Results for “Eutrophication” — Page 4

DOE OSTI2026

AmeriFlux FLUXNET-1F US-EKN Elkhorn Slough North Marsh

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-EKN Elkhorn Slough North Marsh. This is the FLUXNET version of the carbon flux data for the site US-EKN Elkhorn Slough North Marsh produced by applying the standard ONEFlux (1F) software. Site Description - Tidally restricted and diked salt marsh. Large water-filled basin with picklweek around the edges. Algal eutrophication and anerobic signal.

Paytan, Adina [University of California, Santa Cru↗

DOE OSTI2023

LCA-based environmental sustainability assessment of hybrid additive manufacturing of a turbine blade

In this paper, a cradle-to-gate life cycle assessment (LCA) method is used to compare the overall energy consumption and environmental impact of hybrid additive manufacturing (HAM) and the traditional CNC milling process with a case study of turbine blade manufacturing. Six environmental impacts are assessed in this study: acidification potential (AP), eutrophication potential (EP), global warming potential (GWP), photochemical ozone creation potential (POCP), ozone depletion potential (ODP), and abiotic depletion potential (ADP). The results suggest that HAM can not only reduce energy consumption and material waste but also reduce the environmental impact by 53% from a life cycle perspective. Specifically, the results of GWP, AP, EP, ODP, POCP and ADP of the HAM are only 32.2%, 34.6 %, 44.7%, 27.2%, 25.6%, and 24.7 % of that in traditional CNC machining.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Comparative Life Cycle Analysis of Scalable Single-Junction and Tandem Perovskite Solar Cell (PSC) Systems

Efficient, low-cost solar cells based upon perovskites have the potential to transform the US and global energy portfolio and improve energy security if they can be manufactured in an environmentally sustainable manner. However, previous life cycle analyses (LCA) of perovskite solar cells (PSC) used lab recipes to project the environmental impact of industrial PSC production – using materials and processes that may not be representative of industrial productions due to high material waste and complex synthesis – and such studies were limited to a few single-junction technologies. Thus, the goal of this project was threefold: a) to review the most promising for industrial production single-junction and tandem PSC technologies, b) to build life-cycle materials inventories that reflect scalable production of these technologies, and c) to conduct comprehensive life-cycle analysis of these technologies and compare their environmental impact with those of established commercial technologies. In response, this project identified challenges for fabrication transitioning from laboratory to sustainable industrial production, developed life-cycle inventory (LCI) data for scaling to industrial production four promising single-junction and three tandem PSC systems and produced life-cycle-investigations using, as metrics, a complete spectrum of energy, environmental and ecological impact indicators. Special focus was given to the use of lead, silver and indium in PSC. The project used the Life Cycle Assessment (LCA) methodology as standardized by the Society of Environmental Toxicology and Chemistry (SETAC), ISO standards 14040 and 14044, and the International Energy Agency PVPS Task 12 LCA guidelines. LCA allows the calculation of a number of energy and environmental and impact categories, including energy cumulative energy demand (CED), global warming potential (GWP), human toxicity potential (HTP), eco-toxicity potential (ETP), abiotic resource depletion potential (ADP), acidification potential (AP), ozone depletion potential (ODP), photochemical oxidation potential (POP), eutrophication potential (EP). In addition to those, we calculated the Energy Pay-Back Time (EPBT) and the Energy Return On Investment (EROI). We provide LCA impacts for complete perovskite PV systems – including balance of system components – installed at three irradiation levels and considering reference and future potential module efficiencies. Finally, a sensitivity analysis on perovskite lifetime has been performed, considering 10, 20 and 30 years. Contribution analysis of the impacts of each material and layer of PSC shows, that the use of Pb in metalorganic PSC does not result in significant environmental impacts as the major contributions to environmental indicators arise from the use of Ag and encapsulation materials. Solution-based PSC manufacturing was found to be less impactful to the environment than vapor-based fabrication, and roll-to-roll (RtR) printing uses less energy and generates the lowest emissions. PSC produced with RtR manufacturing could reach the same Energy Return on Energy Investment (EROI) as that of crystalline-Si PV within 12 years of life, whereas the most energy demanding spray coating on rigid substrates, would require a 20-yr life to match the EROI of 30-yr lasting silicon PV. This work lays the foundation for sustainability investigations in a comparative context of large-scale production and deployment of PSC. The results of this project have the potential to have a significant impact on the future of PV manufacturing, by providing industry, policy-makers, and academia with insights necessary to choose which, if any, lead-based solar cell life cycles are environmentally sustainable.

14 SOLAR ENERGY↗

DOE OSTI2021

Saturated Bioenergy Buffers: Site Suitability Classification and Estimated Areas of Candidate Sites in the U.S. Midwest Under Three Scenarios

The loss of nutrients applied to tile-drained row-crop fields is a critically important component of agriculture’s impact on surface water quality, because drain tiles provide a short circuit to ditches and creeks, resulting in rapid nutrient loss. This nutrient loss ultimately advances eutrophication and hypoxia, i.e., the creation of dead zones in bodies of water, both locally and regionally (for example, in western Lake Erie and the Gulf of Mexico). Saturated buffers help address the tile-drainage water quality problem, and incorporating bioenergy crops into saturated bioenergy buffers could provide both environmental protection and an additional source of income for farmers.

09 BIOMASS FUELS↗

DOE OSTI2022

Marine Renewable Energy Applications for Restorative Ocean Farming: Kelp

Kelp farming and kelp forest restoration have both been proposed as a solution to locally decrease the impacts of ocean acidification and eutrophication, often with co-benefits to other forms of aquaculture and mariculture. Compared to global markets, the kelp industry in the United States is still in its early phases, with the first commercial kelp farm founded in Casco Bay, Maine in 2010. Since then, interest and effort in kelp production has been increasing, with farms now present in Maine, New Hampshire, Connecticut, Rhode Island, Massachusetts, New York, Washington, and Alaska. Many research projects are underway in the United States to explore benefits of 3D ocean farming, tackle logistical problems of working in the ocean, autonomous farming, and explore viable end uses for kelp products. In seaweed farming, to remove the stored carbon or excess nutrients from the system, the biomass needs to be harvested at the optimal time to avoid the release of CO 2 that comes with decomposition. Timing of the harvest is also important for maximum crop yield, which can vary based on the final product. Additional monitoring needs can include a variety of water quality metrics, growth measurements, and visuals to ensure the health of the farm, comply with permits, support operations and maintenance functions. The variables measured may vary by desired end use of the product, location of farm, and operational design. Monitoring all of these parameters requires specialized devices that can be costly and challenging to maintain. Monitoring devices often face power and logistical constraints that could prevent kelp farmers from adopting these technologies or receiving accurate, efficient monitoring to assess ecosystem benefits and valuation. Marine energy has been identified as a possible power source for these devices. This project investigates the power needs for conducting kelp farm environmental monitoring compared with the available marine energy resource to evaluate if locally generated ocean energy could provide a solution to these monitoring challenges and benefit kelp farmers. This process was structured as follows: 1. Define what data is needed for farmers and their communities through desk research and interviews with end users. 2. Identify sensors and power requirements currently in use or available for commercial purchase. 3. Analyze current kelp and other mariculture farm locations for the potential marine energy resource. 4. Analyze farm designs and associated structures to make recommendations for marine energy design. 5. Quantify value that investment in sensors could provide in terms of carbon credit possibilities.

09 BIOMASS FUELS↗

DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Decarbonization of Wastewater Treatment with Microalgae Processes.

Microalgae can contribute to the decarbonization of wastewater treatment by municipalities, industries and agriculture, by substituting sunlight for energy intensive conventional treatment processes, while capturing nutrients and carbon in the algal biomass. The carbon fixed into the algal biomass can be converted to renewable natural gas (RNG) using anaerobic digestion or into renewable diesel and sustainable aviation fuel (SAF) using hydrothermal liquefaction (HTL), with greatly reduce the carbon footprints compared to conventional fuels. Bioplastics, biofertilizers and other bioproducts from microalgae biomass also provide potential benefits in greenhouse gas (GHG) reduction and domestic supply chains. Microalgae technologies can counter eutrophication caused by harmful algal blooms by recovering nutrients, N and P, from wastewaters, and even from very low nutrient concentrations found in surface waters. CO2 is required in microalgae cultivation and wastewater treatment to support maximal rates of the photosynthesis, with the CO2 obtained from the wastes themselves, other local sources or even atmospheric CO2. Greenhouse gas mitigation with microalgae processes is based on life cycle assessments, comparing such green processes with current energy intensive wastewater treatment, and nutrient reduction technologies. Microalgae technologies are specifically relevant to smaller, often disadvantaged, communities, where currently about 5,000 algae wastewater treatment ponds are operated by public utilities with many more are operated by industries. However, many, if not most, of these pond facilities require urgent technology upgrades to achieve the potential and goals of low cost GHG mitigation and efficient nutrient recycling. MicroBio Engineering Inc. is developing and has demonstrated several technologies that combine innovative carbon mitigation and decarbonization technologies for a circular economy, with longer-term potential for large-scale biofuels and biofertilizer production.

09 BIOMASS FUELS↗

DOE OSTI2023

Decarbonization of Wastewater Treatment with Microalgae Processes.

Microalgae can contribute to the decarbonization of wastewater treatment by municipalities, industries and agriculture, by substituting sunlight for energy intensive conventional treatment processes, while capturing nutrients and carbon in the algal biomass. The carbon fixed into the algal biomass can be converted to renewable natural gas (RNG) using anaerobic digestion or into renewable diesel and sustainable aviation fuel (SAF) using hydrothermal liquefaction (HTL), with greatly reduce the carbon footprints compared to conventional fuels. Bioplastics, biofertilizers and other bioproducts from microalgae biomass also provide potential benefits in greenhouse gas (GHG) reduction and domestic supply chains. Microalgae technologies can counter eutrophication caused by harmful algal blooms by recovering nutrients, N and P, from wastewaters, and even from very low nutrient concentrations found in surface waters. CO2 is required in microalgae cultivation and wastewater treatment to support maximal rates of the photosynthesis, with the CO2 obtained from the wastes themselves, other local sources or even atmospheric CO2. Greenhouse gas mitigation with microalgae processes is based on life cycle assessments, comparing such green processes with current energy intensive wastewater treatment, and nutrient reduction technologies. Microalgae technologies are specifically relevant to smaller, often disadvantaged, communities, where currently about 5,000 algae wastewater treatment ponds are operated by public utilities with many more are operated by industries. However, many, if not most, of these pond facilities require urgent technology upgrades to achieve the potential and goals of low cost GHG mitigation and efficient nutrient recycling. MicroBio Engineering Inc. is developing and has demonstrated several technologies that combine innovative carbon mitigation and decarbonization technologies for a circular economy, with longer-term potential for large-scale biofuels and biofertilizer production.

09 BIOMASS FUELS↗

DOE OSTI2023

Decarbonization of Wastewater Treatment with Microalgae Processes.

Microalgae can contribute to the decarbonization of wastewater treatment by municipalities, industries and agriculture, by substituting sunlight for energy intensive conventional treatment processes, while capturing nutrients and carbon in the algal biomass. The carbon fixed into the algal biomass can be converted to renewable natural gas (RNG) using anaerobic digestion or into renewable diesel and sustainable aviation fuel (SAF) using hydrothermal liquefaction (HTL), with greatly reduce the carbon footprints compared to conventional fuels. Bioplastics, biofertilizers and other bioproducts from microalgae biomass also provide potential benefits in greenhouse gas (GHG) reduction and domestic supply chains. Microalgae technologies can counter eutrophication caused by harmful algal blooms by recovering nutrients, N and P, from wastewaters, and even from very low nutrient concentrations found in surface waters. CO2 is required in microalgae cultivation and wastewater treatment to support maximal rates of the photosynthesis, with the CO2 obtained from the wastes themselves, other local sources or even atmospheric CO2. Greenhouse gas mitigation with microalgae processes is based on life cycle assessments, comparing such green processes with current energy intensive wastewater treatment, and nutrient reduction technologies. Microalgae technologies are specifically relevant to smaller, often disadvantaged, communities, where currently about 5,000 algae wastewater treatment ponds are operated by public utilities with many more are operated by industries. However, many, if not most, of these pond facilities require urgent technology upgrades to achieve the potential and goals of low cost GHG mitigation and efficient nutrient recycling. MicroBio Engineering Inc. is developing and has demonstrated several technologies that combine innovative carbon mitigation and decarbonization technologies for a circular economy, with longer-term potential for large-scale biofuels and biofertilizer production.

09 BIOMASS FUELS↗

DOE OSTI2023

Genomes to ecosystem function: Targeting critical knowledge gaps in methanogenesis and translation to updated global biogeochemical models

Natural freshwater temperate wetland systems currently represent the largest natural source of atmospheric methane, but are relatively understudied using systems biology tools (e.g. meta-omics) compared to other high producing methane systems (e.g. peat, tropical, or reconstructed wetlands). Using field investigations at the NOAA operated sentinel site on Lake Erie, methane producing activities and responses to geochemical conditions will be determined along seasonal and spatial gradients (Objective 1). Here, a combination of high-throughput activity and gas measurements, combined with high-resolution systems biology and analytical methods, will provide in depth knowledge of the microbiological, chemical, and physical constraints on methane production in wetlands. Using laboratory microcosms, the formation of anoxic microsites and their capacity to facilitate methane production in wetland soils will be simulated (Objective 2). This objective will validate the findings from the field investigations, offering a more controlled environment for teasing out the role of different yet interrelated variables. Lastly, these field and laboratory data will be used for multi-scale, process-level evaluation of an ecosystem biogeochemical model that accommodates these newly identified processes and parameterizes representation of these processes along relevant environmental gradients (Objective 3).This research will identify multiple interacting geochemical, ecological, and metabolic constraints that are poorly understood, oversimplified, or missing in global biogeochemical methane models. This proposal targets the role of oxygen limitation on methane processes in soil domains, to improve reactive transport models of microbial carbon cycling across terrestrial-aquatic soils and generate data on nutrient cycling activities in Great Lake wetlands. This information could provide new insights into the microbial controllers of Lake Erie eutrophication.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Optimizing cost-effective and benchmarked industry standards to quantify nutrient bioextraction by seaweed

Interest in the utility of seaweed farms to mitigate coastal eutrophication, or nutrient loading, has grown commensurate with the recent rise of the farmed seaweed industry in the U.S. But economic valuation of this ecosystem service remains elusive in part because of challenges in quantifying this spatiotemporally variable biological process with reproducible and comparable metrics. Regulatory bodies that permit wastewater discharge or lease area for aquaculture farms require water quality testing and reporting of dissolved total nitrogen (N) in nearshore marine environments. These metrics must meet EPA standards for testing and reporting (e.g., Total Kjeldahl Nitrogen - TKN). However, these metrics are inherently highly variable over space and time in dynamic nearshore systems, and expensive to evaluate with sufficient breadth to constrain this variance, creating a critical bottleneck to direct quantification of farmed seaweed net uptake rates in situ.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Mitigation of Acute Ammonia Emissions With Biochar During Swine Manure Agitation Before Pump-Out: Proof-of-the-Concept

Ammonia (NH 3 ) emissions from animal agriculture can cause eutrophication of water ecosystems and are precursors to secondary particulate matter (PM 2 .5 ). NH 3 emissions from stored swine manure represent nutrient loss affecting the fertilizing value of manure. The short-term emission bursts occur when farmers agitate manure before emptying storage and fertilizing fields. There is no proven technology to mitigate gaseous emissions during agitation, while the hazards of acute releases (e.g., H 2 S) are well-known. Biochar mitigates NH 3 emissions from manure over the long-term. The objective of this research was to evaluate the mitigation of acute NH 3 emissions during/after agitation. Two biochars, highly alkaline and porous (HAP from corn stover) and red oak (RO), were tested. The 6 and 12 mm-thick layers of biochar powder were surficial applied followed by 3 min agitation. NH 3 concentrations were measured before/during/after agitation. Mitigation was assessed by comparing: (i) the maximum (peak) flux, (ii) total emission (from agitation start till NH 3 concentration returned to the before-agitation), and (iii) the total emissions during agitation. The 12 mm HAP significantly ( p < 0.05) reduced (i–iii) by 63, 70, and 85%, respectively. The 6 mm HAP significantly reduced (i–iii) by 76, 75, and 78%, respectively. The 12 mm RO significantly reduced (i–iii) by 9, 53, and 57%, respectively. The 6 mm RO significantly reduced (i–iii) by 61, 86, and 63%, respectively. The NH 3 emission kinetics model confirmed that a 6 mm dose was just as effective as the larger dose. More research is needed to optimize and scale-up mitigating emissions and retention of nutrients in manure with biochar.

Chen, Baitong↗

DOE OSTI2023

Comparing the response of the indigenous microbial community to crude oil amendment in oxic versus hypoxic conditions

The Caspian Sea is the world’s largest landlocked saline lake which lies between Europe and Asia. This region is particularly known for its large-scale oil reserves, pipelines, and drilling activities, which have contributed to the environmental decline of this lake. In addition to pollution from the petroleum industry, drainage from various river basins brings an influx of residential, industrial, and agricultural effluents that induce eutrophication and hypoxic conditions in deeper, colder waters, creating an oxygen gradient. The temperature and oxygen stratification in this environment has presented a unique opportunity to investigate the potential of the biodegradative processes carried out by the indigenous microbial community. We believe these indigenous microbes possess different metabolic capabilities to degrade oil as they adapted to declining oxygen concentrations and temperatures with increasing depths over a prolonged period. Hence, community structure and composition will vary with depth. Microcosms were set up to observe the indigenous microbial reaction after a 60 ppm native crude oil amendment over 115 days. Surface water microcosms were incubated at 28ºC and aerated while deep water microcosms were incubated at 8ºC under anaerobic conditions. These two environmental conditions represent the temperature and oxygen extremes along the gradient and were selected as we try to simulate the indigenous community’s response to this oil contamination. DNA was extracted and amplified from these microcosms and sequenced. Bioinformatic analysis was performed to track changes in the abundance of taxa present and biodiversity over different time points to show the progression of community structure. All microcosms showed the presence of hydrocarbon-degrading phyla, whose presence is consistent with other reports from oil-enriched environments. However, distinct communities were observed in oxic versus hypoxic microcosms. Orders of Bacteria related to sulfate and nitrogen cycling were found in hypoxic microcosms, indicating a possible mechanism for the anaerobic biodegradation of crude oil. GC-MS analysis of initial and final microcosms also provided evidence of degradation of hydrocarbon fractions in both warm, oxic and cold, hypoxic conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Native Microalgae-Bacteria Consortia: A Sustainable Approach for Effective Urban Wastewater Bioremediation and Disinfection

Urban wastewater is a significant by-product of human activities. Conventional urban wastewater treatment plants have limitations in their treatment, mainly concerning the low removal efficiency of conventional and emerging contaminants. Discharged wastewater also contains harmful microorganisms, posing risks to public health, especially by spreading antibiotic-resistant bacteria and genes. Therefore, this study assesses the potential of a native microalgae-bacteria system (MBS) for urban wastewater bioremediation and disinfection, targeting NH4+-N and PO43−-P removal, coliform reduction, and antibiotic resistance gene mitigation. The MBS showed promising results, including a high specific growth rate (0.651 ± 0.155 d−1) and a significant average removal rate of NH4+-N and PO43−-P (9.05 ± 1.24 mg L−1 d−1 and 0.79 ± 0.06 mg L−1 d−1, respectively). Microalgae-induced pH increase rapidly reduces coliforms (r > 0.9), including Escherichia coli, within 3 to 6 days. Notably, the prevalence of intI1 and the antibiotic resistance genes sul1 and blaTEM are significantly diminished, presenting the MBS as a sustainable approach for tertiary wastewater treatment to combat eutrophication and reduce waterborne disease risks and antibiotic resistance spread.

Sousa, Joana F.↗

DOE OSTI2023

A Comparison of Multiple Macroalgae Cultivation Systems and End-Use Strategies of Saccharina latissima and Gracilaria tikvahiae Based on Techno-Economic Analysis and Life Cycle Assessment

Macroalgae can be processed into various products with the potential to substitute land-based crops; their cultivation can bioextract nutrients from coastal waters. This study investigated the economic cost and environmental impacts of multiple seaweed cultivation platforms, cultivation strategies, and processing/end-use strategies through techno-economic analysis (TEA) and life cycle assessment (LCA) with a focus on Saccharina latissima and Gracilaria tikvahiae. Cultivation platforms included single-layer longline, dual-layer longline, single-layer strip, and dual-layer strip systems. Processing/end-use products included seaweed to biofuel, dried sea vegetables, marketable commercial fertilizer, and animal feed. Economic and environmental costs decreased with dual-layer and strip cultivation systems. Cultivation costs were highest using the common single-layer longline system ($4.44 kg−1 dry weight (dw) S. latissima and $6.73 kg−1 dw G. tikvahiae when cultivated on rotation). The use of the dual-layer strip system reduced cultivation costs to $2.19 kg−1 dw for S. latissima and $3.43 kg−1 dw for G. tikvahiae. Seaweed drying was the major contributor to economic and environmental costs for macroalgae processing. Yet, all scenarios achieved environmental benefits for marine eutrophication. The best environmental performance was observed when biomass was processed to dry sea vegetables, assuming the offset of land-based vegetable production, or used as biofeedstock for anaerobic digestion for combined heat and power.

Wu, Jingjing (ORCID:0000000305311353)↗

DOE OSTI2024

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗