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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impacts, processes and projections of the quasi-biennial oscillation

In the tropical stratosphere, deep layers of eastward and westward winds encircle the globe and descend regularly from the upper stratosphere to the tropical tropopause. With a complete cycle typically lasting almost 2.5 years, this quasi-biennial oscillation (QBO) is arguably the most predictable mode of atmospheric variability that is not linked to the changing seasons. Here, the QBO affects climate phenomena outside the tropical stratosphere, including ozone transport, the North Atlantic Oscillation and the Madden–Julian Oscillation, and its high predictability could enable better forecasts of these phenomena if models can accurately represent the coupling processes. Climate and forecasting models are increasingly able to simulate stratospheric oscillations resembling the QBO, but exhibit common systematic errors such as weak amplitude in the lowermost tropical stratosphere. Uncertainties about the waves that force the oscillation, particularly the momentum fluxes from small-scale gravity waves excited by deep convection, make its simulation challenging. Improved representation of the processes governing the QBO is expected to lead to better forecasts of the oscillation and its impacts, increased understanding of unusual events such as the two QBO disruptions observed since 2016, and more reliable future projections of QBO behaviour under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

58 GEOSCIENCES↗
DOE OSTI2020

Effective radiative forcing and adjustments in CMIP6 models

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Variability of Water Vapor in the Tropical Middle Atmosphere Observed From Satellites and Interpreted Using SD-WACCM Simulations

Water vapor in the middle atmosphere plays an essential role in global warming, ozone depletion, and the formation of polar stratospheric and mesospheric clouds. We show that tropical middle atmospheric water vapor simulated with the specified-dynamics version of the Whole Atmosphere Community Climate Model (SD-WACCM) is consistent with changes observed in a merged satellite data set, which encompasses the period 1993–2020. Consistent with previous work, we find no significant trend in the stratosphere in either the observations or the simulation; in the mesosphere, we find a long-term trend of 0.1 ppmv per decade, but only in the observations. We also analyze an SD-WACCM simulation for the longer period 1980–2019 to quantify the contribution of various factors to the decadal variation of middle atmospheric water vapor. Over 1980–1995, the simulated water vapor in the upper stratosphere and mesosphere, averaged zonally and over ±30° latitude, increases by 0.30 ppmv per decade due to increasing methane emissions. After 1995, a significant abrupt decrease of water vapor of 0.37 ppmv per decade and then a gradual increase of 0.33 ppmv per decade result from changes in stratospheric cold point temperature. The cold-point temperature is strongly influenced by the strength of the Brewer-Dobson circulation. The acceleration of the Brewer-Dobson circulation before about 2003 leads to a cooler tropical tropopause and a decrease of water vapor, and the deceleration thereafter leads to corresponding warming of the tropopause and an increase in water vapor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Comparison of Machine Learning Methods to Forecast Tropospheric Ozone Levels in Delhi

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R2 values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R 2 of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Omega-3 fatty acids attenuate cardiovascular effects of short-term exposure to ambient air pollution

Background: Exposure to air pollution is associated with elevated cardiovascular risk. Evidence shows that omega-3 polyunsaturated fatty acids (omega-3 PUFA) may attenuate the adverse cardiovascular effects of exposure to fine particulate matter (PM 2.5 ). However, it is unclear whether habitual dietary intake of omega-3 PUFA protects against the cardiovascular effects of short-term exposure to low-level ambient air pollution in healthy participants. In the present study, sixty-two adults with low or high dietary omega-3 PUFA intake were enrolled. Blood lipids, markers of vascular inflammation, coagulation and fibrinolysis, and heart rate variability (HRV) and repolarization were repeatedly assessed in 5 sessions separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily PM 2.5 and maximum 8-h ozone (O 3 ) concentrations were obtained from nearby air quality monitoring stations. Linear mixed-effects models were used to assess the associations between air pollutant concentrations and cardiovascular responses stratified by the omega-3 intake levels. Results: The average concentrations of ambient PM 2.5 and O 3 were well below the U.S. National Ambient Air Quality Standards during the study period. Significant associations between exposure to PM 2.5 and changes in total cholesterol, von Willebrand factor (vWF), tissue plasminogen activator, D-dimer, and very-low frequency HRV were observed in the low omega-3 group, but not in the high group. Similarly, O 3 -associated adverse changes in cardiovascular biomarkers (total cholesterol, high-density lipoprotein, serum amyloid A, soluable intracellular adhesion molecule 1, and vWF) were mainly observed in the low omega-3 group. Lag-time-dependent biphasic changes were observed for some biomarkers. Conclusions: This study demonstrates associations between short-term exposure to PM 2.5 and O 3 , at concentrations below regulatory standard, and subclinical cardiovascular responses, and that dietary omega-3 PUFA consumption may provide protection against such cardiovascular effects in healthy adults.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality

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 (PM 2.5 ). 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, O 3 , sulfate, nitrate, ammonium, elemental carbon, tropospheric O 3 residual, and column nitrogen dioxide (NO 2 ). 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 O 3 . However, relatively large biases still exist for cloud predictions, some PM 2.5 species, and PM 10 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), O 3 , nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM 2.5 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.

58 GEOSCIENCES↗
DOE OSTI2020

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

Nade, Dada R.↗
DOE OSTI2026

Indirect climate impacts of the Hunga eruption

Injection of sulfur and water vapour by the Hunga volcanic eruption significantly altered chemical composition and radiative budget of the stratosphere. Yet, whether the eruption could also affect surface climate, especially via indirect pathways, remains poorly understood. Here we investigate these effects using large ensembles of simulations with the CESM2(WACCM6) Earth system model, incorporating interactive chemistry and aerosols in both coupled ocean and atmosphere-only configurations. We find some statistically significant extratropical regional climate responses to the eruption driven by circulation changes; these are partially linked to the modulation of El Niño–Southern Oscillation, and its associated teleconnections, and to perturbations of the stratospheric polar vortex in both hemispheres. The stratospheric anomalies affect surface climate through modulating the North Atlantic Oscillation in the Northern Hemisphere (up to three boreal winters following the eruption) and the Southern Annular Mode in the Southern Hemisphere in late 2023. The latter is partly related to a concurrent reduction in Antarctic ozone, as increased stratospheric aerosols and water vapor reach the polar vortex. Our study suggests that the eruption could have had a non-negligible influence on regional surface climate, and discusses the mechanisms via which such an influence could occur. However, the results also highlight that this forcing is relatively weak compared to interannual variability, and is subject to model uncertainties in the representation of key processes. More research is thus needed before definitive statements on the role of the eruption in contributing to surface climate and weather events in the following years are made.

Geosciences↗
DOE OSTI2020

Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0 °C above 1850–1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30 °N, 15 °N, 15 °S, and 30 °S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-to-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5 °C vs. 2.0 °C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO 2 concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

42 ENGINEERING↗
DOE OSTI2024

The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

We present a variable-resolution global chemistry-climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban-to-rural chemical regimes, mesoscale convective systems, and land-surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi-decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25-km uniform-resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal-to-diurnal cycles and extremes, notably reducing the central US dry-and-warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process-level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land-biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Origin of the isotopic composition of natural perchlorate: Experimental results for the impact of reaction pathway and initial ClO x reactant

Natural perchlorate (ClO 4 - ) exists in many places on Earth, in lunar regolith, meteorites, and on the surface of Mars. Terrestrial natural ClO 4 - has widely variable Cl and O stable isotopic compositions (δ 37 Cl, δ 18 O, Δ 17 O). The δ 18 O and Δ 17 O values of ClO 4 - from the most hyper-arid locations co-vary. ClO 4 - from less arid areas has relatively little 17 O excess and poor Δ 17 O-δ 18 O correlation. ClO 4 - from the Atacama Desert has unusually low δ 37 Cl (<-10‰) and exhibits a positive correlation between δ 37 Cl and δ 18 O, while the δ 37 Cl of ClO 4 - from all other locations varies between -5 and +7‰ with no δ 37 Cl-δ 18 O covariation. To evaluate the impact of different precursors (ClO x ) and reaction pathways on the isotopic composition of ClO 4 - , we measured the isotopic composition of ClO 4 - produced in the laboratory by UV or O 3 mediated aqueous oxidation of Cl-, OCl-, ClO2-, and ClO2° as well as O 3 mediated oxidation of dry NaCl. ClO x oxidation in aqueous or dry systems enriched in O 3 produced ClO 4 - with Δ 17 O values that generally increased with the number of O atoms required and included evidence that the site-specific 17 O anomaly in O 3 was preferentially transferred to ClO 4 - . Based on the inferred number of O atoms sourced from O 3 , and known Cl and O reaction pathways, it appears that ClO 2 ° and ClO 3 * were required intermediates in the production of ClO 4 - in the O 3 experiments. ClO x aqueous oxidation by UV irradiation produced ClO 4 - with a large range of δ 18 O values and little or no 17 O anomaly. ClO 3 - was produced to a much greater extent than ClO 4 - in all experiments except dry oxidation of NaCl by O 3 . The isotopic composition of ClO 3 - was distinct from that of ClO 4 - produced from the same initial reactants. Combined results of O 3 and UV mediated reactions largely bracketed the range of natural ClO 4 - δ 18 O and Δ 17 O values as well as δ 37 Cl values of non-Atacama natural samples, but no conditions produced the low δ 37 Cl values of Atacama ClO 4 - . Finally, our results indicate that variation in production mechanisms, possibly combined with isotopically variable precursors, could be responsible for much of the observed isotopic variation in natural ClO 4 - and ClO 3 - .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deep Convection‐Driven Downward Transport of Trace Gases and Aerosols From the Free Troposphere to the Boundary Layer

Deep convective clouds regulate Earth's energy and moisture budgets, yet their impact on the atmospheric boundary layer (BL) composition remains underexplored. Using long-term observations from three mid-latitude sites, we show that deep convection (DC) consistently enhances nighttime surface ozone and is often accompanied by modest increases in ultrafine particle concentrations. Within the BL, the condensational growth of these transported ultrafine particles may contribute up to 60% of total cloud condensation nuclei (CCN). Mass flux calculations suggest that short-lived convective cores (∼30 min) account for ∼2% of total vertical air mass transport relative to steady entrainment, increasing to ∼13% when the trailing stratiform regions are included. These results show that DC provides an episodic but efficient pathway linking the free troposphere and BL, influencing oxidant budgets, CCN variability, and climate forcing. Accurately representing this process in climate models may help reduce uncertainties in climate projections, under both preindustrial and present-day conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Validation of an Erythema-Weighted UV Model Using Broadband Solar Irradiance Measurements From Eleven U.S. Sites: Preprint

Erythema-weighted UV solar irradiance (UV-E) has a potential impact on human health if the recommended maximum exposure times are exceeded. In spite of this, it is not measured at most sites that measure Global Horizontal Irradiance (GHI). However, since UV-E is highly correlated with GHI and total ozone content it can be estimated from this information with sufficient accuracy to assisst in public health recommendations. The Power Model (PM) provides a simple method to estimate the erythema-weighted UV irradiance (UV-E) from measured GHI, total ozone column and air mass. In this work, the performance of the PM method is assessed using high-quality data from 11 sites in the continental U.S. (part of SURFRAD and SOLRAD networks) and total ozone estimates publicly available from the MERRA-2 re-analysis database. A three year period (2021- 2023) at 1-minute frequency is considered. The results (for time aggregations of 5 and 60 minutes) show a high Pearson's correlations (> 0.99), consistently positive mean bias deviations (below 13%) and dispersions in the 8-19% range at all sites. Relative values are expressed in terms of the corresponding measurement mean. The performance indicators remain consistent across time resolutions (5 or 60 minutes), suggesting that the model's performance is robust and not significantly affected by short-term variability (which is captured by GHI). Spatial patterns reveal higher biases and RMSD in northern and eastern locations. These values represent a significant improvement over widely used satellite-based global UV-E estimates and open the possibility of using the PM with satellite-based GHI estimates for operational UV-E mapping over the contiguous U.S. territory.

14 SOLAR ENERGY↗
DOE OSTI2021

Data from Bioenergy Sorghum Maintains Photosynthetic Capacity in Elevated Ozone Concentrations

Elevated tropospheric ozone concentration (O3) significantly reduces photosynthesis and productivity in several C4 crops including maize, switchgrass and sugarcane. However, it is unknown how O3 affects plant growth, development and productivity in sorghum ( Sorghum bicolor L.), an emerging C4 bioenergy crop. Here, we investigated the effects of elevated O3 on photosynthesis, biomass and nutrient composition of a number of sorghum genotypes over two seasons in the field using free-air concentration enrichment (FACE), and in growth chambers. We also tested if elevated O3 altered the relationship between stomatal conductance and environmental conditions using two common stomatal conductance models. Sorghum genotypes showed significant variability in plant functional traits, including photosynthetic capacity, leaf N content and specific leaf area, but responded similarly to O3. At the FACE experiment, elevated O3 did not alter net CO2 assimilation (A), stomatal conductance (gs), stomatal sensitivity to the environment, chlorophyll fluorescence and plant biomass, but led to reductions in the maximum carboxylation capacity of phosphoenolpyruvate and increased stomatal limitation to A in both years. These findings suggest that bioenergy sorghum is tolerant to O3 and could be used to enhance biomass productivity in O3 polluted regions.

Feedstock Production↗
DOE OSTI2021

Bioenergy sorghum maintains photosynthetic capacity in elevated ozone concentrations

Abstract Elevated tropospheric ozone concentration (O 3 ) significantly reduces photosynthesis and productivity in several C 4 crops including maize, switchgrass and sugarcane. However, it is unknown how O 3 affects plant growth, development and productivity in sorghum ( Sorghum bicolor L.), an emerging C 4 bioenergy crop. Here, we investigated the effects of elevated O 3 on photosynthesis, biomass and nutrient composition of a number of sorghum genotypes over two seasons in the field using free‐air concentration enrichment (FACE), and in growth chambers. We also tested if elevated O 3 altered the relationship between stomatal conductance and environmental conditions using two common stomatal conductance models. Sorghum genotypes showed significant variability in plant functional traits, including photosynthetic capacity, leaf N content and specific leaf area, but responded similarly to O 3 . At the FACE experiment, elevated O 3 did not alter net CO 2 assimilation ( A ), stomatal conductance ( g s ), stomatal sensitivity to the environment, chlorophyll fluorescence and plant biomass, but led to reductions in the maximum carboxylation capacity of phosphoenolpyruvate and increased stomatal limitation to A in both years. These findings suggest that bioenergy sorghum is tolerant to O 3 and could be used to enhance biomass productivity in O 3 polluted regions.

09 BIOMASS FUELS↗
DOE OSTI2022

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Tracking Seasonal and Interannual Variability in Photosynthetic Downregulation in Response to Water Stress at a Temperate Deciduous Forest

Abstract The understanding and modeling of photosynthetic dynamics affected by climate variability can be highly uncertain. In this paper, we examined a well‐characterized eddy covariance site in a drought‐prone temperate deciduous broadleaf forest combining tower measurements and satellite observations. We find that an increase in spring temperature usually leads to enhanced spring gross primary production (GPP), but a GPP reduction in late growing season due to water limitation. We evaluated how well a coupled fluorescence‐photosynthesis model (SCOPE) and satellite data sets track the interannual and seasonal variations of tower GPP from 2007 to 2016. In SCOPE, a simple stress factor scaling of Vcmax as a linear function of observed predawn leaf water potential ( ψ pd ) shows a good agreement between modeled and measured interannual variations in both GPP and solar‐induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The modeled and satellite‐observed changes in SIF yield are ~30% smaller than corresponding changes in light use efficiency (LUE) under severe stress, for which a common linear SIF to GPP scaling would underestimate the stress reduction in GPP. Overall, GOME‐2 SIF tracks interannual tower GPP variations better than satellite vegetations indices (VIs) representing canopy “greenness.” However, it is still challenging to attribute observed SIF variations unequivocally to greenness or physiological changes due to large GOME‐2 footprint. Higher‐resolution SIF data sets (e.g., TROPOMI) already show the potential to well capture the downregulation of late‐season GPP and could pave the way to better disentangle canopy structural and physiological changes in the future.

He, Liyin↗