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For catalytic converter-equipped light-duty gasoline vehicles (LDGV), the hot-stabilized tailpipe emissions for pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) are well controlled. However, there are few reported real-world measurements of cold starts. Idling cold start and hot-stabilized trip exhaust emissions were measured for 37 LDGVs using a portable emissions measurement system (PEMS). Five vehicles were also measured for transient driving cold starts. On average, it took approximately 400, 150, 330, and 120 s to accumulate 90 percent of the idle cold start increments for fuel use, CO, HC, and NOx, respectively. Driving cold start increments were substantially higher than idling cold start increments, whereas cold start duration was typically shorter. For example, driving cold start contributed approximately 64%, 68%, 58%, and 4.5% of the trip total CO, HC, NOx, and carbon dioxide (CO2), respectively. This study is unique in quantifying the cold start contribution on a trip basis with real-world data. Although the cold start increment is sensitive to driving compared to idling, in either case, cold starts contribute substantially to total exhaust mass emissions. Furthermore, driver decisions regarding driving versus idle can substantially affect the contribution of cold starts, especially for CO and NOx. [ABSTRACT FROM AUTHOR]

ABSTRACT The objective of this research is to evaluate differences in fuel consumption and tailpipe emissions of flexible fuel vehicles (FFVs) operated on ethanol 85 (E85) versus gasoline. Theoretical ratios [...]

ABSTRACT Long-haul freight trucks typically idle for 2000 or more hours per year, motivating interest in reducing idle fuel use and emissions using auxiliary power units (APUs) and shore-power (SP). [...]

Nonroad construction vehicles and equipment powered by diesel engines contribute to mobile source air pollution. The engines of this equipment emit significant amounts of carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter. These pollutants pose serious problems for human health and the environment. Therefore, it is necessary to regulate and control the levels of these pollutants. Furthermore, there are emerging requirements and incentives for 'greening' of construction vehicle fleets and operations. Currently, there are two types of standards that regulate air pollution for these types of vehicles: technological standards for engines and quality standards for air. It is also necessary to quantify the levels of emissions that nonroad construction vehicles and equipment produce. Quantification may be based on existing data sources (such as the EPA NONROAD model) or by collecting data directly from the vehicles as they work in the field. The purpose of this paper is to introduce the challenges to quantification of emissions from nonroad construction vehicles, describe associated governmental regulations and incentives for reducing emissions, identify and compare various sources of emissions data, establish the need to collect additional data, and propose a future research agenda that focuses on air pollution generated by construction vehicles. DOI: 10.1061/(ASCE)CO.1943-7862.0000008 CE Database subject headings: Vehicles; Construction equipment; Air pollution; Emissions; Regulations; Data analysis.

ABSTRACT Motor graders are a common type of nonroad vehicle used in many road construction and maintenance applications. In-use activity, fuel use, and emissions were measured for six selected motor [...]

Conventional evaluation approaches for complex technologies, such as gas turbine systems, typically use process simulators for modeling, which are usually complicated and time-consuming. In order to facilitate policy analysis, a simplified desktop model for gas turbine systems based upon the air-standard Brayton cycle is developed in Microsoft EXCEL. The simplified model incorporates key process details and includes a comprehensive cost model. The model is calibrated based on a typical 'Frame 7F' heavy duty gas turbine fired with natural gas and syngas. The model generally produces accurate and reasonable estimates for performance and cost comparable to reference data. The model responds appropriately to different syngas compositions, such as based on variation in moisture content and C[O.sub.2] removal. Changes in syngas composition lead to different syngas heating values and thus affect gas turbine performance and cost. The effects of changes in inputs on key outputs are evaluated. Six key inputs are identified that are critical in order to obtain accurate estimates. The simplified model provides detailed technical information in a format that supports strategic planning and analysis. DOI: 10.1061/(ASCE)0733-9402(2007) 133:2(82) CE Database subject headings: Models; Turbines; Simulation; Sensitivity analysis.

ABSTRACT Integrated gasification combined cycle (IGCC) technology is a promising alternative for clean generation of power and coproduction of chemicals from coal and other feedstocks. Advanced concepts for IGCC systems [...]

ABSTRACT Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially [...]

ABSTRACT Vehicle-specific power (VSP) is useful for explaining a substantial portion of variability in real-world vehicle emissions, such as those measured with portable emissions monitoring systems (PEMS). VSP is a [...]

ABSTRACT Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum [...]

ABSTRACT The purpose of this study is to demonstrate a methodology for quantification of high emissions hot spots along roadways based upon real-world, on-road vehicle emissions measurements. An emissions hot [...]

ABSTRACT Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. [...]

ABSTRACT The objectives of this paper are to (1) quantify variability in hourly utility oxides of nitrogen (N[O.sub.x]) emission factors, activity factors, and total emissions; (2) investigate the autocorrelation structure [...]

ABSTRACT A study design procedure was developed and demonstrated for the deployment of portable onboard tailpipe emissions measurement systems for selected highway vehicles fueled by gasoline and E85 (a blend [...]

Quantitative methods for characterizing both variability and uncertainty are applied to case studies of nitrogen oxides (N[O.sub.x]) and total hydrocarbon air pollutant emission factors for construction, farm and industrial engines. A database was developed and statistical methods were used to identify statistically significant categories, including gasoline engines, two-stroke diesel engines, and four-stroke diesel engines. Emissions were not found to be statistically significantly different for older versus newer nonroad diesel engines nor when comparing naturally aspirated and turbocharged engines. Interengine variability in emissions was quantified using Weibull, gamma, and lognormal distributions. Bootstrap simulation was used to characterize confidence intervals for the mean. The 95% confidence intervals for the mean emission factors were as small as -10 to + 11% and as large as -48 to +49%, with an average range of -26 to +27%. Asymmetry in the confidence intervals is attributable to small sample sizes and skewness in the data. Estimates of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories. CE Database keywords: Uncertainty; Emissions; Variability; Air pollution; Nitrogen oxide; Construction equipment.

ABSTRACT The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, [...]

ABSTRACT Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed [...]