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Predictions of O 3 , CO, total NO y and individual NO y species (NO, NO 2 , HNO 3 , PAN, alkyl nitrates and aerosol nitrate) from a fine resolution regional air quality modeling system for the South Coast Air Basin (SoCAB) and San Joaquin Valley Air Basin (SJVAB) of California are presented and evaluated for the 2008 ARCTAS-CARB campaign. The measurements of the chemical compounds from the fire plumes during the field campaign allow for the evaluation of the model's ability to simulate fire-influenced air masses as well. In general, the model successfully simulated the broad spatial distribution of chemical compounds in both air basins as well as the variation within the basins. Using inventories that reflect 2008 emissions levels, the model performed well in simulating NO x (NO + NO 2 ) in SoCAB. Therefore, the under prediction of O 3 over these areas is more likely caused by uncertainties with the VOC emissions, chemistry, or discrepancies in the meteorology. The model did not capture the relatively high levels of O 3 , and some reactive nitrogen species that were measured off shore of the SoCAB, indicating potential missing sources or the transport from on shore to off shore was not successfully captured. In SJVAB, the model had good performance in simulating different chemical compounds in the Fresno and Arvin areas. However, enhanced concentrations of O 3 , NO x , HNO 3 and PAN near dairy farms were significantly underestimated in the model. Negative biases also exist for O 3 and HNO 3 near oil fields, suggesting larger uncertainties associated with these emission sources. While the model simulated the total NO y mixing ratios reasonably well, the prediction for partitioning between individual compounds showed larger uncertainties in the model simulation. Although the fire emissions inventory was updated to include the latest emissions estimates and speciation profiles, our model shows limited improvement in simulating the enhancement of O 3 , CO, and PAN under fire impact as compared to a previous version of the modeling system. Further improvements in simulating fire emissions, especially the timing and the plume injection heights, are desired in order to better simulate the impact of fires. [ABSTRACT FROM AUTHOR]

With the promulgation of the National Ambient Air Quality Standards (NAAQS or standard) for 8-hr ozone (O3), the U.S. Environmental Protection Agency (EPA) issued modeling guidance that advocated the use of results from photochemical air quality models in a relative sense. In doing so, the EPA provided guidance on how to calculate relative response factors (RRFs) that can project current design value (DV) mixing ratios into the future for the purpose of determining the attainment status with respect to the O3standard. The RRFs recommended by the EPA represent the average response of the photochemical model over a broad range of O3mixing ratios above a specified cutoff threshold. However, it is known that O3response to emission reductions of limiting precursors (i.e., NOxand/or VOC) is greater on days with higher O3mixing ratios compared to days with lower mixing ratios. In this study, we present a segmented RRF concept termed band-RRF, which takes into account the different model responses at different O3mixing ratios. The new band-RRF concept is demonstrated in the San Joaquin Valley (SJV) region of California for the 1-hr and 8-hr O3standards. The 1-hr O3analysis is relevant to work done in support of the SJV O3State Implementation Plan (SIP) submitted to the EPA in 2013. The 8-hr example for the future year of 2019 is presented for illustrative purposes only. Further work will be conducted with attainment deadline of 2032 as part of upcoming SIPs for the 0.075 parts per million (ppm) 8-hr O3standard. The applicability of the band-RRF concept to the particulate matter (PM2.5) standards is also discussed.Implications:Results of photochemical models are used in regulatory applications in a relative sense using relative response factors (RRFs), which represent the impacts of emissions reductions over a wide range of ozone (O3) values. It is possible to extend the concept of RRFs to account for the fact that higher O3 mixing ratios (both 1-hr and 8-hr) respond more to emissions controls of limiting precursors than do lower O3 mixing ratios. We demonstrate this extended concept, termed band-RRF, for the 1-hr and 8-hr O3 National Ambient Air Quality Standard (NAAQS or standard) in the San Joaquin Valley of California. This extension can also be made applicable to the 24-hr PM2.5 and annual PM2.5 standards. [ABSTRACT FROM PUBLISHER]

Abstract: In this study, the University of Iowa’s Chemical Weather Forecasting System comprising meteorological predictions using the WRF model, and off-line chemical weather predictions using tracer and full chemistry versions of the STEM model, designed to support the flight planning during the ARCTAS 2008 mission is described and evaluated. The system includes tracers representing biomass burning and anthropogenic emissions from different geographical emissions source regions, as well as air mass age indicators. We demonstrate how this forecasting system was used in flight planning and in the interpretation of the experimental data obtained through the case study of the summer mission ARCTAS DC-8 flight executed on July 9 2008 that sampled near the North Pole. The comparison of predicted meteorological variables including temperature, pressure, wind speed and wind direction against the flight observations shows that the WRF model is able to correctly describe the synoptic circulation and cloud coverage in the Arctic region The absolute values of predicted CO match the measured CO closely suggesting that the STEM model is able to capture the variability in observations within the Arctic region. The time–altitude cross sections of source region tagged CO tracers along the flight track helped in identifying biomass burning (from North Asia) and anthropogenic (largely China) as major sources contributing to the observed CO along this flight. The difference between forecast and post analysis biomass burning emissions can lead to significant changes (∼10–50%) in primary CO predictions reflecting the large uncertainty associated with biomass burning estimates and the need to reduce this uncertainty for effective flight planning. [Copyright &y& Elsevier]

Abstract: The sectoral and regional contributions from northern hemisphere anthropogenic and biomass burning emission sectors to black carbon (BC) distributions over the continental United States (CONUS) in summer 2008 are studied using the Sulfur Transport and dEposition Model (STEM). North American (NA) emissions heavily (>70% of total emissions) affect the BC levels from the surface to ∼5 km, while non-NA plumes compose more than half of the BC above ∼5 km. Among all sectors, NA and non-NA biomass burning, NA transportation and non-NA residential emissions are the major contributors. The sectoral contributions vary among ten regions defined by the US Environmental Protection Agency (EPA): NA anthropogenic emissions enhance northeastern US BC levels; biomass burning strongly impacts northern California and southeastern US; and the influence of extra-regional plumes is largest in the northwestern US but extends to eastern US. The mean contribution from non-NA sources to US surface BC is ∼0.05 μg m−3, with a maximum value of ∼0.11 μg m−3 in the northwestern US. The non-NA contributions to column BC are higher than to surface BC, ranging from 30% to 80%, depending on region. EPA region 8 is most sensitive to extra-regional BC, partially explaining the observed increasing BC trend there during the past decades associated with the increasing Asian BC emissions. Measurements from the June 24 DC-8 flight during the ARCTAS-CARB field campaign show that BC/(organic matter + nitrate + sulfate) mass ratios fairly well represent BC''s warming potential over southern California, which can be approximated by BC/(organic matter + sulfate) and BC/sulfate for plumes affected and unaffected by fires, respectively. The responses of BC/(organic matter + sulfate) and BC/sulfate to removing each emission sector are further discussed, indicating that mitigating NA transportation emissions has the highest potential for regional air quality and climate co-benefits. [Copyright &y& Elsevier]

Aerosol distributions in Asia calculated over a 4-year period and constrained by satellite observations of aerosol optical depth (AOD) are presented. Vast regions in Asia that include > 80% of the population have PM2.5 concentrations that exceed on an annual basis the WHO guideline of 10 μg/m³, often by factors of 2 to 4. These high aerosol loadings also have important radiative effects, causing a significant dimming at the surface, and mask ∼45% of the warming by greenhouse gases. Black carbon (BC) concentrations are high throughout Asia, representing 5-10% of the total AOD, and contributing significantly to atmospheric warming (its warming potential is ∼55% of that due to CO2). PM levels and AODs in year 2030, estimated based on simulations that consider future changes in emissions, are used to explore opportunities for win—win strategies built upon addressing air quality and climate change together. It is found that in 2030 the PM2.5 levels in significant parts of Asia will increase and exacerbate health impacts; but the aerosols will have a larger masking effect on radiative forcing, due to a decrease in BC and an increase in SO2 emissions. [ABSTRACT FROM AUTHOR]

Regional gross primary productivity (GPP) estimates are crucial to estimating carbon-climate feedbacks but are highly uncertain with existing methods. An emerging approach uses atmospheric carbonyl sulphide (COS) as a tracer for carbon dioxide: COS plant uptake is simulated by scaling GPP. A critical parameter for this method is leaf-scale relative uptake (LRU). Plant chamber and eddy covariance studies find a narrow range of LRU values but some atmospheric modelling studies assign values well outside this range. Here we study this discrepancy by conducting new regional chemical transport simulations for North America using the underlying data from previous studies. We find the wide range of ecosystem model GPP estimates can explain the discrepancy in LRU values. We also find that COS concentration uncertainty is more sensitive to GPP uncertainty than to LRU parameter uncertainty. These results support the COS tracer technique as a useful approach for constraining GPP estimates. [ABSTRACT FROM AUTHOR]