Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems

A harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O₃ concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O₃ maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O₃ is partly due to its inability to correctly predict nighttime lows.Total PM_2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of ?10.4% and ?65.2%, respectively. However, as with O₃, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM_2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM_2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM_2.5 mass in AURAMS versus 2.0% in CMAQ.     

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.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

Responses of future air quality to emission controls over North Carolina,Part II: Analyses of future-year predictions and their policy implications

The MM5/CMAQ system evaluated in Part I paper is applied to study the impact of emission control on future air quality over North Carolina (NC). Simulations are conducted at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August 2009 and 2018. Simulated PM_2.5 in 2009 and 2018 show distribution patterns similar to those in 2002. PM_2.5 concentrations over the whole domain in January and July reduced by 5.8% and 23.3% in 2009 and 12.0% and 35.6% in 2018, respectively, indicating that the planned emission control strategy has noticeable effects on PM_2.5 reduction in this region, particularly in summer. More than 10% and 20% of 1-h and 8-h O₃ mixing ratios are reduced in July 2009 and 2018, respectively, demonstrating the effectiveness of emission control for O₃ reduction in summer. However, O₃ mixing ratios in January 2009 and 2018 increase by more than 5% because O₃ chemistry is VOC-limited in winter and the effect of NO_x reduction dominates over that of VOC reduction under such a condition. The projected emission control simulated at 4-km will reduce the number of sites in non-attainment for max 8-h O₃ from 49 to 23 in 2009 and to 1 in 2018 and for 24-h average PM_2.5 from 1 to 0 in 2009 and 2018 based on the latest 2008 O₃ and 2006 PM_2.5 standards. The variability in model predictions at different grid resolutions contributes to 1–3.8 ppb and 1–7.9 μg m^?3 differences in the projected future-year design values for max 8-h O₃ and 24-h average PM_2.5, respectively.     

Characteristics and origins of air pollutants in Wuhan,China, based on observations and hybrid receptor models

To identify the characteristics of air pollutants and factors attributing to the formation of haze in Wuhan, this study analyzed the hourly observations of air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO) from March 1, 2013, to February 28, 2014, and used hybrid receptor models for a case study. The results showed that the annual average concentrations for PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO during the whole period were 89.6 μg m^?3, 134.9 μg m^?3, 54.9 μg m^?3, 32.4 μg m^?3, 62.3 μg m^?3, and 1.1 mg m^?3, respectively. The monthly variations revealed that the peak values of PM_2.5, PM₁₀, NO₂, SO₂, and CO occurred in December because of increased local emissions and severe weather conditions, while the lowest values occurred in July mainly due to larger precipitation. The maximum O₃ concentrations occurred in warm seasons from May to August, which may be partly due to the high temperature and solar radiation. Diurnal analysis showed that hourly PM_2.5, PM₁₀, NO₂, and CO concentrations had two ascending stages accompanying by the two traffic peaks. However, the O₃ concentration variations were different with the highest concentration in the afternoon. A case study utilizing hybrid receptor models showed the significant impact of regional transport on the haze formation in Wuhan and revealed that the mainly potential polluted sources were located in the north and south of Wuhan, such as Baoding and Handan in Hebei province, and Changsha in Hunan province. Implications: Wuhan city requires a 5% reduction of the annual mean of PM_2.5 concentration by the end of 2017. In order to accomplish this goal, Wuhan has adopted some measures to improve its air quality. This work has determined the main pollution sources that affect the formation of haze in Wuhan by transport. We showed that apart from the local emissions, north and south of Wuhan were the potential sources contributing to the high PM_2.5 concentrations in Wuhan, such as Baoding and Handan in Hebei province, Zhumadian and Jiaozuo in Henan province, and Changsha and Zhuzhou in Hunan province.     

Response of Fine Particulate Matter to Emission Changes of Oxides of Nitrogen and Anthropogenic Volatile Organic Compounds in the Eastern United States

Abstract

A three-dimensional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions [PMCAMx]) is used to investigate changes in fine particle (PM_2.5) concentrations in response to 50% emissions changes of oxides of nitrogen (NO_x) and anthropogenic volatile organic compounds (VOCs) during July 2001 and January 2002 in the eastern United States. The reduction of NO_x emissions by 50% during the summer results in lower average oxidant levels and lowers PM_2.5 (8% on average), mainly because of reductions of sulfate (9–11%), nitrate (45–58%), and ammonium (7–11%). The organic particulate matter (PM) slightly decreases in rural areas, whereas it increases in cities by a few percent when NO_x is reduced. Reduction of NO_x during winter causes an increase of the oxidant levels and a rather complicated response of the PM components, leading to small net changes. Sulfate increases (8–17%), nitrate decreases (18– 42%), organic PM slightly increases, and ammonium either increases or decreases a little. The reduction of VOC emissions during the summer causes on average a small increase of the oxidant levels and a marginal increase in PM_2.5. This small net change is due to increases in the inorganic components and decreases of the organic ones. Reduction of VOC emissions during winter results in a decrease of the oxidant levels and a 5–10% reduction of PM_2.5 because of reductions in nitrate (4–19%), ammonium (4–10%), organic PM (12–14%), and small reductions in sulfate. Although sulfur dioxide (SO₂) reduction is the single most effective approach for sulfate control, the coupled decrease of SO₂ and NO_x emissions in both seasons is more effective in reducing total PM_2.5 mass than the SO₂ reduction alone.     

Particulate Matter in California: Part 2—Spatial,Temporal, and Compositional Patterns of PM2.5, PM10–2.5, and PM10

Abstract

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM_2.5 and PM₁₀ concentrations range from 3 to 10 [H9262]g/m³ and from 5 to 18 µg/m³, respectively. In the urban areas of California, annual-averages for PM_2.5 range from 7 to 30 [H9262]g/m³, with observed 24-hr peaks reaching levels as high as 160 [H9262]g/m³. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM_2.5 concentrations that are more prolonged and regional in nature. PM_2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM_2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO₄ ^2?) and nitrate (NO₃ ^?) components of PM_2.5 and PM₁₀ and correlate with reductions in ambient levels of oxides of sulfur (SO_x) and oxides of nitrogen (NO_x). Annual averages for PM_10–2.5 and PM₁₀ exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

The Influences of Ambient Particle Composition and Size on Particle Infiltration in Los Angeles,CA, Residences

Abstract

Particle infiltration is a key determinant of the indoor concentrations of ambient particles. Few studies have examined the influence of particle composition on infiltration, particularly in areas with high concentrations of volatile particles, such as ammonium nitrate (NH₄NO₃). A comprehensive indoor monitoring study was conducted in 17 Los Angeles–area homes. As part of this study, indoor/outdoor concentration ratios during overnight (nonindoor source) periods were used to estimate the fraction of ambient particles remaining airborne indoors, or the particle infiltration factor (F_INF), for fine particles (PM_2.5), its nonvolatile (i.e., black carbon [BC]) and volatile (i.e., nitrate [NO₃ ^?]) components, and particle sizes ranging between 0.02 and 10 μm. F_INF was highest for BC (median = 0.84) and lowest for NO₃ ^? (median = 0.18). The low F_INF for NO₃ ^? was likely because of volatilization of NO₃ ^? particles once indoors, in addition to depositional losses upon building entry. The F_INF for PM_2.5 (median = 0.48) fell between those for BC and NO₃ ^?, reflecting the contributions of both particle components to PM_2.5. F_INF varied with particle size, air-exchange rate, and outdoor NO₃ ^? concentrations. The F_INF for particles between 0.7 and 2 μm in size was considerably lower during periods of high as compared with low outdoor NO₃ ^? concentrations, suggesting that outdoor NO₃ ^? particles were of this size. This study demonstrates that infiltration of PM_2.5 varies by particle component and is lowest for volatile species, such as NH₄NO₃. Our results suggest that volatile particle components may influence the ability for outdoor PM concentrations to represent indoor and, thus, personal exposures to particles of ambient origin, because volatilization of these particles causes the composition of PM_2.5 to differ indoors and outdoors. Consequently, particle composition likely influences observed epidemiologic relationships based on outdoor PM concentrations, especially in areas with high concentrations of NH₄NO₃ and other volatile particles.     

Fine particulate speciation profile and emission factor of municipal solid waste incinerator established by dilution sampling method

In this study, fine particulate matter (PM_2.5) emitted from a municipal solid waste incinerator (MSWI) was collected using dilution sampling method. Chemical compositions of the collected PM_2.5 samples, including carbon content, metal elements, and water-soluble ions, were analyzed. Traditional in-stack hot sampling was simultaneously conducted to compare the influences of dilution on PM_2.5 emissions and the characteristics of the bonded chemical species. The results, established by a dilution sampling method, show that PM_2.5 and total particulate matter (TPM) emission factors were 61.6 ± 4.52 and 66.1 ± 5.27 g ton-waste^?1, respectively. The average ratio of PM_2.5/TPM is 0.93, indicating that more than 90% of PM emission from the MSWI was fine particulate. The major chemical species in PM_2.5 included organic carbon (OC), Cl^?, NH₄⁺, elemental carbon (EC) and Si, which account for 69.7% of PM_2.5 mass. OC was from the unburned carbon in the exhaust, which adsorbed onto the particulate during the cooling process. High Cl^? emission is primarily attributable to wastes containing plastic bags made of polyvinyl chloride, salt in kitchen refuse and waste biomass, and so on. Minor species that account for 0.01–1% of PM_2.5 mass included SO₄^2-, K⁺, Na, K, NO₃^?, Al, Ca²⁺, Zn, Ca, Cu, Fe, Pb, and Mg. The mean ratio of dilution method/in-stack hot method was 0.454. The contents of water-soluble ions (Cl^?, SO₄^2-, NO₃^?) were significantly enriched in PM_2.5 via gas-to-particle conversion in the dilution process. Results indicate that in-stack hot sampling would underestimate levels of these species in PM_2.5.

Implications: PM_2.5 samples from a municipal solid waste incinerator (MSWI) were collected simultaneously by a dilution sampling technique and a traditional in-stack method. PM_2.5 emission factors and chemical speciation profiles were established. Dilution sampling provides more reliable data than in-stack hot sampling. The results can be applied to estimate the PM_2.5 emission inventories of MSWI, and the source profile can be used for contribution estimate of chemical mass balance modeling.     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

Association between Levels of Fine Particulate and Emergency Visits for Pneumonia and other Respiratory Illnesses among Children in Santiago,Chile

ABSTRACT

Recent evidence has implicated the fine fraction of particulate as the major contributor to the increase in mortality and morbidity related to particulate ambient levels. We therefore evaluated the impact of daily variation of ambient PM_2.5 and other pollutants on the number of daily respiratory-related emergency visits (REVs) to a large pediatric hospital of Santiago, Chile. The study was conducted from February 1995 to August 1996. Four monitoring stations from the network of Santiago provided air pollution data. The PM2.5 24-hr average ranged from 10 to 111 μg/m³ during September to April (warm months) and from 10 to 156 μg/m³ during May to August (cold months). Other contaminants (ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) were, in general, low during the study period. The increase in REVs was significantly related to PM₁₀ and PM_2.5 ambient levels, with the relationship between PM_2.5 levels and the number of REVs the stronger. During the cold months, an increase of 45 ìg/m³ in the PM_2.5 24-hr average was related to a 2.7% increase in the number of REVs (95% CI, 1.1–4.4%) with a two-day lag, and to an increase of 6.7% (95% CI, 1.7–12.0%) in the number of visits for pneumonia with a three-day lag. SO₂ and NO₂ were also related to REVs. We conclude that urban air pollutant mixture, particularly fine particulates, adversely affect the respiratory health of children residing in Santiago.     

Day-of-Week Patterns of Particulate Matter and Its Chemical Components at Selected Sites in California

Abstract

This paper analyzes day-of-week variations in concentrations of particulate matter (PM) in California. Because volatile organic compounds (VOCs) and oxides of nitrogen (NO_x) 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 ≤10 μm (PM₁₀) and ≤2.5[H9262]m in aerodynamic diameter (PM_2.5) 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.     

A full year evaluation of the CALIOPE-EU air quality modeling system over Europe for 2004

The CALIOPE-EU high-resolution air quality modeling system, namely WRF-ARW/HERMES-EMEP/CMAQ/BSC-DREAM8b, is developed and applied to Europe (12 km × 12 km, 1 h). The model performances are tested in terms of air quality levels and dynamics reproducibility on a yearly basis. The present work describes a quantitative evaluation of gas phase species (O₃, NO₂ and SO₂) and particulate matter (PM2.5 and PM10) against ground-based measurements from the EMEP (European Monitoring and Evaluation Programme) network for the year 2004. The evaluation is based on statistics. Simulated O₃ achieves satisfactory performances for both daily mean and daily maximum concentrations, especially in summer, with annual mean correlations of 0.66 and 0.69, respectively. Mean normalized errors are comprised within the recommendations proposed by the United States Environmental Protection Agency (US-EPA). The general trends and daily variations of primary pollutants (NO₂ and SO₂) are satisfactory. Daily mean concentrations of NO₂ correlate well with observations (annual correlation r = 0.67) but tend to be underestimated. For SO₂, mean concentrations are well simulated (mean bias = 0.5 μg m^?3) with relatively high annual mean correlation (r = 0.60), although peaks are generally overestimated. The dynamics of PM2.5 and PM10 is well reproduced (0.49 < r < 0.62), but mean concentrations remain systematically underestimated. Deficiencies in particulate matter source characterization are discussed. Also, the spatially distributed statistics and the general patterns for each pollutant over Europe are examined. The model performances are compared with other European studies. While O₃ statistics generally remain lower than those obtained by the other considered studies, statistics for NO₂, SO₂, PM2.5 and PM10 present higher scores than most models.     

Influence of boundary conditions on CMAQ simulations over the Iberian Peninsula

The influence of chemical boundary conditions (BC) on the response of the Community Multiscale Air Quality (CMAQ) model over the Iberian Peninsula was investigated in this study. Three strategies to supply boundary conditions in the context of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) were tested. Alternative methods consist in providing BC from (1) fixed, time-independent, concentration profiles, (2) concentrations predicted in a CMAQ mother domain (48 km, 1 h resolution) and (3) concentration values from the GEOS-Chem chemical-transport global model (2 × 2.5°, 3 h resolution). High resolution (3 km) simulated concentrations of the main pollutants (NO₂, NO, SO₂, O₃, PM₁₀ and PM_2.5) were compared through a comprehensive statistical analysis including observational data from 165 monitoring stations all over the Iberian Peninsula. It was found that model sensitivity to BC for nitrogen and sulphur oxides was limited, being restricted to the vicinity of model boundaries. However, significant domain-wide differences were found when modelling ozone and PM depending on the BC provided to run the tests. Although model performance was affected by spatial and seasonal factors, the results indicate that model-derived, dynamic BC improved CMAQ predictions when compared to those based on static concentrations prescribed in the boundaries. Aggregated statistics suggest that the GEOS-Chem produced the best results for O₃ and PM_2.5 while NO₂ and PM₁₀ were slightly better predicted under the CMAQ nesting approach. Besides the statistical evaluation some other relevant issues in the context of Integrated Assessment Modelling (IAM) are discussed to gain a better insight into the suitability of the methods analyzed and limitations of downscaling methods. Despite being useful to get a better understanding of the role of BC in SIMCA, this study contributed to highlight model deficiencies and therefore to point out future research needs to improve IAM activities in the Iberian Peninsula.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

Evaluation of the community multiscale air quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II—particulate matter

This paper is Part II in a pair of papers that examines the results of the Community Multiscale Air Quality (CMAQ) model version 4.5 (v4.5) and discusses the potential explanations for the model performance characteristics seen. The focus of this paper is on fine particulate matter (PM_2.5) and its chemical composition. Improvements made to the dry deposition velocity and cloud treatment in CMAQ v4.5 addressing compensating errors in 36-km simulations improved particulate sulfate (SO₄²⁻) predictions. Large overpredictions of particulate nitrate (NO₃⁻) and ammonium (NH₄⁺) in the fall are likely due to a gross overestimation of seasonal ammonia (NH₃) emissions. Carbonaceous aerosol concentrations are substantially underpredicted during the late spring and summer months, most likely due, in part, to a lack of some secondary organic aerosol (SOA) formation pathways in the model. Comparisons of CMAQ PM_2.5 predictions with observed PM_2.5 mass show mixed seasonal performance. Spring and summer show the best overall performance, while performance in the winter and fall is relatively poor, with significant overpredictions of total PM_2.5 mass in those seasons. The model biases in PM_2.5 mass cannot be explained by summing the model biases for the major inorganic ions plus carbon. Errors in the prediction of other unspeciated PM_2.5 (PM_Other) are largely to blame for the errors in total PM_2.5 mass predictions, and efforts are underway to identify the cause of these errors.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.     

Experimental and statistical analyses to characterize in-vehicle fine particulate matter behavior inside public transit buses operating on B20-grade biodiesel fuel

This paper presents results from an in-vehicle air quality study of public transit buses in Toledo, Ohio, involving continuous monitoring, and experimental and statistical analyses to understand in-vehicle particulate matter (PM) behavior inside buses operating on B20-grade biodiesel fuel. The study also focused on evaluating the effects of vehicle’s fuel type, operating periods, operation status, passenger counts, traffic conditions, and the seasonal and meteorological variation on particulates with aerodynamic diameter less than 1 micron (PM_1.0). The study found that the average PM_1.0 mass concentrations in B20-grade biodiesel-fueled bus compartments were approximately 15 μg m^?3, while PM_2.5 and PM₁₀ concentration averages were approximately 19 μg m^?3 and 37 μg m^?3, respectively. It was also observed that average hourly concentration trends of PM_1.0 and PM_2.5 followed a “μ-shaped” pattern during transit hours.Experimental analyses revealed that the in-vehicle PM_1.0 mass concentrations were higher inside diesel-fueled buses (10.0–71.0 μg m^?3 with a mean of 31.8 μg m^?3) as compared to biodiesel buses (3.3–33.5 μg m^?3 with a mean of 15.3 μg m^?3) when the windows were kept open. Vehicle idling conditions and open door status were found to facilitate smaller particle concentrations inside the cabin, while closed door facilitated larger particle concentrations suggesting that smaller particles were originating outside the vehicle and larger particles were formed within the cabin, potentially from passenger activity. The study also found that PM_1.0 mass concentrations at the back of bus compartment (5.7–39.1 μg m^?3 with a mean of 28.3 μg m^?3) were higher than the concentrations in the front (5.7–25.9 μg m^?3 with a mean of 21.9 μg m^?3), and the mass concentrations inside the bus compartment were generally 30–70% lower than the just-outside concentrations. Further, bus route, window position, and time of day were found to affect the in-vehicle PM concentrations significantly. Overall, the in-vehicle PM_1.0 concentrations inside the buses operating on B20-grade biodiesel ranged from 0.7 μg m^?3 to 243 μg m^?3, with a median of 11.6 μg m^?3.Statistical models developed to study the effects of vehicle operation and ambient conditions on in-vehicle PM concentrations suggested that while open door status was the most important influencing variable for finer particles and higher passenger activity resulted in higher coarse particles concentrations inside the vehicle compartments, ambient PM concentrations contributed to all PM fractions inside the bus irrespective of particle size.