Role of Traffic Emission on Temporal and Spatial Characteristics of Pollutant Concentration on Urban Road Network: A Case of Beijing

This research aims to calculate PM2.5 concentration on the road network by considering the network-wide traffic status, which can be used to support research about the impact of urban road network pollution concentration on health. The increase in the use and number of vehicles has brought about a large amount of vehicle exhaust emissions and increased urban air pollutants. This is also one of the important reasons why this issue is worth studying. In this research, traffic emission was an estimate based on network-wide traffic status which was calculated from vehicle trajectories and spatial variance-covariance matrix. An identification method of external input pollutants is proposed to determine the occurrence of external pollutants imported into the urban area. To calculate the impact of multiple influencing factors on the pollution concentration of the entire road network, a multivariate linear model was adopted to calculate a variety of influencing factors and calibrate the model parameters by collecting real data. The results show that traffic emissions, external input pollution, and wind impact are the main factors affecting the PM2.5 concentration on urban road networks. Combined with real-time traffic data, we can obtain the temporal and spatial characteristics of the pollutant concentration of the road network. For policymakers, our research can provide a method for calculating the PM2.5 concentration on the road network, which is useful for establishing a health assessment framework in the future.

• Publication year

  2020

• Venue

  Journal of Advanced Transportation

• Publication date

  2020-11-20

• Fields of study

  Environmental Science

• Identifiers
  DOI 10.1155/2020/8883697
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data

  2020cited by this paper
• Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai

  2019cited by this paper
• Evaluating the Effects of One-Way Traffic Management on Different Vehicle Exhaust Emissions Using an Integrated Approach

  2019cited by this paper
• Near-Road Air Pollutant Measurements: Accounting for Inter-Site Variability Using Emission Factors.

  2018cited by this paper
• The use of random forests in modelling short-term air pollution effects based on traffic and meteorological conditions: A case study in Wrocław.

  2018cited by this paper
• Land use regression models for the oxidative potential of fine particles (PM2.5) in five European areas

  2018cited by this paper
• Optimization of PM2.5 Estimation Using Landscape Pattern Information and Land Use Regression Model in Zhejiang, China

  2018influential reference
• Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data

  2018cited by this paper
• Modeling carbon emissions from urban traffic system using mobile monitoring.

  2017cited by this paper
• Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.

  2017influential reference
• Land Use Regression Models for Ultrafine Particles in Six European Areas

  2017cited by this paper
• Characterizing the spatial distribution of ambient ultrafine particles in Toronto, Canada: A land use regression model.

  2016cited by this paper
• Air pollution and risk of respiratory and cardiovascular hospitalizations in the most populous city in Vietnam.

  2016cited by this paper
• Understanding how roadside concentrations of NO x are influenced by the background levels, traffic density, and meteorological conditions using Boosted Regression Trees

  2016cited by this paper
• Land Use Regression Modeling of PM2.5 Concentrations at Optimized Spatial Scales

  2016cited by this paper
• The role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spain

  2016cited by this paper
• Childhood autism spectrum disorders and exposure to nitrogen dioxide, and particulate matter air pollution: A review and meta-analysis.

  2016cited by this paper
• The significant impacts on traffic and emissions of ferrying children to school in Beijing

  2016cited by this paper
• Evolution of surface O3 and PM2.5 concentrations and their relationships with meteorological conditions over the last decade in Beijing

  2015cited by this paper
• Land Use Regression Models of On-Road Particulate Air Pollution (Particle Number, Black Carbon, PM2.5, Particle Size) Using Mobile Monitoring.

  2015cited by this paper
• Adult lung function and long-term air pollution exposure. ESCAPE: a multicentre cohort study and meta-analysis

  2014cited by this paper
• Real-world emissions of gasoline passenger cars in Macao and their correlation with driving conditions

  2014cited by this paper
• A machine learning model of Manhattan air pollution at high spatial resolution

  2014cited by this paper
• An hourly PM10 diagnosis model for the Bilbao metropolitan area using a linear regression methodology

  2013cited by this paper
• Long-term air pollution exposure and cardio- respiratory mortality: a review

  2013cited by this paper
• Air pollution and health risks due to vehicle traffic.

  2013cited by this paper
• Mobile monitoring of particle number concentration and other traffic-related air pollutants in a near-highway neighborhood over the course of a year.

  2012cited by this paper
• Air pollution and airway disease

  2011cited by this paper
• Real-Time Estimation of Arterial Travel Times with Spatial Travel Time Covariance Relationships

  2009cited by this paper
• Measurements and predictors of on-road ultrafine particle concentrations and associated pollutants in Los Angeles

  2008cited by this paper
• Vehicle emission inventories projection based on dynamic emission factors: A case study of Hangzhou, China

  2008cited by this paper
• Investigation into the use of the CUSUM technique in identifying changes in mean air pollution levels following introduction of a traffic management scheme

  2007cited by this paper
• Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA)

  2007cited by this paper
• Mobile platform measurements of ultrafine particles and associated pollutant concentrations on freeways and residential streets in Los Angeles

  2005cited by this paper
• Spatial Characteristics of Fine Particulate Matter: Identifying Representative Monitoring Locations in Seattle, Washington

  2002cited by this paper
• Springer series in statistics

  1986cited by this paper
• Analysis Of Winds And SO2 Concentrations InComplex Terrain

  1970cited by this paper

• Targeted Dissemination of Incident Information With Combinatorial Traffic-Communication Optimization

  2023cites this paper
• Evaluation of Type 322 Un-Signalized Intersection Performance

  2023cites this paper
• The spatial–temporal exposure to traffic-related Particulate Matter emissions

  2023cites this paper
• The Effect of COVID-19 Pandemic on Emitted PM 2.5 in Urban Road 1 Networks: Using Loop Data and Kriging Method for Passenger Cars 2 in the Central Part of the City of Lodz 3

  2022cites this paper
• The Effect of COVID-19 Pandemic on Emitted PM2.5 in Urban Road Networks: Using Loop Data and Kriging Method for Passenger Cars in the Central Part of the City of Lodz

  2022cites this paper
• Analyzing Spatiotemporal Daily Travel Source Carbon Emissions Based on Taxi Trajectory Data

  2021cites this paper
• Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach

  2021cites this paper