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

Wang, Kai; Zhang, Yang; Yahya, Khairunnisa; Wu, S. C.; Grell, Georg

doi:10.1016/j.atmosenv.2014.12.007

Cited by 101 publications

(80 citation statements)

References 69 publications

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“…A recent study (C.F., Mass, personal communication, 2010) found that increasing the surface friction velocity (u * ) by 50 % reduced the bias in surface wind predictions in a complex-terrain domain. This technique was tested and adopted in previous studies Mass and Ovens, 2010;Wang et al, 2015) where it improved the accuracy of air quality predictions. In the current study, a 1-year sensitivity simulation for California in the year 2000 revealed that increasing u * by 50 % improved the mean wind bias from 1.15 to −0.50 m s −1 and lowered the root-mean-square error (RMSE) from 2.95 to 2.20 m s −1 .…”

Section: Meteorology and Emissionsmentioning

confidence: 99%

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

Zhang

Ying

et al. 2015

Atmos. Chem. Phys.

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Abstract. For the first time, a ∼ decadal (9 years from 2000 to 2008) air quality model simulation with 4 km horizontal resolution over populated regions and daily time resolution has been conducted for California to provide air quality data for health effect studies. Model predictions are compared to measurements to evaluate the accuracy of the simulation with an emphasis on spatial and temporal variations that could be used in epidemiology studies. Better model performance is found at longer averaging times, suggesting that model results with averaging times ≥ 1 month should be the first to be considered in epidemiological studies. The UCD/CIT model predicts spatial and temporal variations in the concentrations of O 3 , PM 2.5 , elemental carbon (EC), organic carbon (OC), nitrate, and ammonium that meet standard modeling performance criteria when compared to monthly-averaged measurements. Predicted sulfate concentrations do not meet target performance metrics due to missing sulfur sources in the emissions. Predicted seasonal and annual variations of PM 2.5 , EC, OC, nitrate, and ammonium have mean fractional biases that meet the model performance criteria in 95, 100, 71, 73, and 92 % of the simulated months, respectively. The base data set provides an improvement for predicted population exposure to PM concentrations in California compared to exposures estimated by central site monitors operated 1 day out of every 3 days at a few urban locations. Uncertainties in the model predictions arise from several issues. Incomplete understanding of secondary organic aerosol formation mechanisms leads to OC bias in the model results in summertime but does not affect OC predictions in winter when concentrations are typically highest. The CO and NO (species dominated by mobile emissions) results reveal temporal and spatial uncertainties associated with the mobile emissions generated by the EMFAC 2007 model. The WRF model tends to overpredict wind speed during stagnation events, leading to underpredictions of high PM concentrations, usually in winter months. The WRF model also generally underpredicts relative humidity, resulting in less particulate nitrate formation, especially during winter months. These limitations must be recognized when using data in health studies. All model results included in the current manuscript can be downloaded free of charge at http: //faculty.engineering.ucdavis.edu/kleeman/.

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Section: Meteorology and Emissionsmentioning

confidence: 99%

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

Zhang

Ying

et al. 2015

Atmos. Chem. Phys.

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“…On the other hand, other modeling studies for different summer periods and regions (US and Europe) showed that the DRE on ozone vary spatially, leading to either ozone enhancement or reduction depending on the local meteorological and 10 chemical conditions (Forkel et al, 2012Hogrefe et al, 2015;Kong et al, 2015;Makar et al, 2015a;Wang et al, 2015). Moreover, they showed that the impact on ozone (both enhancement and reduction) was even stronger when the AIE were also taken into account.…”

Section: Introductionmentioning

confidence: 93%

Modeling the impact of solar brightening on summer surface ozone over Europe between 1990 and 2010

Oikonomakis

Aksoyoğlu

Wild

et al. 2018

Preprint

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10Surface solar radiation (SSR) observations have indicated an increasing trend in Europe since the mid-1980s, referred to as solar "brightening". In this study, we used the regional air quality model, CAMx (Comprehensive Air Quality Model with extensions) to simulate and quantify, with various sensitivity runs (where the year 2010 served as the base case), the effects of increased radiation on photolysis rates (PHOT1, PHOT2 and PHOT3 scenarios) and biogenic volatile organic compounds (BVOCs) emissions (BIO scenario), and their consequent impacts on summer surface ozone concentrations over Europe 15 between 1990 and 2010. The PHOT1 and PHOT2 scenarios examined the effect of doubling and tripling the anthropogenic PM 2.5 concentrations, respectively, while the PHOT3 investigated the impact of an increase in just the sulfate concentrations by a factor of 3.4 (as in 1990), applied only to the calculation of photolysis rates. In the BIO scenario, we reduced the 2010 SSR by 3% (keeping plant cover and temperature the same), re-calculated the biogenic emissions and repeated the base case simulations with the new biogenic emissions. The impact on photolysis rates for all three scenarios was an increase (in 2010 20 compared to 1990) of 3-6% which resulted in daytime (10:00-18:00 Local Mean Time (LMT)) mean surface ozone differences of 0.2-0.7 ppb (0.5-1.5%), with the largest hourly difference rising as high as 4-8 ppb (10-16%). The effect of changes in BVOCs emissions on daytime mean surface ozone was much smaller (up to 0.08 ppb, ~ 0.2%), as isoprene and terpene (monoterpene and sesquiterpene) emissions increased only by 2.5-3% and 0.7%, respectively. Overall, the impact of the SSR changes on surface ozone was greater via the effects on photolysis rates compared to the effects on BVOCs 25 emissions, and the sensitivity test of their combined impact (PHOT3+BIO = COMBO scenario) showed nearly additive effects. In addition, all the sensitivity runs were repeated on a second base case with increased NO x emissions to account for any potential underestimation of modeled ozone production; the results did not change significantly in magnitude, but the spatial coverage of the effects was profoundly extended. Finally, the role of the solar "brightening" in the European summer surface ozone trends was suggested to be more important when comparing to the order of magnitude of the ozone trends 30Atmos. Chem. Phys. Discuss., https://doi

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“…In this study, we applied the WRF/Chem v3.6.1 with updates in Wang et al (2015) to simulate air quality and climate under the two RCP scenarios and WRF/Chem v3.7 under the two TDM scenarios. In both versions, the physics options include the Rapid and accurate Radiative Transfer Model for GCM for both shortwave and longwave radiation, the Yonsei University planetary boundary layer scheme and the Morrison double moment microphysics scheme.…”

Section: Model Setup and Methodologymentioning

confidence: 99%

Impacts of projected climate scenarios on future air quality and water-carbon cycle in the United States.

Zhang¹

2017

Air and Water Components of the Environment 2017

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ABSTRACT. -Impacts of projected climate scenarios on future air quality and water-carbon cycle in the United States. Projected changes in anthropogenic emissions and climate changes will impact future air quality, water and carbon cycles, as well as human and environmental health in the United States. In this work, we applied an advanced online-coupled meteorology and chemistry model and an ecohydrological model to simulate such impacts on future air quality, water supplies, and carbon cycles over the continental U.S. for current (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and future (2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054)(2055) years under four climate and emission scenarios including the Representative Concentration Pathways (RCP) 4.5 and 8.5 and the Technology Driver Model (TDM) A1B and B2. A comprehensive evaluation of atmospheric predictions for the current decade using available observations shows an overall good model performance. Future air quality features greater reduction in PM 2.5 by RCP 4.5/8.5 than TDM B2/A1B and decreased ozone (O 3 ) over most areas by RCP4.5 and TDM B2, indicating the benefits of carbon policy and technology improvements with greater emission reductions. The climate warming and reduction in precipitation induced by air pollution are projected to lead to a reduction in water yield under both RCP scenarios but an increase in gross ecosystem productivity in some areas under the RCP8.5 scenario. The results show that air pollution is an important factor to be considered in projecting the impacts of climate change on water and carbon cycles at the continental scale.

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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

Cited by 101 publications

References 69 publications

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

Modeling the impact of solar brightening on summer surface ozone over Europe between 1990 and 2010

Impacts of projected climate scenarios on future air quality and water-carbon cycle in the United States.

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