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Photochemical grid models are being used in technical analyses by the Visibility Improvement State and Tribal Association of the Southeast (VISTAS), a regional air quality planning organization in the southeastern United States, to support state implementation plans for regional haze and related air quality issues. VISTAS has embarked on a multi-phase process of testing and evaluating regional meteorological, emissions and air quality models that will be used to project visibility improvements as required by the regional haze rule. VISTAS has generated 2002 annual emissions and meteorological inputs for two photochemical grid models, the community multi-scale air quality (CMAQ) and the comprehensive air-quality model with extensions (CAMx), at a 36 km resolution for the continental US and at 12 km resolution for the eastern US. The two models were evaluated using speciated PM measurements from various monitoring networks and detailed analysis was performed for organic carbon (OC) mass using the IMPROVE, STN, and SEARCH networks. The differences in model performance between CMAQ and CAMx were used as a diagnostic tool to investigate performance issues for several compounds. CAMx performed substantially better than CMAQ for OC (defined as 1.4×measured organic carbon) which led to investigations into methods for improving the CMAQ OC model performance. The treatment of secondary organic aerosol (SOA) was identified as an area needing improvements in both models. The impact of replacing the CMAQ SOA parameters with those from CAMx was investigated. Further analysis identified several processes that are potentially important for SOA formation that are not treated in either model including, polymerization of the SOA into non-volatile particles and SOA formation from sesquiterpene, isoprene and other biogenic VOCs. A prototype mechanism for several of these missing processes was developed and the CMAQ SOA module was enhanced to include these SOA formation processes. SOA yields, specifically from biogenic emissions, were increased by the modified SOA module and CMAQ model performance for particulate OC at the IMPROVE, SEARCH, and STN sites in the VISTAS region was improved. © 2006 Elsevier Ltd. All rights reserved.

Abstract: We conducted four source apportionment simulations using the Community Multiscale Air Quality (CMAQ) photochemical grid modelling system in order to investigate and assess the relative importance of specific emissions sources and/or geographic regions on ambient ozone and PM air quality in the Alberta Oil Sands Region (AOSR). Local point and area sources, medium range transport of mobile sources and biogenic emissions were examined. The elimination of emissions from local stationary point sources reduced 8-h ozone concentrations and greatly reduces the PM2.5 concentrations in AOSR; similar results are seen in the local area source zero-out simulations but with less ozone and PM2.5 reductions than seen in the local point source zero-out run. Although the mobile source medium-range transport reduced 8-h ozone concentrations in the urban plume from Edmonton that results in some ozone and PM2.5 concentration reductions in the southern part of the AOSR, it has little effect on the elevated ozone and PM2.5 concentrations in the oil sands development area of the AOSR where the highest ozone and PM2.5 concentrations are estimated. The elimination of all anthropogenic emissions in Alberta so that only biogenic emissions remained resulted in large reductions in 8-h ozone concentrations in the AOSR, with the highest remaining ozone in the 50–52ppb range occurring south of Fort McMurray; very low PM2.5 concentrations are also estimated across Alberta, including the AOSR, when anthropogenic emissions are eliminated in Alberta. [Copyright &y& Elsevier]

Abstract: The Community Multiscale Air Quality (CMAQ) and the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling systems were used to simulate emissions and air quality in North Eastern Alberta where a rapid rise in oil sands development has caused air quality concerns over the last decade. The models were run on a 36/12/4 km domain for the four month period of May through August 2002. A model performance evaluation was conducted by comparing the CMAQ model estimates against ambient air quality measurements. In the Alberta oil sands region, the model tended to achieve or nearly achieve ozone model performance goals, albeit with an underestimation bias. The magnitudes of the observed PM2.5 concentrations were matched by the modeling system, except when the observed PM2.5 concentrations were influenced by emissions from forest fires in which case the model underestimated the observed PM2.5 concentrations. The CMAQ-estimated 4th highest daily maximum 8-hour ozone concentrations in the oil sands region were below the 65 ppb Canada Wide Standard (CWS) as well as the 58 ppb Alberta Management Plan Trigger Level. The highest estimated ozone concentrations occurred near the oil sands development area just north of Fort McMurray with values approaching, but below, the 58 ppb Management Plan Trigger Level; estimated ozone concentrations are much lower in the farther northern portions of the oil sands region. The acute (i.e., maximum 3-day value) SUM60 vegetative ozone exposure metric was mostly less than 100 ppb h, which is below the threshold of concern for crops. However, just north of Fort McMurray there were small areas where the acute SUM60 metric exceeded the 500–700 ppb h threshold of concern for crops with maximum values in plumes from sources in the oil sands mine area of ∼900 ppb h. The maximum chronic (three-month average) SUM60 ozone exposure metric was below the thresholds of concern. The CMAQ-estimated maximum 98th percentile 24-hour average PM2.5 concentration occurs in the mine area north of Fort McMurray and was below the CWS threshold (30 μg m−3), however it was above the Alberta Management Plan Trigger Level (20 μg m−3). The estimated 98th percentile 24- hour average PM2.5 concentrations were mostly in the 2–6 μg m−3 range with regions of higher PM2.5 concentrations predicted just north of Fort McMurray in the oil sands development region. [Copyright &y& Elsevier]