State Implementation Plan

Abstract: The MOVES model was developed by the U.S. Environmental Protection Agency (U.S. EPA) to estimate emissions from on-road mobile sources and nonroad sources in the United States. Coupling high-resolution on-road vehicle activity data with appropriate MOVES emission rates further advances research efforts designed to assess the environmental impacts of transportation design and operation strategies. However, the complicated MOVES interface and slow performance makes it difficult to assess large, regional scale transportation networks and to undertake analyses of large-scale systems that are dynamic in nature. The MOVES-Matrix system develops an initial Large Matrix of MOVES outputs by running MOVES 146,853 times on the PACE high performance computing cluster to generate more than 90 billion emission rates to populate the matrix for a single area with one fuel regime and one inspection and maintenance program. A total of 117 such Large Matrices would be needed for the entire United States. The MOVES-Matrix system developed can be used to conduct the emissions modeling 200-times faster than using MOVES. The hypothetical case study shows that MOVES-Matrix is able to generate the exact same emission results as the MOVES model to ensure the validity for regulatory analysis. The resulting matrix allows users to link emission rates to big data projects and to evaluate changes in emissions for dynamic transportation systems in near-real-time. MOVES-Matrix does not currently estimate emissions from starts, hoteling or evaporative emissions, and the research team is working on MOVES-Matrix version 2 that supports incorporating off-network modeling.Implications: MOVES-Matrix should be of interest to a broad readership including those interested in vehicle emission modeling, near-road air quality modeling, transportation conformity analysis. The paper should also interest engineers who are involved in transportation regulatory and conformity analysis, state implementation plan, and who are seeking an efficient way of conducting regulatory emission modeling and air quality analysis in the United States.

Abstract: An APCA (now, the Air Waste Management Association) International Specialty Conference was held in San Francisco, California in February 1988 to exchange new information on novel applications, model theory, measurement processes, and software related to receptor models used in the management of air resources. Forty-six papers were presented in eight sessions which addressed: (1) PM{sub 10} source apportionment for state implementation plan development; (2) measurements and source apportionment of pollutants other than PM{sub 10}; (3) the requirements and availability of receptor model data bases; (4) the implementation of receptor models and their input data bases on microcomputers; (5) source characterization methods and results; and (6) model evaluation and development.

Abstract: In 2006, the U.S. Environmental Protection Agency implemented a more stringent standard for particulate matter with an effective diameter less than or equal to 2.5 microns (PM2.5). The implementation timeline for this standard will vary by state/district regulatory agency. For example, the San Joaquin Valley Air Pollution Control District has proposed to include cotton gins in their PM2.5 State Implementation Plan under the assumption that the PM2.5 emissions from cotton gins are significant enough to warrant further study and possibly additional control measures above and beyond the current mandate to install enhanced “1D-3D” cyclones on all emission points. All cotton gins across the cotton belt will eventually be impacted by this standard. The primary issues surrounding particulate matter regulations for the cotton ginning industry are: 1) limited or lack of PM2.5 data; 2) potential overprediction of current dispersion models; and 3) effects of sampler errors. The cotton ginners’ associations across the cotton belt, including the National, Texas, Southern, Southeastern, and California associations, have agreed that there is an urgent need to collect gin emission data to address these issues. In response to the gin association’s requests the project outlined in this paper was developed.