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Abstract: Increased use of ethanol in the United States fuel supply will impact emissions and ambient concentrations of greenhouse gases, “criteria” pollutants for which the U. S. EPA sets ambient air quality standards, and a variety of air toxic compounds. This paper focuses on impacts of increased ethanol use on ozone and air toxics under a potential implementation scenario resulting from mandates in the U. S. Energy Independence and Security Act (EISA) of 2007. The assessment of impacts was done for calendar year 2022, when 36 billion gallons of renewable fuels must be used. Impacts were assessed relative to a baseline which assumed ethanol volumes mandated by the first renewable fuels standard promulgated by U. S. EPA in early 2007. This assessment addresses both impacts of increased ethanol use on vehicle and other engine emissions, referred to as “downstream” emissions, and “upstream” impacts, i.e., those connected with fuel production and distribution. Air quality modeling was performed for the continental United States using the Community Multi-scale Air Quality Model (CMAQ), version 4.7. Pollutants included in the assessment were ozone, acetaldehyde, ethanol, formaldehyde, acrolein, benzene, and 1,3-butadiene. Results suggest that increased ethanol use due to EISA in 2022 will adversely increase ozone concentrations over much of the U.S., by as much as 1ppb. However, EISA is projected to improve ozone air quality in a few highly-populated areas that currently have poor air quality. Most of the ozone improvements are due to our assumption of increases in nitrogen oxides (NO x ) in volatile organic compound (VOC)-limited areas. While there are some localized impacts, the EISA renewable fuel standards have relatively little impact on national average ambient concentrations of most air toxics, although ethanol concentrations increase substantially. Significant uncertainties are associated with all results, due to limitations in available data. These uncertainties are discussed in detail. [Copyright &y& Elsevier]

Abstract: An emission pre-processing tool is generally needed to transform a bulk annual emission inventory into gridded, temporal (monthly, weekly, and hourly), and speciated emissions in order to use complex air quality models such as the Community Multi-scale Air Quality (CMAQ) model to assess control strategies, forecast air quality, and investigate pollution formation and transport processes. To support the regional air quality modeling in the Pearl River Delta (PRD), we developed an emission pre-processing system, Sparse Matrix Operator Kernel Emissions-PRD (SMOKE-PRD), based on the U.S. Environmental Protection Agency (USEPA)/SMOKE model. This paper introduces the methods and procedures for adapting the SMOKE model to the PRD regional bulk emissions. These include the compilation of the PRD local source-class clarification codes, the incorporation of the PRD local emission inventory, and the updating of spatial, temporal, and chemical speciation information. The SMOKE-PRD system was evaluated, and a case study on ozone simulation was conducted to demonstrate the applicability of the SMOKE-PRD system. Results show that the model can properly simulate temporal variations, spatial patterns, and peak values of O3 concentrations in the PRD region, suggesting the SMOKE-PRD system was successfully localized and can be used to provide model-ready emissions for regional air quality modeling in the PRD region. This work can be extended for adapting the SMOKE model to process emissions for modeling use in other regions of China. [Copyright &y& Elsevier]

Abstract: This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O3 concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA''s AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O3 concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2ppb was 4.2ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50ppb. In fact the model tends to under-predict when concentrations exceed 70ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0ppb (Normalized Mean Error (NME)=20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions. [Copyright &y& Elsevier]

Abstract: Cities in the Southwestern United States (Southwest) are often close to violating tropospheric ozone (ozone) and particulate matter (PM) federal air quality standards, and local climate and weather conditions play a large part in determining whether or not pollutant levels exceed the federally mandated limits and by what magnitude. The Kolmogorov–Zurbenko (KZ) filter method has been used in a number of studies in the Eastern United States to determine meteorological controls on ozone concentrations and to separate out those effects in order to examine underlying trends. The Southwest, however, experiences a different climate regime than other parts of the country, and atmospheric controls on air quality in the region have not been examined in this manner. This paper determines which meteorological variables most influence ozone and PM in the Southwest and examines patterns of underlying pollutant trends due to emissions. Ozone and PM data were analyzed over the time period 1990–2003 for the Southwest''s five major metropolitan areas: Albuquerque, NM; El Paso, TX; Las Vegas, NV; Phoenix, AZ; and Tucson, AZ. Results indicate that temperature and mixing height most strongly influence ozone conditions, while moisture levels (particularly relative humidity) are the strongest predictors of PM concentrations in all five cities examined. Meteorological variability typically accounts for 40–70% of ozone variability and 20–50% of PM variability. Long-term ozone trends are highly variable, but records from most stations indicate increasing concentrations over the last decade. Long-term trends in PM concentrations were relatively flat in all five cities analyzed but contained coincident extremes unrelated to meteorology. [Copyright &y& Elsevier]

To study the potential impacts of climate change on air quality and public health over the eastern United States, a coupled global/regional-scale modeling system consisting of the NASA-Goddard Institute for Space Studies Atmosphere–Ocean model, the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) model for air quality has been developed. Evaluation results of the modeling system used to simulate climate and ozone air quality over the eastern United States during the five summers of 1993–1997 are presented in this paper. The results indicate that MM5 and CMAQ capture interannual and synoptic-scale variability present in surface temperature and ozone observations in the current climate, while the magnitude of fluctuations on shorter time scales is underestimated. A comparison of observed and predicted spatial patterns of daily maximum ozone concentrations shows best performance in predicting patterns for average and above-average ozone concentrations. The frequency distributions of the duration of extreme heat and ozone events show similar features for both model predictions and observations. Finally, application of a synoptic map-typing procedure reveals that the MM5/CMAQ system succeeded in simulating the average ozone concentrations associated with several frequent pressure patterns, indicating that the effects of synoptic-scale meteorology on ozone concentrations are captured by the modeling system. It is concluded that the GCM/MM5/CMAQ system is a suitable tool for the simulation of summertime surface temperature and ozone air quality conditions over the eastern United States in the present climate. [Copyright &y& Elsevier]

Public education campaigns, to be successful, must repeat simple, consistent messages over time, using various sources and media. During the 2000, 2001, and 2002 ozone seasons, the North Central Texas Council of Governments (NCTCOG) employed a four-pronged, multimedia approach to educate the public about air quality in the Dallas/Fort Worth (DFW) region. The four-pronged approach included several varied information sources: