On-road Traffic Operation Data Aligned with Model Validation Need for Project-Level PM2.5 Conformity Analysis
When applying MOVES (MOtor Vehicle Emission Simulator) in project-level PM (particulate matter) conformity analysis, link-based traffic characteristics are required at local roadway level so as to ensure realistically representation of the local scale air quality modeling assessments. Fractions of the link traffic volume and average speed are represented by each vehicle type, which is defined as an emission source type in MOVES. Heavy truck traffic has been recognized one of the major PM emission sources (PM2.5 or PM10), and on-road traffic source emissions vary with traffic operation conditions (e.g., speed, acceleration or deceleration) and fleet compositions (i.e., percentage of vehicle types in traffic streams). Operating mode distribution is one of critical variables representing the attribute of a link traffic activity. The US Environmental Protection Agency (EPA) recommends obtaining the data from either other locations with similar geometric and traffic characteristics, or output from micro-simulation models. However, locally acquiring accurate fleet composition and relevant traffic operation data is always a challenge at various categories of roadways. And also little practical experiences are reported on MOVES model calibration and validation of the link-based emission factors. No outcomes from traffic simulation models are viewed reliable unless passing the calibration and validation tests. The goal of the proposed research is three-fold: 1) to explore methods and relevant models to extract required datasets from the existing traffic data sources and/or that can be obtained by using advanced data collection techniques to be compatible with the project-level PM2.5 conformity analysis; and 2) to explore the relationship between MOVES modeled emission rates and roadside ambient emission monitoring concentrations within an identified dimension around (or at a distance away from) the central line of the roadway, where the influences of ambient non-traffic sources and meteorological factors could be negligible; and 3) to develop a methodological framework for performing model validation for conformity analysis to MOVES and microscopic traffic simulation models in an integrated way. The following two research activities are proposed: 1. Investigate applied traffic data sources and collection techniques applied in a number of selected states in the US for all possible categories of roadways. Two major types of data courses will be investigated: 1) data sources and technologies for generating transportation activity relevant inputs for the project-level PM2.5 conformity by using MOVES, and 2) data sources and techniques for generating required data for validations of MOVES and traffic simulation model. Major traffic flow characteristics, such as traffic flow speed, vehicle classification, acceleration/deceleration, and road slop as well, are required to be obtained simultaneously for concerned periods of time. Data collection techniques that are commonly used in different states will be investigated and identified to be suitable for the conformity analysis. The techniques may include manual, portable (road tube), loop, video detection, and permanent Automatic Traffic Recorders (ATR), and intelligent transportation systems (ITS) methods. Meteorological data sources and, emission monitoring data collection technologies, as required by applying MOVES will be investigated. Models for generating data from the identified data courses to be easily applicable to MOVES and PM2.5 conformity analysis will be developed. 2. Since on-site monitored emission concentration data contains the influences of other ambient non-traffic sources or surrounding metrological factors, it is necessary to identify which geometric layout of the monitoring instruments relative to the roadway will minimize such an impact. And furthermore, the relationship between MOVES modeled emission rates and roadside monitored PM2.5 concentrations will be explored. The space dimension around (or at a distance away from) the central line of the roadway will be investigated theoretically and empirically by using the sample data in a case study to identify possible scope where the ambient factors could be negligible. The research results are expected to be helpful to developing approaches of evaluating modeled emission rates by applying the monitored roadside pollutant concentrations. 3. Develop model validation procedure in applying MOVES along with microscopic traffic simulation for project-level conformity analysis by using local link-based on-road data to improve the accuracy of local scale air quality modeling assessments. A case study will be conducted at a typical freeway, arterial, and a local street, all of which are located in a nonattainment and maintenance (N&M) area. The PM2.5 N&M areas are identified through evaluating regional level data acquired at a local metropolitan planning organization (MPO) and county environmental service agency. The data will be carefully evaluated against National Ambient Air Quality Standards (NAAQS). Traffic data and PM2.5 as well as meteorological data will be collected simultaneously at the study site. Proper design of applying the identified traffic data collection technique and/or data sources will be involved in this activity. The gained data will be used for studying the calibration and validation procedure of both models (no standard procedure is currently available for MOVES). Criteria for applying the identified data source as input of link-based traffic activities will be verified and/or recommended for update. 4. Identify potential new inputs for project level MOVES analysis that are currently not used; and identify traffic activity and/or operation related criteria for requiring hot-spot analysis.
The research result will better clarify the localized data barrier in project-level PM2.5 conformity analysis and provide a proof-of-concept framework for developing solutions by taking advantage of the existing traffic data sources and collection techniques. More significantly, a real-world case study for validating MOVES and traffic simulation models in an integrated manner will be provided to facilitate the application of the involved traffic and emission related models in the project-level conformity analysis. Convincible model validation procedure is a key factor to ensure the reliability and quality control of conformity analysis when MOVES and traffic simulation models are applied. Finally, recommendation about utilizing regional level data as part of project-level analysis will be expected to maximize the data source at MPOs or county environmental services while reducing the data collection burden at the microscopic level.
The University of Cincinnati
June 11, 2014
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