of Atmospheric Pollutants from On-road Vehicles in Low-temperature Areas in Winter[J]. Journal of Northeastern University:Natural Science Edition, 2019, 40(9):1343-1349. (in Chinese) [15] ZHANG Xiao-ying. Simulation Study of Vehicle Pollutants Based on CALINE4 and OSPM Models[D]. Harbin:Harbin Institute of Technology, 2014. (in Chinese) [16] MUCHTAR F, RAMLI M I. Estimation of CO Vehicular Emission on Arterial Roads in Makassar City Based on Caline-4[C]//IOP Conference Series:Earth and Environmental Science 235(2019)012056.[S.l.]:IOC Publishing Ltd, 2019. [17] SHI Wei, ZHANG Hong, SHI Rui, et al. Dispersion Models of Motor-vehicles CO Exhaust Pollutant Based on CALINE4:A Case Study on East Binghe Road in Taiyuan, Shanxi[J]. Journal of Shanxi University:Natural Science Edition, 2011, 34(1):147-152. (in Chinese) [18] YIN Cui-qin, JIN La-hua. Application of the CALINE4 Model in Motor Vehicles Emission in Forecast Assessment of Expressway Construction on Jiedong in Guangzhou City[J]. Journal of Jinan University:Natural Science, 2008, 29(3):276-280, 285. (in Chinese) [19] FU Fu-gang, MA Xu-dong, ZHOU Xiao-juan. Application of the CALINE4 Model in Motor Vehicles Emission in Environmental Impact Assessment of Expressway Construction on Anshun to Ziyun in Guizhou Province[J]. Environment and Ecology in the Three Gorges, 2011, 33(2):53-57. (in Chinese) [20] WANG Zheng, QIU Zhao-wen. Research of Plain Express Way Motor Vehicles Exhaust Pollution Levels Based on CALINE4 Model[J]. Energy Conservation & Environmental Protection in Transportation, 2015, (3):17-21. (in Chinese) [21] National Meteorological Information Center. Monthly Data Set of China's Terrestrial Cumulative Years (1981-2010) (1981-2010)[EB/OL]. (2012-08-28)[2018-09-09]. http://data.cma.cn/data/detail/dataCode/A.0029.0004.html. (in Chinese) [22] WANG Zhi-xin, JI Xue-zhi, ZHI Huai-bin. Particle and Smoke in Diesel Engine's Emission[J]. Diesel Engine, 2006, 28(6):19-21. (in Chinese) [23] WANG Liang. Study on Relationship among Dynamic Smoke, Filter Type Smoke Fs and Particles[J]. Modern Vehicle Power, 2016(4):32-35. (in Chinese)
2020, Vol. 14 
