@article{he_glotfelty_yahya_alapaty_yu_2017, title={Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?}, volume={154}, journal={Atmospheric Environment}, author={He, J. and Glotfelty, T. and Yahya, K. and Alapaty, K. and Yu, S. C.}, year={2017}, pages={42–52} }
 @article{yahya_glotfelty_wang_zhang_nenes_2017, title={Modeling regional air quality and climate: Improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1}, volume={10}, number={6}, journal={Geoscientific Model Development}, author={Yahya, K. and Glotfelty, T. and Wang, K. and Zhang, Y. and Nenes, A.}, year={2017}, pages={2333–2363} }
 @article{saha_khlystov_yahya_zhang_xu_ng_grieshop_2017, title={Quantifying the volatility of organic aerosol in the southeastern US}, volume={17}, number={1}, journal={Atmospheric Chemistry and Physics}, author={Saha, P. K. and Khlystov, A. and Yahya, K. and Zhang, Y. and Xu, L. and Ng, N. L. and Grieshop, A. P.}, year={2017}, pages={501–520} }
 @article{zhang_hong_yahya_li_zhang_he_2016, title={Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States}, volume={138}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.05.006}, abstractNote={An online-coupled meteorology-chemistry model, WRF/Chem-MADRID, has been deployed for real time air quality forecast (RT-AQF) in southeastern U.S. since 2009. A comprehensive evaluation of multi-year RT-AQF shows overall good performance for temperature and relative humidity at 2-m (T2, RH2), downward surface shortwave radiation (SWDOWN) and longwave radiation (LWDOWN), and cloud fraction (CF), ozone (O3) and fine particles (PM2.5) at surface, tropospheric ozone residuals (TOR) in O3 seasons (May-September), and column NO2 in winters (December-February). Moderate-to-large biases exist in wind speed at 10-m (WS10), precipitation (Precip), cloud optical depth (COT), ammonium (NH4+), sulfate (SO42−), and nitrate (NO3−) from the IMPROVE and SEARCH networks, organic carbon (OC) at IMPROVE, and elemental carbon (EC) and OC at SEARCH, aerosol optical depth (AOD) and column carbon monoxide (CO), sulfur dioxide (SO2), and formaldehyde (HCHO) in both O3 and winter seasons, column nitrogen dioxide (NO2) in O3 seasons, and TOR in winters. These biases indicate uncertainties in the boundary layer and cloud process treatments (e.g., surface roughness, microphysics cumulus parameterization), emissions (e.g., O3 and PM precursors, biogenic, mobile, and wildfire emissions), upper boundary conditions for all major gases and PM2.5 species, and chemistry and aerosol treatments (e.g., winter photochemistry, aerosol thermodynamics). The model shows overall good skills in reproducing the observed multi-year trends and inter-seasonal variability in meteorological and radiative variables such as T2, WS10, Precip, SWDOWN, and LWDOWN, and relatively well in reproducing the observed trends in surface O3 and PM2.5, but relatively poor in reproducing the observed column abundances of CO, NO2, SO2, HCHO, TOR, and AOD. The sensitivity simulations using satellite-constrained boundary conditions for O3 and CO show substantial improvement for both spatial distribution and domain-mean performance statistics. The model's forecasting skills for air quality can be further enhanced through improving model inputs (e.g., anthropogenic emissions for urban areas and upper boundary conditions of chemical species), meteorological forecasts (e.g., WS10, Precip) and meteorologically-dependent emissions (e.g., biogenic and wildfire emissions), and model physics and chemical treatments (e.g., gas-phase chemistry in winter conditions, cloud processes and their interactions with radiation and aerosol).}, journal={ATMOSPHERIC ENVIRONMENT}, author={Zhang, Yang and Hong, Chaopeng and Yahya, Khairunnisa and Li, Qi and Zhang, Qiang and He, Kebin}, year={2016}, month={Aug}, pages={162–182} }
 @article{yahya_wang_campbell_chen_glotfelty_he_pirhalla_zhang_2017, title={Decadal application of WRF/Chem for regional air quality and climate modeling over the US under the representative concentration pathways scenarios. Part 1: Model evaluation and impact of downscaling}, volume={152}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.12.029}, abstractNote={An advanced online-coupled meteorology-chemistry model, i.e., the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied for current (2001–2010) and future (2046–2055) decades under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios to examine changes in future climate, air quality, and their interactions. In this Part I paper, a comprehensive model evaluation is carried out for current decade to assess the performance of WRF/Chem and WRF under both scenarios and the benefits of downscaling the North Carolina State University's (NCSU) version of the Community Earth System Model (CESM_NCSU) using WRF/Chem. The evaluation of WRF/Chem shows an overall good performance for most meteorological and chemical variables on a decadal scale. Temperature at 2-m is overpredicted by WRF (by ∼0.2–0.3 °C) but underpredicted by WRF/Chem (by ∼0.3–0.4 °C), due to higher radiation from WRF. Both WRF and WRF/Chem show large overpredictions for precipitation, indicating limitations in their microphysics or convective parameterizations. WRF/Chem with prognostic chemical concentrations, however, performs much better than WRF with prescribed chemical concentrations for radiation variables, illustrating the benefit of predicting gases and aerosols and representing their feedbacks into meteorology in WRF/Chem. WRF/Chem performs much better than CESM_NCSU for most surface meteorological variables and O3 hourly mixing ratios. In addition, WRF/Chem better captures observed temporal and spatial variations than CESM_NCSU. CESM_NCSU performance for radiation variables is comparable to or better than WRF/Chem performance because of the model tuning in CESM_NCSU that is routinely made in global models.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Wang, Kai and Campbell, Patrick and Chen, Ying and Glotfelty, Timothy and He, Jian and Pirhalla, Michael and Zhang, Yang}, year={2017}, month={Mar}, pages={562–583} }
 @article{yahya_campbell_zhang_2017, title={Decadal application of WRF/chem for regional air quality and climate modeling over the US under the representative concentration pathways scenarios. Part 2: Current vs. future simulations}, volume={152}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.12.028}, abstractNote={Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046–2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Campbell, Patrick and Zhang, Yang}, year={2017}, month={Mar}, pages={584–604} }
 @article{yahya_wang_campbell_glotfelty_he_zhang_2016, title={Decadal evaluation of regional climate, air quality, and their interactions over the continental US and their interactions using WRF/Chem version 3.6.1}, volume={9}, number={2}, journal={Geoscientific Model Development}, author={Yahya, K. and Wang, K. and Campbell, P. and Glotfelty, T. and He, J. and Zhang, Y.}, year={2016}, pages={671–695} }
 @article{duan_sun_zhang_yahya_wang_madden_caldwell_cohen_mcnulty_2017, title={Impact of air pollution induced climate change on water availability and ecosystem productivity in the conterminous United States}, volume={140}, ISSN={0165-0009 1573-1480}, url={http://dx.doi.org/10.1007/S10584-016-1850-7}, DOI={10.1007/s10584-016-1850-7}, number={2}, journal={Climatic Change}, publisher={Springer Science and Business Media LLC}, author={Duan, Kai and Sun, Ge and Zhang, Yang and Yahya, Khairunnisa and Wang, Kai and Madden, James M. and Caldwell, Peter V. and Cohen, Erika C. and McNulty, Steven G.}, year={2017}, pages={259–272} }
 @article{giordano_brunner_flemming_hogrefe_im_bianconi_badia_balzarini_baro_chemel_et al._2015, title={Assessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2}, volume={115}, journal={Atmospheric Environment}, author={Giordano, L. and Brunner, D. and Flemming, J. and Hogrefe, C. and Im, U. and Bianconi, R. and Badia, A. and Balzarini, A. and Baro, R. and Chemel, C. and et al.}, year={2015}, pages={371–388} }
 @article{brunner_savage_jorba_eder_giordano_badia_balzarini_baro_bianconi_chemel_et al._2015, title={Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2}, volume={115}, journal={Atmospheric Environment}, author={Brunner, D. and Savage, N. and Jorba, O. and Eder, B. and Giordano, L. and Badia, A. and Balzarini, A. and Baro, R. and Bianconi, R. and Chemel, C. and et al.}, year={2015}, pages={470–498} }
 @article{im_bianconi_solazzo_kioutsioukis_badia_balzarini_baro_bellasio_brunner_chemel_et al._2015, title={Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone}, volume={115}, journal={Atmospheric Environment}, author={Im, U. and Bianconi, R. and Solazzo, E. and Kioutsioukis, I. and Badia, A. and Balzarini, A. and Baro, R. and Bellasio, R. and Brunner, D. and Chemel, C. and et al.}, year={2015}, pages={404–420} }
 @article{yahya_he_zhang_2015, title={Multiyear applications of WRF/Chem over continental US: Model evaluation, variation trend, and impacts of boundary conditions}, volume={120}, ISSN={["2169-8996"]}, DOI={10.1002/2015jd023819}, abstractNote={AbstractMultiyear applications of an online‐coupled meteorology‐chemistry model allow an assessment of the variation trends in simulated meteorology, air quality, and their interactions to changes in emissions and meteorology, as well as the impacts of initial and boundary conditions (ICONs/BCONs) on simulated aerosol‐cloud‐radiation interactions over a period of time. In this work, the Weather Research and Forecasting model with Chemistry version 3.4.1 (WRF/Chem v. 3.4.1) with the 2005 Carbon Bond mechanism coupled with the Volatility Basis Set module for secondary organic aerosol formation (WRF/Chem‐CB05‐VBS) is applied for multiple years (2001, 2006, and 2010) over continental U.S. This work also examines the changes in simulated air quality and meteorology due to changes in emissions and meteorology and the model's capability in reproducing the observed variation trends in species concentrations from 2001 to 2010. In addition, the impacts of the chemical ICONs/BCONs on model predictions are analyzed. ICONs/BCONs are downscaled from two global models, the modified Community Earth System Model/Community Atmosphere model version 5.1 (CESM/CAM v5.1) and the Monitoring Atmospheric Composition and Climate model (MACC). The evaluation of WRF/Chem‐CB05‐VBS simulations with the CESM ICONs/BCONs for 2001, 2006, and 2010 shows that temperature at 2 m (T2) is underpredicted for all three years likely due to inaccuracies in soil moisture and soil temperature, resulting in biases in surface relative humidity, wind speed, and precipitation. With the exception of cloud fraction, other aerosol‐cloud variables including aerosol optical depth, cloud droplet number concentration, and cloud optical thickness are underpredicted for all three years, resulting in overpredictions of radiation variables. The model performs well for O3 and particulate matter with diameter less than or equal to 2.5 (PM2.5) for all three years comparable to other studies from literature. The model is able to reproduce observed annual average trends in O3 and PM2.5 concentrations from 2001 to 2006 and from 2006 to 2010 but is less skillful in simulating their observed seasonal trends. The 2006 and 2010 results using CESM and MACC ICONs/BCONs are compared to analyze the impact of ICONs/BCONs on model performance and their feedbacks to aerosol, clouds, and radiation. Comparing to the simulations with MACC ICONs/BCONs, the simulations with the CESM ICONs/BCONs improve the performance of O3 mixing ratios (e.g., the normalized mean bias for maximum 8 h O3 is reduced from −17% to −1% in 2010), PM2.5 in 2010, and sulfate in 2006 (despite a slightly larger normalized mean bias for PM2.5 in 2006). The impacts of different ICONs/BCONs on simulated aerosol‐cloud‐radiation variables are not negligible, with larger impacts in 2006 compared to 2010.}, number={24}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Yahya, Khairunnisa and He, Jian and Zhang, Yang}, year={2015}, month={Dec}, pages={12748–12777} }
 @article{campbell_zhang_yahya_wang_hogrefe_pouliot_knote_hodzic_san jose_perez_et al._2015, title={A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) phase 2 over North America: Part I. Indicators of the sensitivity of O-3 and PM2.5 formation regimes}, volume={115}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.12.026}, abstractNote={Under the Air Quality Model Evaluation International Initiative, Phase 2 (AQMEII-2), three online-coupled air quality model simulations, with six different configurations, are analyzed for their performance, inter-model agreement, and responses to emission and meteorological changes between 2006 and 2010. In this Part I paper, we focus on evaluating O3 and PM2.5 indicator-based analyses, which are important in the development of applicable control strategies of O3 and PM2.5 pollution in different regions worldwide. The O3 indicators agree on widespread NOx-limited and localized VOC-limited conditions in the U.S. The NOy and O3/NOy indicators overpredict the extent of the VOC-limited chemistry in southeast U.S., but are more robust than the H2O2/HNO3, HCHO/NOy, and HCHO/NO2 indicators at the surface, which exhibit relatively more inter-model variability. The column HCHO/NO2 indicator is underpredicted in the O3 and non-O3 seasons, but there is regional variability. For surface PM2.5 indicators, there is good inter-model agreement for the degree of sulfate neutralization; however there are systematic underpredictions in the southeast U.S. There is relatively poor inter-model agreement for the less robust adjusted gas ratio indicator, which is largely overpredicted in the summer and both under- and overpredicted in winter in the southeast U.S. There is good inter-model agreement for the O3 indicator sensitivities, indicating a predominant shift to more NOx-limited conditions in 2010 relative to 2006. There is less agreement for PM2.5 indicator sensitivities, which are less robust, while indicating shifts to either regime due to different responses of aerosol treatments to changes in emissions and meteorology.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Campbell, Patrick and Zhang, Yang and Yahya, Khairunnisa and Wang, Kai and Hogrefe, Christian and Pouliot, George and Knote, Christoph and Hodzic, Alma and San Jose, Roberto and Perez, Juan L. and et al.}, year={2015}, month={Aug}, pages={569–586} }
 @article{yahya_wang_gudoshava_glotfelty_zhang_2015, title={Application of WRF/Chem over North America under the AQMEII Phase 2: Part I. Comprehensive evaluation of 2006 simulation}, volume={115}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.08.063}, abstractNote={The Weather Research and Forecasting model with Chemistry (WRF/Chem) version 3.4.1 has been modified to include the Carbon Bond 2005 (CB05) gas-phase mechanism, the Modal for Aerosol Dynamics for Europe (MADE) and the Volatility Basis Set (VBS) approach for secondary organic aerosol (hereafter WRF/Chem-CB05-MADE/VBS), and aerosol-cloud-radiation feedbacks to improve predictions of secondary organic aerosols (SOA) and to study meteorology-chemistry feedbacks. In this Part I paper, a comprehensive evaluation is performed for WRF/Chem-CB05-MADE/VBS to simulate air quality over a large area in North America for the full year of 2006. Operational, diagnostic, and mechanistic evaluations have been carried out for major meteorological variables, gas and aerosol species, as well as aerosol-cloud-radiation variables against surface measurements, sounding data, and satellite data on a seasonal and annual basis. The model performs well for most meteorological variables with moderate to relatively high correlation and low mean biases (MBs), but with a cold bias of 0.8–0.9 °C in temperature, a moderate overprediction with normalized mean biases (NMBs) of 17–22% in wind speed, and large underpredictions with NMBs of −65% to −62% in cloud optical depths and cloud condensation nuclei over the ocean. Those biases are attributed to uncertainty in physical parameterizations, incomplete treatments of hydrometeors, and inaccurate aerosol predictions. The model shows moderate underpredictions in the mixing ratios of O3 with an annual NMB of −12.8% over rural and national park sites, which may be caused by biases in temperature and wind speed, underestimate in wildfire emissions, and underestimate in biogenic organic emissions (reflected by an NMB of −79.1% in simulated isoprene mixing ratio). The model performs well for PM2.5 concentrations with annual NMBs within ±10%; but with possible bias compensation for PM2.5 species concentrations. The model simulates well the domainwide organic carbon and SOA concentrations at two sites in the southeastern U.S. but it overpredicts SOA concentrations at two sites and underpredicts OC at one site in the same area. Those biases in site-specific SOA and OC predictions are attributed to underestimates in observed SOA, uncertainties in VOC emissions, inaccurate meteorology, and the inadequacies in the VBS treatment. Larger biases exist in predictions of dry and wet deposition fluxes of gas and PM species due mainly to overpredictions in their concentrations and precipitation, uncertainties in model treatments of deposition processes, and uncertainties in the CASTNET dry deposition data. Comparison of WRF and WRF/Chem simulations shows that the inclusion of chemical feedbacks to meteorology, clouds, and radiation results in improved predictions in most meteorological variables. Aerosol optical depth correlates strongly with aerosol concentration and cloud optical depth. The relationships between the aerosol and cloud variables are complex as the cloud variables are not only influenced by aerosol concentrations but by larger-scale dynamical processes.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Wang, Kai and Gudoshava, Masi Lin and Glotfelty, Timothy and Zhang, Yang}, year={2015}, month={Aug}, pages={733–755} }
 @article{wang_zhang_yahya_wu_grell_2015, title={Implementation and initial application of new chemistry-aerosol options in WRF/Chem for simulating secondary organic aerosols and aerosol indirect effects for regional air quality}, volume={115}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.12.007}, abstractNote={Atmospheric aerosols play important roles in affecting regional meteorology and air quality through aerosol direct and indirect effects. Two new chemistry-aerosol options have been developed in WRF/Chem v3.4.1 by incorporating the 2005 Carbon Bond (CB05) mechanism and coupling it with the existing aerosol module MADE with SORGAM and VBS modules for simulating secondary organic aerosol (SOA), aqueous-phase chemistry in both large scale and convective clouds, and aerosol feedback processes (hereafter CB05-MADE/SORGAM and CB05-MADE/VBS). As part of the Air Quality Model Evaluation International Initiative (AQMEII) Phase II model intercomparison that focuses on online-coupled meteorology and chemistry models, WRF/Chem with the two new options is applied to an area over North America for July 2006 episode. The simulations with both options can reproduce reasonably well most of the observed meteorological variables, chemical concentrations, and aerosol/cloud properties. Compared to CB05-MADE/SORGAM, CB05-MADE/VBS greatly improves the model performance for organic carbon (OC) and PM2.5, reducing NMBs from −81.2% to −13.1% and from −26.1% to −15.6%, respectively. Sensitivity simulations show that the aerosol indirect effects (including aqueous-phase chemistry) can reduce the net surface solar radiation by up to 53 W m−2 with a domainwide mean of 12 W m−2 through affecting cloud formation and radiation scattering and reflection by increasing cloud cover, which in turn reduce the surface temperature, NO2 photolytic rate, and planetary boundary layer height by up to 0.3 °C, 3.7 min−1, and 64 m, respectively. The changes of those meteorological variables further impact the air quality through the complex chemistry-aerosol-cloud-radiation interactions by reducing O3 mixing ratios by up to 5.0 ppb. The results of this work demonstrate the importance of aerosol indirect effects on the regional climate and air quality. For comparison, the impacts of aerosol direct effects on both regional meteorology and air quality are much lower with the reduction on net surface solar radiation only by up to 17 W m−2 and O3 only by up to 1.4 ppb, which indicates the importance and necessity to accurately represent the aerosol indirect effects in the online-couple regional models.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Wang, Kai and Zhang, Yang and Yahya, Khairunnisa and Wu, Shiang-Yuh and Grell, Georg}, year={2015}, month={Aug}, pages={716–732} }
 @article{knote_tuccella_curci_emmons_orlando_madronich_baro_jimenez-guerrero_luecken_hogrefe_et al._2015, title={Influence of the choice of gas-phase mechanism on predictions of key gaseous pollutants during the AQMEII phase-2 intercomparison}, volume={115}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.11.066}, abstractNote={The formulations of tropospheric gas-phase chemistry (“mechanisms”) used in the regional-scale chemistry-transport models participating in the Air Quality Modelling Evaluation International Initiative (AQMEII) Phase 2 are intercompared by the means of box model studies. Simulations were conducted under idealized meteorological conditions, and the results are representative of mean boundary layer concentrations. Three sets of meteorological conditions – winter, spring/autumn and summer – were used to capture the annual variability, similar to the 3-D model simulations in AQMEII Phase 2. We also employed the same emissions input data used in the 3-D model intercomparison, and sample from these datasets employing different strategies to evaluate mechanism performance under a realistic range of pollution conditions. Box model simulations using the different mechanisms are conducted with tight constraints on all relevant processes and boundary conditions (photolysis, temperature, entrainment, etc.) to ensure that differences in predicted concentrations of pollutants can be attributed to differences in the formulation of gas-phase chemistry. The results are then compared with each other (but not to measurements), leading to an understanding of mechanism-specific biases compared to the multi-model mean. Our results allow us to quantify the uncertainty in predictions of a given compound in the 3-D simulations introduced by the choice of gas-phase mechanisms, to determine mechanism-specific biases under certain pollution conditions, and to identify (or rule out) the gas-phase mechanism as the cause of an observed discrepancy in 3-D model predictions. We find that the predictions of the median diurnal cycle of O3 over a set of emission conditions representing a network of station observations is within 4 ppbv (5%) across the different mechanisms. This variability is found to be very similar on both continents. There are considerably larger differences in predicted concentrations of NOx (up to ± 25%), key radicals like OH (40%), HO2 (25%) and especially NO3 (>100%). Secondary substances like H2O2 (25%) or HNO3 (10%), as well as key volatile organic compounds like isoprene (>100%) or CH2O (20%) differ substantially as well. Calculation of an indicator of the chemical regime leads to up to 20% of simulations being classified differently by different mechanism, which would lead to different predictions of the most efficient emission reduction strategies. All these differences are despite identical meteorological boundary conditions, photolysis rates, as well as identical biogenic and inorganic anthropogenic emissions. Anthropogenic VOC emissions only vary in the way they are translated in mechanism-specific compounds, but are identical in the total emitted carbon mass and its spatial distribution. Our findings highlight that the choice of gas-phase mechanism is crucial in simulations for regulatory purposes, emission scenarios, as well as process studies that investigate other components like secondary formed aerosol components. We find that biogenic VOCs create considerable variability in mechanism predictions and suggest that these, together with nighttime chemistry should be areas of further mechanism improvement.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Knote, Christoph and Tuccella, Paolo and Curci, Gabriele and Emmons, Louisa and Orlando, John J. and Madronich, Sasha and Baro, Rocio and Jimenez-Guerrero, Pedro and Luecken, Deborah and Hogrefe, Christian and et al.}, year={2015}, month={Aug}, pages={553–568} }
 @article{yahya_zhang_vukoyich_2014, title={Real-time air quality forecasting over the southeastern United States using WRF/Chem-MADRID: Multiple-year assessment and sensitivity studies}, volume={92}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.04.024}, abstractNote={An air quality forecasting system is a tool for protecting public health by providing an early warning system against harmful air pollutants. In this work, the online-coupled Weather Research and Forecasting Model with Chemistry with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (WRF/Chem-MADRID) is used to forecast ozone (O3) and fine particles (PM2.5) concentrations over the southeastern U.S. for three O3 seasons from May to September in 2009, 2010, and 2011 and three winters from December to February during 2009–2010, 2010–2011, and 2011–2012. The forecasted chemical concentrations and meteorological variables are evaluated with observations from networks data in terms of spatial distribution, temporal variation, and discrete and categorical performance statistics. The model performs well for O3 and satisfactorily for PM2.5 in terms of both discrete and categorical evaluations but larger biases exist in PM species. The model biases are due to uncertainties in meteorological predictions, emissions, boundary conditions, chemical reactions, as well as uncertainties/differences in the measurement data used for evaluation. Sensitivity simulations show that using MEGAN online biogenic emissions and satellite-derived wildfire emissions result in improved performance for PM2.5 despite a degraded performance for O3. A combination of both can reduce normalize mean bias of PM2.5 from −18.3% to −11.9%. This work identifies a need to improve the accuracy of emissions by using dynamic biogenic and fire emissions that are dependent on meteorological conditions, in addition to the needs for more accurate anthropogenic emissions for urban areas and more accurate meteorological forecasts.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Zhang, Yang and Vukoyich, Jeffrey M.}, year={2014}, month={Aug}, pages={318–338} }