Search

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: Operational, diagnostic, and comparative evaluations of two one-atmosphere regional models were performed for the full calendar year 2002 in support of regional haze regulatory applications in the eastern US. Using consistent emissions, meteorological and air quality data sets, the community multi-scale air quality and comprehensive air quality model with extensions models were exercised on a nested 36/12km grid system and evaluated across a broad range of time and space scales for numerous gas-phase and fine particulate species derived from routine and research-grade ambient measurements at six monitoring networks. Performance by both models for speciated fine particulate matter (PM) across the eastern US ranged from quite good (e.g., SO4 2−) to poor (e.g., soil). For most species, model bias was higher in the winter and lower (usually negative) in the summer suggesting potential issues related to vertical mixing (e.g., too little in winter), temporal allocation of emissions, and/or other model science processes or inputs. These results may be used to (a) guide one-atmosphere model refinements, (b) improve data input preparation procedures, (c) evaluate methods for rigorous, stressful performance testing, and (d) clarify the uncertainty in model estimates for regional haze and PM2.5 control strategy programs. [Copyright &y& Elsevier]

Abstract: Policy Relevant Background (PRB) ozone, as defined by the US Environmental Protection Agency (EPA), refers to ozone concentrations that would occur in the absence of all North American anthropogenic emissions. PRB enters into the calculation of health risk benefits, and as the US ozone standard approaches background levels, PRB is increasingly important in determining the feasibility and cost of compliance. As PRB is a hypothetical construct, modeling is a necessary tool. Since 2006 EPA has relied on global modeling to establish PRB for their regulatory analyses. Recent assessments with higher resolution global models exhibit improved agreement with remote observations and modest upward shifts in PRB estimates. This paper shifts the paradigm to a regional model (CAMx) run at 12km resolution, for which North American boundary conditions were provided by a low-resolution version of the GEOS-Chem global model. We conducted a comprehensive model inter-comparison, from which we elucidate differences in predictive performance against ozone observations and differences in temporal and spatial background variability over the US. In general, CAMx performed better in replicating observations at remote monitoring sites, and performance remained better at higher concentrations. While spring and summer mean PRB predicted by GEOS-Chem ranged 20–45ppb, CAMx predicted PRB ranged 25–50ppb and reached well over 60ppb in the west due to event-oriented phenomena such as stratospheric intrusion and wildfires. CAMx showed a higher correlation between modeled PRB and total observed ozone, which is significant for health risk assessments. A case study during April 2006 suggests that stratospheric exchange of ozone is underestimated in both models on an event basis. We conclude that wildfires, lightning NO x and stratospheric intrusions contribute a significant level of uncertainty in estimating PRB, and that PRB will require careful consideration in the ozone standard setting process. [Copyright &y& Elsevier]

Abstract: Past photochemical modeling of the western United States (US) using the Comprehensive Air quality Model with extensions (CAMx) and the Community Multiscale Air Quality (CMAQ) model has resulted in large springtime ozone over predictions in the complex high-elevation terrain of the western United States (US). Comparisons against rural measurement data have shown that both models over predicted ozone levels by 20ppb or more. A systematic investigation using CAMx revealed that excessive vertical transport in mountainous terrain draws down upper tropospheric ozone introduced by the lateral boundary conditions (developed by a global chemistry model), which can routinely exceed 1ppm near the tropopause. This is not an unreasonable concentration at such altitudes during the spring, and there is observational evidence that stratospheric ozone intrusions result in occasional large ground-level concentrations in the western US, but not at the frequency and intensity simulated by the CAMx and CMAQ models. Past versions of CAMx and CMAQ possess similar algorithms to diagnose vertical velocity, and similar first-order accurate vertical advection algorithms. These similarities, in conjunction with poor vertical resolution of the upper troposphere, have resulted in similar ozone performance issues. Numerous approaches were explored with CAMx in an attempt to externally reduce the rates of vertical transport over complex terrain. Ultimately, we formulated and tested a new vertical advection methodology that included improvements to how vertical velocities are determined and introduced a second-order accurate advection solver technique. Together these improvements proved to yield the most successful results in reducing upper tropospheric ozone transport to the surface. CAMx was then run to simulate ozone throughout the western US for a full year to evaluate the effects of the new vertical transport algorithm on model performance. Ozone performance improvements exceeded those achieved through the application of arbitrary reductions in the upper tropospheric/stratospheric lateral boundary conditions. [Copyright &y& Elsevier]