Congestion Mitigation and Air Quality (CMAQ) Improvement Program: Cost-Effectiveness Tables Development and Methodology

2015PDFTech ReportAir qualityCost effectivenessPollutantsExhaust gasesNitrogen oxidesCarbon monoxideOrganic compoundsMobile sourcesMOVES2010bCMACUnited StatesJohn A. Volpe National Transportation Systems Center (U.S.)Puckett, SeanNoel, GeorgeJackson, LaurenMarjoncu, ErikRazo, MichaelReed, ErinJohn A. Volpe National Transportation Systems Center (U.S.)United States. Federal Highway Administration. Office of Planning, Environment, and RealtyAGR-IMPACTS-EnvironmentNTL-ENERGY AND ENVIRONMENT-Air QualityNTL-ENERGY AND ENVIRONMENT-Environment ImpactsVolpe National Transportation Systems Center, Technical Reference CenterThis document presents summary and detailed findings from a research effort to develop estimates of the cost-effectiveness of a range of project types funded under the Congestion Mitigation and Air Quality (CMAQ) Improvement Program. In this study, cost-effectiveness was measured in terms of dollars per short ton of pollutant reduced. The estimates were generated to satisfy Title 23, Chapter 1, Section 149 of the United States Code, which mandates illustrative estimates of the cost-effectiveness of projects eligible for CMAQ funding. This research offers separate cost-effectiveness estimates by each criteria pollutant and applicable precursor under the CMAQ program, including: carbon monoxide (CO) monoxide, nitrogen oxides (NOx), volatile organic compounds (VOCs), and particulate matter (PM10 and PM2.5). This research utilized EPA\u2019s MOVES2010b (Motor Vehicle Emission Simulator 2010, Version B) model to identify emission impacts by criteria pollutant and applicable precursors. In this research, estimates of project-level impacts (e.g., VMT impacts, travel speeds) were combined with unit (e.g., per-mile, per-hour) emission rates from MOVES2010b to yield estimated emission impacts in lieu of using either direct estimates from projects or relatively outdated tools (e.g., MOBILE6.2, (Mobile Source Emission Factor Model)). The analysis confirmed the presence of distinct levels of cost-effectiveness across types of projects and pollutants. Project types with estimated high cost-effectiveness include: \u2022 Heavy-duty vehicle idle reduction strategies (with high cost-effectiveness for all pollutants in the study); \u2022 heavy vehicle engine replacements (with high cost-effectiveness for all pollutants except for carbon monoxide); \u2022 diesel retrofit technologies (with high cost-effectiveness for PM2.5, PM10 and CO); \u2022 transit service expansion (with high cost-effectiveness for NOx, VOCs and CO); \u2022 park and ride projects (with high cost-effectiveness for NOx, VOCs and CO); \u2022 extreme-temperature cold start technologies (with high cost-effectiveness for VOCs and CO); \u2022 intermodal freight projects (with high cost-effectiveness for NOx); and \u2022 dust mitigation (with high cost-effectiveness for PM10)