DOI: 10.6086/d1pt0j
title: Connected Emission Control Technologies for Freight Vehicles

description: This project explores how connected vehicle technology can be used to
 reduce the impacts of air pollutant emissions from freight vehicles.
 Specifically, the objective of this project is to develop new vehicle
 routing algorithms for determining travel routes for heavy-duty diesel
 trucks that would reduce the exposure of local residents to air pollutant
 emissions from these trucks. The core of the methodology is to first
 estimate the total amount of human exposure to pollutant emissions
 generated by a truck when that truck travels on a particular road
 segment.  Once this is performed for all road segments, the
 estimated exposure value can be used in a least cost path algorithm to
 find a travel route that would minimize the total exposure value for the
 trip. To evaluate the potential benefits of this air pollution mitigation
 strategy, simulation-based experiments were carried out using the
 Reseda-Northridge area of Southern California as a case study. Overall, it
 was found that as compared to the fastest route, the low exposure route
 could result in more than 30% reduction in total air pollutant exposure
 for about 40% of the 400 simulated trips while keeping the increase in
 trip travel time to no more than 10%.
description: The traffic emission exposure modeling includes three steps and
 four components: 1) an emissions model is first used to quantify pollutant
 emissions from traffic activity; 2) next, a dispersion model is applied to
 compute the pollutant concentrations in the study area; and 3) a pollutant
 exposure model is then utilized to account for how much pollutant is
 actually inhaled by a target population group--in this research, inhaled
 mass (IM) is used as the metric for pollutant exposure. The final exposure
 estimates can be generated on a roadway link-by-link basis in a roadway
 network and used as input to a routing engine as part of the routing
 cost. 1) A
 digital roadway map is at the heart of any routing or navigation
 application. The map represents geographic features (e.g., location,
 length, shape), and stores attributes (e.g., road type, lane number, speed
 limit) of the roadway network. Then, traffic activities on roadways are
 estimated based on traffic demand and network attributes. In this study,
 we use street map of North America provided by ESRI due to the
 highly-detailed street information [12]. Posted speed limit values are
 assigned as average traffic speed in this project. For this particular
 implementation, EMFAC2011 is applied for mesoscale emission factor
 calculation. Emission factors for specific vehicle categories are
 downloaded from EMFAC2011 online database
 (https://www.arb.ca.gov/emfac/2011/). Then, link-by-link emission factors
 are determined based on the overall traffic speed on the links and saved
 as a new attribute of the roadway network. 2) An atmospheric dispersion
 model is utilized to estimate the concentration of air pollutants emitted
 from traffic sources at specific receptor locations. R-LINE
 (https://www.cmascenter.org/r-line/) is used in this study, where
 micrometeorology data inputs for R-LINE such as temperature, wind speed,
 wind direction, surface friction velocity, and Monin-Obukhov length are
 obtained from the South Coast Air Quality Management District.
 3) In this study,
 <i>inhaled mass (IM)</i> is used as the metric and calculated
 as <i>IM=C∙Pop∙t∙BR. </i>where <i>C</i> is the
 pollutant concentration (<i>µg/m<sup>3</sup></i>)
 in a given microenvironment as calculated by R-LINE.
 <i>Pop</i> is the number of subjects in the microenvironment.
 <i>t </i>is the duration of each trip
 (<i>hour</i>), and <i>BR</i> denotes the breathing
 rate (<i>m<sup>3</sup>/hour/capita</i>) of the
 subjects exposed to the pollutant. We apply the new routing algorithm to
 high-emitting vehicles (e.g., trucks) in order to minimize the target
 population’s exposure to certain pollutants for the purpose of protecting
 their health. <i></i>Then, we use a
 weighting method that transforms the multi-cost routing into a single-cost
 routing problem. An alternative route can be potentially found with less
 <em>IM </em>within a reasonable duration.  
description: <strong>street_attributes.xlsx</strong>: the
 attribute table of the street links corresponding to the R-LINE source
 input. The fields are described in the header.
 <strong>sensitive_facilities.xlsx</strong>: the table
 of sensitive facilities. The fields are described in the header.
 <strong>2010sfc.txt</strong>,
 <strong>2010pfl.txt</strong>: surface and profile
 meteorological parameters for R-LINE. Please refer to AERMOD/AERMET
 mannual for field description (https://www3.epa.gov/scram001/7thconf/aermod/<strong>aermet</strong>ugb.pdf).