The landscape ecology of eastern white pine in northern lower Michigan

Master of ScienceForest EcologyUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/115731/1/39015056308169.pd

Development of organic gas exhaust speciation profiles for nonroad spark-ignition and compression-ignition engines and equipment

<div><p>The composition of exhaust emissions from nonroad engines and equipment varies based on a number of parameters, including engine type, emission control technology, fuel composition, and operating conditions. Speciated emissions data which characterize the chemical composition of these emissions are needed to develop chemical speciation profiles used for air quality modeling and to develop air toxics inventories. In this paper, we present results of an extensive review and analysis of available exhaust speciation data for total organic gases (TOG) for spark ignition (SI) engines running on gasoline/ethanol blends now in widespread use, and compression ignition (CI) engines running on diesel fuel. We identified two data sets best suited for development of exhaust speciation profiles. Neither of these data sets have previously been published. We analyzed the resulting speciation profiles for differences in SI engine exhaust composition between 2-stroke and 4-stroke engines using E0 (0% ethanol) and E10 (10% ethanol) blends, and differences in CI engine exhaust composition among engines meeting different emission standards. Exhaust speciation profiles were also analyzed to compare differences in maximum incremental reactivity (MIR) values; this is a useful indicator for evaluating how organic gases may affect ozone formation for air quality modeling. Our analyses found significant differences in speciated emissions from 2-stroke and 4-stroke SI engines, and between engines running on E0 and E10 fuels. We found significant differences in profiles from pre-Tier 1 CI engines, engines meeting Tier 1 standards, and engines meeting Tier 2 standards. Although data for nonroad CI engines meeting tier 4 standards with control devices such as particulate filters and selective catalyst reduction (SCR) devices were not available, data from highway CI engines suggest these technologies will substantially change profiles for nonroad CI engines as well (EPA, 2014c).</p><p>Implications: <i>The nonroad engine data sets analyzed in this study will substantially improve exhaust speciation profiles used to characterize organic gas emissions from nonroad engines. Since nonroad engines are major contributors to ambient air pollution, these profiles can considerably improve U.S. emission inventories for gaseous air toxics emitted from nonroad engines. The speciation profiles developed in this paper can be used to develop more accurate emission inputs to chemical transport models, leading to more accurate air quality modeling.</i></p></div

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

<div><p>Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data. </p><p></p><p>Implications: </p><p>PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.</p><p></p><p></p></div