Quantification of Variability and Uncertainty in Lawn and Garden Equipment NOxand Total Hydrocarbon Emission Factors

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 to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation.Uncertainty refers to lack of knowledge regarding the true value of emissions.Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data.Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines.Variability was quantified using empirical and parametric distributions.Bootstrap simulation was used to characterize confidence intervals for the fitted distributions.The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NO x emissions were from -30 to +41% and from -45 to +75%, respectively.The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NO x .These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (EIs). INTRODUCTIONEmission inventories (EIs) are used for temporal emissions trend characterization, for emissions budgeting for regulatory and compliance purposes, and in air quality models for estimating ambient air quality.Nonquantified errors and biases in the EIs can lead to erroneous conclusions regarding emissions trends, apportionment of emissions, compliance, and the relationship between emissions and ambient pollutant concentration.The National Research Council (NRC), in a recent report on modeling of mobile source emissions, has recommended that efforts be conducted to quantify uncertainties in these emissions. 1In developing uncertainty estimates, it is important to properly distinguish between variability and uncertainty.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 to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation.Uncertainty refers to lack of knowledge regarding the true value of emissions.Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data.When developing EIs, it is important to have a good estimate of the average emission factor and to understand the range of uncertainty regarding the estimated average value.A quantitative approach to the characterization of variability and uncertainty is presented here as an important means for conveying the quality of estimates to analysts and decision-makers.The approach is applied to a case study for nonroad mobile sources, specifically lawn and garden (L&G) equipment.The 1990 Clean Air Act Amendments specifically directed the U.S. Environmental Protection Agency (EPA) to study the contribution of nonroad engines to urban air pollution and regulate them if warranted."Nonroad" is a term that covers a diverse collection of engines, equipment, and vehicles.Also referred to as "off-road" or "off-highway," the nonroad category includes outdoor power equipment, recreational equipment, farm equipment, construction equipment, L&G equipment, and marine vessels.