A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Exploring the risks and benefits of flexibility in biodiversity offset location in a case study of migratory shorebirds

Biodiversity offsets aim to counterbalance the residual impacts of development on species and ecosystems. Guidance documents explicitly recommend that biodiversity offset actions be located close to the location of impact because of higher potential for similar ecological conditions, but allowing greater spatial flexibility has been proposed. We examined the circumstances under which offsets distant from the impact location could be more likely to achieve no net loss or provide better ecological outcomes than offsets close to the impact area. We applied a graphical model for migratory shorebirds in the East Asian–Australasian Flyway as a case study to explore the problems that arise when incorporating spatial flexibility into offset planning. Spatially flexible offsets may alleviate impacts more effectively than local offsets; however, the risks involved can be substantial. For our case study, there were inadequate data to make robust conclusions about the effectiveness and equivalence of distant habitat-based offsets for migratory shorebirds. Decisions around offset placement should be driven by the potential to achieve equivalent ecological outcomes; however, when considering more distant offsets, there is a need to evaluate the likely increased risks alongside the potential benefits. Although spatially flexible offsets have the potential to provide more cost-effective biodiversity outcomes and more cobenefits, our case study showed the difficulty of demonstrating these benefits in practice and the potential risks that need to be considered to ensure effective offset placement.     

Recycling food and agriculture by-products to mitigate climate change: a review

Food loss and waste is a major issue affecting food security, environmental pollution, producer profitability, consumer prices, and climate change. About 1.3 billion tons of food products are yearly lost globally, with China producing approximately 20 million tons of soybean dregs annually. Here, we review food and agricultural byproducts with emphasis on the strategies to convert this waste into valuable materials. Byproducts can be used for animal and plant nutrition, biogas production, food, extraction of oils and bioactive substances, and production of vinegar, wine, edible coatings and organic fertilizers. For instance, bioactive compounds represent approximately 8–20% of apple pomace, 5–17% of orange peel, 10–25% of grape seeds, 3–15% of pomegranate peel, and 2–13% of date palm seeds. Similarly, the pharmaceutical industry uses approximately 6.5% of the total output of gelatin derived from fish bones and animal skin. Animals fed with pomegranate peel and olive pomace improved the concentration of deoxyribonucleic acid and protein, the litter size, the milk yield, and nest characteristics. Biogas production amounts to 57.1% using soybean residue, 53.7% using papaya peel, and 49.1% using sugarcane bagasse.

     

Sulfonated graphene nanomaterials for membrane antifouling,pollutant removal,and production of chemicals from biomass: a review

Water pollution and the unsustainable use of fossil fuel derivatives require advanced catalytic methods to clean waters and to produce fine chemicals from modern biomass. Classical homogeneous catalysts such as sulfuric, phosphoric, and hydrochloric acid are highly corrosive and non-recyclable, whereas heterogeneous catalysts appear promising for lignocellulosic waste depolymerization, pollutant degradation, and membrane antifouling. Here, we review the use of sulfonated graphene and sulfonated graphene oxide nanomaterials for improving membranes, pollutant adsorption and degradation, depolymerization of lignocellulosic waste, liquefaction of biomass, and production of fine chemicals. We also discuss the economy of oil production from biomass. Sulfonated graphene and sulfonated graphene oxide display an unusual large theoretical specific surface area of 2630 m²/g, allowing the reactants to easily enter the internal surface of graphene nanosheets and to reach active acid sites. Sulfonated graphene oxide is hydrophobic and has hydrophilic groups, such as hydroxyl, carboxyl, and epoxy, thus creating cavities on the graphene nanosheet’s surface. The adsorption capacity approached 2.3–2.4 mmol per gram for naphthalene and 1-naphthol. Concerning membranes, we observe an improvement of hydrophilicity, salt rejection, water flux, antifouling properties, and pollutant removal. The nanomaterials can be reused several times without losing catalytic activity due to the high stability originating from the stable carbon–sulfur bond between graphene and the sulfonic group.

     

Materials,fuels, upgrading,economy, and life cycle assessment of the pyrolysis of algal and lignocellulosic biomass: a review

Climate change issues are calling for advanced methods to produce materials and fuels in a carbon–neutral and circular way. For instance, biomass pyrolysis has been intensely investigated during the last years. Here we review the pyrolysis of algal and lignocellulosic biomass with focus on pyrolysis products and mechanisms, oil upgrading, combining pyrolysis and anaerobic digestion, economy, and life cycle assessment. Products include oil, gas, and biochar. Upgrading techniques comprise hot vapor filtration, solvent addition, emulsification, esterification and transesterification, hydrotreatment, steam reforming, and the use of supercritical fluids. We examined the economic viability in terms of profitability, internal rate of return, return on investment, carbon removal service, product pricing, and net present value. We also reviewed 20 recent studies of life cycle assessment. We found that the pyrolysis method highly influenced product yield, ranging from 9.07 to 40.59% for oil, from 10.1 to 41.25% for biochar, and from 11.93 to 28.16% for syngas. Feedstock type, pyrolytic temperature, heating rate, and reaction retention time were the main factors controlling the distribution of pyrolysis products. Pyrolysis mechanisms include bond breaking, cracking, polymerization and re-polymerization, and fragmentation. Biochar from residual forestry could sequester 2.74 tons of carbon dioxide equivalent per ton biochar when applied to the soil and has thus the potential to remove 0.2–2.75 gigatons of atmospheric carbon dioxide annually. The generation of biochar and bio-oil from the pyrolysis process is estimated to be economically feasible.

     

Coupled electrochemical methods for nitrogen and phosphorus recovery from wastewater: a review

Environmental Chemistry Letters - Declining mineral resources, high fertilizer production cost and widespread eutrophication are calling for the recovery of nitrogen and phosphorus from wastewaters...     

Microwave-assisted synthesis of biodegradable and antibacterial thiophene,furan and thiazole derivatives

Environmental Chemistry Letters - The rise of bacterial resistance to common clinical antibiotics is calling for alternative techniques to synthesize antibacterial drugs with high biodegradability....     

Factors influencing property selection for conservation revolving funds

Finding sustainable ways to increase the amount of private land protected for biodiversity is challenging for many conservation organizations. In some countries, organizations use revolving‐fund programs, whereby land is purchased and then sold to conservation‐minded owners under condition they enter into a conservation covenant or easement. The sale proceeds are used to purchase, protect, and sell additional properties, incrementally increasing the amount of protected private land. Because the effectiveness of this approach relies on selecting appropriate properties, we explored factors currently considered by practitioners and how these are integrated into decision making. We conducted exploratory, semistructured interviews with managers from each of the 5 major revolving funds in Australia. Responses indicated although conservation factors are important, financial and social factors are also highly influential. A major determinant was whether the property could be resold within a reasonable period at a price that replenishes the fund. To facilitate resale, often selected properties include the potential for the construction of a dwelling. Practitioners face with clear trade‐offs between conservation, financial, amenity, and other factors in selecting properties and 3 main challenges: recovering the costs of acquisition, protection, and resale; reselling the property; and meeting conservation goals. Our findings suggest the complexity of these decisions may constrain revolving‐fund effectiveness. Drawing from participant responses, we identified potential strategies to mitigate these risks, such as providing adequate recreational space without jeopardizing ecological assets. We suggest managers could benefit from a shared‐learning and adaptive approach to property selection given the commonalities between programs. Understanding how practitioners deal with complex decisions in the implementation of revolving funds helps identify future research to improve the performance of this conservation tool.