Weather Research And Forecasting-Community Multiscale Air Quality Research Articles

Aircraft landing and takeoff emission impacts on surface O3 and PM2.5 through aerosol direct feedback effects estimated by the coupled WRF-CMAQ model

The aerosol direct feedback effects (ADFEs) are neglected in traditional air quality modeling studies (where meteorology is used as input and not affected by the chemistry and aerosol microphysics) for estimating the impacts of aircraft emissions on air quality. In this study, aircraft landing and take-off (LTO) attributable change of O3 and PM2.5 concentrations through ADFEs for the year 2005 within the contiguous United States (CONUS) are quantified by a coupled meteorology-chemistry modeling system: Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model. We first quantified the effects of ADFEs of all aerosols within the CONUS (not the effects of aircraft LTO emissions) on surface meteorology and air quality and found that ADFEs changed on average the downward short-wave radiation (SWR), 2-m temperature (T2), planetary boundary layer (PBL) height, O3 and PM2.5 by −7.38 W/m2, −0.47 K, −20.72 m, −0.41 ppb and +0.28 μg/m3 in 2005. We also found a seasonal influence where ADFE-influenced change (decrease) of SWR, T2, PBL, O3 and change (increase) of PM2.5 were higher in summer than in winter. We found that the aircraft LTO emissions’ contribution to domain average surface concentration of O3 and PM2.5 were +0.0065 ppb and +0.0022 μg/m3 respectively when ADFEs are accounted for. The ADFEs decrease aircraft LTO attributable surface O3 and PM2.5 change by 21% and 23% respectively comparing with that without ADFE in 2005. We also found that in both without-and-with ADFE cases, the aircraft LTO emissions increases domain average of O3 from April to October and decreases from November to March showing a strong seasonal pattern. Our modeling study revealed that use of a coupled model with ADFE shows localized changes in air quality by aircraft LTO emissions across the domain which were masked when looking at domain averages for both O3 and PM2.5, and which may be important for accurately quantifying health risk due to air pollution exposures in densely populated areas.

Effects of cool roofs on turbulent coherent structures and ozone air quality in Seoul

Abstract The cool-roof strategy is an effective way of mitigating severe urban heat islands, and its impacts on urban flow and air quality deserve in-depth investigations. This study examines the effects of cool roofs on turbulent coherent structures and ozone air quality in Seoul, South Korea using the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model with a 50 m horizontal grid spacing. Cool roofs decrease the daily average air temperature, planetary boundary layer (PBL) height, and wind speed in the urban area of Seoul by 0.80 °C, 230 m, and 0.17 m s−1, respectively. Due to the lowered air temperature by cool roofs, the sea breeze and convective structures weaken and eddies at the PBL top appear less frequently. Since high O3 concentration air flows into Seoul by the sea breeze, the weakened sea breeze decreases the daily average O3 concentration near the surface by 3.3 ppb. Air at lower level is transported upward across the PBL top by convective structures and eddies at the PBL top. The transported air at lower level has lower O3 concentration and higher concentrations of O3 precursors than air at upper level. Therefore, the weakened convective structures and less-frequent appearance of eddies at the PBL top by cool roofs weaken the upward transport of O3 precursors at lower level across the PBL top. As a result, the chemical production of O3 and O3 concentration slightly above the PBL top are decreased. An integrated process rate analysis shows that cool roofs weaken the effects of turbulent coherent structures on O3 concentration.

Application of linear minimum variance estimation to the multi-model ensemble of atmospheric radioactive Cs-137 with observations

Abstract. Great efforts have been made to simulate atmospheric pollutants, but their spatial and temporal distributions are still highly uncertain. Observations can measure their concentrations with high accuracy but cannot estimate their spatial distributions due to the sporadic locations of sites. Here, we propose an ensemble method by applying a linear minimum variance estimation (LMVE) between multi-model ensemble (MME) simulations and measurements to derive a more realistic distribution of atmospheric pollutants. The LMVE is a classical and basic version of data assimilation, although the estimation itself is still useful for obtaining the best estimates by combining simulations and observations without a large amount of computer resources, even for high-resolution models. In this study, we adopt the proposed methodology for atmospheric radioactive caesium (Cs-137) in atmospheric particles emitted from the Fukushima Daiichi Nuclear Power Station (FDNPS) accident in March 2011. The uniqueness of this approach includes (1) the availability of observed Cs-137 concentrations near the surface at approximately 100 sites, thus providing dense coverage over eastern Japan; (2) the simplicity of identifying the emission source of Cs-137 due to the point source of FDNPS; (3) the novelty of MME with the high-resolution model (3 km horizontal grid) over complex terrain in eastern Japan; and (4) the strong need to better estimate the Cs-137 distribution due to its inhalation exposure among residents in Japan. The ensemble size is six, including two atmospheric transport models: the Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model and non-hydrostatic icosahedral atmospheric model (NICAM). The results showed that the MME that estimated Cs-137 concentrations using all available sites had the lowest geometric mean bias (GMB) against the observations (GMB =1.53), the lowest uncertainties based on the root mean square error (RMSE) against the observations (RMSE =9.12 Bq m−3), the highest Pearson correlation coefficient (PCC) with the observations (PCC =0.59) and the highest fraction of data within a factor of 2 (FAC2) with the observations (FAC2 =54 %) compared to the single-model members, which provided higher biases (GMB =1.83–4.29, except for 1.20 obtained from one member), higher uncertainties (RMSE =19.2–51.2 Bq m−3), lower correlation coefficients (PCC =0.29–0.45) and lower precision (FAC2 =10 %–29 %). At the model grid, excluding the measurements, the MME-estimated Cs-137 concentration was estimated by a spatial interpolation of the variance used in the LMVE equation using the inverse distance weights between the nearest two sites. To test this assumption, the available measurements were divided into two categories, i.e. learning and validation data; thus, the assumption for the spatial interpolation was found to guarantee a moderate PCC value (> 0.4) within an approximate distance of at least 70 km. Extra sensitivity tests for several parameters, i.e. the site number and the weighting coefficients in the spatial interpolation, the time window in the LMVE and the ensemble size, were performed. In conclusion, the important assumptions were the time window and the ensemble size; i.e. a shorter time window (the minimum in this study was 1 h, which is the observation interval) and a larger ensemble size (the maximum in this study was six, but five is also acceptable if the members are effectively selected) generated better results.

Spatiotemporal variation in the impact of meteorological conditions on PM2.5 pollution in China from 2000 to 2017

Fine particulate matter (PM2.5) concentration that exceeds standards is causing poor air quality in most Chinese cities. Meteorological conditions are an important factor affecting PM2.5 concentration, but few quantitative studies have been conducted on the effects of long-term and large-scale changes in meteorological factors on PM2.5 pollution. In this study, a Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system was applied to study the spatial and temporal distributions of the impact of meteorological conditions on PM2.5 pollution in China from 2000 to 2017. During the study period, Me-PM2.5 decreased in general (P = 0.0018) in nationwide, and showed significant spatiotemporal variations. There was an overall increasing trend for Beijing, Fujian, Shaanxi, Gansu, and Qinghai provinces (P < 0.05) as the meteorological conditions deteriorated, and there was an overall negative trend for nine provinces (P < 0.05) which indicated meteorological conditions were causing a decrease in concentrations. Substantial differences in the impact of meteorological changes on PM2.5 pollution were observed across the provinces, with FMe-PM2.5 (fluctuating range of Me-PM2.5) between 9.3% and 55.1%. In addition, the best, typical, and worst meteorological years were selected based on Me-PM2.5; these should be considered when setting air quality goals and pollution control plans.

A preliminary study of turbulent coherent structures and ozone air quality in Seoul using the WRF-CMAQ model at a 50 m grid spacing

The effects of turbulent coherent structures on daytime ozone air quality in Seoul, South Korea are investigated through a case study using the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model at a horizontal grid spacing of 50 m. In Seoul, sea breeze and convective structures develop in the daytime. Due to the different wind directions above and below the planetary boundary layer (PBL) top, eddies are formed at the PBL top when updrafts related to convective structures reach above the PBL top. Air at lower level, which has higher concentrations of O3 precursors and lower O3 concentration than air at upper level, is transported upward by convective structures and eddies at the PBL top. Some of the transported air reaches above the PBL top, resulting in the vigorous chemical production of O3 above the PBL top in the afternoon. An integrated process rate analysis is performed to examine the impacts of turbulent coherent structures on O3 concentration in detail. The chemical production of O3 generally appears in updraft areas except near the surface because O3 precursors at lower level are transported by updrafts. Below the height of ~1 km, the horizontal advection of air from other areas to updraft areas increases O3 concentration in updraft areas because O3 concentration in updraft areas is generally lower than that in other areas. Slightly above the PBL top, air with low O3 concentration diverges from updraft areas and air with high O3 concentration at upper level is transported downward by downdrafts around updraft areas.

Effects of air pollution control measures on air quality improvement in Guangzhou, China

The ambient air quality of Guangzhou in 2016 has significantly improved since Guangzhou and its surrounding cities implemented a series of air pollution control measures from 2014 to 2016. This study not only estimated the effects of meteorology and emission control measures on air quality improvement in Guangzhou but also assessed the contributions of emissions reduction from various sources through the combination of observation data and simulation results from Weather Research and Forecasting - Community Multiscale Air Quality (WRF-CMAQ) modeling system. Results showed that the favorable meteorological conditions in 2016 alleviated the air pollution. Compared to change in meteorology, implementing emission control measures in Guangzhou and surrounding cities was more beneficial for air quality improvement, and it could reduce the concentrations of SO2, NO2, PM2.5, PM10, and O3 by 9.7 μg m−3 (48.4%), 9.2 μg m−3 (17.7%), 7.7 μg m−3 (14.6%), 9.7 μg m−3 (13.4%), and 12.0 μg m−3 (7.7%), respectively. Furthermore, emission control measures that implemented in Guangzhou contributed most to the concentration reduction of SO2, NO2, PM2.5, and PM10 (46.0% for SO2, 15.2% for NO2, 9.4% for PM2.5, and 9.1% for PM10), and it increased O3 concentration by 2.4%. With respect to the individual contributions of source emissions reduction, power sector emissions reduction showed the greatest contribution in reducing the concentrations of SO2, NO2, PM2.5, and PM10 due to the implementation of Ultra-Clean control technology. As for O3 mitigation, VOCs product-related source emissions reduction was most effective, and followed by transportation source emissions reduction, while the reductions of power sector, industrial boiler, and industrial process source might not be as effective. Our findings provide scientific advice for the Guangzhou government to formulate air pollution prevention and control policies in the future.

PAN–Precursor Relationship and Process Analysis of PAN Variations in the Pearl River Delta Region

Peroxy acetyl nitrate (PAN) is an important photochemical product formed from the reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx) under sunlight. In this study, a field measurement was conducted at a rural site (the backgarden site, or BGS) of the Pearl River Delta (PRD) region in 2006, with the 10 min maximum PAN mixing ratios of 3.9 ppbv observed. The factors influencing the abundance of PAN at the BGS site was evaluated by the process analysis through the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model. The results suggested that the increase of PAN abundance at the BGS site was mainly controlled by the gas-phase chemistry, followed by vertical transport, while its loss was modulated mainly by dry deposition and horizontal transport. As the dominant important role of gas-phase chemistry, to provide detailed information on the photochemical formation of PAN, a photochemical box model with near-explicit chemical mechanism (i.e., the master chemical mechanism, MCM) was used to explore the relationship of photochemical PAN formation with its precursors based on the measured data at the BGS site. It was found that PAN formation was VOC-limited at the BGS site, with the oxidation of acetaldehyde the most important pathway for photochemical PAN production, followed by the oxidation and photolysis of methylglyoxal (MGLY). Among all the primary VOC precursors, isoprene and xylenes were the main contributors to PAN formation. Overall, our study provides new insights into the PAN photochemical formation and its controlling factors, and highlighted the importance of gas chemistry on the PAN abundance in the PRD region.

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part II: Air quality projections and the interplay between emissions and climate change

In Part II of this work we present the results of the downscaled offline Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) model, included in the “Technology Driver Model” (TDM) approach to future U.S. air quality projections (2046–2050) compared to a current-year period (2001–2005), and the interplay between future emission and climate changes. By 2046–2050, there are widespread decreases in future concentrations of carbon monoxide (CO), nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), ammonia (NH3), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5) due mainly to decreasing on-road vehicle (ORV) emissions near urban centers as well as decreases in other transportation modes that include non-road engines (NRE). However, there are widespread increases in daily maximum 8-hr ozone (O3) across the U.S., which are due to enhanced greenhouse gases (GHG) including methane (CH4) and carbon dioxide (CO2) under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario, and isolated areas of larger reduction in transportation emissions of NOx compared to that of VOCs over regions with VOC-limited O3 chemistry. Other notable future changes are reduced haze and improved visibility, increased primary organic to elemental carbon ratio, decreases in PM2.5 and its species, decreases and increases in dry deposition of SO2 and O3, respectively, and decreases in total nitrogen (TN) deposition. There is a tendency for transportation emission and CH4 changes to dominate the increases in O3, while climate change may either enhance or mitigate these increases in the west or east U.S., respectively. Climate change also decreases PM2.5 in the future. Other variable changes exhibit stronger susceptibility to either emission (e.g., CO, NOx, and TN deposition) or climate changes (e.g., VOC, NH3, SO2, and total sulfate deposition), which also have a strong dependence on season and specific U.S. regions.

Residential emissions predicted as a major source of fine particulate matter in winter over the Yangtze River Delta, China

Air pollution is an increasingly critical health issue responsible for numerous diseases and deaths worldwide. In China, to address severe air pollution in the Yangtze River Delta region, the local government has formulated Five-Year Plans to set the road map for air pollution control by phased targets in 2020, but the effectiveness of these policies is still uncertain. There is therefore a need for accurate prediction of control strategies. Here we present a computational evaluation of the predicted effectiveness of four emission control strategies: normal or enhanced emission reduction for industry and power plants, and normal or enhanced emission reduction for industry, power plants and transportation, designed on the basis of policies of the 13th Five-Year Plans. Effectiveness was tested on concentrations of PM2.5, e.g., particulate matter with aerodynamic diameter less than 2.5 μm, using the two-way coupled Weather Research and Forecasting—Community Multiscale Air Quality (WRF-CMAQ) model. Results show that by implementing the four emission control strategies, only Hangzhou with the strictest emission controls in four main cities (Hangzhou, Hefei, Nanjing and Shanghai) can meet the 20% reduction goals of PM2.5 concentrations in the 13th Five-Year Plan, indicating that current policies are not sufficient to control the severe air pollution in the Yangtze River Delta region. Sensitivity tests show that residential emissions have the highest contributions to the PM2.5 concentrations in January in the four main cities of Hangzhou, Hefei, Nanjing and Shanghai, followed by agriculture, industry, transportation and power plants. Predicted annual mean reduction percentages for PM2.5 are the highest in Hangzhou, from − 9.7 to − 20.1%, followed by Nanjing, from − 8.2 to − 18.7%, Shanghai, from − 7.4 to − 15.8%, and Hefei, from − 6.1 to − 13.8%. This finding highlights the predominance of residential emissions, which should be better controlled, notably coal burning. By comparison, predicted annual contributions of regional transport and natural sources to mean PM2.5 concentrations in four cities range from 29.2 to 36.6%. Overall, a major finding is that residential sources are of comparable importance to industrial, power plant and transportation sources to PM2.5 concentrations, especially for winter. This information will help governments of other regions of China, as well as other developing countries, to formulate more appropriate emission control strategies where coal is used for heating and cooking purposes in the developing countries.

Air quality simulation of existing city block using chemistry-coupled CFD model

In urban area, roadside air pollution is a serious environmental issue. In order to evaluate the roadside air pollution, it is requires to consider the both of chemical reaction and shape of buildings. In this study, a chemistry-coupled CFD (computational fluid dynamics) model was applied to assess the roadside air quality in a real situation. CBM-IV (Carbon bond mechanism IV) was used as the chemical reaction model coupled to the CFD model. The performance of the chemistry-coupled CFD model was tested in Umeda-shindo (Osaka prefecture), where roadside monitoring station is located, 24 hours on 23rd August 2010. The boundary conditions were calculated by air quality model WRF-CMAQ (Weather Research and Forecasting - Community Multiscale Air Quality Modeling System). Results showed that comparing with the observation data, the chemistry-coupled CFD results showed better accuracy in NOx concentration than the WRF-CMAQ data. In a real situation, the building geometry and mobile emission were found to have great impacts on the urban air quality in the CFD simulation, emphasizing the importance to assess the roadside air pollution with high spatial resolution.

Impact of Aerosol Direct Effect on Wintertime PM2.5 Simulated by an Online Coupled Meteorology-Air Quality Model over East Asia

This study aims to evaluate the impacts of the aerosol direct effect on simulated concentrations of fine particulate matter (PM2.5) over East Asia, which is controlled by heavy local air pollution and long-range transport. The online coupled Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) modeling system was applied to one-way and two-way simulations (without and with the aerosol direct effect) of a period from January till March of 2014. The differences between the two simulations showed that there were particularly large impacts of the aerosol direct effect on the eastern Asian continent with high aerosol loading. The temporal mean contributions of the direct effect averaged over the regions from Northeast to Central China were a 15% decrease in the surface shortwave radiation, a 9.0% decrease in the planetary boundary layer (PBL) height, and an 8.6% increase in the ground-level PM2.5 concentration. In addition, there were negative contributions of the direct effect to the PM2.5 concentration over the ocean from the Sea of Japan to the East China Sea (a 1.0% decrease on average throughout the period). The PM2.5 decrease over the ocean was likely attributable to a reduction in the secondary PM2.5 outflow from the continent to the downwind region, which was caused by the increased dry deposition of PM2.5 precursors from the increased ground-level concentrations within a more stable PBL over the continent. Overall, the substantial decrease in the surface shortwave radiation due to the aerosol direct effect led to enhanced atmospheric stability and therefore increased the ground-level PM2.5 in the heavily polluted region.

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

Abstract. In this study, a regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006–2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of −0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate–chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m−2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8–9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate–chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Assessment of regional air quality resulting from emission control in the Pearl River Delta region, southern China

To evaluate the impact of emission control measures on the air quality in the Pearl River Delta (PRD) region of South China, statistic data including atmospheric observations, emissions and energy consumptions during 2006–2014 were analyzed, and a Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model was used for various scenario simulations. Although energy consumption doubled from 2004 to 2014 and vehicle number significantly increased from 2006 to 2014, ambient SO2, NO2 and PM10 were reduced by 66%, 20% and 24%, respectively, mainly due to emissions control efforts. In contrast, O3 increased by 19%. Model simulations of three emission control scenarios, including a baseline (a case in 2010), a CAP (a case in 2020 assuming control strength followed past control tendency) and a REF (a case in 2020 referring to the strict control measures based on recent policy/plans) were conducted to investigate the variations of air pollutants to the changes in NOx, VOCs and NH3 emissions. Although the area mean concentrations of NOx, nitrate and PM2.5 decreased under both NOx CAP (reduced by 1.8%, 0.7% and 0.2%, respectively) and NOx REF (reduced by 7.2%, 1.8% and 0.3%, respectively), a rising of PM2.5 was found in certain areas as reducing NOx emissions elevated the atmospheric oxidizability. Furthermore, scenarios with NH3 emission reductions showed that nitrate was sensitive to NH3 emissions, with decreasing percentages of 0–10.6% and 0–48% under CAP and REF, respectively. Controlling emissions of VOCs reduced PM2.5 in the southwestern PRD where severe photochemical pollution frequently occurred. It was also found that O3 formation in PRD was generally VOCs-limited while turned to be NOx-limited in the afternoon (13:00–17:00), suggesting that cutting VOCs emissions would reduce the overall O3 concentrations while mitigating NOx emissions in the afternoon could reduce the peak O3 levels.

エアロゾル直接効果が冬季の東アジアにおけるPM&lt;sub&gt;2.5&lt;/sub&gt; シミュレーションに及ぼす影響評価

Numerical simulations were performed in order to evaluate the impact of the direct effect of aerosol particles on meteorology and air quality over East Asia. The online coupled Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) modeling system was applied from January to March 2014 for cases with/without feedback: two-way/one-way simulations. Ground-level shortwave radiation and PM2.5 concentration in the two-way simulation were respectively smaller and higher than those in the one-way simulation over the Asian Continent, particularly in China with remarkably high PM2.5 concentration. These differences indicate that the aerosol direct effect substantially influence the atmospheric stability, and therefore the dispersion efficiency of air pollutants.

Assessment of the aerosol optics component of the coupled WRF–CMAQ model using CARES field campaign data and a single column model

The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) – Community Multiscale Air Quality (CMAQ) model. This campaign included comprehensive measurements of aerosol composition and optical properties at two ground sites and aloft from instrumentation on-board two aircraft. A single column model (SCM) was developed to evaluate the accuracy and consistency of the coupled model using both observation and model information. Two cases (June 14 and 24, 2010) are examined in this study. The results show that though the coupled WRF–CMAQ estimates of aerosol extinction were underestimated relative to these measurements, when measured concentrations and characteristics of ambient aerosols were used as input to constrain the SCM calculations, the estimated extinction profiles agreed well with aircraft observations. One of the possible causes of the WRF–CMAQ extinction errors is that the simulated sea-salt (SS) in the accumulation mode in WRF–CMAQ is very low in both cases while the observations indicate a considerable amount of SS. Also, a significant amount of organic carbon (OC) is present in the measurement. However, in the current WRF–CMAQ model all OC is considered to be insoluble whereas most secondary organic aerosol is water soluble. In addition, the model does not consider external mixing and hygroscopic effects of water soluble OC which can impact the extinction calculations. In conclusion, the constrained SCM results indicate that the scattering portion of the aerosol optics calculations is working well, although the absorption calculation could not be effectively evaluated. However, a few factors such as greatly underestimated accumulation mode SS, misrepresentation of water soluble OC, and incomplete mixing state representation in the full coupled model simulation are possible causes of the underestimated extinction. Improved SS emission modeling and revisions to more fully account for OC in the optical calculations are being pursued. More sensitivity tests related to the factors mentioned previously are needed for future optical properties development.

Development of a regional-scale pollen emission and transport modeling framework for investigating the impact of climate change on allergic airway disease

Abstract. 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 coupled Weather Research and Forecasting Community Multiscale Air Quality (WRF/CMAQ) 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 of 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 (USA) 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 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.