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.     

Co-development of an integrated assessment framework to evaluate the effectiveness and impact of selected nature-based water treatment technologies in Sri Lanka,The Philippines,and Vietnam

Water quality is a critical challenge in Asia in the context of growing industrialization, urbanization, and climate change. Nature-based solutions (NbS) could play an important role in reducing urban water pollution, while generating multiple co-benefits that could make cities more liveable and resilient. In this regard, a number of pilot and demonstration projects have been set up to explore their potential across cities in Asia. Their effectiveness and impacts, however, have not been adequately documented, thus how they can be sustained, replicated and up-scaled remain poorly understood. This study aims to contribute to addressing this challenge by co-developing an integrated assessment framework and employing it to understand how existing evaluations of NbS in the region can be improved. It focuses specifically on a set of nature-based solutions that have been employed for water treatment across six cities in Southeast Asia (two in each Sri Lanka, the Philippines, and Vietnam), namely, floating wetlands, constructed wetlands and maturation ponds. The study also suggests specific methodologies for capturing a set of core indicators considered relevant for assessing the effectiveness and capturing the multi-faceted impacts of the examined NbS.     

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.

     

Livelihood vulnerability to climate change in the mountains of Northern Vietnam: comparing the Hmong and the Dzao ethnic minority populations

Environment, Development and Sustainability - Livelihoods of ethnic minority populations living in the mountains of Northern Vietnam are highly vulnerable to climate-induced natural hazards....     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Selective separation of cobalt versus nickel by split-phosphinate complexation using a phosphonium-based ionic liquid

Environmental Chemistry Letters - The rising demand of metals for batteries is calling for advanced methods to separate metallic mixtures in mineral ores and electronic waste. In particular, the...     

Design,Modelling and Assessment of Emission Scenarios Resulting from a Network of Wood Biomass Boilers

The use of wood biomass as a fuel for domestic and industrial heating systems allows for a reduction of CO₂ emissions at a global scale, but it may also result in worse local air quality conditions, due to their emissions of particulate matter. The aim of this study is to assess the actual trend of atmospheric pollution in a study area, assuming that all heating systems are replaced by small size biomass boilers linked to the buildings through district heating network. Ground level concentrations of particulate matter, emitted by different heating systems, are therefore evaluated through numerical simulations performed by means of an atmospheric dispersion model (Sirane). As a first step, we have compared the environmental impact of a woodchip boilers network with that given by the use of traditional heating systems, i.e. wood stoves and natural gas boilers. As a second step, we have analysed the impact of such a network taking into account different emission scenarios, related to different boilers operating conditions. Results show that the environmental performances of a woodchip boilers network can be optimized by combining it with other renewable sources of energy devoted to the supply of hot water. The adopted analysis methodology can be applied to other real or hypothetic punctual sources on the territory.     

Contamination status and potential release of trace metals in a mangrove forest sediment in Ho Chi Minh City,Vietnam

Can Gio district is located in the coastal area of Ho Chi Minh City, southern Vietnam. Discharge of wastewater from Ho Chi Minh City and neighboring provinces to the rivers of Can Gio has led to concerns about the accumulation of trace metals (As, Cu, Cr, Ni, Pb, and Zn) in the coastal sediments. The main objective of this study was to assess the distribution of As, Cu, Cr, Ni, Pb, and Zn in surface and core sediments and to evaluate the contamination status in relation to local background values, as well as the potential release of these selected trace metals from sediments to the water environment. Sediment characteristization, including determination of fine fraction, pH, organic matter, and major elements (Al, Fe, Ca, K, Mg, and S), was carried out to investigate which parameters affect the trace metal enrichment. Fine fraction and Al contents were found to be the controlling proxies affecting the distribution of trace metals while other sediment characteristics did not show any clear influence on trace metals’ distribution. Although As concentrations in the sediments were much higher compared to its reference value in other areas, the enrichment factor based on local background values suggests minor contamination of this element as well as for Cr, Cu, and Pb. Risk assessment suggested a medium to very high risk of Mn, Zn, and Ni under acidification. Of importance is also that trace metals in sediments were not easily mobilized by organic complexation based on their low extractabilities by ammonium-EDTA extraction.

     

High photocatalytic removal of NO gas over SnO2 nanoparticles under solar light

Environmental Chemistry Letters - Tin oxide nanoparticles (SnO2 NPs) with a diameter less than 10 nm are usually used in waste water treatment via the photocatalytic reaction. However,...     

Supervisor expediency to employee expediency: The moderating role of leader–member exchange and the mediating role of employee unethical tolerance

We utilize social learning theory to test the role‐modeling effect of supervisor expediency (i.e., a supervisor's use of unethical practices to expedite work for self‐serving purposes). In particular, we examine the relationship between supervisor expediency and employee expediency, as moderated by leader–member exchange (LMX) and mediated by employee unethical tolerance. We predict that employees are more likely to model their supervisors' expedient behaviors when their relationship is characterized by high‐LMX (a high‐quality exchange relationship that is rich in socioemotional support). Furthermore, we argue that supervisor expediency, especially when LMX is high, influences employees' attitudes of unethical tolerance, which then affects employees' expedient behaviors. Across 2 multisource field studies and a third time‐lagged field study, we found general support for our theoretical predictions. Theoretical and practical implications are discussed.