ARL Weekly News – May 13, 2022
Sandia Labs Supplements MACCS Code with HYSPLIT Capabilities
Sandia National Laboratories has published its report documenting the effort to supplement the Gaussian atmospheric transport and diffusion model currently in MACCS, a nuclear accident consequence analysis code, with a new option using ARL’s HYSPLIT model. Now, calculations in MACCS may use the HYSPLIT-generated air concentration, and ground deposition values to calculate the same range of output quantities (dose, health effects, risks, etc.). Specific scenarios and sensitivity studies were designed to examine how the results generated by the traditional MACCS Gaussian plume segment model compare to the new, higher fidelity HYSPLIT/MACCS modeling option. The comparisons provided in the report can also help decision-makers evaluate the potential benefit of using results based on higher fidelity modeling with the additional computational burden needed to perform the calculations.
About MACCS: MACCS was developed by Sandia National Laboratories for the U.S. NRC for the purpose of simulating and analyzing the impacts of severe nuclear accidents at nuclear power plants on the surrounding population and environment. MACCS is used by U.S. nuclear power plant license renewal applicants to support the plant specific evaluation of severe accident mitigation alternatives as part of the applicant’s environmental report for license renewal. MACCS is also used in severe accident mitigation design alternatives analyses and severe accident consequence analyses for environmental impact statements and environmental assessments for new reactor applications.
ARL’s Roland Draxler, Glenn Rolph, Ariel Stein, Tianfeng Chai, and Mark Cohen aided Sandia with the assessment and integration of HYSPLIT with MACCS. The full report is available from Sandia here.
PACE Mission Applications Program
Alice Crawford participated in the NASA PACE air quality and applied atmospheric sciences focus session on Wednesday 11 May. The virtual event included breakout sessions and panel discussions with active attendee participation. PACE is NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem mission, currently in the design phase of mission development. It is scheduled to launch in 2024 to provide satellite observations of global ocean biology, aerosols, and clouds. More info on the PACE Applications Program is available on their website.
Eric Roy one the ARL interns from summer 2020 from the LaPenta Internship program, has been accepted to graduate school at MIT and expects to work in the group of Dr. Noelle Eckley Selin on mercury modeling with GEOS-CHEM.
Preprint Available: Evaluation and Bias Correction of Probabilistic Ash Forecasts by Alice Crawford, Tianfeng Chai, Binyu Wang, Allison Ring, Barbara Stunder, Christopher Loughner, Michael Pavolonis and Justin Sieglaff and submitted to Atmospheric Chemistry and Physics is now accessible and open for interactive public discussion until 22 Jun 2022 at: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-290/
Abstract: Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small pieces of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident, but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble relative frequency of exceedance and agreement in percentile levels are suited for strategies in which areas with certain concentrations or mass loadings of ash need to be avoided with a chosen amount of confidence.
Published: Bae, M., B.-U. Kim, H.C. Kim, J.H. Woo, and S. Kim: An observation-based adjustment method of regional contribution estimation from upwind emissions to downwind PM2.5 concentrations, Environment International, 163(2022), 107214, doi:10.1016/j.envint.2022.107214, 2022
Abstract: We propose a method to adjust contributions from upwind emissions to downwind PM2.5 concentrations to account for the differences between observed and simulated PM2.5 concentrations in an upwind area. Emissions inventories (EI) typically have a time lag between the inventory year and the release year. In addition, traditional emission control policies and social issues such as the COVID-19 pandemic cause steady or unexpected changes in anthropogenic emissions. These uncertainties could result in overestimation of the emission impacts of upwind areas on downwind areas if emissions used in modeling for the upwind areas were larger than the reality. In this study, South Korea was defined as the downwind area while other regions in Northeast Asia including China were defined as the upwind areas to evaluate applicability of the proposed adjustment method. We estimated the contribution of emissions released from the upwind areas to PM2.5 concentrations in South Korea from 2015 to 2020 using a three-dimensional photochemical model with two EIs. In these two simulations for 2015–2020, the annual mean foreign contributions differed by 4.1–5.5 µg/m3. However, after adjustment, the differences decreased to 0.4–1.1 µg/m3. The adjusted annual mean foreign contributions were 12.7 and 8.8 µg/m3 during 2015–2017 and 2018–2020, respectively. Finally, we applied the adjustment method to the COVID-19 pandemic period to evaluate the applicability for short-term episodes. The foreign contribution of PM2.5 during the lockdown period in China decreased by 30% after adjustment and the PM2.5 normalized mean bias in South Korea improved from 15% to −4%. This result suggests that the upwind contribution adjustment can be used to alleviate the uncertainty of the emissions inventory used in air quality simulations. We believe that the proposed upwind contribution adjustment method can help to correctly understand the contributions of local and upwind emissions to PM2.5 concentrations in downwind areas.
Published: Jung, J., Y. Choi, S. Mousavinezhad, D. Kang, D.C. Wong, J. Park, A. Pouyaei, M. Momeni, and H. Kim: Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NOx and VOC emissions using satellite observation, Atmospheric Research, 270 (2022), 106076, doi: 10.1016/j.atmosres.2022.106076, 2022
Abstract: To investigate changes in the ozone (O3) chemical production regime over the contiguous United States (CONUS) with accurate knowledge of concentrations of its precursors, we applied an inverse modeling technique with Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) and total formaldehyde (HCHO) retrieval products in the summers of 2011, 2014, and 2017, years in which United States National Emission Inventory were based. The inclusion of dynamic chemical lateral boundary conditions and lightning-induced nitric oxide emissions significantly account for the contribution of background sources in the free troposphere. Satellite-constrained nitrogen oxide (NOx) and non-methane volatile organic compounds (NMVOCs) emissions mitigate the discrepancy between satellite and modeled columns: the inversion suggested 2.33–2.84 (1.07–1.34) times higher NOx over the CONUS (over urban regions) and 0.28–0.81 times fewer NMVOCs emissions over the southeastern United States. The model-derived HCHO/NO2 column ratio shows gradual spatial changes in the O3 production regime near urban cores relative to previously defined threshold values representing NOx and VOC sensitive conditions. We also found apparent shifts from the NOx-saturated regime to the transition regime (or the transition regime to the NOx-limited regime) over the major cities in the western United States. In contrast, rural areas, especially in the east-southeastern United States, exhibit a decreased HCHO/NO2 column ratio by −1.30 ± 1.71 with a reduction in HCHO column primarily driven by meteorology, becoming sensitive to VOC emissions. Results show that incorporating satellite observations into numerical modeling could help policymakers implement appropriate emission control policies for O3 pollution.