Use of Subsampled Traffic Data to Estimate Roadway Emissions,Including Conversion to MOBILE6 Vehicle Classifications

Abstract

Air quality is degraded by many factors, among which the emissions from on‐road vehicles play a significant role. Timely and accurate estimate of such emissions becomes very important for policy‐making and effective control measures. However, lack of traffic data and outdated emission software make this task difficult. This research has demonstrated a new method that facilitates the vehicular emission inventories at the local level by using shorter-time Highway Performance Monitoring System (HPMS) traffic data along with the latest U.S. Environment Protection Agency (EPA) emission modeling software, MOBILE6. The conversion methodology was developed for converting readily available HPMS traffic volume data into EPA MOBILE-based traffic classifications, and a corresponding software program was written for automating the process. EPA MOBILE6 model was used to obtain emissions of nitrogen oxides (NO_x), volatile organic compound (VOC), and cabon monoxide (CO) emitted by the parent traffic and subsampled traffic data, and these emissions were additionally compared. The case study has shown that the difference of the magnitude between the emission estimates produced by certain subsampled and parent traffic data are minor, indicating that subsampled HPMS data can be used for reporting parent traffic emissions. It was also observed that traffic emissions follow a Weibull distribution, and NO_x emissions were more sensitive to the traffic data composition than VOC and CO. Lastly, use of average emission values of 20 or 30 consecutive minutes appears to be valid for representing hourly emissions.     

Spatial Variability of Different Fractions of Particulate Matter within an Urban Environment and between Urban and Rural Sites

ABSTRACT

The spatial variability of different fractions of particulate matter (PM) was investigated in the city of Basel, Switzerland, based on measurements performed throughout 1997 with a mobile monitoring station at six sites and permanently recorded measurements from a fixed site. Additionally, PM₁₀ measurements from the following year, which were concurrently recorded at two urban and two rural sites, were compared.

Generally, the spatial variability of PM₄, PM₁₀, and total suspended particulates (TSP) within this Swiss urban environment (area = 36 km²) was rather limited. With the exception of one site in a street canyon next to a traffic light, traffic density had only a weak tendency to increase the levels of PM. Mean PM₁₀ concentration at six sites with different traffic densities was in the range of less than ±10% of the mean urban PM₁₀ level. However, comparing the mean PM levels on workdays to that on weekends indicated that the impact of human activities, including traffic, on ambient PM levels may be considerable.

Differences in the daily PM₁₀ concentrations between urban and more elevated rural sites were strongly influenced by the stability of the atmosphere. In summer, when no persistent surface inversions exist, differences between urban and rural sites were rather small. It can therefore be concluded that spatial variability of annual mean PM concentration between urban and rural sites in the Basel area may more likely be caused by varying altitude than by distance to the city center.     

Developing a High-Resolution Vehicular Emission Inventory by Integrating an Emission Model and a Traffic Model: Part 2—A Case Study in Beijing

Abstract

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 × 10⁷ L, 4.28 × 10⁴ t, 1.97 × 10³ t, 0.28 × 10³ t, and 0.14 × 10³ t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Abstract

Emissions inventories of fine particulate matter (PM_2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM_2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM_2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5–20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM_2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM_2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

The sensitivity of modeled ozone to the temporal distribution of point, area, and mobile source emissions in the eastern United States

Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields used in air quality models (AQMs) generally show less temporal variability than corresponding measurements from continuous emissions monitors (CEM) and field campaigns would imply. If emissions control scenarios to reduce emissions at peak ozone forming hours are to be assessed with AQMs, the effect of emissions' daily variability on modeled ozone must be understood. We analyzed the effects of altering all anthropogenic emissions' temporal distributions by source group on 2002 summer-long simulations of ozone using the Community Multiscale Air Quality Model (CMAQ) v4.5 and the Carbon Bond IV (CBIV) chemical mechanism with 12 km resolution. We find that when mobile source emissions were made constant over the course of a day, 8-h maximum ozone predictions changed by ±7 parts per billion by volume (ppbv) in many urban areas on days when ozone concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation of point sources resulted in ozone changes of +6 and −6 ppbv, but only for small areas near sources. Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone, especially in urban areas at night; results suggest that shifting the emissions of NO_x from day to night, for example in electric powered vehicles recharged at night, could have beneficial impacts on air quality.     

Comparison between weekend and weekday ozone concentration in large cities in France

This paper examines ozone data from five large French cities (Marseilles, Lyon, Paris, Strasbourg and Toulouse) in spring and summer over a three-year period to study the possible influence of local primary pollutant emissions. In these cities the level of traffic emission varies according to the day of the week. There is a decrease of about 25% in traffic emissions between non-consecutive Tuesdays and Sundays. Traffic emissions on Fridays are about 40% more than on non-consecutive Sundays whereas they seem to be similar for non-consecutive Tuesdays and Thursdays. Despite this variation in traffic emissions between Fridays and Sundays, 85% of daily ozone maxima are identical for all days compared; in 15% of cases, percentiles of daily ozone maxima vary by about 20% at the most. This difference is observed for the highest values of daily ozone maxima that we can find both in rural and urban sites. Marseilles is the most pollution-sensitive city; every site of this area is concerned, which gives a regional origin to ozone variability. In the less-populated Toulouse area, differences between ozone on Fridays and Sundays are less significant. Our results show the importance of advection phenomena of ozone. It calls into question strategies of local reductions in traffic during ozone episodes.     

Spatial distribution of source locations for particulate nitrate and sulfate in the upper-midwestern United States

Two back-trajectory analysis methods designed to be used with multiple site data, simplified quantitative transport bias analysis (SQTBA) and residence time weighted concentration (RTWC), were applied to nitrate and sulfate concentration data from two rural sites (the Mammoth Cave National Park and the Great Smoky Mountain National Park) and five urban sites (Chicago, Cleveland, Detroit, Indianapolis, and St. Louis) for an intensive investigation on the spatial patterns of origins for these two species in the upper-midwestern area. The study was made by dividing the data into five categories: all sites and all seasons, rural sites in summer, rural sites in winter, urban sites in summer, and urban sites in winter. A general conclusion was that the origins of the nitrate in these seven sites were mainly in the upper-midwestern areas, while the sulfate in these seven sites were mainly from the Ohio and Tennessee River Valley areas. The upper-midwestern areas are regions of high ammonia emissions rather than high NO_x emissions. In the winter, metropolitan areas showed the highest nitrate emission potential suggesting the importance of local NO_x emissions. In the summer, ammonia emissions from fertilizer application in the lower midwestern area made a significant contribution to nitrate in the rural sites of this study. The impact of the wind direction prevalence on the source spatial patterns was observed by comparing the urban and rural patterns of the summer. The differences between the results of two methods are discussed and suggestions for applying these methods are also provided.     

Criteria and Air-Toxic Emissions from In-Use Automobiles in the National Low-Emission Vehicle Program

Abstract

The U.S. Environmental Protection Agency (EPA) implemented a program to identify tailpipe emissions of criteria and air-toxic contaminants from in-use, light-duty low-emission vehicles (LEVs). EPA recruited 25 LEVs in 2002 and measured emissions on a chassis dynamometer using the cold-start urban dynamometer driving schedule of the Federal Test Procedure. The emissions measured included regulated pollutants, particulate matter, speciated hydrocarbon compounds, and carbonyl compounds. The results provided a comparison of emissions from real-world LEVs with emission standards for criteria and air-toxic compounds. Emission measurements indicated that a portion of the in-use fleet tested exceeded standards for the criteria gases. Real-time regulated and speciated hydrocarbon measurements demonstrated that the majority of emissions occurred during the initial phases of the cold-start portion of the urban dynamometer driving schedule. Overall, the study provided updated emission factor data for real-world, in-use operation of LEVs for improved emissions modeling and mobile source inventory development.     

A mobile pollutant measurement laboratory—measuring gas phase and aerosol ambient concentrations with high spatial and temporal resolution

A mobile pollutant measurement laboratory was designed and built at the Paul Scherrer Institute (Switzerland) for the measurement of on-road ambient concentrations of a large set of trace gases and aerosol parameters with high time resolution (<15 s for most instruments), along with geographical and meteorological information. This approach allowed for pollutant level measurements both near traffic (e.g. in urban areas or on freeways/main roads) and at rural locations far away from traffic, within short periods of time and at different times of day and year. Such measurements were performed on a regular base during the project year of gas phase and aerosol measurements (YOGAM). This paper presents data measured in the Zürich (Switzerland) area on a late autumn day (6 November) in 2001. The local urban particle background easily reached 50 000 cm⁻³, with additional peak particle number concentrations of up to 400 000 cm⁻³. The regional background of the total particle number concentration was not found to significantly correlate with the distance to traffic and anthropogenic emissions of carbon monoxide and nitrogen oxides. On the other hand, this correlation was significant for the number concentration of particles in the size range 50–150 nm, indicating that the particle number concentration in this size range is a better traffic indicator than the total number concentration. Particle number size distribution measurements showed that daytime urban ambient air is dominated by high number concentrations of ultrafine particles (nanoparticles) with diameters <50 nm, which are immediately formed by traffic exhaust and thus belong to the primary emissions. However, significant variation of the nanoparticle mode was also observed in number size distributions measured in rural areas both at daytime and nighttime, suggesting that nanoparticles are not exclusively formed by primary traffic emissions. While urban daytime total number concentrations were increased by a factor of 10 compared to the nighttime background, corresponding factors for total surface area and total volume concentrations were 2 and 1.5, respectively.     

Air Quality Modeling of Interpollutant Trading for Ozone Precursors in an Urban Area

Abstract

Emission trading is a market‐based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O₃) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO_x) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O₃ concentrations and based on reductions in population exposures to O₃ were developed and evaluated using a three‐dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O₃ concentrations averaged over 8 hr. Emissions of VOC and NO_x from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O₃ concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day‐to‐day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology.     

A gas/aerosol air pollutants study over the urban area of Rome using a comprehensive chemical transport model

The aim of this study was to identify areas of potential relevant exposure to pollutants within Rome's urban core. To meet this goal, intensive field campaigns were conducted and simulations were performed, using the flexible air quality regional model (FARM), to study winter and summer pollution episodes. The simulations were performed using a complete emission inventory that included traffic flow model results of the Roman street network to better describe, with respect to the available diffuse national emission inventory, the hourly variation of traffic emissions in the city. The meteorological reconstruction was performed by means of both prognostic and diagnostic models by using experimental data collected during the field campaigns. To evaluate the capability of the FARM model to capture the main features of the selected episodes, a comparison of modelled results against observed air quality data for different pollutants was performed at urban and rural sites. FARM performed well in predicting ozone (O₃) and nitrogen dioxide (NO₂) concentrations, showing a good reproduction of both daily peaks and their diurnal variations. The model also showed a good capability to reproduce the magnitude of volatile alkane, aromatic and carbonyl compound concentrations. PM₁₀ model results revealed the tendency to under-predict the observed values. PM composition model results were compared with observed data, evidencing good results for elemental carbon (EC), nitrate (NO₃⁻) and ammonium (NH₄⁺), underestimation for sulphate (SO₄²⁻) and poor performance for organic matter (OM). The soil components of PM were found to be significantly under-predicted by the model, especially during Saharan dust episodes. Overall, the study results show large areas of high O₃ and PM₁₀ concentrations where levels of pollutants should be carefully monitored and population exposure evaluated.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Nonparametric factorial analysis of daily weigh-in-motion traffic: implications for the ozone “weekend effect” in Southern California

The Ozone Weekend Effect (OWE) has become increasingly more frequent and widespread in southern California since the mid-1970s. Although a number of hypotheses have been suggested to explain the effect, there remains uncertainty associated with the root factors contributing to elevated weekend ozone concentrations. Targeting the time window of the 1997 Southern California Ozone Study (SCOS97), this paper examines traffic activity data for 14 vehicle classes at 27 weigh-in-motion (WIM) stations in southern California. Nonparametric factorial analyses of light-duty vehicle (LDV) and heavy-duty truck (HDT) traffic volumes indicate significant differences in daily volumes by day of week and between the weekly patterns of daily LDV and HDT volumes. Across WIM stations, the daily LDV volume was highest on Friday and decreased by 10% on weekends compared to that on midweek days. In contrast, daily HDT volumes showed dramatic weekend drops of 53% on Saturday and 64% on Sunday. As a result, LDV to HDT ratios increased by 145% on weekends. Nonparametric tests also suggest that weekly traffic patterns varied significantly between WIM stations located close to (central) and far from (peripheral) the Los Angeles Metro area. Weekend increases in LDV/HDT ratios were more pronounced at central WIM sites due to greater weekend declines of HDT relative to LDV traffic. The implications of these weekly traffic patterns for the OWE in southern California were investigated by estimating daily WIM traffic on-road running exhaust emissions of total organic gas (TOG) and oxides of nitrogen (NO_x) using EMFAC2002 emission factors. The results support the California Air Resource Board's (CARB's) NO_x reduction hypothesis that greater weekend NO_x reductions relative to volatile organic compound (VOC) emissions, in combinations with the VOC-limited ozone system, contribute to the OWE observed in the region. The results from this study can be used to develop weekend on-road mobile emission inventories for the purpose of air quality modeling.     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.     

Improving the accuracy of emission inventories with a machine-learning approach and investigating transferability across cities

ABSTRACT

This study presents a novel method for integrating the output of a microscopic emission modeling approach with a regional traffic assignment model in order to achieve an accurate greenhouse gas (GHG, in CO_2-eq) emission estimate for transportation in large metropolitan regions. The CLustEr-based Validated Emission Recalculation (CLEVER) method makes use of instantaneous speed data and link-based traffic characteristics in order to refine on-road GHG inventories. The CLEVER approach first clusters road links based on aggregate traffic characteristics, then assigns representative emission factors (EFs), calibrated using the output of microscopic emission modeling. In this paper, cluster parameters including number and feature vector were calibrated with different sets of roads within the Greater Toronto Area (GTA), while assessing the spatial transferability of the algorithm. Using calibrated cluster sets, morning peak GHG emissions in the GTA were estimated to be 2,692 tons, which is lower than the estimate generated by a traditional, average speed approach (3,254 tons). Link-level comparison between CLEVER and the average speed approach demonstrates that GHG emissions for uncongested links were overestimated by the average speed model. In contrast, at intersections and ramps with more congested links and interrupted traffic flow, the average speed model underestimated GHG emissions. This proposed approach is able to capture variations in traffic conditions compared to the traditional average speed approach, without the need to conduct traffic simulation.

Implications: A reliable traffic emissions estimate is necessary to evaluate transportation policies. Currently, accuracy and transferability are major limitations in modeling regional emissions. This paper develops a hybrid modeling approach (CLEVER) to bridge between computational efficiency and estimation accuracy. Using a k-means clustering algorithm with street-level traffic data, CLEVER generates representative emission factors for each cluster. The approach was validated against the baseline (output of a microscopic emission model), demonstrating transferability across different cities .     

Comparison of the MOVES2010a,MOBILE6.2, and EMFAC2007 mobile source emission models with on-road traffic tunnel and remote sensing measurements

The Desert Research Institute conducted an on-road mobile source emission study at a traffic tunnel in Van Nuys, California, in August 2010 to measure fleet-averaged, fuel-based emission factors. The study also included remote sensing device (RSD) measurements by the University of Denver of 13,000 vehicles near the tunnel. The tunnel and RSD fleet-averaged emission factors were compared in blind fashion with the corresponding modeled factors calculated by ENVIRON International Corporation using U.S. Environmental Protection Agency's (EPA's) MOVES2010a (Motor Vehicle Emissions Simulator) and MOBILE6.2 mobile source emission models, and California Air Resources Board's (CARB's) EMFAC2007 (EMission FACtors) emission model. With some exceptions, the fleet-averaged tunnel, RSD, and modeled carbon monoxide (CO) and oxide of nitrogen (NO_x) emission factors were in reasonable agreement (±25%). The nonmethane hydrocarbon (NMHC) emission factors (specifically the running evaporative emissions) predicted by MOVES were insensitive to ambient temperature as compared with the tunnel measurements and the MOBILE- and EMFAC-predicted emission factors, resulting in underestimation of the measured NMHC/NO_x ratios at higher ambient temperatures. Although predicted NMHC/NO_x ratios are in good agreement with the measured ratios during cooler sampling periods, the measured NMHC/NO_x ratios are 3.1, 1.7, and 1.4 times higher than those predicted by the MOVES, MOBILE, and EMFAC models, respectively, during high-temperature periods. Although the MOVES NO_x emission factors were generally higher than the measured factors, most differences were not significant considering the variations in the modeled factors using alternative vehicle operating cycles to represent the driving conditions in the tunnel. The three models predicted large differences in NO_x and particle emissions and in the relative contributions of diesel and gasoline vehicles to total NO_x and particulate carbon (TC) emissions in the tunnel.

Implications: Although advances have been made to mobile source emission models over the past two decades, the evidence that mobile source emissions of carbon monoxide and hydrocarbons in urban areas were underestimated by as much as a factor of 2–3 in past inventories underscores the need for on-going verification of emission inventories. Results suggest that there is an overall increase in motor vehicle NMHC emissions on hot days that is not fully accounted for by the emission models. Hot temperatures and concomitant higher ratios of NMHC emissions relative to NO_x both contribute to more rapid and efficient formation of ozone. Also, the ability of EPA's MOVES model to simulate varying vehicle operating modes places increased importance on the choice of operating modes to evaluate project-level emissions.     

Source origin of trace elements in PM from regional background,urban and industrial sites of Spain

Despite their significant role in source apportionment analysis, studies dedicated to the identification of tracer elements of emission sources of atmospheric particulate matter based on air quality data are relatively scarce. The studies describing tracer elements of specific sources currently available in the literature mostly focus on emissions from traffic or large-scale combustion processes (e.g. power plants), but not on specific industrial processes. Furthermore, marker elements are not usually determined at receptor sites, but during emission. In our study, trace element concentrations in PM₁₀ and PM_2.5 were determined at 33 monitoring stations in Spain throughout the period 1995–2006. Industrial emissions from different forms of metallurgy (steel, stainless steel, copper, zinc), ceramic and petrochemical industries were evaluated. Results obtained at sites with no significant industrial development allowed us to define usual concentration ranges for a number of trace elements in rural and urban background environments. At industrial and traffic hotspots, average trace metal concentrations were highest, exceeding rural background levels by even one order of magnitude in the cases of Cr, Mn, Cu, Zn, As, Sn, W, V, Ni, Cs and Pb. Steel production emissions were linked to high levels of Cr, Mn, Ni, Zn, Mo, Cd, Se and Sn (and probably Pb). Copper metallurgy areas showed high levels of As, Bi, Ga and Cu. Zinc metallurgy was characterised by high levels of Zn and Cd. Glazed ceramic production areas were linked to high levels of Zn, As, Se, Zr, Cs, Tl, Li, Co and Pb. High levels of Ni and V (in association) were tracers of petrochemical plants and/or fuel-oil combustion. At one site under the influence of heavy vessel traffic these elements could be considered tracers (although not exclusively) of shipping emissions. Levels of Zn–Ba and Cu–Sb were relatively high in urban areas when compared with industrialised regions due to tyre and brake abrasion, respectively.     

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.     

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NO_x) emissions and the larger resulting from controlling of the less certain mobile NO_x emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.     

Transport of Atmospheric Fine Particulate Matter: Part 2—Findings from Recent Field Programs on the Intraurban Variability in Fine Particulate Matter

Abstract

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.