In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitiv...In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitivity for regional level has been well studied. However, the uncertainty analysis for project level running emissions has not been well understood. In this research, the MOVES model project level sensitivity tests on running emissions were conducted thru the analysis of vehicle specific power （VSP）, scaled tractive power （STP）, and MOVES emission rates versus speed curves. This study tested the speed, acceleration, and grade-three most critical variables for vehicle specific power for light duty vehicles and scaled tractive power for heavy duty vehicles. For the testing of STP, four regulatory classes of heavy duty vehicles including light heavy duty （LHD）, medium heavy duty （MHD）, heavy heavy duty （HHD） and bus were selected. MOVES project running emission rates were also tested for CO, PM2.5, NOx, and VOC versus the operating speeds. A Latin Hypercube （LH） sampling based on method for estimation of the ＂Sobal＂ sensitivity indices shows that the speed is the most critical variable among the three inputs for both VSP and STP. Acceleration and grades show lower response to the main effects and sensitivity indices. MOVES emission rates versus speeds curves for light duty vehicles show that highest emission occurs at lower speed range. No significant differences on emission rates among the regulatory classes of heavy duty vehicles are identified.展开更多
The measurement and assessment of dust emissions from different landforms are important to understand the atmospheric loading of PM10 （particulate matter ≤10 μm aerodynamic diameter） and to assess natural sources ...The measurement and assessment of dust emissions from different landforms are important to understand the atmospheric loading of PM10 （particulate matter ≤10 μm aerodynamic diameter） and to assess natural sources of dust; however, the methodology and technique for determining the dust still present significant research challenges. In the past, specialized field observation and field wind tunnel studies have been used to understand the dust emission. A series of wind tunnel tests were carried out to identify natural sources of dust and measure the magnitudes of dust emissions from different landforms. The method used in this study allowed the measurement of the PM10 emission rate using a laboratory based environmental boundary layer wind tunnel. Results indicated that PM10 emissions demonstrated strong temporal variation and were primarily driven by aerodynamic entrainment. Sand dunes, playa, and alluvial fans had the largest dust emission rates （0.8-5.4 mg/（me.s）） while sandy gravel, Gobi desert and abandoned lands had the lowest emission rates （0.003-0.126 mg/（m2.s））. Dust emissions were heavily dependent on the surface conditions, especially the availability of loose surface dust. High dust emissions were a result of the availability of dust- particle materials for entrainment while low dust emissions were a result of surface crusts and gravel cover. Soil surface property （surface crusts and gravel cover） plays an important role in controlling the availability of dust-sized particles for entrainment. The dust emission rate depended not only on the surface conditions but also on the friction velocity. The emission rate of PM10 varies as a power function of the friction velocity. Although dynamic abrasion processes have a strong influence on the amount of dust entrainment, aerodynamic entrainment may provide an important mechanism for dust emissions. Large volumes of dust entrained by aerodynamic entrainment cannot only occur at low shear velocity without saltation, but may dominate the展开更多
Large commercial cattle feedlots are significant sources of particulate matter (PM) emissions. This research compared WindTrax and the flux-gradient technique in estimating emissions of PM with aerodynamic diameter &l...Large commercial cattle feedlots are significant sources of particulate matter (PM) emissions. This research compared WindTrax and the flux-gradient technique in estimating emissions of PM with aerodynamic diameter < 10 μm (PM<sub>10</sub>) from cattle feedlots. Meteorological conditions were measured and PM<sub>10</sub> concentrations were profiled vertically (i.e., 2.0 to 7.62 m) at a large commercial beef cattle feedlot in Kansas from May through September 2011. Results show that between the two methods evaluated, WindTrax was least sensitive to changes in heights and number of heights used in the emission estimation, with calculated PM<sub>10</sub> emission rates varying by up to 18% only. On the other hand, PM<sub>10</sub> emission rates produced by the flux-gradient technique varied by almost 56% when changing either heights and/or number of heights in emission calculation. Both methods were sensitive to height settings, with their respective PM<sub>10</sub> emission rates higher when the lowest height setting (2.0 m) was included. Calculating PM<sub>10</sub> emission rates with the 7.62-m height led to lower estimates for the flux-gradient technique but no significant change in estimates was observed for WindTrax. As demonstrated in this study, for the flux-gradient technique, settings for the lowest and highest heights were the most critical in emission estimation;exclusion of other heights in between showed only to 2% to 6% change in calculated PM<sub>10</sub> emission rates. In general, the higher PM<sub>10</sub> emission rates were obtained with the flux-gradient technique. However, eliminating the lowest height (2.0 m) in the calculation and, at the same time, using a specific set of formulations for the flux-gradient technique made its calculated PM<sub>10</sub> emission rates slightly lower (but not significantly different) than those from WindTrax.展开更多
Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and vo...Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and volatile organic compounds. Vehicular traffic is also a promoter of climate change due to its greenhouse gas emissions, such as CO and CO2. Awareness of the spatiotemporal distribution of urban traffic, including the velocity distribution, allows knowing the spatiotemporal distribution of the air pollutant vehicular emissions required to understand urban air pollution. Although no well-established traffic theory exists, some models and approaches, like cellular automata, have been proposed to study the main aspects of this phenomenon. In this paper, a simple approach for estimating the space-time distribution of the air pollutant emission rates in traffic cellular automata is proposed. It is discussed with the Fukui-Ishibashi (FI) and Nagel-Schreckenberg (NS) models for traffic flow of identical vehicles in a single lane. We obtained the steady-state emission rates of the FI and NS models, being larger those produced by the first one, with relative differences of up to 45% in hydrocarbons, 56% in carbon monoxide, and 77% in nitrogen oxides.展开更多
基金support by U.S.Environmental Protection AgencyOhio Department of Transportation
文摘In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitivity for regional level has been well studied. However, the uncertainty analysis for project level running emissions has not been well understood. In this research, the MOVES model project level sensitivity tests on running emissions were conducted thru the analysis of vehicle specific power （VSP）, scaled tractive power （STP）, and MOVES emission rates versus speed curves. This study tested the speed, acceleration, and grade-three most critical variables for vehicle specific power for light duty vehicles and scaled tractive power for heavy duty vehicles. For the testing of STP, four regulatory classes of heavy duty vehicles including light heavy duty （LHD）, medium heavy duty （MHD）, heavy heavy duty （HHD） and bus were selected. MOVES project running emission rates were also tested for CO, PM2.5, NOx, and VOC versus the operating speeds. A Latin Hypercube （LH） sampling based on method for estimation of the ＂Sobal＂ sensitivity indices shows that the speed is the most critical variable among the three inputs for both VSP and STP. Acceleration and grades show lower response to the main effects and sensitivity indices. MOVES emission rates versus speeds curves for light duty vehicles show that highest emission occurs at lower speed range. No significant differences on emission rates among the regulatory classes of heavy duty vehicles are identified.
基金supported by the National Basic Research Program of China (2016YFA0601901, 2013CB956001)
文摘The measurement and assessment of dust emissions from different landforms are important to understand the atmospheric loading of PM10 （particulate matter ≤10 μm aerodynamic diameter） and to assess natural sources of dust; however, the methodology and technique for determining the dust still present significant research challenges. In the past, specialized field observation and field wind tunnel studies have been used to understand the dust emission. A series of wind tunnel tests were carried out to identify natural sources of dust and measure the magnitudes of dust emissions from different landforms. The method used in this study allowed the measurement of the PM10 emission rate using a laboratory based environmental boundary layer wind tunnel. Results indicated that PM10 emissions demonstrated strong temporal variation and were primarily driven by aerodynamic entrainment. Sand dunes, playa, and alluvial fans had the largest dust emission rates （0.8-5.4 mg/（me.s）） while sandy gravel, Gobi desert and abandoned lands had the lowest emission rates （0.003-0.126 mg/（m2.s））. Dust emissions were heavily dependent on the surface conditions, especially the availability of loose surface dust. High dust emissions were a result of the availability of dust- particle materials for entrainment while low dust emissions were a result of surface crusts and gravel cover. Soil surface property （surface crusts and gravel cover） plays an important role in controlling the availability of dust-sized particles for entrainment. The dust emission rate depended not only on the surface conditions but also on the friction velocity. The emission rate of PM10 varies as a power function of the friction velocity. Although dynamic abrasion processes have a strong influence on the amount of dust entrainment, aerodynamic entrainment may provide an important mechanism for dust emissions. Large volumes of dust entrained by aerodynamic entrainment cannot only occur at low shear velocity without saltation, but may dominate the
文摘Large commercial cattle feedlots are significant sources of particulate matter (PM) emissions. This research compared WindTrax and the flux-gradient technique in estimating emissions of PM with aerodynamic diameter < 10 μm (PM<sub>10</sub>) from cattle feedlots. Meteorological conditions were measured and PM<sub>10</sub> concentrations were profiled vertically (i.e., 2.0 to 7.62 m) at a large commercial beef cattle feedlot in Kansas from May through September 2011. Results show that between the two methods evaluated, WindTrax was least sensitive to changes in heights and number of heights used in the emission estimation, with calculated PM<sub>10</sub> emission rates varying by up to 18% only. On the other hand, PM<sub>10</sub> emission rates produced by the flux-gradient technique varied by almost 56% when changing either heights and/or number of heights in emission calculation. Both methods were sensitive to height settings, with their respective PM<sub>10</sub> emission rates higher when the lowest height setting (2.0 m) was included. Calculating PM<sub>10</sub> emission rates with the 7.62-m height led to lower estimates for the flux-gradient technique but no significant change in estimates was observed for WindTrax. As demonstrated in this study, for the flux-gradient technique, settings for the lowest and highest heights were the most critical in emission estimation;exclusion of other heights in between showed only to 2% to 6% change in calculated PM<sub>10</sub> emission rates. In general, the higher PM<sub>10</sub> emission rates were obtained with the flux-gradient technique. However, eliminating the lowest height (2.0 m) in the calculation and, at the same time, using a specific set of formulations for the flux-gradient technique made its calculated PM<sub>10</sub> emission rates slightly lower (but not significantly different) than those from WindTrax.
文摘Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and volatile organic compounds. Vehicular traffic is also a promoter of climate change due to its greenhouse gas emissions, such as CO and CO2. Awareness of the spatiotemporal distribution of urban traffic, including the velocity distribution, allows knowing the spatiotemporal distribution of the air pollutant vehicular emissions required to understand urban air pollution. Although no well-established traffic theory exists, some models and approaches, like cellular automata, have been proposed to study the main aspects of this phenomenon. In this paper, a simple approach for estimating the space-time distribution of the air pollutant emission rates in traffic cellular automata is proposed. It is discussed with the Fukui-Ishibashi (FI) and Nagel-Schreckenberg (NS) models for traffic flow of identical vehicles in a single lane. We obtained the steady-state emission rates of the FI and NS models, being larger those produced by the first one, with relative differences of up to 45% in hydrocarbons, 56% in carbon monoxide, and 77% in nitrogen oxides.
