ALBERT

Description: Quantifying the impacts of aerosols on climate requires a detailed knowledge of both the anthropogenic and the natural contributions to the aerosol population. Recent work has suggested a previously unrecognized natural source of ultrafine particles resulting from breaking waves at the surface of large freshwater lakes. This work is the first modeling study to investigate the potential for this newly discovered source to affect the aerosol number concentrations on regional scales. Using the WRF-Chem modeling framework, the impacts of wind-driven aerosol production from the surface of the Great Lakes were studied for a July 2004 test case. Simulations were performed for a base case with no lake surface emissions, a case with lake surface emissions included, and a default case wherein large freshwater lakes emit marine particles as if they were oceans. Results indicate that the lake surface emissions can enhance the surface-level aerosol number concentration by ~20% over the remote northern Great Lakes and by ~5% over other parts of the Great Lakes. These results were highly sensitive to the new particle formation (i.e., nucleation) parameterization within WRF-Chem; when the new particle formation process was deactivated, surface-layer enhancements from the lake emissions increased to as much as 200%. The results reported here have significant uncertainties associated with the lake emission parameterization and the way ultrafine particles are modeled within WRF-Chem. Nevertheless, the magnitudes of the impacts found in this study suggest that further study to quantify the emissions of ultrafine particles from the surface of the Great Lakes is merited.

Description: Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R 〉 0.9) but were significantly biased (~25%) with consistent under-predictions for spring months when there is significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ± 10 ppb but not found to significantly affect peak ozone surface concentrations.

Description: Intermittent coherent structures can be responsible for a large fraction of the exchange between a forest canopy and the atmosphere. Quantifying their contribution to momentum and heat fluxes is necessary to interpret measurements of trace gases and aerosols within and above forest canopies. The primary objective of the Community Atmosphere-Biosphere Interactions Experiment (CABINEX) field campaign (10 July 2009 to 9 August 2009) was to study the chemistry of volatile organic compounds (VOC) within and above a forest canopy. In this manuscript we provide an analysis of coherent structures and canopy-atmosphere exchange during CABINEX to support in-canopy gradient measurements of VOC. We quantify the number and duration of coherent structure events and their percent contribution to momentum and heat fluxes with two methods: (1) quadrant-hole analysis, and (2) wavelet analysis. Despite differences in the duration and number of events, both methods predict that coherent structures contribute 40–50% to momentum fluxes and 44–65% to heat fluxes during the CABINEX campaign. Contributions associated with coherent structures are slightly greater under stable atmospheric conditions. By comparing heat fluxes within and above the canopy, we determine the degree of coupling between upper canopy and atmosphere, and find that they are coupled the majority of the time. Uncoupled canopy-atmosphere events occur in the early morning (4–8 a.m. local time) approximately 30% of the time. This study confirms that coherent structures contribute significantly to the exchange of heat and momentum between the canopy and atmosphere at the CABINEX site, and indicates the need to include these transport processes when studying the mixing and chemical reactions of trace gases and aerosols between a forest canopy and the atmosphere.

Description: Despite critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, a "best available" set of SOA modeling parameters is selected by comparing predicted SOA yields and mass concentrations with observed yields and mass concentrations from a comprehensive list of published smog chamber studies. Evaluated SOA model parameters include existing parameters for two product (2p) and volatility basis set (VBS) modeling frameworks, and new 2p-VBS parameters; 2p-VBS parameters are developed to exploit advantages of the VBS approach within the computationally-economical and widely-used 2p framework. Fine particulate matter (PM2.5) and SOA mass concentrations are simulated for the continental United States using CMAQv.4.7.1; results are compared for a base case (with default CMAQ parameters) and two best available parameter cases to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future modeling and measurement efforts. The comparisons of SOA yield predictions with data from 22 published chamber studies illustrate that: (1) SOA yields for naphthalene, and cyclic and 〉 C5 straight-chain/branched alkanes are not well represented using either the newly developed or existing parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for four of seven volatile organic compound+oxidant systems, the 2p-VBS parameters better represent chamber data than do the default CMAQ v.4.7.1 parameters. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 15% and 7%, respectively, for the high-NOx case and up to 215% (~3 μg m−3) and 55%, respectively, for the low-NOx case. Percent bias between model-based and observationally-based secondary organic carbon (SOC) improved from −63% for the base case to −15% for the low-NOx case. The ability to robustly assign "best available" parameters in all volatile organic compound+oxidant systems, however, is critically limited due to insufficient data; particularly for photo-oxidation of diverse monoterpenes, sesquiterpenes, and alkanes under a range of atmospherically relevant conditions.

Description: Quantifying the impacts of aerosols on climate requires a detailed knowledge of both the anthropogenic and the natural contributions to the aerosol population. Recent work has suggested a previously unrecognized natural source of ultrafine particles resulting from breaking waves at the surface of large freshwater lakes. This work is the first modeling study to investigate the potential for this newly discovered source to affect the aerosol number concentrations on regional scales. Using the WRF-Chem modeling framework, the impacts of wind-driven aerosol production from the surface of the Great Lakes were studied for a July 2004 test case. Simulations were performed for a base case with no lake surface emissions, a case with lake surface emissions included, and a default case wherein large freshwater lakes emit marine particles as if they were oceans. Results indicate that the lake surface emissions can enhance the surface level aerosol number concentration by ∼20 % over the remote northern Great Lakes and by ∼5 % over other parts of the Great Lakes. These results were highly sensitive the nucleation parameterization within WRF-Chem; when the nucleation process was deactivated, surface-layer enhancements from the lake emissions increased to as much as 200 %. The results reported here have significant uncertainties associated with the lake emission parameterization and the way ultrafine particles are modeled within WRF-Chem. Nevertheless, the magnitude of the impacts found in this study suggest that further study of this phenomena is merited.

Description: Regional climate change impact (CCI) studies have widely involved downscaling and bias-correcting (BC) Global Climate Model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables (evapotranspiration, ET; runoff; snow water equivalent, SWE; and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW) Region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ Andrews). Simulation results from the coupled ECHAM5/MPI-OM model with A1B emission scenario were firstly dynamically downscaled to 12 km resolutions with WRF model. Then a quantile mapping based statistical downscaling model was used to downscale them into 1/16th degree resolution daily climate data over historical and future periods. Two series climate data were generated according to the option of bias-correction (i.e. with bias-correction (BC) and without bias-correction, NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological datasets. These impact models include a macro-scale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrologic model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However, significant differences rise from projected SWE, crop yield from dry lands, and HJ Andrews's ET between BC and NBC data. Even though BC post-processing has no significant impacts on most of the studied variables when taking PNW as a whole, their effects have large spatial variations and some local areas are substantially influenced. In addition, there are months during which BC and NBC post-processing produces significant differences in projected changes, such as summer runoff. Factor-controlled simulations indicate that BC post-processing of precipitation and temperature both substantially contribute to these differences at region scales. We conclude that there are trade-offs between using BC climate data for offline CCI studies vs. direct modeled climate data. These trade-offs should be considered when designing integrated modeling frameworks for specific applications; e.g., BC may be more important when considering impacts on reservoir operations in mountainous watersheds than when investigating impacts on biogenic emissions and air quality (where VOCs are a primary indicator).

Description: Exposure to bioaerosol allergens such as pollen can cause exacerbations of allergenic airway disease (AAD) in sensitive populations, and thus cause serious public health problems. Assessing these health impacts by linking the airborne pollen levels, concentrations of respirable allergenic material, and human allergenic response under current and future climate conditions is a key step toward developing preventive and adaptive actions. To that end, a regional-scale pollen emission and transport modeling framework was developed that treats allergenic pollens as non-reactive tracers within the WRF/CMAQ air-quality modeling system. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model was used to generate a daily pollen pool that can then be emitted into the atmosphere by wind. The STaMPS is driven by species-specific meteorological (temperature and/or precipitation) threshold conditions and is designed to be flexible with respect to its representation vegetation species and plant functional types (PFTs). The hourly pollen emission flux was parameterized by considering the pollen pool, friction velocity, and wind threshold values. The dry deposition velocity of each species of pollen was estimated based on pollen grain size and density. An evaluation of the pollen modeling framework was conducted for southern California for the period from March to June 2010. This period coincided with observations by the University of Southern California's Children's Health Study (CHS), which included O3, PM2.5, and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 km and 4 km were constructed, and six representative allergenic pollen genera were included: birch tree, walnut tree, mulberry tree, olive tree, oak tree, and brome grasses. Under the current parameterization scheme, the modeling framework tends to underestimate walnut and peak oak pollen concentrations, and tends to overestimate grass pollen concentrations. The model shows reasonable agreement with observed birch, olive, and mulberry tree pollen concentrations. Sensitivity studies suggest that the estimation of the pollen pool is a major source of uncertainty for simulated pollen concentrations. Achieving agreement between emission modeling and observed pattern of pollen releases is the key for successful pollen concentration simulations.

Description: To understand more fully the effects of global changes on ambient concentrations of ozone and particulate matter with aerodynamic diameter smaller than 2.5 μm (PM2.5) in the US, we conducted a comprehensive modeling effort to evaluate explicitly the effects of changes in climate, biogenic emissions, land use, and global/regional anthropogenic emissions on ozone and PM2.5 concentrations and composition. Results from the ECHAM5 global climate model driven with the A1B emission scenario from the Intergovernmental Panel on Climate Change (IPCC) were downscaled using the Weather Research and Forecasting (WRF) model to provide regional meteorological fields. We developed air quality simulations using the Community Multiscale Air Quality Model (CMAQ) chemical transport model for two nested domains with 220 and 36 km horizontal grid cell resolution for a semi-hemispheric domain and a continental United States (US) domain, respectively. The semi-hemispheric domain was used to evaluate the impact of projected Asian emissions changes on US air quality. WRF meteorological fields were used to calculate current (2000s) and future (2050s) biogenic emissions using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). For the semi-hemispheric domain CMAQ simulations, present-day global emissions inventories were used and projected to the 2050s based on the IPCC A1B scenario. Regional anthropogenic emissions were obtained from the US Environmental Protection Agency National Emission Inventory 2002 (EPA NEI2002) and projected to the future using the MARKet ALlocation (MARKAL) energy system model assuming a business as usual scenario that extends current decade emission regulations through 2050. Our results suggest that daily maximum 8 h average ozone (DM8O) concentrations will increase in a range between 2 to 12 ppb across most of the continental US, with the highest increase in the South, Central, and Midwest regions of the US, due to increases in temperature, enhanced biogenic emissions, and changes in land use. The effects of these factors are only partially offset by reductions in DM8O associated with decreasing US anthropogenic emissions. Increases in PM2.5 levels between 2 and 4 μg m−3 in the Northeast, Southeast, and South regions are mostly a result of enhanced biogenic emissions and land use changes. Little change in PM2.5 in the Central, Northwest, and Southwest regions was found, even when PM precursors are reduced with regulatory curtailment. Changes in temperature, relative humidity, and boundary conditions shift the composition but do not alter overall PM2.5 mass concentrations.

Description: Despite the critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, advantages of the volatility basis set (VBS) modeling approach are exploited to develop parameters for use in the computationally-efficient and widely-used two product (2p) SOA modeling framework, standard in chemical transport models such as CMAQ (Community Multiscale Air Quality) and GEOS-Chem (Goddard Earth Observing System–Chemistry). Calculated SOA yields and mass loadings obtained using the newly-developed 2p-VBS parameters and existing 2p and VBS parameters are compared with observed yields and mass loadings from a comprehensive list of published smog chamber studies to determine a "best available" set of SOA modeling parameters. SOA and PM2.5 levels are simulated using CMAQv.4.7.1; results are compared for a base case (with default 2p CMAQ parameters) and two "best available" parameter cases chosen to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Comparisons of published smog chamber data with SOA yield predictions illustrate that: (1) SOA yields for naphthalene and cyclic and 〉 C5 alkanes are not well represented using either newly developed (2p-VBS) or existing (2p and VBS) parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for 4 of 7 volatile organic compound + oxidant systems, the 2p-VBS parameters better represent existing data. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 10–15% and 7%, respectively, for the high-NOx case and up to 215% (~ 3 μg m−3) and 55%, respectively, for the low-NOx case. The ability to robustly assign "best available" parameters, however, is limited due to insufficient data for photo-oxidation of diverse monoterpenes and sesquiterpenes under a variety of atmospherically relevant NOx conditions. These results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future measurement and modeling efforts.