Dataset Information

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States.

ABSTRACT: Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)- Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and/or emissions are also evaluated during the same timeframe using spectral decomposition of observed and modeled ozone time series with the aim of identifying the underlying forcing mechanisms that control ozone exceedances and making informed recommendations for the optimal use of regional-scale air quality models. The evaluation is focused on the warm season's (i.e., May-September) daily maximum 8-hr (DM8HR) ozone concentrations, the 4th highest (4th) and average of top 10 DM8HR ozone values (top10), as well as the spectrally-decomposed components of the DM8HR ozone time series using the Kolmogorov-Zurbenko (KZ) filter. Results of the dynamic evaluation are presented for six regions in the U.S., consistent with the National Oceanic and Atmospheric Administration (NOAA) climatic regions. During the earlier 11-yr period (1990-2000), the simulated and observed trends are not statistically significant. During the more recent 2000-2010 period, all trends are statistically significant and WRF-CMAQ captures the observed trend in most regions. Given large number of sites for the 2000-2010 period, the model captures the observed trends in the Southwest (SW) and MW but has significantly different trend from that seen in observations for the other regions. Observational analysis reveals that it is the long-term forcing that dictates how high the ozone exceedances will be; there is a strong linear relationship between the long-term forcing and the 4th highest or the average of the top10 ozone concentrations in both observations and model output. This finding indicates that improving the model's ability to reproduce the long-term component will also enable better simulation of ozone extreme values that are of interest to regulatory agencies.

SUBMITTER: Astitha M

PROVIDER: S-EPMC6071429 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States.

Astitha Marina M Luo Huiying H Rao S Trivikrama ST Hogrefe Christian C Mathur Rohit R Kumar Naresh N

Atmospheric environment (Oxford, England : 1994) 20170101

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)- Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and/or emissions are also evaluated during the same timeframe using spectral decomposition ...[more]

PMID: 30078987

Similar Datasets

Project description:Regional air quality models are widely being used to understand the spatial extent and magnitude of the ozone non-attainment problem and to design emission control strategies needed to comply with the relevant ozone standard through direct emission perturbations. In this study, we examine the manageable portion of ground-level ozone using two simulations of the Community Multiscale Air Quality (CMAQ) model for the year 2010 and a probabilistic analysis approach involving 29 years (1990-2018) of historical ozone observations. The modeling results reveal that the reduction in the peak ozone levels from total elimination of anthropogenic emissions within the model domain is around 13-21 ppb for the 90th-100th percentile range of the daily maximum 8-hr ozone concentrations across the contiguous United States (CONUS). Large reductions in the 4th highest 8-hr ozone are seen in the regions of West (interquartile range (IQR) of 17-33%), South (IQR 22-34%), Central (IQR 19-31%), Southeast (IQR 25-34%), and Northeast (IQR 24-37%). However, sites in the western portion of the domain generally show smaller reductions even when all anthropogenic emissions are removed, possibly due to the strong influence of global background ozone, including sources such as intercontinental ozone transport, stratospheric ozone intrusions, wildfires, and biogenic precursor emissions. Probabilistic estimates of the exceedances for several hypothetical thresholds of the 4th highest 8-hr ozone indicate that, in some areas, exceedances of such hypothetical thresholds may occur even with no anthropogenic emissions due to the ever-present atmospheric stochasticity and the current global tropospheric ozone burden. Implications: Because air pollution is intricately linked to adverse health effects, National Ambient Air Quality Standards (NAAQS) have been established for criteria pollutants to safeguard human health and the environment. Areas not in compliance with the relevant standards are required to develop plans and policies to reduce their air pollution levels. Regional-scale air quality models are currently being used routinely to inform policies to identify the emissions reduction required to meet and maintain the NAAQS throughout the country. This paper examines the feasibility of the 4th highest ozone, which is used to derive the ozone design value for NAAQS, complying with various current and hypothetical 8-hr ozone thresholds over CONUS based on the information embedded in 29 years of historical ozone observations and two modeling scenarios with and without anthropogenic emissions loading.

Project description:The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O3, sulfate, nitrate, ammonium, elemental carbon, tropospheric O3 residual, and column nitrogen dioxide (NO2). For example, the mean biases have been reduced by more than 10 W m-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O3. However, relatively large biases still exist for cloud predictions, some PM2.5 species, and PM10 that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O3, nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

Project description:Soybean (Glycine max L. Merrill) is an economically important commodity for United States agriculture. Nonetheless, the profitability of soybean production has been negatively impacted by soybean diseases. The economic impacts of 23 common soybean diseases were estimated in 28 soybean-producing states in the U.S., from 1996 to 2016 (the entire data set consisted of 13,524 data points). Estimated losses were investigated using a variety of statistical approaches. The main effects of state, year, pre- and post-discovery of soybean rust, region, and zones based on yield, harvest area, and production, were significant on "total economic loss" as a function of diseases. Across states and years, the soybean cyst nematode, charcoal rot, and seedling diseases were the most economically damaging diseases while soybean rust, bacterial blight, and southern blight were the least economically damaging. A significantly greater mean loss (51%) was observed in states/years after the discovery of soybean rust (2004 to 2016) compared to the pre-discovery (1996 to 2003). From 1996 to 2016, the total estimated economic loss due to soybean diseases in the U.S. was $95.48 billion, with $80.89 billion and $14.59 billion accounting for the northern and southern U.S. losses, respectively. Over the entire time period, the average annual economic loss due to soybean diseases in the U.S. reached nearly $4.55 billion, with approximately 85% of the losses occurring in the northern U.S. Low yield/harvest/production zones had significantly lower mean economic losses due to diseases in comparison to high yield/harvest/production zones. This observation was further bolstered by the observed positive linear correlation of mean soybean yield loss (in each state, due to all diseases considered in this study, across 21 years) with the mean state wide soybean production (MT), mean soybean yield (kg ha-1), and mean soybean harvest area (ha). Results of this investigation provide useful insights into how research, policy, and educational efforts should be prioritized in soybean disease management.

Dataset Information

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States.

Publications

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets