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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

MODIS 3km Aerosol Product: Algorithm and Global Perspective

After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

Remer, L. A.↗
NASA NTRS2012

Improving Post-Hurricane Katrina Forest Management with MODIS Time Series Products

Hurricane damage to forests can be severe, causing millions of dollars of timber damage and loss. To help mitigate loss, state agencies require information on location, intensity, and extent of damaged forests. NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data products offers a potential means for state agencies to monitor hurricane-induced forest damage and recovery across a broad region. In response, a project was conducted to produce and assess 250 meter forest disturbance and recovery maps for areas in southern Mississippi impacted by Hurricane Katrina. The products and capabilities from the project were compiled to aid work of the Mississippi Institute for Forest Inventory (MIFI). A series of NDVI change detection products were computed to assess hurricane induced damage and recovery. Hurricane-induced forest damage maps were derived by computing percent change between MODIS MOD13 16-day composited NDVI pre-hurricane "baseline" products (2003 and 2004) and post-hurricane NDVI products (2005). Recovery products were then computed in which post storm 2006, 2007, 2008 and 2009 NDVI data was each singularly compared to the historical baseline NDVI. All percent NDVI change considered the 16-day composite period of August 29 to September 13 for each year in the study. This provided percent change in the maximum NDVI for the 2 week period just after the hurricane event and for each subsequent anniversary through 2009, resulting in forest disturbance products for 2005 and recovery products for the following 4 years. These disturbance and recovery products were produced for the Mississippi Institute for Forest Inventory's (MIFI) Southeast Inventory District and also for the entire hurricane impact zone. MIFI forest inventory products were used as ground truth information for the project. Each NDVI percent change product was classified into 6 categories of forest disturbance intensity. Stand age and stand type raster data, also provided by MIFI, were used along with the forest disturbance/recovery products to create forest damage stratification products integrating 3 stand type classes, 6 stand age classes, and 6 forest disturbance intensity classes. This stratification product will be used to aid MIFI timber inventory planning and to prepare for damage assessments due to future hurricane events. Validation of MODIS percent NDVI change products was performed by comparing the MODIS percent NDVI change products to those from Landsat data for the same time and MIFI inventory district area.

Lewis, Mark David↗
NASA NTRS2014

Demonstration of AIRS Total Ozone Products to Operations to Enhance User Readiness

Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Berndt, Emily↗
NASA NTRS2015

Development and Application of Hyperspectral Infrared Ozone Retrieval Products for Operational Meteorology

Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Berndt, Emily↗
NASA NTRS2014

A Spatially Coherent Global Soil Moisture Product with Improved Temporal Resolution

Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11 km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures. The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN). The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

spatial↗
DOE OSTI2011

Fragranced consumer products: Chemicals emitted, ingredients unlisted

Fragranced consumer products are pervasive in society. Relatively little is known about the composition of these products, due to lack of prior study, complexity of formulations, and limitations and protections on ingredient disclosure in the U.S. We investigated volatile organic compounds (VOCs) emitted from 25 common fragranced consumer products-laundry products, personal care products, cleaning supplies, and air fresheners-using headspace analysis with gas chromatography/mass spectrometry (GC/MS). Our analysis found 133 different VOCs emitted from the 25 products, with an average of 17 VOCs per product. Of these 133 VOCs, 24 are classified as toxic or hazardous under U.S. federal laws, and each product emitted at least one of these compounds. For 'green' products, emissions of these compounds were not significantly different from the other products. Of all VOCs identified across the products, only 1 was listed on any product label, and only 2 were listed on any material safety data sheet (MSDS). While virtually none of the chemicals identified were listed, this nonetheless accords with U.S. regulations, which do not require disclosure of all ingredients in a consumer product, or of any ingredients in a mixture called 'fragrance.' Because the analysis focused on compounds emitted and listed, rather than exposures and effects, it makes no claims regarding possible risks from product use. Results of this study contribute to understanding emissions from common products, and their links with labeling and legislation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Interaction of turbulent premixed flames with combustion products: Role of stoichiometry

Stabilization methods of turbulent flames often involve mixing of reactants with hot products of combustion. The stabilizing effect of combustion product enthalpy has been long recognized, but the role played by the chemical composition of the product gases is typically overlooked. We employ a counterflow system to pinpoint the effects of the combustion product stoichiometry on the structure of turbulent premixed flames under conditions of both stable burning and local extinction. To that end, a turbulent jet of lean-to-rich, CH 4 /O 2 /N 2 -premixed reactants at a turbulent Reynolds number of 1050 was opposed to a stream of hot products of combustion that were generated in a preburner. While the combustion product stream temperature was kept constant, its stoichiometry was varied independently from that of the reactant stream, leading to reactant-to-product stratification of relevance to practical combustion systems. The detailed structure of the turbulent flame front was analyzed in two series of experiments using laser-induced fluorescence (LIF): joint CH 2 O LIF and OH LIF measurements and joint CO LIF and OH LIF measurements. Results revealed that a decrease in local CH 2 O+OH and CO+OH reaction rates coincide with the depletion of OH radicals in the vicinity of the combustion product stream. These critical combustion reaction rates were more readily quenched in the presence of products of combustion from a stoichiometric flame, whereas they were favored by lean combustion products. As a result, stoichiometric combustion products contributed to a greater occurrence of local extinction. Furthermore, they limited the capacity of premixed reactants to ignite and of the turbulent premixed flames to stabilize. In contrast, lean and rich combustion products facilitated flame ignition and stability and reduced the rate of local extinction. The influence of the combustion product stream on the turbulent flame front was limited to a zone of approximately two millimeters from the gas mixing layer interface (GMLI) of the product stream. As a result, flame fronts that were separated from the GMLI by larger distances were unaffected by the product stream stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Final Report: Scale-up of Algal Biofuel Production Using Waste Nutrients

Renewable fuels can be more environmentally friendly than conventional fuels and can be produced locally, supporting energy independence. Liquid renewable fuels are of special interest due to their high energy density. Algae are a promising prospective feedstock for low carbon intensity liquid biofuels, due to their high productivity and potential for high lipid or carbohydrate content. Their ability to grow on wastewater and waste nutrients and on non-arable land are cost and sustainability advantages. The organic matter content of wastewater promotes mixotrophic and/or heterotrophic growth of both algae and bacteria, boosting biomass productivity further. However, economic and technologic challenges persist that prevent the scale-up of algal biofuels to commercial relevance. These challenges include algal harvesting, drying, dewatering, and the conversion of algal biomass to usable fuels (Hannon et al 2010, Dunlap and Shaw 2009, Pienkos et al. 2009). The US Department of Energy (DOE) Bioenergy Technologies Office (BETO) supports research to overcome these challenges and outlines the research and development goals for algal biofuels in their Multi-Year Program Plan (MYPP). The long-term goals of the MYPP for algal biofuels research are briefly as follows: develop the domestic ability to produce algal biofuels at a scale of 5 billion gallons per year (BGY) by 2030 and demonstrate technologies that produce biofuel intermediates from algae at a cost of $3/gallon of gasoline equivalent (GGE) by 2022 (BETO MYPP 2016). This research reported herein was funded to investigate methods of meeting an intermediate milestone of 2,500 gallons of biofuel intermediate per acre per year for a non-integrated process by improving algal productivity, harvesting efficiency, and conversion to biofuel intermediates. Use of wastewater and wastewater nutrients was a key distinguishing characteristic of this project. In pursuit of 2,500 gallons of biofuel intermediate (BFI) per acre per year, California Polytechnic State University, San Luis Obispo (Cal Poly) sought to develop the capability to produce biofuel intermediates from microalgae grown on municipal wastewater at a 20-acre algae-based wastewater treatment facility in Delhi, California (37.43° N), which includes 7 acres of raceway ponds. Coupling algal biofuel production with wastewater treatment capitalizes on the abundant waste nutrients and carbon present in wastewater and reduces use of clean water in algal biorefinery systems. In this research, the performance of the full-scale wastewater treatment plant was characterized by measuring productivity, wastewater treatment performance, hydraulic characteristics, and energy consumption. Nine 1,000-L pilot raceways with CO2 addition were used in experiments to maximize productivity. Low-cost, energy-efficient algae bioflocculation and settling were monitored. Population genetics were monitored in an attempt to correlate taxa with superior productivity and/or settling. Algae-bacterial biomass was converted to biofuel intermediates via bench-scale hydrothermal liquefaction (HTL), and the resulting fuel quality was characterized. To develop rapid strain screening capabilities, a climate simulating photobioreactor (“LEAPS”) was developed and validated against outdoor raceways. A techno-economic analysis (TEA) and a lifecycle assessment (LCA) were performed to model process economics and sustainability. The major outcomes of this research included demonstration of 33 g/m2-day annual average algal-bacterial productivity in pilot raceways, and a biofuel intermediate yield of 0.35 g intermediate/g algae biomass via HTL, for a yield of 4,100 gallons BFI per acre per year, assuming a 90% harvest efficiency and ignoring other minor losses. This exceeded the project goal of 2,500 gallons of BFI per acre per year and nearly met the 2030 program goal, highlighting the promise of integrating wastewater treatment and biofuels production. The biocrude BFI produced by the process is refined to diesel and naphtha fuels. These fuels are normalized to the energy content of gasoline (gallons gasoline equivalent, GGE, for comparison to other fuels). Results from the TEA of the this complete “well-to-wheel” process demonstrated that, at a 400-ha scale, a minimum fuel selling price (MFSP) of $12.55/GGE, which could be decreased 57% to $7.14/GGE when including revenue from coupling the biofuel production with the co-products of wastewater treatment services and low carbon fuel credits from California and Federal programs. Due mainly to the high capital costs of thickener centrifuges and hydrothermal processing equipment, the fuel cost is sensitive to scale, with significantly lower costs expected for larger farms. In this research project, significant advances were made in improving raceway algal productivity and fuel production from algae biomass, while also improving process economics. These outcomes brought the algal biofuel technology closer to being a sustainable and marketable process. The remainder of this executive summary is organized into the following six primary project tasks: (1) to optimize biomass productivity for a selected strain at Delhi, (2) to maximize algal productivity and harvesting efficiency in Delhi pilot ponds, (3) a full-scale raceway hydraulic characterization, (4) biomass processing to biofuel intermediates, and (5) scale-up engineering analysis, modeling, and planning.

09 BIOMASS FUELS↗
NASA NTRS1989

Continental shelf fish production estimation from CZCS chlorophyll data

A method for ocean fish production estimation was proposed for development. The method was to use data acquired with the Coastal Zone Color Scanner, and processed into chlorophyll concentrations by the GSFC ocean Sciences Division, in combination with fish production and primary production data acquired from different ocean areas. A linear relation exits between annual fish production and annual phytoplankton carbon production for a wide range of coastal ocean environments. The uses of several existing algorithms which relate primary production to CZCS chlorophyll data as input to the fish production regression model is proposed. A question relating phytoplankton production to CZCS chlorophyll was obtained by Eppley (1984) using chlorophyll data obtained from field samples, equivalent to chlorophyll data obtained from CZCS imagery, and primary production data obtained from ship-board observations on a wide variety of coastal and open ocean environments. This equation was modified with additional data and was successfully tested using CZCS data and field chlorophyll and phytoplankton production data obtained from northeastern North American continental shelf waters and Atlantic open ocean waters. The modified Eppley (1984) relation also estimated phytoplankton annual carbon production in the Sargasso Sea within the confidence limits of a mean value obtained from the Eppley (1984) equation for oceanic waters that provide about 90 percent of total ocean primary production. The modified Eppley production formula applied to CZCS chlorophyll data obtained from several northeastern North American coastal environments gave phytoplankton annual carbon production values similar to the values used in the fish production regression equation.

Iverson, Richard L.↗
NASA NTRS2009

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to map areas of snow that are actively melting.

Foster, James L.↗
NASA NTRS2010

Quantification of Juniperus Ashei Pollen Production for the Development of Forecasting Models

Juniperus ashei pollen is considered one of the most allergenic species of Cupressaceae in North America. Juniperus ashei is distributed throughout central Texas, Northern Mexico, the Arbuckle Mountains of south central Oklahoma, and the Ozark Mountains of northern Arkansas and southwestern Missouri. The large amount of airborne pollen that J. ashei produces affects inhabitants of cities and towns adjacent to juniper woodland areas and because juniper pollen can be transported over long distances, it affects populations that are far away. In order to create a dynamic forecast system for allergy and asthma sufferers, pollen production must be estimated. Estimation of pollen production requires the estimation of male cone production. Two locations in the Arbuckle Mountains of Oklahoma and 4 locations in the Edwards Plateau region of Texas were chosen as sampling sites. Trees were measured to determine approximate size. Male to female ratio was determined and pollen cone production was estimated using a qualitative scale from 0 to 2. Cones were counted from harvested 1/8 sections of representative trees. The representative trees were measured and approximate surface area of the tree was calculated. Using the representative tree data, the number of cones per square meter was calculated for medium production (1) and high production (2) trees. These numbers were extrapolated to calculate cone production in other trees sampled. Calibration was achieved within each location's sub-plot by counting cones on 5 branches collected from 5 sides of both high production and medium production trees. The total area sampled in each location was 0.06 hectare and total cone production varied greatly from location to location. The highest production area produced 5.8 million cones while the lowest production area produced 72,000 cones. A single representative high production tree in the Arbuckle Mountains produced 1.38 million cones. The number of trees per location was relatively uniform, but the number of high cone production trees varied greatly. Although there is great diversity in the locations making it difficult to determine which factors are most important, cone production was well correlated with certain stand characteristics including trunk diameter.

Bunderson, L. D.↗
DOE OSTI2018

Inter-Annual Precipitation Variability Decreases Switchgrass Productivity from Arid to Mesic Environments

Cellulosic biofuels are an important source of renewable biomass within the alternative energy portfolio. Switchgrass (Panicum virgatum L.), a perennial C 4 grass native to North America, is widely studied as a biofuel feedstock for its consistently high yields and minimal input requirements. The influences of precipitation amount and temporal variability on the fertilizer response of switchgrass productivity are not fully understood. Moreover, global climate models predict changes in rainfall patterns towards lower and increasingly variable soil water availability in several productive areas worldwide, which may impact net primary production of biofuel crops. We conducted a meta-analysis of aboveground net primary production of switchgrass from 48 publications encompassing 82 different locations, 11 soil types, 52 switchgrass cultivars, fertilizer inputs between 0 to 896 kg N ha –1 year –1 , and 1 to 6 years of annual productivity measures repeated on the same stand. Productivity of the lowland ecotype doubled with N rates > 131 kg N ha –1 year –1 , but upland ecotype productivity increased only by 50%. Results showed an optimum N rate of 30 to 60 kg N ha –1 year –1 for both ecotypes, after which biomass gain per unit of N added decreased. Growing season precipitation (GSPPT) and inter-annual precipitation variability (inter-PPTvar) affected both ecotypes similarly. Long-term mean annual precipitation (MAP) differentially affected lowland and upland productivity, depending on the N level. Productivity responses to MAP and GSPPT were similar for both upland and lowland ecotypes at none or low N rates. When N increased beyond 60 kg N ha –1 year –1 , lowland cultivars had a greater growth response to MAP than uplands. Productivity increased with increasing GSPPT and MAP and had a positive linear response to MAP ranging from 600 to 1200 mm year –1 . One third of the variability in switchgrass production was accounted for by inter-PPTvar. After accounting for MAP, sites with higher inter-PPTvar had lower switchgrass productivity than sites with lower inter-PPTvar. Increased inter-annual variation in precipitation reduced production of both ecotypes. As a result, predicted changes in the amount and timing of precipitation thus likely will exert greater influence on production of upland than lowland ecotypes of switchgrass.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comparing first- and second-generation bioethanol by-products from sugarcane: Impact on soil carbon and nitrogen dynamics

The first- and second-generation bioethanol by-products (bagasse and fermentation by-product, respectively) have different biochemical characteristics relating to carbon (C) and nitrogen (N) due to their production processes. To examine the impacts of fermentation by-product and bagasse on soil C and N dynamics, a 120 day laboratory incubation experiment was conducted by applying these amendments in soil at an equal carbon application rate (2.2 g C kg -1 soil). There was a significant increase in overall cumulative CO 2 -C production from amended soil compared to the control soil, though the loss was greatest in bagasse amended soil. However, δ13C-CO 2 measurements suggested that fermentation by-product addition suppressed native soil C mineralization and prompted strong negative C priming (-57%). In contrast, bagasse amendment maintained similar native soil C mineralization to control soil. Decreased microbial biomass turnover time appears to be the major driving force for increased CO 2 -C production and soil C loss following bioethanol by-product amendments. Increased mineral N production indicated net N mineralization after fermentation by-product addition, while addition of bagasse resulted in lower N availability and N immobilization. Overall, results suggested that fermentation by-product application is advantageous in maintaining native soil C stock and N mineralization compared to bagasse. Thus, in a sustainable second-generation bioethanol production system, bagasse may be used for second-generation bioethanol production and the cogenerated by-product could be used as an amendment to improve soil C stock and N availability.

09 BIOMASS FUELS↗
DOE OSTI2021

Metabolic engineering of the oleaginous yeast Yarrowia lipolytica PO1f for production of erythritol from glycerol

Abstract Background Sugar alcohols are widely used as low-calorie sweeteners in the food and pharmaceutical industries. They can also be transformed into platform chemicals. Yarrowia lipolytica , an oleaginous yeast, is a promising host for producing many sugar alcohols. In this work, we tested whether heterologous expression of a recently identified sugar alcohol phosphatase (PYP) from Saccharomyces cerevisiae would increase sugar alcohol production in Y. lipolytica . Results Y. lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica . We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). This strain was able to produce 27.5 ± 0.7 g/L erythritol from glycerol during batch growth and 58.8 ± 1.68 g/L erythritol during fed-batch growth in shake-flasks experiments. In addition, the glycerol utilization was increased by 2.5-fold. We were also able to demonstrate that this strain efficiently produces erythritol from crude glycerol, a major byproduct of the biodiesel production. Conclusions We demonstrated the application of a promising enzyme for increasing erythritol production in Y. lipolytica . We were further able to boost production by combining the expression of this enzyme with other approaches known to increase erythritol production in Y. lipolytica . This suggest that this new enzyme provides an orthogonal route for boosting production and can be stacked with existing designs known to increase sugar alcohol production in yeast such as Y. lipolytica . Collectively, this work establishes a new route for increasing sugar alcohol production and further develops Y. lipolytica as a promising host for erythritol production from cheap substrates such as glycerol.

09 BIOMASS FUELS↗
NASA NTRS2012

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Spruce, Joseph P.↗
NASA NTRS2016

Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)

The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying FT and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).

Cal/Val↗
NASA NTRS2019

A Comparison of the GPROF Algorithm Results in the 2A-CLIM and 2A Data Products

The GPROF algorithm is used to retrieve precipitation values from all the GPM mission partner radiometers (i.e. GMI, MHS, ATMS, SSMIS, AMSR2). GPM produces two precipitation retrieval products (processing at level 2) using the GPROF algorithm. One has the type designation 2A and the other the designation 2A-CLIM. As a result understanding the difference between the two products is important for using and understanding them. Both of these GPROF products use exactly the same algorithm and a-priori databases. The only difference between the two types is the ancillary products used in the initial processing step. In the case of the 2A-CLIM products, ECMWF ERA-I is used as ancillary data. In the case of the 2A products, JMA's GANAL product is used as ancillary data. This presentation will provide a comparison between the two products using zonal mean comparisons. It will provide comparisons separately for land and ocean retrievals. It will compare the GMI differences over the entire current GPM mission life. As the only difference between the two products is the ancillary information used to create them, the comparison provides an elementary sensitivity study of the variables used from the reanalysis products and their impact on the GPROF retrieval. The purpose of the presentation is to provide users with an insight into the two GPROF products and provide them key information useful when using either of the products in scientific studies. Lastly, the presentation also discusses the reasons why only the 2A-CLIM product can be produced for the 17+ years of TRMM era data products.

GPM↗
DOE OSTI2012

Product Binding Varies Dramatically between Processive and Nonprocessive Cellulase Enzymes

Cellulases hydrolyze {beta}-1,4 glycosidic linkages in cellulose, which are among the most prevalent and stable bonds in Nature. Cellulases comprise many glycoside hydrolase families and exist as processive or nonprocessive enzymes. Product inhibition negatively impacts cellulase action, but experimental measurements of product-binding constants vary significantly, and there is little consensus on the importance of this phenomenon. To provide molecular level insights into cellulase product inhibition, we examine the impact of product binding on processive and nonprocessive cellulases by calculating the binding free energy of cellobiose to the product sites of catalytic domains of processive and nonprocessive enzymes from glycoside hydrolase families 6 and 7. The results suggest that cellobiose binds to processive cellulases much more strongly than nonprocessive cellulases. We also predict that the presence of a cellodextrin bound in the reactant site of the catalytic domain, which is present during enzymatic catalysis, has no effect on product binding in nonprocessive cellulases, whereas it significantly increases product binding to processive cellulases. This difference in product binding correlates with hydrogen bonding between the substrate-side ligand and the cellobiose product in processive cellulase tunnels and the additional stabilization from the longer tunnel-forming loops. The hydrogen bonds between the substrate- and product-side ligands are disrupted by water in nonprocessive cellulase clefts, and the lack of long tunnel-forming loops results in lower affinity of the product ligand. These findings provide new insights into the large discrepancies reported for binding constants for cellulases and suggest that product inhibition will vary significantly based on the amount of productive binding for processive cellulases on cellulose.

09 BIOMASS FUELS↗