Air Quality Impacts of Distributed Energy Resources Implemented in the Northeastern United States

Abstract

Emissions from the potential installation of distributed energy resources (DER) in the place of current utility-scale power generators have been introduced into an emissions inventory of the northeastern United States. A methodology for predicting future market penetration of DER that considers economics and emission factors was used to estimate the most likely implementation of DER. The methodology results in spatially and temporally resolved emission profiles of criteria pollutants that are subsequently introduced into a detailed atmospheric chemistry and transport model of the region. The DER technology determined by the methodology includes 62% reciprocating engines, 34% gas turbines, and 4% fuel cells and other emerging technologies. The introduction of DER leads to retirement of 2625 MW of existing power plants for which emissions are removed from the inventory. The air quality model predicts maximum differences in air pollutant concentrations that are located downwind from the central power plants that were removed from the domain. Maximum decreases in hourly peak ozone concentrations due to DER use are 10 ppb and are located over the state of New Jersey. Maximum decreases in 24-hr average fine particulate matter (PM_2.5) concentrations reach 3 μg/m3 and are located off the coast of New Jersey and New York. The main contribution to decreased PM_2.5 is the reduction of sulfate levels due to significant reductions in direct emissions of sulfur oxides (SO_x) from the DER compared with the central power plants removed. The scenario presented here represents an accelerated DER penetration case with aggressive emission reductions due to removal of highly emitting power plants. Such scenario provides an upper bound for air quality benefits of DER implementation scenarios.     

Modeling the benefits of power plant emission controls in Massachusetts

Older fossil-fueled power plants provide a significant portion of emissions of criteria air pollutants in the United States, in part because these facilities are not required to meet the same emission standards as new sources under the Clean Air Act. Pending regulations for older power plants need information about any potential public health benefits of emission reductions, which can be estimated by combining emissions information, dispersion modeling, and epidemiologic evidence. In this article, we develop an analytical modeling framework that can evaluate health benefits of emission controls, and we apply our model to two power plants in Massachusetts. Using the CALPUFF atmospheric dispersion model, we estimate that use of Best Available Control Technology (BACT) for NOx and SO2 would lead to maximum annual average secondary particulate matter (PM) concentration reductions of 0.2 microg/m3. When we combine concentration reductions with current health evidence, our central estimate is that the secondary PM reductions from these two power plants would avert 70 deaths per year in a population of 33 million individuals. Although benefit estimates could differ substantially with different interpretations of the health literature, parametric perturbations within CALPUFF and other simple model changes have relatively small impacts from an aggregate risk perspective. While further analysis would be required to reduce uncertainties and expand on our analytical model, our framework can help decision-makers evaluate the magnitude and distribution of benefits under different control scenarios.     

Air emission inventories in North America: a critical assessment

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.     

Air Emission Inventories in North America: A Critical Assessment

Abstract

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.     

The sensitivity of the CHIMERE model to emissions reduction scenarios on air quality in Northern Italy

The sensitivity of the CHIMERE model to emission reduction scenarios on particulate matter PM2.5 and ozone (O₃) in Northern Italy is studied. The emissions of NO_x, PM2.5 SO₂, VOC or NH₃ were reduced by 50% for different source sectors for the Lombardy region, together with 5 additional scenarios to estimate the effect of local measures on improving the air quality for the Po valley area. Firstly, we evaluate the model performance by comparing calculated surface aerosol concentrations for the standard case (no emission reductions) with observations for January and June 2005. Calculated monthly mean PM10 concentrations are in general underestimated. For June, modelled PM10 concentrations slightly overestimate the measurements. Calculated monthly mean SO₄, NO₃^?, NH₄⁺ concentrations are in good agreement with the observations for January and June. Secondly, the model sensitivity of emission reduction scenarios on PM2.5 and O₃ calculated concentrations for the Po valley area is evaluated. The most effective scenarios to abate PM2.5 concentration are based on the SNAP2 (non-industrial combustion plants) and SNAP7 (road traffic) sectors, for which the NO_x and PM2.5 emissions are reduced by 50%. The number of days that the 2015 PM2.5 limit value of 25 μg m^?3 in Milan is exceeded by reducing primary PM2.5 and NO_x emissions for SNAP2 and 7 by 50%, does not change in January when compared to the standard case for the Milan area. It appears that 40% of the PM2.5 concentration in the greater Milan area is caused by the emissions surrounding the Lombardy region and from the model boundary conditions.This study also showed that a more effective pollutant reduction (emissions) per ton of pollutant reduced (concentrations) for the greater Milan area is obtained by reducing the primary PM2.5 emissions for SNAP7 by 50%. The most effective scenario on PM2.5 decrease for which precursor emissions are reduced is achieved by reducing SO₂ emissions by 50% for SNAP7.Our study showed that during summer time, the largest reductions in O₃ concentrations are achieved for SNAP7 emission reductions, when volatile organic compounds (VOCs) are reduced by 50%.     

A modeling study of coarse particulate matter pollution in Beijing: regional source contributions and control implications for the 2008 Summer Olympics

In the last 10 yr, Beijing has made a great effort to improve its air quality. However, it is still suffering from regional coarse particulate matter (PM10) pollution that could be a challenge to the promise of clean air during the 2008 Olympics. To provide scientific guidance on regional air pollution control, the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality Model (CMAQ) air quality modeling system was used to investigate the contributions of emission sources outside the Beijing area to pollution levels in Beijing. The contributions to the PM10 concentrations in Beijing were assessed for the following sources: power plants, industry, domestic sources, transportation, agriculture, and biomass open burning. In January, it is estimated that on average 22% of the PM10 concentrations can be attributed to outside sources, of which domestic and industrial sources contributed 37 and 31%, respectively. In August, as much as 40% of the PM10 concentrations came from regional sources, of which approximately 41% came from industry and 31% from power plants. However, the synchronous analysis of the hourly concentrations, regional contributions, and wind vectors indicates that in the heaviest pollution periods the local emission sources play a more important role. The implications are that long-term control strategies should be based on regional-scale collaborations, and that emission abatement of local sources may be more effective in lowering the PM10 concentration levels on the heavy pollution days. Better air quality can be attained during the Olympics by placing effective emission controls on the local sources in Beijing and by controlling emissions from industry and power plants in the surrounding regions.     

Natural emissions for regional modeling of background ozone and particulate matter and impacts on emissions control strategies

Natural emissions adopted in current regional air quality modeling are updated to better describe natural background ozone and PM concentrations for North America. The revised natural emissions include organosulfur from the ocean, NO from lightning, sea salt, biogenic secondary organic aerosol (SOA) precursors, and pre-industrial levels of background methane. The model algorithm for SOA formation was also revised. Natural background ozone concentrations increase by up to 4 ppb in annual average over the southeastern US and Gulf of Mexico due to added NO from lightning while the revised biogenic emissions produced less ozone in the central and western US. Natural PM_2.5 concentrations generally increased with the revised natural emissions. Future year (2018) simulations were conducted for several anthropogenic emission reduction scenarios to assess the impact of the revised natural emissions on anthropogenic emission control strategies. Overall, the revised natural emissions did not significantly alter the ozone responses to the emissions reductions in 2018. With revised natural emissions, ozone concentrations were slightly less sensitive to reducing NOx in the southeastern US than with the current natural emissions due to higher NO from lightning. The revised natural emissions have little impact on modeled PM_2.5 responses to anthropogenic emission reductions. However, there are substantial uncertainties in current representations of natural sources in air quality models and we recommend that further study is needed to refine these representations.     

Revised estimates of construction activity and emissions: Effects on ozone and elemental carbon concentrations in southern California

Emissions from diesel-powered construction equipment are an important source of nitrogen oxides (NO_x) and particulate matter (PM). A new emission inventory for construction equipment emissions is developed based on surveys of diesel fuel use; the revised inventory is compared to current emission inventories. California's OFFROAD model estimates are 4.5 and 3.1 times greater, for NO_x and PM respectively, than the fuel-based estimates developed here. The most relevant uncertainties are the overall amount of construction activity/diesel fuel use, exhaust emission factors for PM and NO_x, and the spatial allocation of emissions to county level and finer spatial scales. Construction permit data were used in this study to estimate spatial distributions of emissions; the resulting distribution is well correlated with population growth. An air quality model was used to assess the impacts of revised emission estimates. Increases of up to 15 ppb in predicted peak ozone concentrations were found in southern California. Elemental carbon and fine particle mass concentrations were in better agreement with observations using revised emission estimates, whereas negative bias in predictions of ambient NO_x concentrations increased.     

Air quality impact of the coal-fired power plants in the northern passageway of the China West-East Power Transmission Project

This paper analyzes the air quality impacts of coal-fired power plants in the northern passageway of the West-East Power Transmission Project in China. A three-layer Lagrangian model called ATMOS, was used to simulate the spatial distribution of incremental sulfur dioxide (SO2) and coarse particulate matter (PM10) concentrations under different emission control scenarios. In the year 2005, the emissions from planned power plants mainly affected the air quality of Shanxi, Shaanxi, the common boundary of Inner Mongolia and Shanxi, and the area around the boundary between Inner Mongolia and Ningxia. In these areas, the annually averaged incremental SO2 and PM10 concentrations exceed 2 and 2.5 microg/m3, respectively. The maximum increases of the annually averaged SO2 and PM10 concentrations are 8.3 and 7.2 microg/m3, respectively, which occur around Hancheng city, near the boundary of the Shaanxi and Shanxi provinces. After integrated control measures are considered, the maximum increases of annually averaged SO2 and PM10 concentrations fall to 4.9 and 4 microg/m3, respectively. In the year 2010, the areas affected by planned power plants are mainly North Shaanxi, North Ningxia, and Northwest Shanxi. The maximum increases of the annually averaged SO2 and PM10, concentrations are, respectively, 6.3 and 5.6 microg/m3, occurring in Northwest Shanxi, which decline to 4.4 and 4.1 microg/m3 after the control measures are implemented. The results showed that the proposed power plants mainly affect the air quality of the region where the power plants are built, with little impact on East China where the electricity will be used. The influences of planned power plants on air quality will be decreased greatly by implementing integrated control measures.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

Reduction of atmospheric emissions due to switching from fuel oil to natural gas at a power plant in a critical area in Central Mexico

ABSTRACT

A case study was conducted to evaluate the SO₂ emission reduction in a power plant in Central Mexico, as a result of the shifting of fuel oil to natural gas. Emissions of criteria pollutants, greenhouse gases, organic and inorganic toxics were estimated based on a 2010 report of hourly fuel oil consumption at the “Francisco Pérez Ríos” power plant in Tula, Mexico. For SO₂, the dispersion of these emissions was assessed with the CALPUFF dispersion model. Emissions reductions of > 99% for SO₂, PM and Pb, as well as reductions >50% for organic and inorganic toxics were observed when simulating the use of natural gas. Maximum annual (993 µg/m³) and monthly average SO₂ concentrations were simulated during the cold-dry period (152–1063 µg/m³), and warm-dry period (239–432 µg/m³). Dispersion model results and those from Mexico City’s air quality forecasting system showed that SO₂ emissions from the power plant affect the north of Mexico City in the cold-dry period. The evaluation of model estimates with 24 hr SO₂ measured concentrations at Tepeji del Rio suggests that the combination of observations and dispersion models are useful in assessing the reduction of SO₂ emissions due to shifting in fuels. Being SO₂ a major precursor of acid rain, high transported sulfate concentrations are of concern and low pH values have been reported in the south of Mexico City, indicating that secondary SO₂ products emitted in the power plant can be transported to Mexico City under specific atmospheric conditions.

Implications: Although the surroundings of a power plant located north of Mexico City receives most of the direct SO₂ impact from fuel oil emissions, the plume is dispersed and advected to the Mexico City metropolitan area, where its secondary products may cause acid rain. The use of cleaner fuels may assure significant SO₂ reductions in the plant emissions and consequent acid rain presence in nearby populated cities and should be compulsory in critical areas to comply with annual emission limits and health standards.     

Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.     

北京市燃煤的空气质量影响及其控制研究

建立了2005年北京市燃煤污染源排放清单,利用MM5-CMAQ模型计算了各区县各行业燃煤对北京市空气质量的影响。研究表明,2005年1月北京市燃煤源对各监测站点SO_2浓度的贡献在70%以上,对PM_(10)和NO_x浓度的贡献约为20%～40%和10%～30%;7月本地燃煤源对SO_2浓度的贡献在40%～50%左右。1月采暖锅炉对空气质量影响最大,占50%～70%;7月电厂的影响最大。依据北京市奥运空气质量保障方案以及"十一五"期间能源规划,建立了2010年燃煤污染源大气排放的规划情景,并模拟了各规划措施对大气质量的改善效果。通过实施电厂脱硫脱硝除尘、炼焦工业停产、钢铁行业和水泥行业搬迁减产、供热锅炉改造、平房用煤改造等措施,与2005年相比,SO_2平均浓度下降30%左右,NO_x和PM_(10)浓度的下降幅度15%。     

The impact of CO2 capture in the power and heat sector on the emission of SO2, NOx,particulate matter,volatile organic compounds and NH3 in the European Union

This study quantifies the trade-offs and synergies between climate and air quality policy objectives for the European power and heat (P&H) sector. An overview is presented of the expected performance data of CO₂ capture systems implemented at P&H plants, and the expected emission of key air pollutants, being: SO₂, NO_X, NH₃, volatile organic compounds (VOCs) and particulate matter (PM). The CO₂ capture systems investigated include: post-combustion, oxyfuel combustion and pre-combustion capture.For all capture systems it was found that SO₂, NO_x and PM emissions are expected to be reduced or remain equal per unit of primary energy input compared to power plants without CO₂ capture. Increase in primary energy input as a result of the energy penalty for CO₂ capture may for some technologies and substances result in a net increase of emissions per kWh output. The emission of ammonia may increase by a factor of up to 45 per unit of primary energy input for post-combustion technologies. No data are available about the emission of VOCs from CO₂ capture technologies.A simple model was developed and applied to analyse the impact of CO₂ capture in the European P&H sector on the emission level of key air pollutants in 2030. Four scenarios were developed: one without CO₂ capture and three with one dominantly implemented CO₂ capture system, varying between: post-combustion, oxyfuel combustion and pre-combustion.The results showed a reduction in GHG emissions for the scenarios with CO₂ capture compared to the baseline scenario between 12% and 20% in the EU 27 region in 2030. NO_x emissions were 15% higher in the P&H sector in a scenario with predominantly post-combustion and lower when oxyfuel combustion (?16%) or pre-combustion (?20%) were implemented on a large scale. Large scale implementation of the post-combustion technology in 2030 may also result in significantly higher, i.e. increase by a factor of 28, NH₃ emissions compared to scenarios with other CO₂ capture options or without capture. SO₂ emissions were very low for all scenarios that include large scale implementation of CO₂ capture in 2030, i.e. a reduction varying between 27% and 41%. Particulate Matter emissions were found to be lower in the scenarios with CO₂ capture. The scenario with implementation of the oxyfuel technology showed the lowest PM emissions followed by the scenario with a significant share allocated to pre-combustion, respectively ?59% and ?31%. The scenario with post-combustion capture resulted in PM emissions varying between 35% reduction and 26% increase.     

The impact of ozone on a salt marsh cordgrass (Spartina alterniflora)

Spartina alterniflora plants were collected from salt marshes within New Jersey, South Carolina, and Georgia USA and shipped to The Pennsylvania State University. New plants were grown from rhizomes in six open-top field chambers. Three chambers received charcoal-filtered air, and three received charcoal-filtered air plus 80 ppb ozone, 8 h/day for 65 days. Flower, leaf, and shoot number per plant were recorded weekly. Photosynthetic rates were measured in week 5, and foliar injury was assessed during week 9. Final dry weight of roots, shoots, and rhizomes were determined. While ozone-treated plants from all states expressed symptoms of ozone injury, plants from South Carolina exhibited no effect of ozone on any other measured variable. Plants from the Georgia site showed ozone-induced reductions in all measured variables except leaf dry weight. Ozone-treated plants from New Jersey showed reductions in photosynthetic rate, leaf and shoot number, and root dry weights. Only plants from New Jersey produced flowers, with ozone treatment causing delay in flowering and reduction in the number of flower spikes produced.     

Emission inventory for the road transport sector in Sardinia (Italy)

Atmospheric emission inventories are important tools for studying air quality and to set up possible remediation plans in areas characterised by nonattainment of the limit values established by legislation. In industrialised countries a considerable fraction of the emissions is due to road traffic, in particular in urban areas. For this reason emissions from road traffic must be estimated as accurately as possible, a task that can be performed, for the European vehicle fleet, thanks to the availability of the COPERT III methodology. This methodology is powerful and accurate, even if its algorithms can be difficult to apply in a regional emission inventory; moreover the collection of the necessary input data requires a lot of resources and time. This paper describes the road traffic emission inventory estimated for Region Sardinia (Italy) with a bottom-up approach. The estimation has been done by means of a software tool (EMITRA—EMIssions from road TRAnsport) which implements the COPERT III methodology. The resulting emission inventory has been compared against another emission inventory for Sardinia and against emission inventories for other Italian regions, to evaluate its reliability.     

Multi-criteria analysis for PM10 planning

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source–receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source–receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.     

Modeling of potential power plant plume impacts on Dallas-Fort Worth visibility

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called "white haze." The objective of this work was to assess whether reductions in the emissions of SO2 from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF6 tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO2 from the modeled power plant.     

Assessment of heavy metal releases from the use phase of road transport in Europe

An emission inventory was compiled for heavy metal air emissions from road transport in Europe (EU-40). For the database, country-specific data was taken such as the diesel and gasoline fuel consumption per country, the content of Pb in gasoline and diesel fuel and the share of different vehicle types. For tyre and brake wear emissions, average wear rates and heavy metal contents of different materials were used to develop emission factors for tyre and brake wear. It covers exhaust emissions (Pb from gasoline and diesel) as well as non-exhaust emissions (As, Cd, Cr, Ni and Pb from the wear of brake linings and vehicle tyres). The base year is 2000, and two scenarios were developed for 2010, a business as usual (BAU) scenario and a maximum feasible technical reduction (MFTR) scenario. Both result in a remarkable decrease in Pb exhaust emissions and a rising share of non-exhaust emissions. To assess the results, the inventory is (a) compared to an inventory compiled with a top-down approach that covers the same area and years but only emissions from combustion processes and (b) added to an inventory covering all sectors for heavy metal air emissions.     

A combined approach for the evaluation of a volatile organic compound emissions inventory

Emissions inventories significantly affect photochemical air quality model performance and the development of effective control strategies. However, there have been very few studies to evaluate their accuracy. Here, to evaluate a volatile organic compound (VOC) emissions inventory, we implemented a combined approach: comparing the ratios of carbon bond (CB)-IV VOC groups to nitrogen oxides (NOx) or carbon monoxide (CO) using an emission preprocessing model, comparing the ratios of VOC source contributions from a source apportionment technique to NOx or CO, and comparing ratios of CB-IV VOC groups to NOx or CO and the absolute concentrations of CB-IV VOC groups using an air quality model, with the corresponding ratios and concentrations observed at three sites (Maryland, Washington, DC, and New Jersey). The comparisons of the ethene/NOx ratio, the xylene group (XYL)/NOx ratio, and ethene and XYL concentrations between estimates and measurements showed some differences, depending on the comparison approach, at the Maryland and Washington, DC sites. On the other hand, consistent results at the New Jersey site were observed, implying a possible overestimation of vehicle exhaust. However, in the case of the toluene group (TOL), which is emitted mainly from surface coating and printing sources in the solvent utilization category, the ratios of TOL/ NOx or CO, as well as the absolute concentrations revealed an overestimate of these solvent sources by a factor of 1.5 to 3 at all three sites. In addition, the overestimate of these solvent sources agreed with the comparisons of surface coating and printing source contributions relative to NOx from a source apportionment technique to the corresponding value of estimates at the Maryland site. Other studies have also suggested an overestimate of solvent sources, implying a possibility of inaccurate emission factors in estimating VOC emissions from surface coating and printing sources. We tested the impact of these overestimates with a chemical transport model and found little change in ozone but substantial changes in calculated secondary organic aerosol concentrations.