Identification and Characterization of Potential Discharge Areas for Radionuclide Transport by Groundwater from a Nuclear Waste Repository in Sweden

This paper describes solute transport modeling carried out as a part of an assessment of the long-term radiological safety of a planned deep rock repository for spent nuclear fuel in Forsmark, Sweden. Specifically, it presents transport modeling performed to locate and describe discharge areas for groundwater potentially carrying radionuclides from the repository to the surface where man and the environment could be affected by the contamination. The modeling results show that topography to large extent determines the discharge locations. Present and future lake and wetland objects are central for the radionuclide transport and dose calculations in the safety assessment. Results of detailed transport modeling focusing on the regolith and the upper part of the rock indicate that the identification of discharge areas and objects considered in the safety assessment is robust in the sense that it does not change when a more detailed model representation is used.     

PM2.5 Emissions from Aluminum Smelters: Coefficients and Environmental Impact

ABSTRACT

From 2004 to 2009, aiming to better understand implications for its smelters, Rio Tinto Alcan conducted a detailed study of PM_2.5 and PM₁₀ (particulate matter [PM] ≤ 2.5 and 10 μm in aerodynamic diameter, respectively) in its facilities. This involved a two-level study: part 1, emission quantification; and part 2, assessment of aluminum smelter contribution to the surrounding environment. In the first part, U.S. Environmental Protection Agency Other Test Method (OTM) OTM27 and OTM28 are assessed as relevant and efficient methods for measuring fine particle emissions from aluminum smelter stacks. Rio Tinto Alcan has also developed a safe and robust method called CYCLEX to measure PM_2.5 and condensable particulate matter (CPM) at the roof vents of potrooms. This work aims to determine the PM_2.5 emission coefficients of 17, 55, and 417 g·t^?1 of aluminum produced (including CPM) in anode baking furnace exhaust (fume treatment center), at potroom scrubber stacks (gas treatment centers), and at potroom roof vents, respectively. Results indicate that roof vents are the primary PM_2.5 emitters (85% of all smelter emissions) and that 71% of all smelter PM_2.5 comes from CPM. In the second part, preliminary inorganic speciation studies are conducted by scanning electron microscopy–energy-dispersive X-ray analysis and by isotopic ratios to track smelter emissions to their surrounding environment. This paper releases the first speciation results for an aluminum smelter, and the preliminary isotopic ratio study indicates a 3% impact in terms of PM_2.5 emissions for a representative smelter in an urban area.

IMPLICATIONS Aluminum smelters tend to continuously improve their competitiveness by incrementally increasing production. In this context, assessing the effect of major contaminants is overriding, and ambient air modeling is often the preferred way to do so. Fine particles fit this category, and the primary aluminum industry needs to accurately know their emission factors to obtain representative modeling. Moreover, not all aluminum smelters have a method to measure PM_2.5 at roof vents, the primary emission outlets. Therefore, this paper describes the first-rate PM_2.5 measurement methods for aluminum smelter roof vents without down-comers. It also provides insight for environmental managers for tracking PM_2.5 emissions in plant surroundings.     

Attainment and Maintenance of Particulate Standards in an Industrialized Region

The problems and priorities of air quality maintenance planning will depend in large part on the specific characteristics of a given region. For highly industrialized areas, maintenance planning for total suspended particulate matter (TSP) will pose an especially difficult challenge because of limitations in emissions inventories, modeling capabilities, air quality data, control technology assessments, and current regulatory policy.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.     

An integrated approach to model the biomagnification of organic pollutants in aquatic food webs of the Yangtze Three Gorges Reservoir ecosystem using adapted pollution scenarios

The impounding of the Three Gorges Reservoir (TGR) at the Yangtze River caused large flooding of urban, industrial, and agricultural areas, and profound land use changes took place. Consequently, substantial amounts of organic and inorganic pollutants were released into the reservoir. Additionally, contaminants and nutrients are entering the reservoir by drift, drainage, and runoff from adjacent agricultural areas as well as from sewage of industry, aquacultures, and households. The main aim of the presented research project is a deeper understanding of the processes that determines the bioaccumulation and biomagnification of organic pollutants, i.e., mainly pesticides, in aquatic food webs under the newly developing conditions of the TGR. The project is part of the Yangtze-Hydro environmental program, financed by the German Ministry of Education and Science. In order to test combinations of environmental factors like nutrients and pollution, we use an integrated modeling approach to study the potential accumulation and biomagnification. We describe the integrative modeling approach and the consecutive adaption of the AQUATOX model, used as modeling framework for ecological risk assessment. As a starting point, pre-calibrated simulations were adapted to Yangtze-specific conditions (regionalization). Two exemplary food webs were developed by a thorough review of the pertinent literature. The first typical for the flowing conditions of the original Yangtze River and the Daning River near the city of Wushan, and the second for the stagnant reservoir characteristics of the aforementioned region that is marked by an intermediate between lake and large river communities of aquatic organisms. In close cooperation with German and Chinese partners of the Yangtze-Hydro Research Association, other site-specific parameters were estimated. The MINIBAT project contributed to the calibration of physicochemical and bathymetric parameters, and the TRANSMIC project delivered hydrodynamic models for water volume and flow velocity conditions. The research questions were firstly focused on the definition of scenarios that could depict representative situations regarding food webs, pollution, and flow conditions in the TGR. The food webs and the abiotic site conditions in the main study area near the city of Wushan that determine the environmental preconditions for the organisms were defined. In our conceptual approach, we used the pesticide propanil as a model substance.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Modeling of flow and contaminant transport in coupled stream-aquifer systems

This paper describes an integrated approach for modeling flow and contaminant transport in hydraulically connected stream-aquifer systems. The code, FTSTREAM, extended the capabilities of the ground-water model, FTWORK, to incorporate chemical fate and transport in streams. Flow in the stream network is modeled as an unsteady, spatially varying flow, while transport modeling is based on a one-dimensional advection-dispersion equation. In addition to sorption and decay during transport in ground water, the model incorporates volatilization, settling and decay during transport in surface water. The interaction between surface water and ground water is accommodated by a leakage term and is implemented in the model using an iterative Picard-type procedure to ensure mass conservation across the interface between the two systems. The modeling approach is used to simulate contaminant transport in the Mad River, Ohio, which is hydraulically connected to a buried valley aquifer of sand and gravel outwash. The river is a receiving stream in the upstream part of the modeled area. Downstream, heavy pumping from a municipal well field causes the river to become a loosing stream. Induced infiltration from the river is responsible for a considerable portion of the well yield. The flow and transport model, developed for this study, simulates coupling between flow in the aquifer and the river. Hypothetical sources of contamination are introduced at selected locations in the upstream portion of the aquifer. The model is then used to simulate the expected transport in both the aquifer and the stream. A series of simulations elucidates the role of the river in facilitating the transport of the hypothetical contaminants in ground water and surface water. Effect of sorption, retardation and volatilization on contaminant transport is also examined for the case of the volatile organic compounds.     

Review of indoor emission source models. Part 1. Overview

Indoor emission source models are mainly used as a component in indoor air quality (IAQ) modeling, which, in turn, is part of exposure and risk modeling. They are also widely used to interpret the experimental data obtained from environmental chambers and buildings. This paper compiles 52 indoor emission source models found in the literature. Together, they represent the achievements that IAQ modelers have made in recent years. While most models have a certain degree of usefulness, genuine predictive models are still few, and there is undoubtedly much room for improvement. This review consists of two parts. Part 1--this paper-provides an overview of the 52 models, briefly discussing their validity, usefulness, limitations, and flaws (if any). Part 2 focuses on parameter estimation, a topic that is critically important to modelers but has not been systematically discussed.     

National estimates of outdoor air toxics concentrations

The Clean Air Act identifies 189 hazardous air pollutants (HAPs), or "air toxics," associated with a wide range of adverse human health effects. The U.S. Environmental Protection Agency has conducted a modeling study with the Assessment System for Population Exposure Nationwide (ASPEN) to gain a greater understanding of the spatial distribution of concentrations of these HAPs resulting from contributions of multiple emission sources. The study estimates year 1990 long-term outdoor concentrations of 148 air toxics for each census tract in the continental United States, utilizing a Gaussian air dispersion modeling approach. Ratios of median national modeled concentrations to estimated emissions indicate that emission totals without consideration of emission source type can be a misleading indicator of air quality. The results also indicate priorities for improvements in modeling methodology and emissions identification. Model performance evaluation suggests a tendency for underprediction of observed concentrations, which is likely due, at least in part, to a number of limitations of the Gaussian modeling formulation. Emissions estimates for HAPs have a high degree of uncertainty and contribute to discrepancies between modeled and monitored concentration estimates. The model's ranking of concentrations among monitoring sites is reasonably good for most of the gaseous HAPs evaluated, with ranking accuracy ranging from 66 to 100%.     

Spatially distributed pesticide exposure assessment in the Central Valley, California, USA

Field runoff is an important transport mechanism by which pesticides move into the hydrologic environment of intensive agricultural regions such as California's Central Valley. This study presents a spatially explicit modeling approach to extend Pesticide Root Zone Model (PRZM), a field-scale pesticide transport model, into basin level. The approach was applied to simulate chlorpyrifos use in the Central Valley during 2003-2007. The average value of loading as percent of use (LAPU) is 0.031%. Results of this study provide strong evidence that surface runoff generation and pesticide application timing are the two influencing factors on the spatial and temporal variability of chlorpyrifos sources from agricultural fields. This is one of the first studies in coupling GIS and field-scale models and providing simulations for the dynamics of pesticides over an agriculturally dominated landscape. The demonstrated modeling approach may be useful for implementations of best management practice (BMP) and total maximum daily load (TMDL).     

The World on a Collision Course and the Need for a New Economy

The first part of the paper is an attempt to demonstrate that what we are going through at the present time is not just an economic-financial crisis, but a crisis of humanity. It seems that for the first time in human history several crises converge to simultaneously reach their maximum level of tension. The dominant economic model is to a great degree responsible for the world’s collision course. Hence a number of myths that sustain the model are listed and analyzed. It is argued that a new economy, coherent with the problematiques of the twenty first century, needs urgently to be devised. The second part proposes the foundations for a new economy based on five fundamental postulates that allow the construction of transdisciplinary, holistic, and systemic visions to adequately understand the interdependence of all the elements that sustain life. It is stressed that it is no longer acceptable that Universities still teach economic theories of the nineteenth century in order to tackle twenty first century problems that have no precedence.     

Analysis of air toxics emission inventory: inhalation toxicity-based ranking

Air toxics emission inventories play an important role in air quality regulatory activities. Recently, Minnesota Pollution Control Agency (MPCA) staff compiled a comprehensive air toxics emission inventory for 1996. While acquiring data on the mass of emissions is a necessary first step, equally important is developing information on the potential toxicity of the emitted pollutants. To account for the toxicity of the pollutants in the emission inventory, inhalation health benchmarks for acute effects, chronic effects, and cancer were used to weight the mass of emissions. The 1996 Minnesota emissions inventory results were ranked by mass of emissions and by an index comprised of emissions divided by health benchmarks. The results show that six of eight pollutants ranked highest by toxicity were also the pollutants of concern indicated in environmental monitoring data and modeling data. Monitoring data and modeling results did not show high impacts of the other two pollutants that were identified by the toxicity-based emission ranking method. The biggest limitation in this method is the lack of health benchmark values for many pollutants. Despite uncertainties and limited information, this analysis provides useful information for further targeting pollutants and source categories for control.     

Comparing estimates of fugitive landfill methane emissions using inverse plume modeling obtained with Surface Emission Monitoring (SEM), Drone Emission Monitoring (DEM), and Downwind Plume Emission Monitoring (DWPEM)

ABSTRACT

As part of the global effort to quantify and manage anthropogenic greenhouse gas emissions, there is considerable interest in quantifying methane emissions in municipal solid waste landfills. A variety of analytical and experimental methods are currently in use for this task. In this paper, an optimization-based estimation method is employed to assess fugitive landfill methane emissions. The method combines inverse plume modeling with ambient air methane concentration measurements. Three different measurement approaches are tested and compared. The method is combined with surface emission monitoring (SEM), above ground drone emission monitoring (DEM), and downwind plume emission monitoring (DWPEM). The methodology is first trialed and validated using synthetic datasets in a hand-generated case study. A field study is also presented where SEM, DEM and DWPEM are tested and compared. Methane flux during two-days measurement campaign was estimated to be between 228 and 350 g/s depending on the type of measurements used. Compared to SEM, using unmanned aerial systems (UAS) allows for a rapid and comprehensive coverage of the site. However, as showed through this work, advancement of DEM-based methane sampling is governed by the advances that could be made in UAS-compatible measurement instrumentations. Downwind plume emission monitoring led to a smaller estimated flux compared with SEM and DEM without information about positions of major leak points in the landfill. Even though, the method is simple and rapid for landfill methane screening. Finally, the optimization-based methodology originally developed for SEM, shows promising results when it is combined with the drone-based collected data and downwind concentration measurements. The studied cases also discovered the limitations of the studied sampling strategies which is exploited to identify improvement strategies and recommendations for a more efficient assessment of fugitive landfill methane emissions.

Implications: Fugitive landfill methane emission estimation is tackled in the present study. An optimization-based method combined with inverse plume modeling is employed to treat data from surface emission monitoring, drone-based emission monitoring and downwind plume emission monitoring. The study helped revealing the advantages and the limitations of the studied sampling strategies. Recommendations for an efficient assessment of landfill methane emissions are formulated. The method trialed in this study for fugitive landfill methane emission could also be appropriate for rapid screening of analogous greenhouse gas emission hotspots.     

A Comparison of Measured and Simulated Ozone Concentrations in the Rural Areas of the Eastern United States during Summer 1995

ABSTRACT

The recent regulatory actions toward a longer-term (i.e., 8-hr) average ozone standard have brought forth the potential for many rural areas in the eastern United States to be in noncompliance. However, since a majority of these rural areas have generally few sources of anthropogenic emissions, the measured ozone levels primarily reflect the effects of the transport of ozone and its precursor pollutants and natural emissions. While photochemical grid models have been applied to urban areas to develop ozone mitigation measures, these efforts have been limited to high ozone episode events only and do not adequately cover rural regions. In this study, we applied a photochemical modeling system, RAMS/UAM-V, to the eastern United States from June 1-August 31, 1995. The purpose of the study is to examine the predictive ability of the modeling system at rural monitoring stations that are part of the Clean Air Status Trends Network (CASTNet) and the Gaseous Pollutant Monitoring Program (GPMP).

The results show that the measured daily 1-hr ozone maxima and the seasonal average of the daily 1-hr ozone maxima are in better agreement with the predictions of the modeling system than those for the daily 8-hr ozone maxima. Also, the response of the modeling system in reproducing the measured range of ozone levels over the diurnal cycle is poor, suggesting the need for improvement in the treatment of the physical and chemical processes of the modeling system during the nighttime and morning hours if it is to be used to address the 8-hr ozone standard.     

Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona

We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.     

A comparison of measured and simulated ozone concentrations in the rural areas of the eastern United States during summer 1995

The recent regulatory actions toward a longer-term (i.e., 8-hr) average ozone standard have brought forth the potential for many rural areas in the eastern United States to be in noncompliance. However, since a majority of these rural areas have generally few sources of anthropogenic emissions, the measured ozone levels primarily reflect the effects of the transport of ozone and its precursor pollutants and natural emissions. While photochemical grid models have been applied to urban areas to develop ozone mitigation measures, these efforts have been limited to high ozone episode events only and do not adequately cover rural regions. In this study, we applied a photochemical modeling system, RAMS/UAM-V, to the eastern United States from June 1-August 31, 1995. The purpose of the study is to examine the predictive ability of the modeling system at rural monitoring stations that are part of the Clean Air Status Trends Network (CASTNet) and the Gaseous Pollutant Monitoring Program (GPMP). The results show that the measured daily 1-hr ozone maxima and the seasonal average of the daily 1-hr ozone maxima are in better agreement with the predictions of the modeling system than those for the daily 8-hr ozone maxima. Also, the response of the modeling system in reproducing the measured range of ozone levels over the diurnal cycle is poor, suggesting the need for improvement in the treatment of the physical and chemical processes of the modeling system during the nighttime and morning hours if it is to be used to address the 8-hr ozone standard.     

Particulate matter modeling in the Los Angeles basin using SAQM-AERO

The SARMAP air quality model, enhanced with aerosol modeling capability, and its associated components were developed to understand causes of ozone (O3) and particulate matter exceedances in the San Joaquin Valley of California. In order for this modeling system to gain increasing acceptance and use in guiding air quality management, it is important to assess how transportable this modeling system is across geographic domains. We describe the first application of the modeling system outside the "home" domain for which it was developed and evaluated. We have chosen the August 27-28, 1987, intensive monitoring period of the Southern California Air Quality Study to evaluate the performance of the modeling system and to assess its sensitivity to emission control options. The predicted surface concentrations of O3 and other gas-phase species were spatially and temporally correlated with measured data. The fractional normalized absolute error was 0.32 to 0.36 for O3, and somewhat larger for other species. The fractional normalized bias for O3 on August 27 and 28, 1987, was 0.02 to 0.04. The simulated PM2.5 mass and constituent species concentrations reproduced the magnitude and variability of the observed daytime concentrations at most locations; however, nighttime PM2.5 concentrations were overpredicted by the model. The model's response to emission control options was consistent with other models of the same genre.     

Rethinking the assessment of photochemical modelin systems in air quality planning applications

The U.S. Environmental Protection Agency provides guidelines for demonstrating that future 8-hr ozone (O3) design values will be at or below the National Ambient Air Quality Standards on the basis of the application of photochemical modeling systems to simulate the effect of emission reductions. These guidelines also require assessment of the model simulation against observations. In this study, we examined the link between the simulated relative responses to emission reductions and model performance as measured by operational evaluation metrics, a part of the model evaluation required by the guidance, which often is the cornerstone of model evaluation in many practical applications. To this end, summertime O3 concentrations were simulated with two modeling systems for both 2002 and 2009 emission conditions. One of these two modeling systems was applied with two different parameterizations for vertical mixing. Comparison of the simulated base-case 8-hr daily maximum O3 concentrations showed marked model-to-model differences of up to 20 ppb, resulting in significant differences in operational model performance measures. In contrast, only relatively minor differences were detected in the relative response of O3 concentrations to emission reductions, resulting in differences of a few ppb or less in estimated future year design values. These findings imply that operational model evaluation metrics provide little insight into the reliability of the actual model application in the regulatory setting (i.e., the estimation of relative changes). In agreement with the guidance, it is argued that more emphasis should be placed on the diagnostic evaluation of O3-precursor relationships and on the development and application of dynamic and retrospective evaluation approaches in which the response of the model to changes in meteorology and emissions is compared with observed changes. As an example, simulated relative O3 changes between 1995 and 2007 are compared against observed changes. It is suggested that such retrospective studies can serve as the starting point for targeted diagnostic studies in which individual aspects of the modeling system are evaluated and refined to improve the characterization of observed changes.     

Changing speed-VMT distributions: the effects on emissions inventories and conformity

The emissions factor modeling component of the motor vehicle emissions inventory (MVEI) modeling suite is currently being revised by the California Air Resources Board (CARB). One of the proposed changes in modeling philosophy is a shift from using link-based travel activity data to trip-based travel data for preparing mobile emissions inventories. Also as part of the revisions, new speed correction factors (SCFs) will be developed by CARB for the revised model. The new SCFs will be derived from vehicle emissions on 15 new driving cycles, each constructed to represent a typical trip at a specific average speed. This paper discusses how the new SCFs will affect transportation conformity and emissions inventory development, and evaluates the differences in total emissions produced by trip-based and link-based distributions of speed and vehicle miles of travel (VMT). We simulated both link-based and trip-based speed-VMT distributions using travel data from the Sacramento and San Diego travel demand models. On the basis of the simulation results, there is reason to expect that mobile emissions inventories constructed using the proposed trip-based philosophy will differ markedly from those constructed in the current manner. Noting that results may vary by region, increases are expected in the CO and HC inventory levels, with concomitant decreases in the NOx mobile emissions inventories.