Modeling In-Use Vehicle Emissions and the Effects of Inspection and Maintenance Programs

Different ways for modeling the impact of vehicle emission inspection and maintenance programs on fleet hydrocarbon emissions are examined. A dynamic model is developed for forecasting fleet emissions in which individual vehicle performance is modeled as a stochastic process and vehicle emissions are tracked over time. Emissions inspection and repair are incorporated into the model, allowing for the stochastic aspects of both testing and repair. This model is compared to EPA’s model for evaluating the impact of vehicle emissions inspection and maintenance. We find that the way vehicle emission equipment deterioration overtime is modeled is important for forecasting emissions from the fleet and for assessing the success of inspection and maintenance programs. For inspection programs, we find that factors such as the proportion of vehicles tested, and repair effectiveness and duration have the greatest impact on emission reductions. The ability of different emission testing regimes to identify polluting vehicles has less impact on a program’s overall potential for emissions reduction. Policy recommendations for I&M testing and predictions of emission reduction credits from these tests will depend in important ways on the methods used in the underlying emissions models.     

Comparison among model estimates of critical loads of acidic deposition using different sources and scales of input data

The critical load (CL) of acidic atmospheric deposition represents the load of acidity deposited from the atmosphere to the earth’s surface at which harmful acidification effects on sensitive biological receptors are thought to occur. In this study, the CL for forest soils was estimated for 27 watersheds throughout the United States using a steady-state mass balance approach based on both national and site-specific data and using different approaches for estimating base cation weathering. Results suggested that the scale and source of input data can have large effects on the calculated CL and that the most important parameter in the steady-state model used to estimate CL is base cation weathering. These results suggest that the data and approach used to estimate weathering must be robust if the calculated CL is to be useful for its intended purpose.     

A comparison of results from two test methods for assessing the toxicity of aminotriazole to Selenastrum capricornutum

Two different test methods for assessing the toxicity of aminotriazole to Selenastrum capricornutum are compared. Growth medium composition is demonstrated to have a significant effect on the toxicity of aminotriazole.     

Advanced REACH Tool (ART): calibration of the mechanistic model

The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.     

A Statistical Model for FEV1 Response to Arbitrary Dynamic Ozone Exposure Conditions

ABSTRACT

Lung function response to inhaled ozone at ambient air pollution levels is known to be a function of ozone concentration, exposure duration, and minute ventilation. Most data-driven exposure-response models address exposures under static condition (i.e., with a constant ozone concentration and exercise pattern). Such models are simplifications, as both ambient ozone concentrations and normal human activity patterns change with time. The purpose of this study was to develop a dynamic model of response with the advantages of a statistical model (a relatively simple structure with few parameters). A previously proposed mechanistic model for changes in specific airways resistance was adapted to describe the percent change in forced expiratory volume in one second (FEV₁). This model was then reduced using the fit to three existing exposure-response data sets as criterion. The resulting model consists of a single linear differential equation together with an algebraic logistic equation. Under restricted static conditions the model reduces to a logistic model presented earlier by the authors.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 11. A Lognormal Model Relating Human Lung Function Decrease to O3 Exposure

Forced expiratory volume in 1 second (FEV1) was measured in 21 men exercising while exposed to four O₃ concentrations (0.0,0.08,0.10, and 0.12 ppm). A lognormal multiple linear regression model was fitted to their mean FEV1 measurements to predict FEV1 percent decrease as a function of O₃ concentration and exposure duration. The exercise level used was probably comparable to heavy manual labor. The longest O₃, exposure studied was 6 h. Extrapolating cautiously to an 8-h workday of heavy manual labor, the model predicts that O3 concentrations of 0.08, 0.10, and 0.12 ppm would decrease FEV1 by 9,15, and 20 percent, respectively.     

ANALYSIS OF WASTE LOAD ALLOCATION PROCEDURES1

A study was made to analyze and modify procedures used for stream assimilation capacity and point source wasteload allocation calculations. This paper describes the sources and types of information collected and the analysis of alternative computation methods developed during the study. The calculation of stream assimilation capacity or Total Maximum Daily Load (TMDL), will depend upon assumed stream flows, quality standards, reaction rates, and modeling procedures. The “critical conditions” selected for TMDL calculations usually are low flows and warm temperatures. The complexity of water quality models used for TMDL and allocation calculations can range from simple, complete mixing to calibrated and verified mathematical models. A list of 20 wasteload allocation (WLA) methods was developed. Five of these WLA's were applied to an example stream to permit comparisons based on cost, equity, efficient use of stream assimilation capacity, and sensitivity to fundamental stream quality data. Based on insensitivity to data errors and current use by several states, the WLA method of “equal percent treatment” was preferable in the example stream.