Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 2: Impact of vehicle emission on urban air quality

Abstract. A companion paper developed a vehicle emission inventory with high temporal–spatial resolution (HTSVE) with a bottom-up methodology based on local emission factors, complemented with the widely used emission factors of COPERT model and near-real-time (NRT) traffic data on a specific road segment for 2013 in urban Beijing (Jing et al., 2016), which is used to investigate the impact of vehicle pollution on air pollution in this study. Based on the sensitivity analysis method of switching on/off pollutant emissions in the Chinese air quality forecasting model CUACE, a modelling study was carried out to evaluate the contributions of vehicle emission to the air pollution in Beijing's main urban areas in the periods of summer (July) and winter (December) 2013. Generally, the CUACE model had good performance of the concentration simulation of pollutants. The model simulation has been improved by using HTSVE. The vehicle emission contribution (VEC) to ambient pollutant concentrations not only changes with seasons but also changes with time. The mean VEC, affected by regional pollutant transports significantly, is 55.4 and 48.5 % for NO2 and 5.4 and 10.5 % for PM2.5 in July and December 2013 respectively. Regardless of regional transports, relative vehicle emission contribution (RVEC) to NO2 is 59.2 and 57.8 % in July and December 2013, while it is 8.7 and 13.9 % for PM2.5. The RVEC to PM2.5 is lower than the PM2.5 contribution rate for vehicle emission in total emission, which may be due to dry deposition of PM2.5 from vehicle emission in the near-surface layer occuring more easily than from elevated source emission.

[1]  W. Stockwell,et al.  The second generation regional acid deposition model chemical mechanism for regional air quality modeling , 1990 .

[2]  Y. Qin,et al.  Traffic source emission and street level air pollution in urban areas of Guangzhou, South China (P.R.C.) , 1993 .

[3]  David G. Streets,et al.  Present and future emissions of air pollutants in China:: SO2, NOx, and CO , 2000 .

[4]  Dongquan He,et al.  Assessment of Vehicular Pollution in China , 2001, Journal of the Air & Waste Management Association.

[5]  J. Hao,et al.  [Motor vehicle source contributions to air pollutants in Beijing]. , 2001, Huan jing ke xue= Huanjing kexue.

[6]  Gerhard Wotawa,et al.  Ozone production from Canadian wildfires during June and July of 1995 , 2002 .

[7]  Petr Chylek,et al.  Canadian Aerosol Module: A size‐segregated simulation of atmospheric aerosol processes for climate and air quality models 1. Module development , 2003 .

[8]  J. Hao,et al.  Air pollutants contribution and control strategies of energy-use related sources in Beijing , 2005 .

[9]  J. Schauer,et al.  Seasonal trends in PM2.5 source contributions in Beijing, China , 2005 .

[10]  Zhiwei Han,et al.  Simulation of sulfur transport and transformation in East Asia with a comprehensive chemical transport model , 2006, Environ. Model. Softw..

[11]  S. Xie,et al.  [Development of vehicular emission inventory in China]. , 2006, Huan jing ke xue= Huanjing kexue.

[12]  Nicolas Moussiopoulos,et al.  Wind flow and photochemical air pollution in Thessaloniki, Greece. Part II: Statistical evaluation of European Zooming Model's simulation results , 2006, Environ. Model. Softw..

[13]  Yu Song,et al.  Source apportionment of PM2.5 in Beijing using principal component analysis/absolute principal component scores and UNMIX. , 2006, The Science of the total environment.

[14]  LI Chengcai,et al.  A modeling analysis of a heavy air pollution episode occurred in Beijing , 2006 .

[15]  Haiyan Wang,et al.  The assessment of emission-source contributions to air quality by using a coupled MM5-ARPS-CMAQ modeling system: A case study in the Beijing metropolitan region, China , 2007, Environ. Model. Softw..

[16]  Zhiwei Han,et al.  Evaluation and intercomparison of meteorological predictions by five MM5-PBL parameterizations in combination with three land-surface models , 2008 .

[17]  Oriol Jorba,et al.  The use of a modelling system as a tool for air quality management: annual high-resolution simulations and evaluation. , 2008, The Science of the total environment.

[18]  J. Mao,et al.  Traffic restrictions in Beijing during the Sino-African Summit 2006: aerosol size distribution and visibility compared to long-term in situ observations , 2008 .

[19]  Hui Yuan,et al.  Long-term monitoring and source apportionment of PM2.5/PM10 in Beijing, China. , 2008, Journal of environmental sciences.

[20]  Fei Chen,et al.  An Observational and Modeling Study of Characteristics of Urban Heat Island and Boundary Layer Structures in Beijing , 2009 .

[21]  Tong Zhu,et al.  Use of a mobile laboratory to evaluate changes in on-road air pollutants during the Beijing 2008 Summer Olympics , 2009 .

[22]  Ting Wang,et al.  Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period , 2009 .

[23]  G. Carmichael,et al.  Asian emissions in 2006 for the NASA INTEX-B mission , 2009 .

[24]  Jiming Hao,et al.  Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles , 2009 .

[25]  Hu Jiangkai.  Tentative Verification and Comparison of WRF Forecasts Driven by Data from T213 and T639 Models , 2010 .

[26]  DeHui Chen,et al.  A new-generation sand and dust storm forecasting system GRAPES_CUACE/Dust: Model development, verification and numerical simulation , 2010 .

[27]  Wei Wang,et al.  A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006 , 2011 .

[28]  Y. Roustan,et al.  Estimating the effect of on-road vehicle emission controls on future air quality in Paris, France , 2011 .

[29]  Renjian Zhang,et al.  Elemental Composition of Atmospheric Particles during Periods with and without Traffic Restriction in Beijing: The Effectiveness of Traffic Restriction Measure , 2011 .

[30]  E. Saikawa,et al.  The impact of China's vehicle emissions on regional air quality in 2000 and 2020: A scenario analysis , 2011 .

[31]  Sunling Gong,et al.  Emission inventories of primary particles and pollutant gases for China , 2011 .

[32]  Andrea Pozzer,et al.  Interactive comment on “A high-resolution emission inventory of primary pollutants for the Huabei region, China” by B. Zhao et al , 2011 .

[33]  Tong Zhu,et al.  The impact of circulation patterns on regional transport pathways and air quality over Beijing and its surroundings , 2011 .

[34]  Michael J. Burr,et al.  Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method , 2011 .

[35]  Meigen Zhang,et al.  Emission controls versus meteorological conditions in determining aerosol concentrations in Beijing during the 2008 Olympic Games , 2011 .

[36]  C. Nolte,et al.  Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology , 2013, Climate Dynamics.

[37]  Renjian Zhang,et al.  Characterization and Source Apportionment of PM2.5 in an Urban Environment in Beijing , 2013 .

[38]  Na Liu,et al.  Numerical model-based relationship between meteorological conditions and air quality and its implication for urban air quality management , 2013 .

[39]  Gang Wang,et al.  A new monitoring-simulation-source apportionment approach for investigating the vehicular emission contribution to the PM2.5 pollution in Beijing, China , 2013 .

[40]  Renjian Zhang,et al.  Chemical characterization and source apportionment of PM 2 . 5 in Beijing : seasonal perspective , 2013 .

[41]  He Jian-ju.  Impact of Land Surface Information on WRF's Performance in Complex Terrain Area , 2014 .

[42]  Zi-Rui Liu,et al.  Source apportionment of urban fine particle number concentration during summertime in Beijing , 2014 .

[43]  Lanning Wang,et al.  Air quality forecast of PM 10 in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) system: emission and improvement , 2014 .

[44]  Yu Qin,et al.  Association of cardiopulmonary health effects with source-appointed ambient fine particulate in Beijing, China: a combined analysis from the Healthy Volunteer Natural Relocation (HVNR) study. , 2014, Environmental science & technology.

[45]  Yao Qin.  Effects of relative humidity on the aerosol size distribution and visibility in the winter in Tianjin , 2014 .

[46]  Tim Li,et al.  Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing–Jin–Ji (China) and its nearby surrounding region – Part 1: Aerosol distributions and meteorological features , 2014 .

[47]  A. Piazzalunga,et al.  High secondary aerosol contribution to particulate pollution during haze events in China , 2014, Nature.

[48]  Source attribution of particulate matter pollution over North China with the adjoint method , 2015 .

[49]  Yuesi Wang,et al.  Tracking influential haze source areas in North China using an adjoint model, GRAPES-CUACE , 2015 .

[50]  Irene Cheng,et al.  Overview of receptor-based source apportionment studies for speciated atmospheric mercury , 2015 .

[51]  I. Kioutsioukis,et al.  High resolution WRF ensemble forecasting for irrigation: Multi-variable evaluation , 2016 .

[52]  Lin Wu,et al.  Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory , 2016 .