William Rasdorf

Real-World In-Use Activity, Fuel Use, and Emissions for Nonroad Construction Vehicles: A Case Study for Excavators

Abstract A study design was developed and demonstrated for deployment of a portable emission measurement system (PEMS) for excavators. Excavators are among the most commonly used vehicles in construction activities. The PEMS measured nitric oxide, carbon monoxide, hydrocarbons, carbon dioxide, and opacity-based particulate matter. Data collection, screening, processing, and analysis protocols were developed to assure data quality and to quantify variability in vehicle fuel consumption and emissions rates. The development of data collection procedures was based on securing the PEMS while avoiding disruption to normal vehicle operations. As a result of quality assurance, approximately 90% of the attempted measurements resulted in valid data. On the basis of field data collected for three excavators, an average of 50% of the total nitric oxide emissions was associated with 29% of the time of operation, during which the average engine speed and manifold absolute pressure were significantly higher than corresponding averages for all data. Mass per time emission rates during non-idle modes (i.e., moving and using bucket) were on average 7 times greater than for the idle mode. Differences in normalized average rates were influenced more by intercycle differences than intervehicle differences. This study demonstrates the importance of accounting for intercycle variability in real-world in-use emissions to develop more accurate emission inventories. The data collection and analysis methodology demonstrated here is recommended for application to more vehicles to better characterize real-world vehicle activity, fuel use, and emissions for nonroad construction equipment.

Requirements and Incentives for Reducing Construction Vehicle Emissions and Comparison of Nonroad Diesel Engine Emissions Data Sources

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 chall...

Comprehensive Field Study of Fuel Use and Emissions of Nonroad Diesel Construction Equipment

Limited field data are available for analyses of fuel use and emissions of nonroad diesel construction equipment. This paper summarizes the results of field research that used a portable emissions monitoring system to collect fuel use and emissions data from eight backhoes, six bulldozers, three excavators, four generators, six motor graders, three off-road trucks, one skid-steer loader, three track loaders, and five wheel loaders while they performed various duty cycles. These tests produced approximately 119 h of field data for petroleum diesel and approximately 48 h for B20 biodiesel. Engine attribute data including horsepower, displacement, model year, engine tier, and engine load were collected to determine these factors’ influence on fuel use rates and emission rates of nitrogen oxides, hydrocarbons, carbon monoxide, carbon dioxide, and opacity. Mass per time fuel use rates were developed for each item of equipment, as were mass per time and mass per fuel used emission rates for each pollutant. For petroleum diesel, fuel use and emission rates of each pollutant were found to increase with engine displacement, horsepower, and load and to decrease with model year and engine tier. The results were qualitatively similar for B20 biodiesel. Fuel-based emission rates were found to have less variability and less sensitivity to engine size and load than time-based emission rates. Where possible, development of emission inventories based on fuel consumed, rather than time of activity, is preferred.

Characterization of Real-World Activity, Fuel Use, and Emissions for Selected Motor Graders Fueled with Petroleum Diesel and B20 Biodiesel

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 graders using a portable emission measurement system. Each motor grader was tested with petroleum diesel and B20 biodiesel. Duty cycles were quantified in terms of the empirical cumulative distribution function of manifold absolute pressure (MAP), which is an indicator of engine load. The motor graders were operated under normal duty cycles for road maintenance and repair at various locations in Wake and Nash Counties in North Carolina. Approximately 3 hr of quality-assured, second-by-second data were obtained during each test. An empirical modal-based model of vehicle fuel use and emissions was developed, based on stratifying the data with respect to ranges of normalized MAP, to enable comparisons between duty cycles, motor graders, and fuels. Time-based emission factors were found to increase monotonically with MAP. Fuel-based emission factors were mainly sensitive to differences between idle and non-idle engine operation. Cycle average emission factors were estimated for road “resurfacing”, “roading,” and “shouldering” activities. On average, the use of B20 instead of petroleum diesel leads to a negligible decrease of 1.6% in nitric oxide emission rate, and decreases of 19– 22% in emission rates of carbon monoxide, hydrocarbons, and particulate matter. Emission rates decrease significantly when comparing newer engine tier vehicles to older ones. Significant reductions in tailpipe emissions accrue especially from the use of B20 and adoption of newer vehicles.

Impact of Engine Idling on Fuel Use and CO2 Emissions of Nonroad Diesel Construction Equipment

It is difficult to quantitatively assess the impact of engine idling on fuel use and emissions of construction equipment because of a lack of sufficient data. This paper presents a methodology for evaluating the impact of idling on fuel use and carbon dioxide ( CO2 ) emissions of diesel construction equipment. The results are based on field data collected from 34 items of equipment. Engine idle time may be quantified in terms of equipment operational efficiency ( η ), which is defined as the ratio of nonidle time to total equipment use time (nonidle time plus idle time). Using η and the ratio of idle to nonidle fuel use and CO2 emission rates ( r ), the percentage increase in the total quantities of fuel used and CO2 emitted ( NE ) were calculated for each item of equipment for values of η less than the maximum theoretical operational efficiency of 100%. Results showed that as η decreased (or idle time increased), NE increased. A mathematical model that uses η as a predictor variable was developed to esti...

Field Procedures for Real-World Measurements of Emissions from Diesel Construction Vehicles

Construction vehicles are a source of nonroad mobile air pollutant emissions. Emissions from construction vehicles are typically quantified based on steady-state modal engine dynamometer tests using uninstalled stationary engines. However, these tests do not represent real-world activity. Therefore, there is a need to quantify energy use and air pollutant emissions from construction vehicles based on in-use measurement methods. The purpose of this paper is to outline standard procedures for field data collection for construction vehicles. This methodology is based on second-by-second measurement of in-use activity and air pollutant emissions using a portable emissions measurement system. The field data collection methodology includes the development of a study design, installation and use of instrumentation, and field measurements. After the field data collection, the raw data undergo a quality assurance procedure to check for and correct the synchronization between the engine data and emission data. This...

Comparison of Real-World Emissions of B20 Biodiesel Versus Petroleum Diesel for Selected Nonroad Vehicles and Engine Tiers

Field data for in-use fuel consumption and emission rates were collected for 15 nonroad vehicles by using a portable emission measurement system. Five backhoes, four front-end loaders, and six motor graders were tested once on petroleum diesel and once on B20 biodiesel. The vehicles represented a variety of engine certification tiers. A methodology was developed for study design, field data collection, data screening and quality assurance, data analysis, and benchmarking of the data. On average, 6.9% of data were lost because of quality issues and more than 3 h of valid data were collected in each test. Time-based emission factors increased monotonically with respect to engine manifold absolute pressure. Fuel-based emission factors were sensitive to differences between operations of engines idling and not idling. Typical duty cycles were quantified in terms of frequency distributions of manifold absolute pressure and used to estimate cycle average emission factors. On average, the use of B20 instead of petroleum diesel led to an insignificant 1.8% decrease in the nitric oxide (NO) emission rate and significant decreases of 18%, 26%, and 25% for opacity, hydrocarbons (HC), and carbon monoxide (CO), respectively. Emission rates decreased significantly in newer, higher-tier vehicles compared with older ones. Fuel use, NO, HC, and CO data were of similar magnitude as independent benchmark data. Specific recommendations were made for future work.

Development and Use of Emissions Inventories for Construction Vehicles

Real-world data are insufficient to estimate actual emissions from construction vehicles and to develop effective decisions aimed at reducing emissions. A methodology is developed here for inventorying construction fleet emissions on the basis of representative real-world measurements of construction vehicles by means of a portable emissions measurement system (PEMS). The PEMS enables measurements of actual duty cycles and their corresponding fuel use and emissions. The methodology is demonstrated via application to a fleet of publicly owned construction vehicles used primarily for highway maintenance. Selected backhoes, front-end loaders, and motor graders, representing various model years and engine emissions standards, were measured with PEMS during use. Tests were performed for B20 biodiesel and petroleum diesel (PD) fuels. Emission factors from the PEMS data, combined with owner records of annual fuel consumption for over 1,000 vehicles, were used to estimate annual inventories of tailpipe emissions of nitrogen oxides, particulate matter, hydrocarbons, and carbon monoxide. The emissions inventory was stratified by pollutant, vehicle type, fuel type, and engine tier and was used to assess fleet management strategies aimed at reducing emissions. Case study results illustrate that total fleet emissions would be reduced by 3% to 24% when B20 fuel was being used exclusively instead of PD exclusively, 11% to 50% when all Tier 0 and Tier 1 engines were replaced with Tier 2 engines, and 31% to 72% when B20 fuel was used exclusively in the highest engine tier available. Recommendations are made about development and practical applications of emissions inventories for construction fleet management.

Treatment of engineering design constraints in a relational data base

In this paper, a mechanism for representing and processing design constraints is presented. The mechanism can be used for checking constraints, that is, determining whether they are satisfied or violated, as well as for assigning attribute values such that the applicable constraints are thereby satisfied. Furthermore, thee mechanism provides flexibility in sequencing the enforcement of constraints, by allowing new constraints to be applied to a preexisting state of thee data base as well as to all subsequent transactions on thee data base. In both these respects, the mechanism proposed appears to have applications beyond engineering design. The paper demonstrates the implementation of the constraint management mechanism using the Relational Information Management (RIM) system, a commercially available data base management system (DBMS). (Author)

Modeling the impact of spatial relationships on horizontal curve safety

The curved segments of roadways are more hazardous because of the additional centripetalforces exerted on a vehicle, driver expectations, and other factors. The safety of a curve is dependent on various factors, most notably by geometric factors, but the location of a curve in relation to other curves is also thought to influence the safety of those curves because of a drivers expectation to encounter additional curves. The link between an individual curves geometric characteristics and its safety performance has been established, but spatial considerations are typically not included in a safety analysis. The spatial considerations included in this research consisted of four components: distance to adjacent curves, direction of turn of the adjacent curves, and radius and length of the adjacent curves. The primary objective of this paper is to quantify the spatial relationship between adjacent horizontal curves and horizontal curve safety using a crash modification factor. Doing so enables a safety professional to more accurately estimate safety to allocate funding to reduce or prevent future collisions and more efficiently design new roadway sections to minimize crash risk where there will be a series of curves along a route. The most important finding from this research is the statistical significance of spatial considerations for the prediction of horizontal curve safety. The distances to adjacent curves were found to be a reliable predictor of observed collisions. This research recommends a model which utilizes spatial considerations for horizontal curve safety prediction in addition to current Highway Safety Manual prediction capabilities using individual curve geometric features.