CityDelta: A model intercomparison study to explore the impact of emission reductions in European cities in 2010

This paper gives an overview of the set up, methodology and the obtained results of the CityDelta (phase 1 and 2) project. In the context of the Clean Air For Europe programme of the European Commission, the CityDelta project was designed to evaluate the impact of emission-reduction strategies on air quality at the European continental scale and in European cities. Ozone and particulate matter (PM) are the main components that have been studied. To achieve this goal, a model intercomparison study was organized with the participation of more than 20 modelling groups with a large number of modelling configurations. Two following main topics can be identified in the project. First, in order to evaluate their strengths and weaknesses, the participating models were evaluated against observations in a control year (1999). An accompanying paper will discuss in detail this evaluation aspect for four European cities. The second topic is the actual evaluation of the impact of emission reductions on levels of ozone and PM, with particular attention to the differences between large-scale and fine-scale models. An accompanying paper will discuss this point in detail. In this overview paper the main input to the intercomparison is described as well as the use of the ensemble approach. Finally, attention is given to the policy relevant issue on how to implement the urban air quality signal into large-scale air quality models through the use of functional relationships.     

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.     

Sulfur deposition simulations over China, Japan, and Korea: a model intercomparison study for abating sulfur emission

In response to increasing trends in sulfur deposition in Northeast Asia, three countries in the region (China, Japan, and Korea) agreed to devise abatement strategies. The concepts of critical loads and source?Creceptor (S?CR) relationships provide guidance for formulating such strategies. Based on the Long-range Transboundary Air Pollutants in Northeast Asia (LTP) project, this study analyzes sulfur deposition data in order to optimize acidic loads over the three countries. The three groups involved in this study carried out a full year (2002) of sulfur deposition modeling over the geographic region spanning the three countries, using three air quality models: MM5-CMAQ, MM5-RAQM, and RAMS-CADM, employed by Chinese, Japanese, and Korean modeling groups, respectively. Each model employed its own meteorological numerical model and model parameters. Only the emission rates for SO₂ and NO_x obtained from the LTP project were the common parameter used in the three models. Three models revealed some bias from dry to wet deposition, particularly the latter because of the bias in annual precipitation. This finding points to the need for further sensitivity tests of the wet removal rates in association with underlying cloud?Cprecipitation physics and parameterizations. Despite this bias, the annual total (dry plus wet) sulfur deposition predicted by the models were surprisingly very similar. The ensemble average annual total deposition was 7,203.6?±?370 kt S with a minimal mean fractional error (MFE) of 8.95?±?5.24?% and a pattern correlation (PC) of 0.89?C0.93 between the models. This exercise revealed that despite rather poor error scores in comparison with observations, these consistent total deposition values across the three models, based on LTP group's input data assumptions, suggest a plausible S?CR relationship that can be applied to the next task of designing cost-effective emission abatement strategies.     

Simulating the response of metal contaminated lakes to reductions in atmospheric loading using a modified QWASI model

The changes in metal concentration following significant reductions in atmospheric metal loading of two nickel and copper contaminated lakes in Coniston Valley of the Sudbury Basin of Ontario, Canada were simulated by using steady-state and dynamic versions of a modified Quantitative Water Air Sediment Interaction (QWASI) Model. Metal partitioning and precipitation processes were quantified with the aid of US EPA's MINTEQA2 Model. The dynamic model successfully described the recovery of the two lakes and identified key input, loss and partitioning processes. A useful modelling strategy is to develop one or more steady-state models that give an approximate representation of conditions at defined times, then extend this to a dynamic version which can take into account the differing rates of response of components of the system. This modelling strategy can be used for designing and assessing remediation programs for metal contaminated lakes and watersheds.     

Observations and model simulations of carbon monoxide emission factors from a California highway

A series of twelve intensively monitored 1-hr CO dispersion studies were conducted near Davis, CA, in winter 1996. The experimental equipment included twelve CO sampling ports at elevations up to 50 m, three sonic anemometers, a tethersonde station, aircraft measurements of wind and temperature profile aloft, and a variety of conventional meteorological equipment. The study was designed to explore the role of vehicular exhaust buoyancy during worst-case meteorological conditions, such as low winds oriented in near-parallel alignment with the road during a surface-based nocturnal inversion. From the study, field estimates of the CO emission factor (EF) from a California vehicle fleet were computed using two different methods. The analysis suggests that the CT-EMFAC/EMFAC (EMission FACtor) models currently used to conduct federal conformity modeling significantly overpredict CO emissions for high-speed, free-flowing traffic on California highways.     

Simulating industrial emissions using atmospheric dispersion modeling system: model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp/Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOx, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.     

Crop loss assessment for California: modeling losses with different ozone standard scenarios

Crop yield losses were estimated for ambient O3 concentrations and for a series of potential O3 air quality standards for California, including the current statewide 1-h oxidant (O3) standard of 0.10 ppm (196 microg m(-3)), 12-h growing season averages, and other models. A model for statewide losses was developed using hourly O3 data for all sites in the State, county crop productivity data, and available O3 concentration-yield loss equations to determine potential yield losses for each crop in each county in California for 1984. Losses were based on comparison to an estimated background filtered air concentration of 0.025 or 0.027 ppm, for 12 or 7 h, respectively. Potential losses due to ambient air in 1984 were estimated at 19% to 25% for dry beans, cotton, grapes, lemons, onions, and oranges. Losses of 5% to 9% were estimated for alfalfa and sweet corn. Losses of 4% or less were estimated for barley, field corn, lettuce, grain sorghum, rice, corn silage, spinach, strawberries, sugar beets, fresh tomatoes, processing tomatoes, and wheat. Implementation of either a modified rollback to meet the current 1 h California O3 standard (0.10 ppm) or a three-month, 12-h growing season average of 0.045 ppm was necessary to produce large reductions in potential crop losses.     

Differences in response of two model estuarine crustaceans after lethal and sublethal exposures to chlorpyrifos

This study assessed the in vitro and in vivo effects of an acetylcholinesterase enzyme inhibitor (chlorpyrifos) in two estuarine crustaceans: grass shrimp (Palaemonetes pugio) and mysid (Americamysis bahia). The differences in response were quantified after lethal and sublethal exposures to chlorpyrifos and in vitro assays with chlorpyrifos-oxon. Results from the in vitro experiments indicated that the target enzyme, acetylcholinesterase (AChE), in the two species was similar in sensitivity to chlorpyrifos inhibition with IC50s of 0.98 nM and 0.89 nM for grass shrimp and mysids, respectively. In vivo experiments showed that mysids were significantly more sensitive to chlorpyrifos-induced AChE inhibition after 24 h of exposure. The in vivo EC50s for AChE inhibition were 1.23 μg L^?1 for grass shrimp and 0.027 μg L^?1 for mysids.

Median lethal concentrations (24h LC50 values) were 1.06 μg L^?1 for grass shrimp and 0.068 μg L^?1 for mysids. The results suggest that differences in the response of these two crustaceans are likely related to differences in uptake and metabolism rather than target site sensitivity.     

Measured isoprene emission rates of plants in California landscapes: comparison to estimates from taxonomic relationships

Isoprene emission rates of 64 plant species found in California's urban and natural landscapes were measured using a dynamic flow-through chamber enclosure technique. Species were selected to provide data for previously unmeasured species and to test estimates of isoprene emission rates based upon taxonomic relationships developed for compilation of biogenic emission inventories as proposed by Benjamin et al. (1996, Atmospheric Environment 30, 1437–1452). Branch-level isoprene emission rates ranged from undetectable for 47 species, to 54 μg g⁻¹ h⁻¹ for Quercus kelloggii, California black oak. Isoprene emission rate estimates based on taxonomy agreed well with our measurements for species within the same genus, with the exception of the Quercus genus for which a wide range of isoprene emission rates have been reported. As expected, family-level estimates based on taxonomy showed greater deviation from our measured values than did genus-based estimates. The data developed in the present study support use of a taxonomic predictive methodology, especially if previous measurements within specific families, sub-families, and genera are extensive, and the results of such assignment are treated with proper caution. A taxonomic approach may be most useful where plant species in natural and urban landscapes are numerous, such as in California, where no experimental measurements are available for thousands of species.     

Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution

Air quality models (AQM) consist of many modules (meteorology, emission, chemistry, deposition), and in some conditions such as: vicinity of clouds or aerosols plumes, complex local circulations (mountains, sea breezes), fully coupled models (online method) are necessary. In order to study the impact of lumped chemical mechanisms in AQM simulations, we examine the ability of both different chemical mechanisms: (i) simplified: Condensed Version of the MOdèle de Chimie Atmosphérique 2.2 (CV-MOCA2.2), and (ii) reference: Regional Atmospheric Chemistry Model (RACM), which are coupled online with the Regional Atmospheric Modeling Systems (RAMS) model, on the distribution of pollutants. During the ESCOMPTE experiment (Expérience sur Site pour COntraindre les Modèles de Pollution et de Transport d’Emissions) conducted over Southern France (including urban and industrial zones), Intensive observation periods (IOP) characterized by various meteorological and mixed chemical conditions are simulated. For both configurations of modeling, numerical results are compared with surface measurements (75 stations) for primary (NO_x) and secondary (O₃) species. We point out the impact of the two different chemical mechanisms on the production of species involved in the oxidizing capacity such as ozone and radicals within urban and industrial areas. We highlight that both chemical mechanisms produce very similar results for the main pollutants (NO_x and O₃) in three-dimensional (3D) distribution, despite large discrepancies in 0D modeling. For ozone concentration, we found sometimes small differences (5–10 ppb) between the mechanisms under study according to the cases (polluted or not). The relative difference between the two mechanisms over the whole domain is only −7% for ozone from CV-MOCA 2.2 versus RACM. When the order of magnitude is needed rather than an accurate estimate, a reduced mechanism is satisfactory. It has the advantage of running faster (four times less than CPU time on SGI 3800 with 30 processors). Simplified mechanisms are really important to study cases for which an online coupling is necessary between meso-scale and chemistry models (clouds or aerosols plumes impacts, highly variable meteorology).     

Trends in fine particle concentration and chemical composition in southern California

Airborne fine particle mass concentrations in Southern California have declined in recent years. Trends in sulfate and elemental carbon (EC) particle concentrations over the period 1982-1993 are consistent with this overall improvement in air quality and help to confirm some of the reasons for the changes that are seen. Fine particle sulfate concentrations have declined as a strict sulfur oxides (SOx) emission control program adopted in 1978 was implemented over time. Fine particle elemental (black) carbon concentrations have declined over a period when newer diesel engines and improved diesel fuels have been introduced into the vehicle fleet. Organic aerosol concentrations have not declined as rapidly as the EC particle concentrations, despite the fact that catalyst-equipped cars having lower particle emission rates were introduced into the vehicle fleet alongside the diesel engine improvements mentioned above. This situation is consistent with the growth in population and vehicle miles traveled in the air basin over time. Fine particle ammonium nitrate in the Los Angeles area atmosphere contributes more than half of the fine aerosol mass concentration on the highest concentration days of the year, emphasizing both the need for accurate aerosol nitrate measurements and the likely importance of deliberate control of aerosol nitrate as a part of any serious further fine particle control program for the Los Angeles area.     

Review and prospects of mining chemical dust suppressant: classification and mechanisms

Environmental Science and Pollution Research - Coal mine pollution is a serious threat to the mine safe production and occupational health of miners. Chemical dust suppression can effectively...     

Effects of sulfur dioxide and oxides of nitrogen emission reductions on fine particulate matter mass concentrations: regional comparisons

Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.     

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 2--A case study in Beijing

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 x 10(7) L, 4.28 x 10(4) t, 1.97 x 10(3) t, 0.28 x 10(3) t, and 0.14 x 10(3) 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.     

Effects of SO2 and NOx emission reductions on PM2.5 mass concentrations in the southeastern United States

Measurements from sites of the Southeastern Aerosol Research and Characterization (SEARCH) program, made from 1998 to 2001, are used with a thermodynamic equilibrium model, Simulating Composition of Atmospheric Particles at Equilbrium (SCAPE2), to extend an earlier investigation of the responses of fine particulate nitrate (NO3-) and fine particulate matter (PM2.5) mass concentrations to changes in concentrations of nitric acid (HNO3) and sulfate (SO42-). The responses were determined for a projected range of variations of SO42- and HNO3 concentrations resulting from adopted and proposed regulatory initiatives. The predicted PM2.5 mass concentration decreases averaged 1.8-3.9 microg/m3 for SO42- decreases of 46-63% from current concentrations. Combining the S042- decrease with a 40% HNO3 decrease from current concentrations (approximating expected mobile-source oxides of nitrogen [NOx] reductions by 2020) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0.2 microg/m3 for three nonurban sites and 0.8-1 microg/m3 for one nonurban and two urban sites. Increasing the HNO3 reduction to 55% (an estimate of adding Clear Skies Phase II NOx reductions) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0-0.4 microg/m3. Because of the well-documented losses of particulate NO3- from Federal Reference Method (FRM) filters, only a fraction of these incremental changes would be observed.     

The need for ammonia abatement with respect to secondary PM reductions in Europe

In Europe, secondary particulate matter (PM) comprises 50% or more of PM 2.5. To reduce PM concentrations requires lowering precursor emissions. Since the 1980s, SO(2) emissions have decreased by more than 60%, while particle concentrations have decreased less. NO(x) and NH(3) emissions have decreased slightly. The role of ammonia in particle formation is addressed here. It is shown that secondary PM concentrations can only be effectively reduced if ammonia emissions are decreased in much the same way as those of SO(2) and NO(x).     

Anthropogenic mercury emission inventory with emission factors and total emission in Korea

Mercury emissions concentrations, emission factors, and the total national emission from major anthropogenic sources in Korea for the year 2007 were estimated. Uncontrolled and controlled mercury emission factors and the total emission from each source types are presented. The annual national mercury emission from major anthropogenic sources for the year 2007, on average was 12.8 ton which ranged from 6.5 to 20.2 ton. Averaged emissions of elemental, oxidized, and particulate mercury were estimated at 8.25 ton, 3.69 ton, and 0.87 ton, respectively. Due to the removal of a major portion of particulate and oxidized mercury species, elemental mercury was dominant in stack emission. About 54.8% of mercury emission was contributed by industrial sources, 45.0% by stationary combustion sources and 0.02% by mobile sources. Thermal power plants, oil refineries, cement kilns and incinerators (municipal, industrial, medical, sewage sludge) were the major mercury emitters, contributing about 26%, 25%, 21% and 20%, respectively to the total mercury emission. Other sources (crematory, pulp and paper manufacturing, nonferrous metals manufacturing, glass manufacturing) contributed about 8% of the total emission. Priority should be given in controlling mercury emissions from coal-fired power plants, oil refineries, cement kilns and waste incinerators. More measurements including natural and re-emission sources are to be carried out in the future in order to have a clear scenario of mercury emission from the country and to apply effective control measures.     

Day-of-week patterns of particulate matter and its chemical components at selected sites in California

This paper analyzes day-of-week variations in concentrations of particulate matter (PM) in California. Because volatile organic compounds (VOCs) and oxides of nitrogen (NOx) are not only precursors of ozone (O3) but also of secondary PM, it is useful to know whether the variations by day of week in these precursors are also evident in PM data. Concentrations of PM < or = 10 microm (PM10) and < or = 2.5 microm in aerodynamic diameter (PM2.5) were analyzed. PM concentrations exhibit a general weekly pattern, with the maximum occurring late in the workweek and the minimum occurring on weekends (especially Sunday); however, this pattern does not prevail at all sites and areas. PM nitrate (NO3-) data from Size Selective Inlet (SSI) samplers in the South Coast Air Basin (SoCAB) tend to be somewhat lower on weekends compared with weekdays. During 1988-1991, the weekend average was lower than the weekday average at 8 of 13 locations, with an average decrease of 1%. During 1997-2000, the weekend average was lower than the weekday average at 10 of 13 locations, with an average decrease of 6%. The weekend averages are generally lower than weekday averages for sulfates, organic carbon, and elemental carbon. Because heavy-duty trucks typically represent a major source of elemental carbon, the weekend decrease in heavy-duty truck traffic may also result in a decrease in ambient elemental carbon concentrations.     

Development of an empirical model to estimate real-world fine particulate matter emission factors: the traffic air quality model

The purpose of the study was to quantify the impact of traffic conditions, such as free flow and congestion, on local air quality. The Borman Expressway (I-80/94) in Northwest Indiana is considered a test bed for this research because of the high volume of class 9 truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve traffic management along the highway stretch. An empirical traffic air quality (TAQ) model was developed to estimate the fine particulate matter (PM2.5) emission factors (grams per kilometer) based solely on the measured traffic parameters, namely, average speed, average acceleration, and class 9 truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the U.S. Environmental Protection Agency (EPA)-PART5 model. During congestion (defined as flow-speeds < 50 km/hr [30 mi/hr]), the TAQ model, on average, overpredicted the measured values only by a factor of 1.2, in comparison to a fourfold underprediction using the EPA-PART5 model. On the other hand, during free flow (defined as flow-speeds > 80 km/hr [50 mi/hr]), the TAQ model was conservative in that it overpredicted the measured values by 1.5-fold.