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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Chapter 4: "Waste"-to-Energy for Decarbonization - Transforming Nut Shells Into Carbon-Negative Electricity

This chapter presents a study demonstrating waste pistachio nut shells as a renewable feedstock for climate-friendly electricity generation via industrial gasification technology. The study includes biomass feedstock characterization (i.e., pistachio waste critical material attributes), process variability (i.e., bulk material handling), and overall operational reliability and conversion performance through extended testing. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) were performed to assess the economic feasibility and environmental impact of the technology to transform agricultural waste to biopower. For processing pistachio waste material, among critical material attributes, fines content in the biomass (<1/4") had the largest potential to reduce the operating time of the gasifiers due to plugging. Pelletizing fines and co-feeding them with the mixed pistachio waste increased the average feed density, feed rate, and biochar production. Compared to pine wood chips, mixed pistachio waste yielded higher biochar quantity but slightly reduced quality. In general, a systematic Quality by Design methodology is the preferred approach for designing preprocessing and material conveyance systems, where a downstream technology (end user) for the produced intermediate is specified at the outset. TEA results show that the biochar production rate and selling price had an overwhelming impact on the modeled Minimum Electricity Selling Price (MESP), which ranged from 35.5 to 39.9 cents/kWh for the cases studied (16 h/day operational basis). Moreover, LCA results show that the valorization of pistachio shells for biopower generation is a "carbon negative" process that can help decarbonize the U.S. electricity grid. The specific carbon intensity was -0.29 to -0.71 kg CO2e/kWh, compared to 0.45 kg CO2e/kWh for the average U.S. electricity mix. Biochar production from pistachio waste as a potential means for carbon sequestration was a significant driver for the LCA. The highly stable biochar permanently sequesters a considerable fraction of biochar carbon in the ground, more than enough to offset the life cycle emissions, and can be a complementary climate change mitigation strategy.

bio-char↗
NASA NTRS2021

Air Pollution Trends Measured From Terra: CO and AOD Over Industrial, Fire-prone, and Background Regions

Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend in column amounts of about −0.50 % per year between 2002 to 2018, which is a deceleration compared to analyses performed on shorter records that found −1 % per year. Aerosols are co-emitted with CO from both fires and anthropogenic sources but with a shorter lifetime than CO. A combined trend analysis of CO and aerosol optical depth (AOD) measurements from space helps to diagnose the drivers of regional differences in the CO trend. We use the long-term records of CO from the Measurements of Pollution in the Troposphere (MOPITT) and AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Other satellite instruments measuring CO in the thermal infrared, AIRS, TES, IASI, and CrIS, show consistent hemispheric CO variability and corroborate results from the trend analysis performed with MOPITT CO. Trends are examined by hemisphere and in regions for 2002 to 2018, with uncertainties quantified. The CO and AOD records are split into two sub-periods (2002 to 2010 and 2010 to 2018) in order to assess trend changes over the 16 years. We focus on four major population centers: Northeast China, North India, Europe, and Eastern USA, as well as fire-prone regions in both hemispheres. In general, CO declines faster in the first half of the record compared to the second half, while AOD trends show more variability across regions. We find evidence of the atmospheric impact of air quality management policies. The large decline in CO found over Northeast China is initially associated with an improvement in combustion efficiency, with subsequent additional air quality improvements from 2010 onwards. Industrial regions with minimal emission control measures such as North India become more globally relevant as the global CO trend weakens. We also examine the CO trends in monthly percentile values to understand seasonal implications and find that local changes in biomass burning are sufficiently strong to counteract the global downward trend in atmospheric CO, particularly in late summer.

carbon monoxide↗
NASA NTRSDate not supplied

Global Carbon Consumption Database for Wildland Fire

Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as those left wild. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have established a comprehensive global consumption database directly linked to distinct fuels within various fire danger categories. This database, featuring a spatial resolution of approximately 300 meters, builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized Fuel Characteristic Classification System (FCCS) biomass parameters. Consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. We define ‘residual burned area’ as area burning in a region that has burned on a previous day for the same fire season, and ‘new burned area’ as area burning in a region that has not recently burned. This product serves as a valuable tool when used in conjunction with burned area data to rapidly estimate the carbon consumed and released into the atmosphere. Previously, we developed a similar emissions method utilizing satellite information, in conjunction with the FCCS 30-meter United States fuelbed dataset. We implemented this approach on fires, documented during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets.

Emily Gargulinski↗
DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗
NASA NTRS2013

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

airborne scanner↗
NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event Over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗
NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS ), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗
DOE OSTI2020

Application of an Erosion Wear Model to Predict Wear of Hammer Milling Components

A workable analytical erosion model that relates critical hammermill process parameters (hammermill geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear (more specifically, change in the shape of hammers) in hammer milling operations. Results of the model were compared to experimental observations of the shape of hammers used in the INL Stage 1 Vermeer hammermill. Results showed good agreement between predicted and measured shape of the hammer, and that a quality-by-design (QbD) approach can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Rapid Measurements of Aerosol Ionic Composition and 3-10 nm Particle Size Distributions On The NASA P3 To Better Quantify Processes Affecting Aerosols Advected From East Asia

The Particle Into Liquid Sample (PILS) was deployed on the NASA P3 for airborne measurements of fine particle ionic chemical composition. The data have been quality assured and reside in the NASA data archive. We have analyzed our data to characterize the sources and atmospheric processing of fine aerosol particles advected from the region during the experiments. Fine particle water-soluble potassium was found to serve as a useful aerosol tracer for biomass smoke. Ratios of PILS potassium to sulfate are used as a means of estimating the percent contribution of biomass burning to fine particle mass in mixed plumes advecting from Asia. The high correlations between K+ and NO3(sup -) and NH4(sup +)' indicated that biomass burning was a significant source of these aerosol compounds in the region. It is noteworthy that the air mass containing the highest concentrations of fine particles recorded in all of ACE-Asia and TRACE-P appeared to be advecting from the Bejing/Tientsin urban region and also had the highest K(+), NO3(sup -) and NH4(sup +) concentrations of both studies. Based on K+/SO4(sup 2-) ratio's, we estimated that the plume was composed of approx. 60% biomass burning emissions, possibly from the use of bio-fuels in the urban regions.

Weber, Rodney J.↗
NASA NTRS2018

Improving Aquatic Plant Management in the California Sacramento-San Joaquin Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass), direct operations, and assess management impacts on plant communities. Archived satellite records going are used to review results from previous climate and management events and aide in developing long-term strategies. Modeling at local and watershed scales provides insight into land-use effects on water quality. Plant growth models informed by remote sensing are being applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments, phenology, environmental regulations, and economics in selection of management practices. Initial utilization of remote sensing tools developed for mapping of aquatic invasive weeds improved operational efficiency by focusing limited chemical use to strategic areas with high plant-control impact and incorporating mechanical harvesting when chemical use is restricted. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta, both spatial and temporal, informed by ecological understanding with the objective of improving management and assessment effectiveness.

Aquatic↗
NASA NTRSDate not supplied

Space-Based Lidar Observations of the 3D Structure of the Earth System

Lidar provides precise measurements of the three-dimensional structure of the clouds, aerosols, ocean/land/snow/ice surfaces, as well as ocean subsurface. Lidar also provides unique information about physical propertiesof particulates in the atmosphere for both radiative transfer and air quality applications.In this talk, I will present an overview of our recent studies of aerosols, clouds, ocean and snow using space-based lidar measurements (e.g., LITE, CALIPSO and ICESat-2), such as classifications of aerosols and thermodynamics phase of clouds, cloud microphysical properties, snow depths and phytoplankton biomass. I will also introduce a new concept of 3D Earth system observations with data fusion though combined active/passive remote sensing and machine learning. The new concept aims to reveal vertical structure of the aerosols/clouds/surfaces/subsurface from passive sensors by taking advantage of lidar measurements to effectively resolve the vertical structureby unscrambling the highly convoluted multi-angle, spectral and polarization information from passive sensors and apply the knowledge to a large swath where lidar measurements are not available.

Ali Omar↗
DOE OSTI2023

Global Life Cycle and Techno-Economic Assessment of Algal-Based Biofuels

Techno-economic analyses (TEAs) and life cycle assessments (LCAs) of algal biofuels often focus on locations in suboptimal latitudes for algal cultivation, which can under-represent the sustainability potential of the technology. This study identifies the optimal global productivity potential, environmental impacts, and economic viability of algal biofuels by using validated biophysical and sustainability modeling. The biophysical model simulates growth rates of Scenedesmus obliquusbased on temperature, photoinhibition, and respiration effects at 6685 global locations. Region-specific labor costs, construction factors, and tax rates allow for spatially resolved TEA, while the LCA includes regional impacts of electricity, hydrogen, and nutrient markets across ten environmental categories. The analysis identifies optimal locations for algal biofuel production in terms of environmental impacts and economic viability which are shown to follow biomass yields. Modeling results highlight the global variability of productivity with maximum yields ranging between 24.8 and 27.5 g m -2 d -1 in equatorial regions. Environmental impact results show favorable locations tracked with low-carbon electricity grids, with the well-to-wheels global warming potential (GWP) ranging from 31 to 45 g CO 2eq MJ -1 in South America and Central Africa. When including direct land use change impacts, the GWP ranged between 44 and 55 g CO 2eq MJ -1 in these high-productivity regions. Low-carbon electricity also favors air quality and eutrophication impacts. The TEA shows that minimum algal fuel prices of $\$1.89$-$\$2.15$ per liter of gasoline-equivalent are possible in southeast Asia and Venezuela. Furthermore, this discussion focuses on the challenges and opportunities to reduce fuel prices and the environmental impacts of algal biofuels in various global regions.

09 BIOMASS FUELS↗
DOE OSTI2023

Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Adsorption Thermodynamics for Process Simulation

Adsorption has rapidly evolved in recent decades and is an established separation technology extensively practiced in gas separation industries and others. However, rigorous thermodynamic modeling of multicomponent adsorption equilibrium remains elusive, and industrial practitioners rely heavily on expensive and time-consuming trial-and-error pilot studies to develop adsorption units. Here, this article highlights the need for rigorous adsorption thermodynamic models and the limitations and deficiencies of existing models such as the extended Langmuir isotherm, dual-process Langmuir isotherm, and adsorbed solution theory. It further presents a series of recent advances in the generalization of the classical Langmuir isotherm of single-component adsorption by deriving an activity coefficient model to account for the adsorbed phase adsorbate–adsorbent interactions, substituting adsorbed phase adsorbate and vacant site concentrations with activities, and extending to multicomponent competitive adsorption equilibrium, both monolayer and multilayer. Requiring a minimum set of physically meaningful model parameters, the generalized Langmuir isotherm for monolayer adsorption and the generalized Brunauer–Emmett–Teller isotherm for multilayer adsorption address various thermodynamic modeling challenges including adsorbent surface heterogeneity, isosteric enthalpies of adsorption, BET surface areas, adsorbed phase nonideality, adsorption azeotrope formation, and multilayer adsorption. Also discussed is the importance of quality adsorption data that cover sufficient temperature, pressure, and composition ranges for reliable determination of the model parameters to support adsorption process simulation, design, and optimization.

09 BIOMASS FUELS↗
DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗
NASA NTRS2020

Changing Physical Conditions and Lower and Upper Trophic Level Responses on the US Northeast Shelf

Sea surface temperature (SST), salinity, and chlorophyll concentration (CHL) have changed in the US Northeast Shelf ecosystem over recent decades. The changes in these parameters were distinctly marked by change points around the year 2012 resulting in a 0.83°C increase in SST, a 0.3 PSU increase in salinity, and decrease in CHL in excess of 0.4 mg m–3. Where temperature and salinity shifted in mean level around their respective change points, CHL declined in a more monotonic fashion. Modeled data suggest that the shift in CHL resulted in a greater contribution of pico- and nanophytoplankton and a decreased contribution of microphytoplankton to overall CHL. Complementary estimates of the contribution of different phytoplankton functional types suggest a diminished contribution of diatoms to the phytoplankton community. Hence, not only is there evidence of a decline in the overall primary production capacity of the ecosystem, but also evidence of a fundamental change in the size and quality of phytoplankton supporting food webs. Two ecosystem responses to the observed changes in SST, salinity, and CHL were analyzed. Both length and weight at age have declined for a number of species, and both measures of growth appear to be negatively associated with temperature and positively associated with CHL. Biomass of fish and macroinvertebrates has declined in recent years, with a decrease in pelagic species associated with a decrease in CHL, while the decline in demersal species was associated with an increase in temperature. Collectively, these ecosystem changes appear to be the result of the complex interactions of both thermal effects and changes at the base of the food web.

Kevin D. Friedland↗
NASA NTRS2013

Emissions Estimation from Satellite Retrievals: a Review of Current Capability

Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution.

air quality↗