Citation:

ALAPATY, K. V., R. MATHUR, J. E. PLEIM, C. HOGREFE, S. T. RAO, V. Ramaswamy, S. Galmarini, M. Schapp, R. Vautard, P. Makar, A. Baklanov, G. Kallos, B. Vogel, AND R. Sokhi. New Directions: Understanding Interactions of Air Quality and Climate Change at Regional Scales. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 49(3):1-424, (2012).

Impact/Purpose:

The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Description:

The estimates of the short-lived climate forcers’ (SLCFs) impacts and mitigation effects on the radiation balance have large uncertainty because the current global model set-ups and simulations contain simplified parameterizations and do not completely cover the full range of air quality-climate interactions (AQCI). Most AQCI studies to date used coarse grid models that cannot adequately resolve the highest SLCFs concentrations in the densest source regions and mesoscale circulations/processes (Anderson et al., 2003). Therefore, the radiative and vertical transport impacts and associated air quality issues in coarse grid models are likely to be under-represented at the regional and local scales. Since AQCI can be locally predominant due to the heterogeneity in emissions loading and process interactions, regional models capable of capturing AQCI are critically needed so that the cumulative effects on larger scale radiative forcing of the earth-atmosphere can be accurately assessed. Regional models include detailed physical, dynamical, and chemical formulations. However, the credibility of these models in properly simulating AQCI has not been critically assessed so the models could be used more confidently for developing effective regulatory policies. Global modeling studies have offered important insights into the AQCI processes and the associated uncertainties. The use of diverse formulations and assumptions among models in AEROCOM led to a large spread in the simulated SLCFs impacts on climate whichhas shaped the formation of AEROCOM Phase II (Schulz et al., 2009). In the absence of a roadmap, any new effort with the regional-scale coupled models may also lead to enhanced spread in the simulated AQCI among these models. Many studies highlight that some SLCFs emissions have large uncertainty (e.g., Koch et al., 2011). Carbonaceous aerosol emission source strength is one of the highly uncertain sources of SLCFs as differences among modeled global biomass burning emissions can be as large as ∼ 25% (Koch et al., 2011). There is also a large uncertainty in ammonia emissions (Makar et al., 2009), which, in turn, affects the composition and hygroscopicity of airborne aerosols, thereby affecting the resulting radiative forcing estimation. A systematic analysis of the variability in the emission source strengths in models is needed to facilitate an improved understanding of AQCI in a particular model as well as in model inter-comparisons. Thus, a clear strategy is needed for identifying the causes for the diversity seen in the model simulations and potential methodologies to quantify and reduce uncertainties so that emission scenarios can be determined in the policy context with increased confidence.

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