ALBERT

Description: In recent years, the rapid increase in CO2 concentration has accelerated global warming. As a result, sea levels rise, glaciers melt, extreme weather occurs, and species become extinct. As the world’s largest CO2 emission rights trading market, EU Emissions Trading System (EU-ETS) has reached 1.855 billion tons of quotas by 2019, influencing the development of the global carbon emission market. Crude oil, as one of the major fossil energy sources in the world, its price fluctuation is bound to affect the price of carbon emission rights. Therefore, this paper aims to reveal the correlation between crude oil futures prices and carbon emission rights futures prices by studying the price fluctuation. In this paper, the linkage between West Texas Intermediate (WTI) crude oil futures prices and European carbon futures prices was investigated. In addition, this paper selects continuous data of WTI crude oil futures prices and spot prices with European carbon futures prices from January 8, 2018 to November 27, 2020, and builds a smooth transformation regression (STR) model. The relationship between crude oil futures and carbon futures prices is studied in both forward and reversal linkage through empirical analysis. The results show that crude oil futures prices and carbon futures prices have a mutual effect on each other, and both linear and nonlinear correlations between the two prices exist. Based on the results of this research, some suggestions are provided.

Description: We present a high-efficiency method for simulating seawater intrusion (SWI), with mixing, in confined coastal aquifers based on uncoupled equations in the through-flow region of the aquifer. The flow field is calculated analytically and the tracer transport numerically, via spatial splitting along the principal directions (PD) of transport. Advection-dispersion processes along streamlines are simulated with the very efficient matched artificial dispersivity (MAD) method of Syriopoulou and Koussis and the system of discretized transverse-dispersion equations is solved with the Thomas algorithm. These concepts are embedded in the 2D-MADPD-SWI model, yielding comparable solutions to those of the uncoupled SWI equations with the state-of-the-art FEFLOW code, but faster, while 2D-MADPD-SWI achieves an at least hundredfold faster solution than a variable-density flow model. We demonstrate the utility of the 2D-MADPD-SWI model in stochastic Monte Carlo simulations by assessing the uncertainty on the advance of the 1,500 ppm TDS line (limit of tolerable salinity for irrigation) due to randomly variable hydraulic conductivity and freshwater flow rate.

Description: Wastewater stabilization ponds (WSPs) are commonly used to treat municipal wastewater in the Canadian Arctic. Bacterial community structure and functionality remain mostly uncharacterized for arctic WSPs, yet are presumed important for treatment outcomes during the 3-month summer treatment season with open water in the WSPs. The objective of this study was to investigate treatment performance and related temporal and spatial changes in the structure and putative function of bacterial communities during treatment of municipal wastewater in the WSPs of Pond Inlet and Clyde River, Nunavut over two consecutive summer treatment seasons. Influent raw wastewater contained a high organic load and large bacterial communities (~9 log 16S rRNA copies/mL) belonging mainly to Proteobacteria. Although designed to be facultative ponds, both WSPs remained anaerobic with neutral pH values (7.5–7.8) throughout the summer treatment season. Water quality data showed that nutrients [measured as carbonaceous biological oxygen demand (CBOD5)], total suspended solids, and total ammonia nitrogen were progressively reduced during treatment in the ponds as the summer progressed. The pond bacterial population size and species richness depended on the pond temperature (2–18°C), with 8.5 log 16S rRNA copies/mL and the largest alpha diversities (Shannon-Wiener index of 4-4.5) observed mid-season (late July). While the phylogenetic beta diversity in raw wastewater from the two locations remained similar, pond bacterial communities underwent significant (p 〈 0.05) changes to dominance of Comamonadaceae, Geobacteracea, and Porphyromonadaceae. Multivariate distance based redundancy analysis and predicted gene functionalities in the microbiota agreed with water quality results that microbial removal of nutrients (e.g., CBOD5) peaked in the middle of the summer coinciding with the treatment period with the highest pond temperatures. Information from this study will be useful for further development of models to predict biological treatment outcomes, which could be used to size and assess the feasibility of WSPs in extreme climates. Higher pond temperatures resulted in optimal biological processes and nutrient removal in the middle of the summer. While it is challenging to control environmental factors in a passive wastewater treatment system there are some design considerations that could be used to optimize temperature regimes, such as the depth of the pond.

Description: Occurrences and exposure to high levels of microbial bioaerosols such as pathogenic bacteria, fungi, fungal spores, and viruses can be linked to the deterioration of the environment and public health. This study aimed to review the results available for the unusual bioaerosol distribution scenario in the Asian regions. The amount of bioaerosol load and their environmental behavior in the atmosphere is heavily influenced by air pollution such as haze, fog, dust, and particulate matter (PM) and thus strongly affect the air quality index (AQI). Human factors such as heavy traffic, overcrowds, and biomass burning also affected the prevalence or occurrences of bioaerosols in the atmosphere. Seasonal/temporal and diurnal variation was significantly observed from these studies and in the case of South Asia, post-monsoon and winter months were incredibly concentrated with pathogenic bioaerosols. Many human infections, for example, pneumonia, tuberculosis, brucellosis, anthrax, and query fever (Q-fever), are linked to pathogenic bacterial bioaerosols. Respiratory diseases such as asthma and chronic pulmonary obstructiveness are related to fungal bioaerosols, spores, and viral infections. To facilitate the testing and monitoring appraisal of airborne bioaerosols, artificial intelligence, deep neural networks, and machine learning can be used to develop real-time PCR-based bioaerosol sensors. Moreover, mobile apps and compatible electronic gadgets can be developed for the city dwellers to real-time monitor the concentration of bioaerosols in the air they are breathing.

Description: In the context of the energy crisis and environmental deterioration, the integrated energy system (IES) based on multi-energy complementarity and cascaded utilization of energy is considered as an effective way to solve these problems. Due to the different energy forms and the various characteristics in the IES, the coupling relationships among various energy forms are complicated which enlarges the difficulty of energy efficiency evaluation of the IES. In order to flexibly analyze the energy efficiency of the IES, an operation efficiency evaluation model for the IES is established. First, energy utilization efficiency (EUE) and exergy efficiency (EXE) are proposed based on the first/second law of thermodynamics. Second, the energy efficiency models for five processes and four subsystems of the IES are formed. Lastly, an actual commercial-industrial park with integrated energy is employed to validate the proposed method.

Description: This paper investigates the thermophysical properties and heat transfer performance of graphene nanoplatelet (GNP) and alumina hybrid nanofluids at different mixing ratios. The electrical conductivity and viscosity of the nanofluids were obtained at temperatures between 15–55°C. The thermal conductivity was measured at temperatures between 20–40°C. The natural convection properties, including Nusselt number, Rayleigh number, and heat transfer coefficient, were experimentally obtained at different temperature gradients (20, 25, 30, and 35°C) in a rectangular cavity. The Mouromtseff number was used to theoretically estimate all the nanofluids’ forced convective performance at temperatures between 20–40°C. The results indicated that the thermal conductivity and viscosity of water are increased with the hybrid nanomaterial. On the other hand, the viscosity and thermal conductivity of the hybrid nanofluids are lesser than that of mono-GNP nanofluids. Notwithstanding, of all the hybrid nanofluids, GNP-alumina hybrid nanofluid with a mixing ratio of 50:50 and 75:25 were found to have the highest thermal conductivity and viscosity, enhancing thermal conductivity by 4.23% and increasing viscosity by 15.79%, compared to water. Further, the addition of the hybrid nanomaterials improved the natural convective performance of water while it deteriorates with mono-GNP. The maximum augmentation of 6.44 and 10.48% were obtained for Nuaverage and haverage of GNP-Alumina (50:50) hybrid nanofluid compared to water, respectively. This study shows that hybrid nanofluids are more effective for heat transfer than water and mono-GNP nanofluid.

Description: The ongoing urbanization requires enhanced understanding of the local meteorological and climatological conditions within the urban environment for multiple applications, concerning energy demand, human health, and spatial planning. Identifying areas with harmful meteorological conditions enables citizens and local authorities to take actions to optimize quality of life for urban dwellers. At the moment cities have (in general) limited networks of meteorological monitoring stations. To overcome this lack of observations, the use of non-traditional data sources is rapidly increasing. However, the use of such data sources without enough prior verification has become a controversial topic in the scientific community. This study aims to verify and assess one of the main non-traditional data sources, i.e. smartphones. The goal is to research the potential of smartphones (using the Samsung Galaxy S4 as an example phone model) to correctly sense air temperature, relative humidity, and solar radiation, and to determine to what extent environmental conditions negatively affect their performance. The smartphone readings were evaluated against observations from reference instrumentation at a weather station and a mobile measurement platform. We test the response time of the smartphone thermometer and hygrometer, and the light sensor’s cosine response. In a lab setting, we find that a smartphone can provide reliable temperature information when it is not exposed to direct solar radiation. The smartphone’s hygrometer performs better at low relative humidity levels while it can over-saturate at higher levels. The light sensor records show substantial correlation with global radiation observations, and short response times. Measurements along an urban transect of 10 km show the smartphone’s ability to react to fast changes of temperature in the field, both in time and space. However, a bias correction (dependent on wind speed and radiation) is required to represent the reference temperature. Finally we show that after such a bias correction, a smartphone record can successfully capture spatial variability over a transect as well.

Description: Global food and water insecurity could be serious problems in the upcoming decades with growing demands from the increasing global population and more frequent effect of climatic extremes. As the available water resources are diminishing and facing continuous stress, it is crucial to monitor water demand and water availability to understand the associated water stresses. This study assessed the water stress by applying the water supply stress index (WaSSI) in relation to green (WaSSIG) and blue (WaSSIB) water resources across six major cropland basins including the Mississippi (North America), San Francisco (South America), Nile (Africa), Danube (Europe), Ganges-Brahmaputra (Asia), and Murray-Darling (Australia) for the past 17-years (2003–2019). The WaSSIG and WaSSIB results indicated that the Murray-Darling Basin experienced the most severe (maximum WaSSIG and WaSSIB anomalies) green and blue water stresses and the Mississippi Basin had the least. All basins had both green and blue water stresses for at least 35% (6 out of 17 years) of the study period. The interannual variations in green water stress were driven by both crop water demand and green water supply, whereas the blue water stress variations were primarily driven by blue water supply. The WaSSIG and WaSSIB provided a better understanding of water stress (blue or green) and their drivers (demand or supply driven) across cropland basins. This information can be useful for basin-specific resource mobilization and interventions to ensure food and water security.

Description: This study evaluated the agricultural eco-efficiency (AEE) of 77 counties and districts in Jiangsu Province from 1999 to 2018 using the slack-based measure (SBM) of efficiency in data envelopment analysis (DEA) (SBM-DEA) and analyzed its spatiotemporal evolution characteristics and influencing factors. We found that 1) the overall AEE, pure technology efficiency (PTE), and scale efficiency (SE) exhibited a fluctuating downward trend. AEE exhibited a significantly positive spatial association and an increasingly widening regional inequality. 2) AEE featured the “high south” and “low north” spatial pattern, with the high-value regions concentrated around the Taihu Lake plain region in southern Jiangsu Province (Sunan) and low-value regions scattered across most of the northern Jiangsu Province (Subei) cities. The high-high and low-low spatial association types further confirmed the existence of the north–south agglomeration pattern. 3) PTE and SE exhibited a similar “high south” and “low north” spatial pattern to that of AEE. The areas with the growth trends of AEE, PTE, and SE were clustered in Xuzhou and Nanjing city and in the bordering regions between Yangzhou and the Huai’an city, and also between Changzhou and the Wuxi city. 4) Excessive redundant input and use of pesticides, chemical fertilizers, agricultural diesel, labor, land, and agricultural carbon emissions, all have been the primary factors affecting Jiangsu’s AEE. Irrigation also considerably affected AEE, while mechanical power and agricultural film have minimal effects. The majority of counties and districts in the Subei, central Jiangsu Province (Suzhong), and Ningzhen Yang Hilly region experienced excessive usage of chemical fertilizers, pesticides, chemical fertilizers, agricultural diesel, labor, and land. The findings can improve understanding of the spatial association effect and underlying impediment of AEE and can further help policymakers promoting agricultural eco-efficiency.

Description: Water-soluble species constitute a significant fraction (up to 60–70%) of the total aerosol loading in the marine atmospheric boundary layer (MABL). The “indirect” effects, that is, climate forcing due to modification of cloud properties depend on the water-soluble composition of aerosols. Thus, the characterization of aerosols over the MABL is of greater relevance. Here, we present 1-year long aerosol chemical composition data of PM10 and PM2.5 at a costal location in the northeastern Arabian Sea (Goa; 15.45°N, 73.20°E, 56 m above the sea level). Average water-soluble ionic concentration (sum of anion and cation) is highest (25.5 ± 6.9 and 19.6 ± 5.8 μg·m−3 for PM10 and PM2.5, respectively) during winter season and lowest during post-monsoon (17.3 ± 9.1 and 14.4 ± 8.1 μg·m−3 for PM10 and PM2.5, respectively). Among water-soluble ionic spices, SO42- ion was found to be dominant species in anions and NH4+ is dominant in cations, for both PM10 and PM2.5 during all the seasons. These observations clearly hint to the contribution from anthropogenic emission and significant secondary inorganic species formation. Sea-salt (calculated based on Na+ and Cl−) concentration shows significant temporal variability with highest contribution during summer seasons in both fractions. Sea-salt corrected Ca2+, an indicator of mineral dust is found mostly during summer months, particularly in PM10 samples, indicates contribution from mineral dust emissions from arid/semiarid regions located in the north/northwestern India and southwest Asia. These observations are corroborated with back-trajectory analyses, wherein air parcels were found to derive from the desert area in summer and Indo-Gangetic Plains (a hot spot for anthropogenic emissions) during winter. In addition, we also observe the presence of nss-K+ (sea-salt corrected), for PM2.5, particularly during winter months, indicating influence of biomass burning emissions. The impact on aerosol chemistry is further assessed based on chloride depletion. Chloride depletion is observed very significant during post-monsoon months (October and November), wherein more than 80 up to 100% depletion is found, mediated by excess sulfates highlighting the role of secondary species in atmospheric chemistry. Regional scale characterization of atmospheric aerosols is important for their better parameterization in chemical transport model and estimation of radiative forcing.

Description: Large-scale disturbances such as ice storms may increase in frequency and intensity as climate changes. While disturbances are a natural component of forest ecosystems, climatically driven alteration to historical patterns may impart fundamental change to ecosystem function. At Hubbard Brook Experimental Forest, NH, experimental ice storms of varying severity were applied to replicate plots of mature northern hardwoods to quantify their effects on forested ecosystems. We assessed ice storm treatment effects on insectivorous foliage-gleaning birds and evaluated insectivore predation on model caterpillars in the understory vegetation. These birds are charismatic, of conservation concern, and are major predators of caterpillars. In turn, lepidopterans are the dominant herbivores in temperate forests and are integral to ecosystem function. We predicted that avian abundance would increase due to additional structural heterogeneity caused by ice treatments, with a concomitant increase in caterpillar predation. Point counts were used to measure insectivorous bird activity in the ice storm experiment plots and additional control plots before and after treatments. We deployed and retrieved plasticine model caterpillars and estimated predation from characteristic marks to these surrogates. Abundance of foliage-gleaning birds was higher in the ice storm plots and birds responded to treatments as a single diffuse disturbance rather than on an individual plot level. All species except one were observed both before and after the ice treatments. Surprisingly, predation on caterpillar models was unaffected by ice storm treatments but rather was a function of caterpillar density. The increase in avian abundance in the ice storm treatment plots corroborates other studies of bird responses to relatively small-scale disturbances in forests and the limited change in species composition was expected given the plot size. We conclude that ice storms may provide beneficial changes for foliage-gleaning birds in the growing season following the disturbance.

Description: Strategies for the use of amendments on agricultural soils are needed to help build resilience against potential soil threats. Gypsum is commonly applied to improve soil quality and nutrient supply. However, the sustainability and environmental safety of some gypsum sources is uncertain. This study aims to i. characterize a new by-product, lacto-gypsum, derived from a dairy whey side stream over a 1 year pilot production cycle and ii. assess the temporal variability of the raw form of lacto-gypsum and the stability of its physico-chemical and compositional properties when stored under three potential storage regimes. Results showed that lacto-gypsum compares favorably with conventional equivalents in terms of nutrient and trace element concentrations and represents an environmentally safe material free of contaminants. Storage form did not affect its main physico-chemical characteristics over time and the raw lacto-gypsum remained stable up to 20 days when stored at 4°C. In contrast to conventional gypsum, the lacto-gypsum had very low pH. In general this new lacto-gypsum shows potential as a suitable product for use as a soil amendment or as an acidification agent for animal slurry to reduce ammonia gas emissions during storage. However, further evaluation of this by-product in real life scenarios is required.

Description: With the fossil energy crisis and environmental pollution, wind energy and other renewable energy have been booming. However, the strong intermittence and volatility of wind power make difficult of its integration into grid. To solve this problem, this study proposes a complementary power generation model of wind-hydropower-pumped storage systems, which uses hydropower and pumped storage to adjust the fluctuation of wind power. How to consider the uncertainty and unpredictability of wind power output and make more reliable hydropower generation plan and pumped storage generation plan is the key problem to be solved in the grid with the high proportion of renewable energy. The martingale model of forecast evolution is used to describe the uncertainty evolution of wind power in different regions. According to the flexible load in the region, the flexibility index is used to quantify flexibility, and the transaction price is set to be proportional to flexibility. The two-stage framework of day-ahead and real-time dispatching model is then developed. In the day-ahead stage, different regions trade with each other. If the power after trading is imbalanced, it will be supplemented by hydropower and the grid to meet the power demand. In the real-time stage, the pumped storage is added to quickly balance the deviation of wind power and load between the real-time and day-ahead stages. Finally, considering the positive effect of hydropower on wind power consumption in the grid, a benefit allocation method based on improved Shapley value method is proposed. Test cases are simulated to verify the rationality of the proposed dispatching model and the benefit allocation method. After the cooperation of hydropower and pumped storage, the average revenue growth is 3.02%. The improved benefit allocation scheme makes more benefit of hydropower and pumped storage and promotes the cooperation of multi-participants.

Description: The development of efficient and cost-effective solar photocatalysts capable of producing hydrogen from formic acid as a hydrogen storage medium is still a challenging issue. Herein, we report that iron minerals, ferric iron hydroxy sulfates (FHS), immobilized on a natural layered silicate, magadiite, can be used as a photocatalyst to produce hydrogen from formic acid under irradiation with solar simulator. The material exhibits the hydrogen production rate of 470 μmol g−1 h−1, which is considerably higher than that obtained on other iron minerals and comparable to that obtained on precious metal-based photocatalyst ever reported. The present result may open a way to design efficient photocatalyst for hydrogen production from formic acid in an economically and environmentally friendly way.

Description: Our research aims to analyze how the uncertainties and risks of the overseas oil & gas investment environment change over time and reveal the specific occurrence probabilities of risk on different levels. In the process of long-drawn overseas oil & gas investment that can last for 30 years or longer, it is difficult for investment decision-makers to grasp the occurrence probabilities and trends of some specific risks accurately and in a timely manner. The overseas risk assessment system has made great progress; however, it has remained elusive due to the challenge of too many complex and interweaved factors. With the advent of big data and artificial intelligence, more precise and specific risk evaluations can be conducted. Our research selects 25 indicators from six dimensions and applies a Cloud parameter Bayesian network algorithm to dynamically assess the oil and gas overseas investment risk of 10 countries. The results reveal how risk dynamics have changed over the past two decades. Our research may serve as a reference in future overseas oil & gas investment risk decision-making, and is also significant to outbound investing, engineering, and service projects. The proper use of risk assessment results can be conducive to potential investors who may invest in potential countries in the future.

Description: This study constructed a comprehensive index system and employed a coupling coordination degree model, global spatial autocorrelation models, and local spatial autocorrelation models to quantitatively investigate the spatiotemporal characteristics and dynamic mechanism of the coupling coordination relationship between green urbanization and green finance in China during 2010–2017. The results showed that the level of green urbanization and green finance improved over the study period, but the development of green finance lagged behind the pace of green urbanization and the comprehensive score was still low. The coupling coordination degree presented a trend of continuous optimization, with coordination in eastern China being clearly higher than in central, western, and northeastern China. Furthermore, there was both spatial dependency and spatial heterogeneity in the coupling coordination degree between green urbanization and green finance. Provinces with a high-high clustering mode were mainly distributed in the eastern region, while provinces in western and northeastern China mainly had a low-low clustering mode in 2010. The high-high clustering mode gradually expanded from eastern to central China, while most provinces in western and northeastern China still exhibited low-low clustering in 2017. This indicates that the coupling coordination degree between green urbanization and green finance had strong spatial agglomeration and spatial spillover effects in central and eastern China, while in western and northeastern China its development was still poor.

Description: This work presents an optimized probabilistic modeling methodology that facilitates the modeling of photovoltaic (PV) modules with measured data over a range of environmental conditions. The method applies cuckoo search to optimize kernel parameters, followed by electrical characteristics estimation via relevance vector machine. Unlike analytical modeling techniques, the proposed cuckoo search-relevance vector machine (CS-RVM) takes advantages of no required knowledge of internal PV parameters, more accurate estimation capability and less computational effort. A comparative study has been done among the electrical characteristics predicted by back-propagation neural network (BPNN), radial basis function neural network (RBFNN), support vector machine (SVM), Villalva's model, relevance vector machine (RVM), and the CS-RVM. Experimental results show that the proposed CS-RVM provides the best prediction in most scenarios.

Description: LixFePO4 orthophosphates and fluorite- and pyrochlore-type zirconate materials are widely considered as functional compounds in energy storage devices, either as electrode or solid state electrolyte. These ceramic materials show enhanced cation exchange and anion conductivity properties that makes them attractive for various energy applications. In this contribution we discuss thermodynamic properties of LixFePO4 and yttria-stabilized zirconia compounds, including formation enthalpies, stability, and solubility limits. We found that at ambient conditions LixFePO4 has a large miscibility gap, which is consistent with existing experimental evidence. We show that cubic zirconia becomes stabilized with Y content of ~8%, which is in line with experimental observations. The computed activation energy of 0.92eV and ionic conductivity for oxygen diffusion in yttria-stabilized zirconia are also in line with the measured data, which shows that atomistic modeling can be applied for accurate prediction of key materials properties. We discuss these results with the existing simulation-based data on these materials produced by our group over the last decade. Last, but not least, we discuss similarities of the considered compounds in considering them as materials for energy storage and radiation damage resistant matrices for immobilization of radionuclides.

Description: Revegetation is regarded as an effective means to improve the ecological environment in deserts and profoundly influences the potential ecological functions of the soil fungal community. Therefore, Illumina high-throughput sequencing was performed to characterize the soil fungal diversity and community composition at two soil depths (0–10 cm and 10–20 cm) with four revegetation durations (natural grassland, half-mature, nearly mature, and mature Pinus. sylvestris var. mongolica plantations) in the Mu Us Sandy Land, China. The effects of soil properties on soil fungal communities were also examined to reveal the connection between fungal function and soil environment. The results indicated that 1) soil nutrient content and enzyme activity showed significant differences through the restoration durations, 2) there was no significant effect of soil depth on soil fungal diversity, while the Shannon diversity index of all fungal communities was significantly different among different revegetation durations, 3) compared with grassland, ectomycorrhizal fungi (notably, Inocybe, Tuber, and Calostoma) were abundant in plantations. The endophyte fungus Mortierella was among the top 10 genera in all soil samples and arbuscular mycorrhizal fungus Diversispora was the indicator genus of the grassland, and 4) catalase and total nitrogen were the main factors affecting fungal community composition and were closely related to saprotrophs and pathotrophs, respectively. This new information indicates the variation of soil fungal communities along revegetation durations and highlights the interaction between fungal functions and desert ecosystems.

Description: In semi-arid to arid regions, both anthropogenic sources (urban and agriculture) and deeper Critical Zone (groundwater with long flow paths and water residence times) may play an important role in controlling chemical exports to rivers. Here, we combined two anthropogenic isotope tracers: uranium isotope ratios (234U/238U) and boron isotope ratios (δ11B), with the 87Sr/86Sr ratios to identify and quantify multiple solute (salinity) sources in the Rio Grande river in southern New Mexico and western Texas. The Rio Grande river is a major source of freshwater for irrigation and municipal uses in southwestern United States. There has been a large disagreement about the dominant salinity sources to the Rio Grande and particularly significant sources are of anthropogenic (agriculture practices and shallow groundwater flows, groundwater pumping, and urban developments) and/or geological (natural groundwater upwelling) origins. Between 2014 and 2016, we collected monthly river samples at 15 locations along a 200-km stretch of the Rio Grande river from Elephant Butte Reservoir, New Mexico to El Paso, Texas, as well as water samples from agricultural canals and drains, urban effluents and drains, and groundwater wells. Our study shows that due to the presence of localized and multiple salinity inputs, total dissolved solids (TDS) and isotope ratios of U, B, and Sr in the Rio Grande river show high spatial and temporal variability. Several agricultural, urban, and geological sources of salinity in the Rio Grande watershed have characteristic and distinguishable U, Sr, and B isotope signatures. However, due to the common issue of overlapping signatures as identified by previous tracer studies (such as δ18O, δD, δ34S), no single isotope tracer of U, Sr, or B isotopes was powerful enough to distinguish multiple salinity sources. Here, combining the multiple U, Sr, and B isotope and elemental signatures, we applied a multi-tracer mass balance approach to quantify the relative contributions of water mass from the identified various salinity end members along the 200-km stretch of the Rio Grande during different river flow seasons. Our results show that during irrigation (high river flow) seasons, the Rio Grande had uniform chemical and isotopic compositions, similar to the Elephant Butte reservoir where water is stored and well-mixed, reflecting the dominant contribution from shallow Critical Zone in headwater regions in temperate southern Colorado and northern New Mexico. In non-irrigation (low flow) seasons when the river water is stored at Elephant Butte reservoir, the Rio Grande river at many downstream locations showed heterogeneous chemical and isotopic compositions, reflecting variable inputs from upwelling of groundwater (deeper CZ), displacement of shallow groundwater, agricultural return flows, and urban effluents. Our study highlights the needs of using multi-tracer approach to investigate multiple solutes and salinity sources in rivers with complex geology and human impacts.

Description: Pinoresinol is a high-value monolignol-derived lignan used in plant defense and with human health-supporting effects. The synthetic yield and isolation efficiency of racemic pinoresinol from coniferyl alcohol by conventional radical coupling methods is sub-optimal. In this work, a facile and efficient synthetic approach was developed to synthesize pinoresinol with much higher yield. By using 5-bromoconiferyl alcohol, which was synthesized in high yield from 5-bromovanillin, to make 5,5′-bromopinoresinol via a peroxidase-mediated radical coupling reaction takes advantage of the smaller variety of radical coupling products from the 5-substituted monolignol, producing simpler product mixtures from which 5,5′-bromopinoresinol may be readily crystalized with good yield (total yield of 44.1% by NMR; isolated crystalline yield of 24.6%). Hydro-debromination of the crystalline 5,5′-bromopinoresinol to pinoresinol was essentially quantitative. Gram quantities of pinoresinol were conveniently synthesized by using this approach. This simple alternative pathway to make pinoresinol will impact pinoresinol-related research including structural characterization and modification of lignins, as well as clinical applications of pinoresinol and its derivatives.

Description: The aim of the paper is to identify the consequence of the Constructal Principle in the field of Thermoeconomics of (energy) production systems. This Principle has been recently formulated as an extension of the Maximum Entropy Production Principle and it has been used in literature to explain the shape and structure of all kind of flowing systems. First, the concept of Thermoeconomic Environment is defined consistently with the consumption of environmental resources and residual emissions, which inherently characterize every kind of production system. This approach allows to infer that the evolution of any energy system is strictly related to the exploitation of resources from the Thermoeconomic Environment. Moreover, the widely accepted assumption that energy systems have to be optimized by minimizing the specific resource (exergy) cost of products, has to be regarded as a consequence of a physical principle that tells us which energy systems can persist in time (to survive) and which others would be selected for extinction. The paper shows how the creation of a recycle may allow a reduction of the unit exergy cost of the product, obtaining a more sustainable behavior of the macro-system, made up by the production process together with its supply chains, consistently with the Constructal Principle. Finally, the definition of the Thermoeconomic Environment allows (at least in principle) to properly identify the resource (exergy) cost of disposing off residues and sub-products directly in the environment, without any kind of additional operation. As a consequence, residues and sub-products have to be generally converted into some kind of product by different (new) production processes, supporting the paradigm of the Circular Economy and highlighting the importance of recycling not only for system efficiency, but for system surviving. More generally, the results obtained may be regarded as the physical justifications of the evolutionary tendency toward the more and more complex and highly circular pathways that can be observed in both natural and artificial (energy) production systems.

Description: With the objective of better understanding the sources and dynamics of carbonaceous fractions of the aerosols present in the atmosphere of Montreal, we implemented here an online wet oxidation/isotope ratio mass spectrometry (IRMS) method to simultaneously measure both water-soluble organic carbon (WSOC) content and the corresponding δ13C of aerosol samples collected at four monitoring stations over a 1-year period representing distinct types of environmental conditions (i.e., background, road traffic, industrial, and downtown). We coupled these data with the corresponding concentrations of other carbon fractions: total carbon (TC), elemental carbon plus organic carbon (EC + OC), and carbonates. Results show that TC (6.64 ± 2.88 μg m–3), EC + OC (4.98 ± 2.23 μg m–3), and carbonates (1.71 ± 1.09 μg m–3) were characterized by lower concentrations in winter and higher ones between spring and early autumn, with all fractions expectedly showing significantly lower concentrations for aerosols collected at the background station. We observed a seasonal dependence of the δ13CEC+OC (−25.31 ± 0.94‰) with the EC + OC/total suspended particles (TSP) ratio: (i) an increase of the ratio during late spring, summer and early autumn associated to road traffic emissions characterized by a δ13C of ∼−25‰ and (ii) lower ratios during the winter months indicating the influence of two distinct emission sources, a first one with a δ13C ∼−27‰, suggesting the local influence of combined biomass burning from residential heating and of fossil fuel combustion, and a second one with a δ13C ∼−21‰, likely related to more regional emissions. WSOC (1.14 ± 0.67 μg m–3) presented a similar seasonal pattern for all monitoring stations, with low concentrations in winter, early spring and late autumn that rapidly increased until summer. Our results indicate that this seasonality is controlled by higher anthropogenic contributions from southern Canada and northeastern United States regions and probably from biogenic emissions during the warm months. Moreover, δ13CWSOC (−25.08 ± 1.47‰) showed a 13C-depletion in summer, indicating higher fossil fuel and biogenic contributions, whereas the higher isotope compositions observed in winter may result from the photochemical aging of regional aerosols. Ultimately, we identified the influence of local industrial emissions late in 2013 as well as the impact of aerosol emissions associated to the Lac-Mégantic rail disaster that occurred on July 6, ∼200 km east of Montreal.

Description: Planning for the research and development (R&D) of renewable energy resources (RERs) has not received enough attention. This paper aims to study the planning for the R&D of RERs in order to avoid bottlenecks and ensure sustainable development in developing marine economies. We have established a triple difference model (DDD) model and a wise pig game model between the theoretical government and enterprise. The data on RERs come from the World Bank and International Energy Agency databases. We have three contributions on the basis of distinguishing between mature and immature marine RERs technologies. First, it emphasizes the importance of developing R&D planning for marine RERs immature technology in the future. Second, the DDD model is used to empirically establish whether RERs planning has a significant positive impact on RERs’ output, which explains the importance of existing RERs planning. Third, the wise pig game model is used to analyze the welfare benefits to the government brought by the R&D planning of marine RERs which proves the importance of future RERs R&D planning.

Description: Hydroelectric facilities often release water at variable rates over the day to match electricity demand, resulting in short-term variability in downstream discharge and water levels. This sub-daily variability, known as hydropeaking, has mostly been studied at large facilities. The ongoing global proliferation of small hydropower (SHP) facilities, which in Brazil are defined as having installed capacities between 5 and 30 MW, raises the question of how these facilities may alter downstream flow regimes by hydropeaking. This study examines the individual and cumulative effects of hydropower facilities on tributaries in the upland watershed of the Pantanal, a vast floodplain wetland system located on the upper Paraguay River, mostly in Brazil. Simultaneous hourly discharge measurements from publicly available reference and downstream gage stations were analyzed for 11 reaches containing 24 hydropower facilities. Most of the facilities are SHPs and half are run-of-river designs, often with diversion channels (headraces). Comparison of daily data over an annual period, summarized by indicators of hydrological alteration (HA) that describe the magnitude, frequency, rate of change, and duration of flows, revealed differences at sub-daily scales attributable to hydropeaking by the hydropower facilities. Results showed statistically significant sub-daily HA in all 11 reaches containing hydropower facilities in all months. Discharge indicators that showed the highest percentage of days with increased variability were the mean rates of rise and fall, amplitude, duration of high pulses, maximum discharge, and number of reversals. Those that showed higher percentages of decreased variability included minimum discharge, number of high pulses, duration of stability, and number of low pulses. There was no correlation between HA values and physical characteristics of rivers or hydropower facilities (including installed capacity), and reaches with multiple facilities did not differ in HA from those with single facilities. This study demonstrates that SHPs as well as larger hydropower facilities cause hydrological alterations attributable to hydropeaking. Considering the rapid expansion of SHPs in tropical river systems, there is an urgent need to understand whether the ecological impacts of hydropeaking documented in temperate biomes also apply to these systems.

Description: The Sustainable Development Goals (SDG) have become the international framework for sustainability policy. Its legacy is linked with the Millennium Development Goals (MDG), established in 2000. In this paper a scientometric analysis was conducted to: (1) Present a new methodological approach to identify the research output related to both SDGs and MDGs (M&SDGs) from 2000 to 2017, with the aim of mapping the global research related to M&SDGs; (2) Describe the thematic specialization based on keyword co-occurrence analysis and citation bursts; and (3) Classify the scientific output into individual SDGs (based on an ad-hoc glossary) and assess SDGs interconnections. Publications conceptually related to M&SDGs (defined by the set of M&SDG core publications and a scientometric expansion based on direct citations) were identified in the in-house CWTS Web of Science database. A total of 25,299 publications were analyzed, of which 21,653 (85.59%) were authored by Higher Education Institutions (HEIs) or academic research centers (RCs). The findings reveal the increasing participation of these organizations in this research (660 institutions in 2000–2005 to 1,744 institutions involved in 2012–2017). Some institutions present both a high production and specialization on M&SDG topics (e.g., London School of Hygiene & Tropical Medicine and World Health Organization); and others with a very high specialization although lower production levels (e.g., Stockholm Environment Institute). Regarding the specific topics of research, health (especially in developing countries), women, and socio-economic issues are the most salient. Moreover, it has been observed an important interlinkage in the research outputs of some SDGs (e.g., SDG11 “Sustainable Cities and Communities” and SDG3 “Good Health and Well-Being”). This study provides first evidence of such interconnections, and the results of this study could be useful for policymakers in order to promote a more evidenced-based setting for their research agendas on SDGs.

Description: Resources and environment management have always been a research hotspot. In the context of sustainable development and environmental governance, scholars and policy makers have been increasing their research efforts on natural resource utilization and its environmental impact. By using the Web of Science Core Collection database, this article applies the bibliometric method to accomplish a systematic review about studies on accounting and management of natural resource consumption based on input-output method. The results indicate that both in terms of the quantity and quality of academic achievements and international cooperation, China is in high academic position and has made great contributions to the development in this research field. While energy and water account for a large proportion of the study objects, more attention is paid on the other kinds of natural resources, such as land, metal, and ocean. International trade is an eternal hot topic in this field. With the continuous progress of the multi-regional input-output model, the importance and feasibility in the analysis of sub-national level or region in the global supply chain gradually emerged. Combining input-output model with other methods can obtain more comprehensive and accurate results for scientific decision-making. Meanwhile, the uncertainty and limitations inherent in such models clearly need further attention.

Description: The southern Amazonia is undergoing a major biophysical transition, involving changes in land use and regional climate. This study provides new insights on the relationship between hydroclimatic variables and vegetation conditions in the upper Madeira Basin (~1 × 106 km2). Vegetative dynamics are characterised using the normalized difference vegetation index (NDVI) while hydroclimatic variability is analysed using satellite-based precipitation, observed river discharge, satellite measurements of terrestrial water storage (TWS) and downward shortwave radiation (DSR). We show that the vegetation in this region varies from energy-limited to water-limited throughout the year. During the peak of the wet season (January-February), rainfall, discharge and TWS are negatively correlated with NDVI in February-April (r = −0.48 to −0.65; p 〈 0.05). In addition, DSR is positively correlated with NDVI (r = 0.47–0.54; p 〈 0.05), suggesting that the vegetation is mainly energy-limited during this period. Outside this period, these correlations are positive for rainfall, discharge and TWS (r = 0.55–0.88; p 〈 0.05), and negative for DSR (r = −0.47 to −0.54; p 〈 0.05), suggesting that vegetation depends mainly on water availability, particularly during the vegetation dry season (VDS; late June to late October). Accordantly, the total rainfall during the dry season explains around 80% of the VDS NDVI interannual variance. Considering the predominant land cover types, differences in the hydroclimate-NDVI relationship are observed. Evergreen forests (531,350 km2) remain energy-limited during the beginning of the dry season, but they become water-limited at the end of the VDS. In savannas and flooded savannas (162,850 km2), water dependence occurs months before the onset of the VDS. These differences are more evident during extreme drought years (2007, 2010, and 2011), where regional impacts on NDVI were stronger in savannas and flooded savannas (55% of the entire surface of savannas) than in evergreen forests (40%). A spatial analysis reveals that two specific areas do not show significant hydroclimatic-NDVI correlations during the dry season: (i) the eastern flank of the Andes, characterised by very wet conditions, therefore the vegetation is not water-limited, and (ii) recent deforested areas (~42,500 km2) that break the natural response in the hydroclimate-vegetation system. These findings are particularly relevant given the increasing rates of deforestation in this region.

Description: Agriculture is the major user of water resources, accounting for 70% of global freshwater demand. As the demand for clean water increases, so does the need to implement more efficient strategies for water management in irrigated agriculture. While the benefits of precision irrigation in high-value crops, such as cannabis, tomatoes, and potatoes, are fully recognized, there is still need to investigate and implement cheap and efficient irrigation strategies for widespread low-value crops such as maize. In this study, the soil moisture dynamics in a sprinkler-irrigated maize field in Veneto (Northeastern Italy) was monitored using six time domain reflectometry (TDR) probes for the entire growing season. The TDR sensors were positioned at different depths into two separate sites: an Uninformed Site irrigated based on the farmer's experience and an Informed Site in which a water balance irrigation strategy was applied based on soil moisture measurements. A parsimonious hydrological model was then implemented and calibrated to quantify the different water balance terms (precipitation, evapotranspiration, lateral fluxes, and deep percolation). The comparison between the water budget terms in the two sites highlights that soil moisture monitoring during agriculture activities leads to substantial savings in terms of irrigation water volumes requirements and cost, without compromising the productivity of the crop field. A simplified upscaling of the results at the regional scale, assuming average conditions as in this study site and growing season, reveals that potentially significant economic savings, compared to the total profits linked to maize crops, could be possible.

Description: Response time is the key index of on-line monitoring system. To improve the response speed of traditional bead thermal conductivity CO2 sensor, this paper proposes to use multi-walled carbon nanotubes (MWCNTs) to improve the performance of gas sensor carrier. Nano-sized γ-Al2O3/CeO2 powder was synthesized by chemical precipitation method under the action of ultrasonic wave. SEM morphology reveals a particle size of 20–50 nm. MWCNTs were hydroxylated and the solution was then prepared by adding a certain amount of dispersant under ultrasonic wave. The composite support of γ- Al2O3/CeO2/MWCNTs was prepared by wet mixing carbon nanotube solution into the above support materials. Using dynamic resistance matching and black component technology, the influence of radiation heat and environmental temperature and humidity is reduced. Results show that the designed thermal conductivity sensor has consistent response and recovery time to different concentrations of CO2, with a T90 response time of 9 s and a T90 recovery time of 13 s, which is faster compared to major commercial Carbon dioxide sensors. The average sensitivity of the sensor is 0.0075 V/10% CO2. Therefore, the high thermal conductivity and pore characteristics of carbon nanotubes can effectively improve the response speed of the thermal conductivity sensor.

Description: A total of 94 soil samples from different soil depths (0∼25 cm, 25∼50 cm) were collected of farmland soil around the plain of Beijing, and the concentrations of five heavy metal elements (Cd, Cr, Pb, As, and Hg) were measured using standard methods. The safety utilization evaluation method of heavy metals was based on three different evaluation methods. Then, the governance principles and specific management control strategy were determined in detail according to the core pollution source analysis of each safety grade zone. The results show that there are four different comprehensive safe utilization areas: safe, low-risk, medium-risk, and high-risk utilization. Among them, the study area was dominated by low-risk utilization areas, and the risk trend was gradually weakening from the center of the city to the periphery. Based on the characteristics of different security zones, this study puts on the governance principles of priority protection, long-term monitoring and moderate optimization, strengthens early warning, and cooperates with effective repair and priority governance. And then it puts forward practical control strategies according to the core pollution sources of each safety utilization zone. Our findings may provide a clear direction for rational utilization of land resources and renovation in the future.

Description: To investigate the nexus between natural gas consumption, global carbon dioxide (CO2) emissions, and technological innovation, this study employs a balanced panel dataset of 73 countries for the period 1990–2019 based on the fixed effect and random effect estimation methods. Considering potential heterogeneity in the natural gas-CO2 nexus, this study divides the 73 countries into regional comprehensive economic partnership (RCEP) countries and non-RCEP countries for comparative analysis. The main findings indicate that natural gas consumption can significantly promote CO2 emissions for the full sample and non-RCEP countries, and improved technological innovation can help alleviate CO2 emissions from natural gas consumption. In the RCEP countries, technological innovation can improve the carbon emission reduction effect of natural gas. Furthermore, economic growth and global CO2 emissions show an inverted U-shaped relationship, which confirms the environmental Kuznets curve hypothesis. Finally, several policy implications are provided to reduce global CO2 emissions and promote green recovery in the post-epidemic era.

Description: Most European cities have air pollution levels that exceed the threshold for human health protection. Children are sensitive to air pollution and thus it is important to ensure they are not exposed to high concentrations of air pollutants. In order to make a positive change toward cleaner air, a joint effort is needed, involving all civil society actors. Schools and local communities have a decisive role, and can, for example, become engaged in citizen science initiatives and knowledge coproduction. In 2019, with the aim of raising awareness for air quality, NILU developed a citizen science toolbox to engage primary schools in monitoring air quality using a simple and affordable measuring method based on paper and petroleum jelly. This is a very visual method, where the students can clearly see differences from polluted and non-polluted places by looking at “how dirty” is the paper. In addition to the qualitative analysis, we have developed an air meter scale making possible for the students to obtain an indicative measurement of the air pollution level. The comparison between the paper and petroleum jelly method against reference PM10 data collected at two official air quality stations showed a good agreement. The method is a strong candidate for dust monitoring in citizen science projects, making participation possible and empowering people with simple tools at hand. The toolbox is targeted at primary schools and children aged 6–12 years, although it can easily be adapted to other age groups. The main objective of the toolbox is to involve young children who are usually not targeted in air quality citizen science activities, to develop research skills and critical thinking, as well as increase their awareness about the air they breathe. The toolbox is designed to engage students in hands-on activities, that challenge them to create hypotheses, design scientific experiments, draw conclusions and find creative solutions to the air pollution problem. The toolbox includes all the necessary material for the teachers, including guidance, background information and templates facilitating the incorporation in the school curricula. The toolbox was launched as part of the Oslo European Green Capital in March 2019 and was later included as part of the European Clean Air Day initiative coordinated by the European Citizen Science Association (ECSA) working group on air quality. A total of 30 schools and 60 4th grade classes (aged 8–9 years) participated in the Oslo campaign. The citizen science approach employed in the schools, combined the four key elements that promote knowledge integration: elicit ideas, add new ideas, distinguish among ideas and reflect and sort out ideas. Although the main goal of the study was to provide simple but robust tools for engaging young children in air quality monitoring, we also carried out ex-ante and ex-post evaluations in 12 of the participating classes using a 10-question multiple choice test to have an indication of the contribution of the activity to knowledge integration. The results show that there is an increase in the number of correct answers, as well as a reduction in the misconceptions after conducting the activity. These results indicate that applying a citizen science approach improved science instruction and helped knowledge integration by including students' views and taking advantage of the diverse ideas students generated. Citizen science gives learners an insight into the ways that scientists generate solutions for societal problems. But more important, citizen science provides a way to differ from the classic view of the learner as an absorber of information, by considering the social context of instruction and making the topic personally relevant.

Description: Modeling is essential for modern science, and science-based policies are directly affected by the reliability of model outputs. Artificial intelligence has improved the accuracy and capability of model simulations, but often at the expense of a rational understanding of the systems involved. The lack of transparency in black box models, artificial intelligence based ones among them, can potentially affect the trust in science driven policy making. Here, we suggest that a broader discussion is needed to address the implications of black box approaches on the reliability of scientific advice used for policy making. We argue that participatory methods can bridge the gap between increasingly complex scientific methods and the people affected by their interpretations

Description: Lithium-ion batteries (LIBs) have been one of the most predominant rechargeable power sources due to their high energy/power density and long cycle life. As one of the most promising candidates for the new generation negative electrode materials in LIBs, silicon has the advantages of high specific capacity, a lithiation potential range close to that of lithium deposition, and rich abundance in the earth’s crust. However, the commercial use of silicon in LIBs is still limited by the short cycle life and poor rate performance due to the severe volume change during Li++ insertion/extraction, as well as the unsatisfactory conduction of electron and Li+ through silicon matrix. Therefore, many efforts have been made to control and stabilize the structures of silicon. Magnesiothermic reduction has been extensively demonstrated as a promising process for making porous silicon with micro- or nanosized structures for better electrochemical performance in LIBs. This article provides a brief but critical overview of magnesiothermic reduction under various conditions in several aspects, including the thermodynamics and mechanism of the reaction, the influences of the precursor and reaction conditions on the dynamics of the reduction, and the interface control and its effect on the morphology as well as the final performance of the silicon. These outcomes will bring about a clearer vision and better understanding on the production of silicon by magnesiothermic reduction for LIBs application.

Description: Auto-thermal operation of biomass torrefaction can help avoid additional heat investment and the associated costs to the system. This work provides a general method for relating the feedstock-specific parameters to the energy balance and pre-diagnosing the potential of auto-thermal for different biomass torrefaction and pyrolysis systems. Both solid and gas thermal properties under various torrefaction conditions and their influences to the torrefaction system energy balances are considered. Key parameters that influence the process auto-thermal operation are analyzed, which include torrefaction reaction heat, torrefaction conditions, drying method, biomass species, and inert N2 flowrate. Equations of torgas and biomass higher heating values (HHVs), as well as the torrefaction reaction heat at different operating conditions are developed. It is found that torgas and biomass HHVs increase with torrefaction temperature and biomass weight loss. Torrefaction reaction heat has a linear relationship with the biomass weight loss, with a positive slope at 250–260°C, and a negative slope at 270–300°C, which indicates that torrefaction shifts from endothermic to exothermic at ∼270°C. Applying advanced drying technology and avoiding the use of N2 can help the system achieve auto-thermal operation at lower torrefaction temperature and residence time, thus leading to a higher process energy efficiency and product yield. This is the first work to relate the micro level element changes of biomass to the macro level process energy balances of the torrefaction system. This work is important in design and operation of the torrefaction system in both pilot and industrial scales to improve process efficiency and predict product quality in a reliable and economic manner.

Description: Citizen science is an important vehicle for democratizing science and promoting the goal of universal and equitable access to scientific data and information. Data generated by citizen science groups have become an increasingly important source for scientists, applied users and those pursuing the 2030 Agenda for Sustainable Development. Citizen science data are used extensively in studies of biodiversity and pollution; crowdsourced data are being used by UN operational agencies for humanitarian activities; and citizen scientists are providing data relevant to monitoring the sustainable development goals (SDGs). This article provides an International Science Council (ISC) perspective on citizen science data generating activities in support of the 2030 Agenda and on needed improvements to the citizen science community's data stewardship practices for the benefit of science and society by presenting results of research undertaken by an ISC-sponsored Task Group.

Description: With the growing population, solid waste management (SWM) is becoming a significant environmental challenge and an emerging issue, especially in the eco-sensitive Indian Himalayan region (IHR). Though IHR does not host high local inhabitants, growing tourist footfall in the IHR increases solid wastes significantly. The lack of appropriate SWM facilities has posed a serious threat to the mountain-dwelling communities. SWM is challenging in the highlands due to the remoteness, topographical configuration, increasing urbanization, and harsh climate compared to plain areas. Difficulty in managing SWM has led to improper disposal methods, like open dumping and open burning of waste, that are adversely affecting the fragile IHR ecosystem. Open dumping of unsegregated waste pollutes the freshwater streams, and burning releases major pollutants often linked to the glacier melt. Processes like composting, vermicomposting, and anaerobic digestion to treat biodegradable wastes are inefficient due to the regions' extreme cold conditions. IHR specific SWM rules were revised in 2016 to deal with the rising problem of SWM, providing detailed criteria for setting up solid waste treatment facilities and promoting waste-to-energy (WtE). Despite governments' effort to revise SWM; measures like proper collection, segregation, treatment, and solid waste disposal needs more attention in the IHR. Door-to-door collection, segregation at source, covered transportation, proper treatment, and disposal are the primary steps to resource recovery across the IHR. Approaches such as waste recycling, composting, anaerobic digestion, refuse-derived fuel (RDF), and gas recovery from landfills are essential for waste alteration into valuable products initiatives like 'ban on single-use plastic' and 'polluters to pay' have a potential role in proper SWM in the IHR. Research and technology, capacity building, mass awareness programs, and initiatives like ‘ban on single-use plastic’ and ‘polluters to pay’ have a potential role in proper SWM in the IHR. This review highlights the current status of waste generation, the current SWM practices, and SWM challenges in the IHR. The review also discusses the possible resource recovery from waste in the IHR, corrective measures introduced by the government specific to IHR and, the way forward for improved SWM for achieving sustainable development of the IHR.

Description: An analysis model of wind power consumption capacity is established with the multi-fractal theory. Firstly, the fluctuation characteristics of wind power are described through multi-fractal parameters, and the correlation between wind power fluctuation characteristics and consumption capacity are analyzed. Afterwards, the swinging door algorithm (SDA) is applied to divide the wind power curve in the evaluation period, and the fluctuation process with similar characteristics is clustered. Further, a functional analysis model to evaluate wind power consumption capacity is mentioned based on the fluctuation clustering results. Finally, the effectiveness of the method is verified by an example of a regional power grid in China, and the influence of adjustable parameters in the model on the consumption capacity is quantitatively analyzed.

Description: Identifying governance schemes that promote cooperation among urban stakeholders is a priority in a context where rapid urbanization poses multiple and complex challenges for ensuring the sustainability of cities. Smart cities offer promising governance approaches, especially in the framework of the concept of Urban Living Labs (ULLs), as an enabling environment for so-called user-centric co-creation processes. While embedding a potential to promote solutions that tackle the challenges of urbanization, especially in relation to the energy transition, it is not yet clear how ULLs can effectively involve all relevant actors nor the extent of their impact, especially regarding behaviors. The study first analyzes the interplay between the challenge of urban energy transition and local governance schemes. Then, it explores how findings from behavioral sciences can inform the design of ULLs to effectively promote active engagement in the urban energy transition. Finally, it reviews the theoretical findings in relation to the ULL that has been taking shape in the city of Trento, Italy.

Description: In southern Mediterranean areas, vineyards are facing the combination of increasing air temperature, drought and frequency of extreme events (e.g., heat waves) due to climate change. Since most of the berry growth and ripening phases occur during the aridity period, such environmental constraints are responsible for limitations in yield and berry quality. Within this scenario, to achieve vineyard sustainability, renewed approaches in vineyard management have been proposed and the use of plant biostimulants seems a prominent and environmental friendly practice. The aim of this study was to test four combinations of a tropical plant extract and conventional chemicals for disease control on morpho-anatomical, physiological, biochemical and berry quality in Vitis vinifera L. subsp. vinifera “Aglianico.” In particular, we aimed to evaluate the possibility to counteract the negative effects of the reductions in copper distribution, by applying the tropical plant extract enriched with: micronutrients, enzymes involved in the activation of natural defense, aminoacids, and vitamins. The halved dose of Cu in combination with the tropical plant extract allowed maintaining a reduced vegetative vigor. In the second year of treatment, the addition of the plant extract significantly improved leaf gas exchanges and photochemistry as well as the synthesis of photosynthetic pigments. At berry level, the plant extract induced an increase in phenolics accompanied by a decrease in soluble sugars. The overall results showed that the expected differences in growth performance and productivity in vines are linked to different eco-physiological and structural properties induced by the various treatments. The tropical plant extract also primed plant defenses at the leaf and fruit levels, mainly due to modifications of some structural and biochemical traits, respectively.

Description: Carbon dioxide removal (CDR) from the atmosphere is likely to be needed to limit global warming to 1.5 or 2°C and thereby for meeting the Paris Agreement. There is a debate which methods are most suitable and cost-effective for this goal and thus deeper understanding of system effects related to CDR are needed for effective governance of these technologies. Bio-Energy with Carbon Capture and Storage (BECCS) and Direct Air Carbon Capture and Storage (DACCS) are two CDR methods, that have a direct relation to the electricity system—BECCS via producing it and DACCS via consuming. In this work, we investigate how BECCS and DACCS interact with an intermittent electricity system to achieve net negative emissions in the sector using an energy system model and two regions with different wind and solar resource conditions. The analysis shows that DACCS has a higher levelized cost of carbon (LCOC) than BECCS, implying that it is less costly to capture CO2 using BECCS under the assumptions made in this study. However, due to a high levelized cost of electricity (LCOE) produced by BECCS, the total system cost is lower using DACCS as negative emission provider as it is more flexible and enables cheaper electricity production from wind and solar PV. We also find that the replacement effect outweighs the flexibility effect. Since variations in solar-based systems are more regular and shorter (daily cycles), one could assume that DACCS is better suited for such systems, whereas our results point in the opposite direction showing that DACCS is more competitive in the wind-based systems. The result is sensitive to the price of biomass and to the amount of negative emissions required from the electricity sector. Our results show that the use of the LCOC as often presented in the literature as a main indicator for choosing between different CDR options might be misleading and that broader system effects need to be considered for well-grounded decisions.

Description: Wildland research, management, and policy in western democracies have long relied on concepts of equilibrium: succession, sustained yield, stable age or species compositions, fire return intervals, and historical range of variability critically depend on equilibrium assumptions. Not surprisingly, these largely static concepts form the basis for societal expectations, dominant management paradigms, and environmental legislation. Knowledge generation has also assumed high levels of stasis, concentrating on correlational patterns with the expectation that these patterns would be reliably transferrable. Changes in climate, the introduction of large numbers of exotic organisms, and anthropogenic land conversion are leading to unprecedented changes in disturbance regimes and landscape composition. Importantly, these changes are largely non-reversable; once introduced exotic species are seldom eradicated, climates will continue to warm for the foreseeable future, and many types of land conversion cannot be easily undone. Due to their effects on extant infrastructure and expectations for ecosystem services, these changes are, and will be, viewed by western societies as overwhelmingly negative. The continued acceleration of change will generate increasingly novel systems for which the transferability of correlational relationships will prove unreliable. Our abilities to predict system trajectories will therefore necessarily decrease. In this environment, top-down, expert dominated approaches to environmental decision making are unlikely to produce results that meet broader societal expectations. To be successful we need to embrace a more inclusive paradigm of collaborative governance and multiple forms of knowledge for adapting to constant change, including indigenous epistemological systems. By increasing public and stakeholder participation, we can encourage collaborative social learning allowing all parties to more fully understand the complexities and tradeoffs associated with wildland management and the technical limits of models that seek to quantify those tradeoffs. System novelty will necessarily make forecasting more dependent on predictive modeling and will require better models. Data collection should therefore be strongly influenced by model input requirements and validation; research will need to focus on fundamental and causal relationships to a much greater degree than is done currently.

Description: The rapid development of wind energy has brought a lot of uncertainty to the power system. The accurate ultra-short-term wind power prediction is the key issue to ensure the stable and economical operation of the power system. It is also the foundation of the intraday and real-time electricity market. However, most researches use one prediction model for all the scenarios which cannot take the time-variant and non-stationary property of wind power time series into consideration. In this paper, a Markov regime switching method is proposed to predict the ultra-short-term wind power of multiple wind farms. In the regime switching model, the time series is divided into several regimes that represent different hidden patterns and one specific prediction model can be designed for each regime. The Toeplitz inverse covariance clustering (TICC) is utilized to divide the wind power time series into several hidden regimes and each regime describes one special spatiotemporal relationship among wind farms. To represent the operation state of the wind farms, a graph autoencoder neural network is designed to transform the high-dimensional measurement variable into a low-dimensional space which is more appropriate for the TICC method. The spatiotemporal pattern evolution of wind power time series can be described in the regime switching process. Markov chain Monte Carlo (MCMC) is used to generate the time series of several possible regime numbers. The Kullback-Leibler (KL) divergence criterion is used to determine the optimal number. Then, the spatiotemporal graph convolutional network is adopted to predict the wind power for each regime. Finally, our Markov regime switching method based on TICC is compared with the classical one-state prediction model and other Markov regime switching models. Tests on wind farms located in Northeast China verified the effectiveness of the proposed method.

Description: This study aimed to understand post-agricultural natural forest regeneration in the Southern Brazilian Atlantic Forest and its possible role as a cost-effective, passive approach to forest restoration. The study characterized vegetation structure, floristic composition, and the dynamics of secondary forest chronosequences. Data were collected from 159 plots (10 × 10 m each) across forest remnants in Santa Catarina State, covering forest ages that ranged from 2 to 60 years of regeneration after swidden agriculture. Only areas with no signs of degradation were sampled in order to provide a description of vegetation characteristics that could be used to identify and monitor natural regeneration. A total of 11,455 woody plants were identified and classified into 334 species representing 71 families. As the succession process unfolds, the continuous turnover of species makes forests more diverse and structurally complex. Floristic similarity among forest types is observed during the early stages of succession, but decreases over time. Pioneer species dominate young secondary forests, representing about 40% of the basal area up to 10 years of regeneration. Shade-tolerant species start colonizing the sites at early ages; however, they become more important structural elements only after 30 years of succession. The observed patterns of forest structure and species diversity largely conform to the post-agricultural succession seen in many tropical forests. The high species diversity found in this study highlights the importance of natural regeneration as a strategy to restore ecosystems. Floristic data can be used as a reference for choosing suitable species for active restoration, as well as contributing to the design of integrated restoration strategies. We herein reinforce the potential of natural regeneration as part of large-scale restoration programs, which would be particularly attractive to family farmers by the low cost of supplies and labor.

Description: Microgrids have been emerging and playing valuable roles in several parts of society, from academia of scholars to the energy supply industry of professional practitioners. A microgrid policy appeared in the Thailand 2015 energy development plan. There are many microgrids in Thailand. The first smart microgrid in Thailand is in active operation. Some microgrids are no longer functioning. Other microgrids continue to serve their customers. The remaining microgrid projects are in the process of development. Most present microgrids in Thailand are driven by public policy and legal flexibility. The objective of this research is to investigate the compatible microgrid technology in Thailand and explore the key drivers of microgrid policies in Thailand. The research methodology applied in this research includes data collection (i.e., a document study, interview, group discussion, and microgrid project participation and observation), as well as data analysis and conclusion. The findings of the research show that: in Thailand, the desired microgrid technologies are compatible with 1) inputs of potential local renewable energy resources of solar, wind, biomass, and mini-hydro, and 2) small gaps of human resource capabilities to deal with the technology utilization. The key drivers of the Thailand microgrid policy are 1) electricity access, 2) wealth creation and distribution, 3) environmental protection, and 4) technology development.

Description: In response to climate change and energy transition, natural gas has been rapidly developed as a relatively low-carbon energy source by many countries. However, there remain environmental risks at different stages in the entire process from exploitation to utilization. Firstly, this article identifies various environmental risks and benefits of natural gas along the entire industry chain from upstream exploitation and midstream transportation to downstream utilization. It is found that, during upstream exploitation, hydraulic fracturing has the worst environmental impact. During the midstream storage and transportation stage, methane leakage is the biggest environmental risk. In the downstream combustion and utilization stage, the risk to environment is less than other energy sources, although there are some greenhouse gas effects and water pollution issues. Thus, this article puts forward some policy recommendations for different stages from exploitation to utilization. In the upstream stage, especially hydraulic fracturing activity, we suggest strengthening environmental assessment management, improving policy standards, creating a water quality monitoring plan, and promoting the innovation of key technologies. In terms of the midstream, besides pipeline laying and site selection, we focus on monitoring the system, including leak detection, quality management of engineering materials, and risk identification and management. When it comes to the downstream, we encourage the application of advanced technologies to improve thermal efficiency and reduce emissions, such as gas-fired related technologies, natural gas recycling technologies, distributed energy technologies, and green and low-carbon service technologies.

Description: Studies on inequalities in exposure to flood risk have explored whether population of a lower socio-economic status are more exposed to flood hazard. While evidence exist for coastal flooding, little is known on inequalities for riverine floods. This paper addresses two issues: (1) is the weakest population, in socio-economic terms, more exposed to flood hazard, considering different levels of exposure to hazard? (2) Is the exposure to flood risk homogeneous across the territory, considering different scales of analysis? An analysis of the exposure of inhabitants of Liège province to flood risk was conducted at different scales (province, districts, and municipalities), considering three levels of exposure to flood hazard (level 1- low hazard, level 3- high hazard), and five socio-economic classes (class 1-poorest, class 5-wealthiest households). Our analysis confirms that weaker populations (classes 2 and 3) are usually more exposed to flood hazards than the wealthiest (classes 4 and 5). Still it should be stressed that the most precarious households (class 1) are less exposed than low to medium-range ones (classes 2 and 3). Further on the relation between socio-economic status and exposure to flood hazard varies along the spatial scale considered. At the district level, it appears that classes 4 and 5 are most exposed to flood risk in some peripheral areas. In municipalities located around the center of the city, differences of exposure to risk are not significant.

Description: Effective management of both endangered native and invasive alien crayfishes requires knowledge about distribution, monitoring of existing and early detection of newly established populations. Complementary to traditional survey methods, eDNA sampling has recently emerged as a highly sensitive non-invasive detection method to monitor crayfish populations. To advance the use of eDNA as detection tool for crayfish we used a twofold approach: 1) we designed a novel set of specific eDNA-assays for all native (Austropotamobius torrentium, Austropotamobius pallipes, Astacus astacus) and the most relevant invasive crayfish species (Pacifastacus leniusculus, Faxonius limosus, Faxonius immunis) in Central Europe. To ensure specificity each primer pair was tested in silico, in vitro, and in situ; 2) we assessed the influence of spatio-temporal variables (distance to upstream population, season, stream size) on eDNA detection in seven streams using two different detection methods (qualitative endpoint PCR and quantitative droplet digital PCR, ddPCR). The newly developed eDNA assays successfully detected all crayfish species across different lotic and lentic habitats. eDNA detection rate (endpoint PCR) and eDNA-concentration (ddPCR) were significantly influenced by distance and season. eDNA detection was successful up to 7 km downstream of the source population and across all seasons, although detectability was lowest in winter. eDNA detection rate further decreased with increasing stream size. Finally, eDNA-concentration correlated positively with estimated upstream population size. Overall, we provide near operational eDNA assays for six crayfish species, enabling year-round detection, which represents a clear benefit over conventional methods. Due to its high sensitivity, eDNA detection is also suitable for the targeted search of as-yet unrecorded or newly emerging populations. Using quantitative ddPCR might further allow for a rough estimation of population size, provided that the identified spatio-temporal factors are accounted for. We therefore recommend implementing eDNA-detection as a complementary survey tool, particularly for a large-scale screening of data-deficient catchments or a year-round monitoring.

Description: Large primary forest residuals can still be found in boreal landscapes. Their areas are however shrinking rapidly due to anthropogenic activities, in particular industrial-scale forestry. The impacts of logging activities on primary boreal forests may also strongly differ from those of wildfires, the dominant stand-replacing natural disturbance in these forests. Since industrial-scale forestry is driven by economic motives, there is a risk that stands of higher economic value will be primarily harvested, thus threatening habitats, and functions related to these forests. Hence, the objective of this study was to identify the main attributes differentiating burned and logged stands prior to disturbance in boreal forests. The study territory lies in the coniferous and closed-canopy boreal forest in Québec, Canada, where industrial-scale logging and wildfire are the two main stand-replacing disturbances. Based on Québec government inventories of primary forests, we identified 427 transects containing about 5.5 circular field plots/transect that were burned or logged shortly after being surveyed, between 1985 and 2016. Comparative analysis of the main structural and environmental attributes of these transects highlighted the strong divergence in the impact of fire and harvesting on primary boreal forests. Overall, logging activities mainly harvested forests with the highest economic value, while most burned stands were low to moderately productive or recently disturbed. These results raise concerns about the resistance and resilience of remnant primary forests within managed areas, particularly in a context of disturbance amplification due to climate change. Moreover, the majority of the stands studied were old-growth forests, characterized by a high ecological value but also highly threatened by anthropogenic disturbances. A loss in the diversity and functionality of primary forests, and particularly the old-growth forests, therefore adds to the current issues related to these ecosystems. Since 2013, the study area is under ecosystem-based management, which implies that there have been marked changes in forestry practices. Complementary research will be necessary to assess the capacity of ecosystem-based management to address the challenges identified in our study.

Description: Two common tree species, ash (Fraxinus sp.) and oak (Quercus sp.), could provide readily available media for denitrifying bioreactors that use wood-based carbon for biological nitrate treatment. However, it is not known if the wood from Emerald Ash Borer-killed (EAB-killed) ash trees is an effective carbon source for nitrate removal compared to other wood species or if the high-tannin nature of oak inhibits denitrification potential. This lab-scale study showed that EAB-killed ash woodchips did not significantly differ in nitrate removal or denitrification potential compared to a commercially available blend of hardwood chips. However, neither treatment performed as well as oak woodchips in these metrics. Use of high-tannin oak in bioreactors is currently restricted by a federal standard in the United States. Ash woodchips beneficially exhibited the lowest nitrous oxide production potential, and their dissolved phosphorus leaching fell within the range of other woodchip types. Emerald ash borer-killed ash wood could be an effective source for denitrifying bioreactors located within affected regions and oak woodchips merit additional investigation for the application of denitrifying bioreactors.

Description: In the process of the detection of a false data injection attack (FDIA) in power systems, there are problems of complex data features and low detection accuracy. From the perspective of the correlation and redundancy of the essential characteristics of the attack data, a detection method of the FDIA in smart grids based on cyber-physical genes is proposed. Firstly, the principle and characteristics of the FDIA are analyzed, and the concept of the cyber-physical FDIA gene is defined. Considering the non-functional dependency and nonlinear correlation of cyber-physical data in power systems, the optimal attack gene feature set of the maximum mutual information coefficient is selected. Secondly, an unsupervised pre-training encoder is set to extract the cyber-physical attack gene. Combined with the supervised fine-tuning classifier to train and update the network parameters, the FDIA detection model with stacked autoencoder network is constructed. Finally, a self-adaptive cuckoo search algorithm is designed to optimize the model parameters, and a novel attack detection method is proposed. The analysis of case studies shows that the proposed method can effectively improve the detection accuracy and effect of the FDIA on cyber-physical power systems.

Description: The aim of this paper is to provide an overview of the interrelationship between data science and climate studies, as well as describes how sustainability climate issues can be managed using the Big Data tools. Climate-related Big Data articles are analyzed and categorized, which revealed the increasing number of applications of data-driven solutions in specific areas, however, broad integrative analyses are gaining less of a focus. Our major objective is to highlight the potential in the System of Systems (SoS) theorem, as the synergies between diverse disciplines and research ideas must be explored to gain a comprehensive overview of the issue. Data and systems science enables a large amount of heterogeneous data to be integrated and simulation models developed, while considering socio-environmental interrelations in parallel. The improved knowledge integration offered by the System of Systems thinking or climate computing has been demonstrated by analysing the possible inter-linkages of the latest Big Data application papers. The analysis highlights how data and models focusing on the specific areas of sustainability can be bridged to study the complex problems of climate change.

Description: The leopard cat (Prionailurus bengalensis) is the most widespread feline in Asia. It has been recorded in a range of habitats, including monoculture landscapes, such as oil palm plantations. Here, we report on a study on the presence, home range, activity patterns and diet of the species in an oil palm landscape to assess their viability as biological pest controller of rats. The study took place in United Plantations/PT SSS estate in Central Kalimantan, Borneo, Indonesia. From July 2014 to March 2018, we captured 11 leopard cats in purpose-built cage-traps and fitted them with VHF radio-transmitters. They were tracked for a 44 months study period, during which we collected a total of 2.031 GPS locations used for estimating the respective cats’ activities and home-ranges. The cats are strictly nocturnal and prefer to hide and rest in thick bush, primarily consisting of sword-fern (Nephrolepis sp.) during day-time, but forage both on the ground and in the palm canopy at night. The average home range (95% FK) for male leopard cats is 1.47 km2 (n = 7; SD = 0.62 km2) with slightly smaller home range for females at 1.29 km2 (n = 4; SD = 0.28 km2). All individuals studied were recorded strictly within the oil palm plantation landscape, although mangrove forest habitat makes up 7% of the greater plantation landscape. In conclusion, leopard cats survive and reproduce well in oil palm habitats and are effective biological controllers of rats that can replace the traditionally used expensive and environmentally polluting chemical rat poisons.

Description: This paper investigates whether the macroeconomic uncertainty factors can explain and forecast China’s INE crude oil futures market volatility. We use the GARCH-MIDAS model to investigate the explaining and predicting power of the macroeconomic uncertainties. We considered various geopolitical risk (GPR) indices, economic policy uncertainty (EPU) indices, and infectious disease pandemic (IDEMV) indices in our model. The empirical results suggest that the geopolitical risk, the geopolitical act risk, the global economic policy uncertainty, the economic policy uncertainty from the United Kingdom, and the economic policy uncertainty from Japan comprehensively integrate the information contained in the rest factors, and have superior predictive powers for INE crude oil future volatility. These findings highlight the importance of the impact of macroeconomic uncertainty factors has on the crude oil futures market, and indicate that the macroeconomic uncertainties need to be considered when explaining and forecasting crude oil futures market volatility.

Description: The soil microbiome consists of a vast variety of microorganisms which contribute to essential ecosystem services including nutrient recycling, protecting soil structure, and pathogen suppression. Recalcitrant organic compounds present in soils contaminated with fuel oil can lead to a decrease in functional redundancy within soil microbiomes. Ecopiling is a passive bioremediation technique involving biostimulation of indigenous hydrocarbon degraders, bioaugmentation through inoculation with known petroleum-degrading consortia, and phytoremediation. The current study investigates the assemblage of soil microbial communities and pollutant-degrading potential in soil undergoing the Ecopiling process, through the amplicon marker gene and metagenomics analysis of the contaminated soil. The analysis of key community members including bacteria, fungi, and nematodes revealed a surprisingly diverse microbial community composition within the contaminated soil. The soil bacterial community was found to be dominated by Alphaproteobacteria (60–70%) with the most abundant genera such as Lysobacter, Dietzia, Pseudomonas, and Extensimonas. The fungal community consisted mainly of Ascomycota (50–70% relative abundance). Soil sequencing data allowed the identification of key enzymes involved in the biodegradation of hydrocarbons, providing a novel window into the function of individual bacterial groups in the Ecopile. Although the genus Lysobacter was identified as the most abundant bacterial genus (11–46%) in all of the contaminated soil samples, the metagenomic data were unable to confirm a role for this group in petrochemical degradation. Conversely, genera with relatively low abundance such as Dietzia (0.4–9.0%), Pusillimonas (0.7–2.3%), and Bradyrhizobium (0.8–1.8%) did possess genes involved in aliphatic or aromatic compound degradation.

Description: The current study investigates the effect of large-scale channel modifications via riverine dredging on flood dynamics in low-gradient river systems located in inland-coastal flood transition zones. The study site is the Vermilion River in south Louisiana, US, which is characterized by complex flow regimes, reversal and bi-directional flows, presence of large swamps with significant river-swamp interactions, and large volumes of runoff contributions from lateral tributaries. The study aims to understand the interplay of these factors and how they modulate and get affected by different dredging approaches that vary in spatial extent and the modifications introduced to the channel. The study deploys a hybrid, one-/two-dimensional (1D/2D), hydrodynamic model that simulates flow and stage dynamics in the main river and its major tributaries, as well as the flow exchanges with the interconnected swamp system. Overall, the results show that the dredging activities can significantly alter the flow regime in the watershed and affect flow exchanges between the river and the swamp system. In terms of flooding impact, only dredging approaches that are extensive in spatial extent and modifications to channel longitudinal slope can result in sizeable reductions in flood stages. However, these benefits come at the expense of significant increases in the amplitude and inland propagation of the Gulf tidal wave. On the other hand, less-extensive dredging can still provide moderate and spatially limited flood mitigation; however, they further expose downstream communities to increased levels of flooding, especially during more frequent events. The results reveal that while dredging can increase the hydraulic conveyance of the river system, the large runoff volumes delivered by the urbanized tributaries seem to outweigh the added improvement in the in-channel storage, thus reducing the anticipated flood relief. The results suggest that a watershed-centered approach, instead of a riverine-centered approach is needed for flood management in these systems so that the relative benefits and tradeoffs of different mitigation alternatives can be examined.

Description: Alongside the rapid expansion of wind power installation in China, wind curtailment is also mounting rapidly due to China’s energy endowment imbalance. The hydrogen-based wind-energy storage system becomes an alternative to solve the puzzle of wind power surplus. This article introduced China’s energy storage industry development and summarized the advantages of hydrogen-based wind-energy storage systems. From the perspective of resource conservation, it estimated the environmental benefits of hydrogen-based wind-energy storages. This research also builds a valuation model based on the Real Options Theory to capture the distinctive flexible charging and discharging features of the hydrogen-based wind-energy storage systems. Based on the model, simulation results, including the investment value and operation decision of the hydrogen energy storage system with different electricity prices, system parameters, and different levels of subsidies, are presented. The results show that the hydrogen storage system fed with the surplus wind power can annually save approximately 2.19–3.29 million tons of standard coal consumption. It will reduce 3.31–4.97 million tons of CO2, SO2, NOx, and PM, saving as much as 286.6–429.8 million yuan of environmental cost annually on average. The hydrogen-based wind-energy storage system’s value depends on the construction investment and operating costs and is also affected by the mean-reverting nature and jumps or spikes in electricity prices. The market-oriented reform of China’s power sector is conducive to improve hydrogen-based wind-energy storage systems’ profitability. At present, subsidies are still essential to reduce initial investment and attract enterprises to participate in hydrogen energy storage projects.

Description: There is currently a scarcity of paired in-situ aquatic optical and biogeophysical data for productive inland waters, which critically hinders our capacity to develop and validate robust retrieval models for Earth Observation applications. This study aims to address this limitation through the development of a novel synthetic dataset of top-of-atmosphere and bottom-of-atmosphere reflectances, which is the first to encompass the immense natural optical variability present in inland waters. Novel aspects of the synthetic dataset include: 1) physics-based, two-layered, size- and type-specific phytoplankton inherent optical properties (IOPs) for mixed eukaryotic/cyanobacteria assemblages; 2) calculations of mixed assemblage chlorophyll-a (chl-a) fluorescence; 3) modeled phycocyanin concentration derived from assemblage-based phycocyanin absorption; 4) and paired sensor-specific top-of-atmosphere reflectances, including optically extreme cases and the contribution of green vegetation adjacency. The synthetic bottom-of-atmosphere reflectance spectra were compiled into 13 distinct optical water types similar to those discovered using in-situ data. Inspection showed similar relationships of concentrations and IOPs to those of natural waters. This dataset was used to calculate typical surviving water-leaving signal at top-of-atmosphere, and used to train and test four state-of-the-art machine learning architectures for multi-parameter retrieval and cross-sensor capability. Initial results provide reliable estimates of water quality parameters and IOPs over a highly dynamic range of water types, at various spectral and spatial sensor resolutions. The results of this work represent a significant leap forward in our capacity for routine, global monitoring of inland water quality.

Description: Hydrate-based gas separation is a potential technology for CO2 recovery and storage, and its products can be used for fire prevention and control in mines. Promoters are often employed to accelerate or moderate hydrate formation. In this study, experiments were performed to examine the effects of different concentrations of the thermodynamic promoter tetrahydrofuran (THF) and kinetic promoter sodium dodecyl sulphate (SDS) on CO2 hydrate formation under stirring. The results showed that THF significantly shortens the induction time of CO2 hydrates; however, because THF occupies a large cavity in the hydrate structure, it also reduces the gas absorption and hydrate formation rate. SDS has no obvious effect on the induction time of hydrates, but it can increase the gas storage density and hydrate formation rate. Using THF and SDS together consumed more CO2 than using THF alone or pure water. The peak gas consumption rate was 2.3 times that of the THF system. The hydrate formation efficiency was improved by including both THF and SDS, which maximized both the hydrate formation rate and total gas uptake.

Description: Agricultural residues have been traditionally used as energy resources for many years. In light of current environmental and fossil fuel supplies for energy applications, agricultural residues are regarded as sustainable supplies for energy production. However, the suitability to be renewable fuel and as a co-fuel in coal combustion facilities has to be investigated. A thermal analysis was conducted to investigate the effect of the blending and heating rate of the thermal behavior of Malaysian bituminous coal (Silantek), oil palm biomass (empty fruit bunch), and their blends using thermogravimetric analysis. The investigation was done in an inert atmosphere at the heating rate of 10, 20, and 40°C/min. Characteristics including proximate, ultimate, and calorific analyses were also examined. Six different mass ratios were selected from both samples to study the effect of blending of the two materials. The results showed that thermal degradation of empty fruit bunch (EFB) occurred in three stages while Silantek coal (SC) only involved two regions due to their different fuel properties. The blending of both SC/EFB did not follow their individual samples, which showed non-additive behavior suggesting that there is an interaction between coal and biomass. The outcome of this research provides insight on the behavior of Malaysian bituminous coal and oil palm biomass, which enhances knowledge for the future of energy generation.

Description: To solve the global water shortages and serious water pollution problems, research on semiconductor photocatalysts has generated significant research attention. The degradation of pollutants by titanium dioxide (TiO2) exceeds other semiconductor materials. However, its wide bandgap restricts the photocatalytic reaction under visible light. The large specific surface area and good thermal conductivity of graphene yielded an effective graphene-TiO2 catalyst combination effective under visible light. 2D graphene-TiO2 composites (2D-GTC) have shown promise, so a study of the preparation methods, mechanism and catalytic effect of different pollutants on this material was undertaken. In this current review, the characteristics of different graphene and TiO2 composites and their preparation methods, as well as the effects of different synthesis methods on the catalyst are introduced. The reaction mechanism of 2D-GTC catalysts, the degradation effects of different pollutants in water are all reviewed.

Description: Efforts to include more detailed representations of biogeochemical processes in basin-scale water quality simulation tools face the challenge of how to tractably represent mass exchange between the flowing channels of streams and rivers and biogeochemical hotspots in the hyporheic zones. Multiscale models that use relatively coarse representations of the channel network with subgrid models for mass exchange and reactions in the hyporheic zone have started to emerge to address that challenge. Two such multiscale models are considered here, one based on a stochastic Lagrangian travel time representation of advective pumping and one on multirate diffusive exchange. The two models are formally equivalent to well-established integrodifferential representations for transport of non-reacting tracers in steady stream flow, which have been very successful in reproducing stream tracer tests. Despite that equivalence, the two models are based on very different model structures and produce significantly different results in reactive transport. In a simple denitrification example, denitrification is two to three times greater for the advection-based model because the multirate diffusive model has direct connections between the stream channel and transient storage zones and an assumption of mixing in the transient storage zones that prevent oxygen levels from dropping to the point where denitrification can progress uninhibited. By contrast, the advection-based model produces distinct redox zonation, allowing for denitrification to proceed uninhibited on part of the hyporheic flowpaths. These results demonstrate that conservative tracer tests alone are inadequate for constraining representation of mass transfer in models for reactive transport in streams and rivers.

Description: Climate services, and research on climate services, have mutually developed over the past 20 years, with quality assessment a central issue for orienting both practitioners and researchers. However, quality assessment is becoming more complex as the field evolves, the range and types of climate services expands, and there is an increasing appeal to co-production of climate services. Scholars describe climate services as emerging from complex knowledge systems, where information moves through institutions and actors attribute various qualities to these services. Seeing climate services' qualities as derived from and activated in knowledge systems, we argue for comprehensive assessment conducted with an extended peer community of actors from the system; co-evaluation. Drawing inspiration from Knowledge Quality Assessment and post-normal science traditions, we develop the Co-QA assessment framework; a checklist-based framework for the co-creation of criteria to assess the quality of climate services. The Co-QA framework is a deliberation support tool for critical dialogue on the quality of climate services within a co-construction collective. It provides a novel, structured, and comprehensive way to engage an extended peer community in the process of quality assessment of climate services. We demonstrate how we tested the Co-QA—through interviews, focus groups and desktop research—in two co-production processes of innovative climate services; an ex post evaluation of the “Klimathon” in Bergen, Norway, and an ex ante evaluation for designing place-based climate services in Dordrecht, the Netherlands. These cases reveal the challenges of assessing climate services in complex knowledge systems, where many concerns cannot be captured in straight-forward metrics. And they show the utility of the Co-QA in facilitating co-evaluation.

Description: The coronavirus pandemic is an unprecedented event, putting global supply chains (SCs) into the focus of a wider public. Yet it is unclear what is communicated about this and how and what consequences SC management (SCM) would take away. This research aims at analyzing how text mining can provide insights on the impact of the coronavirus pandemic on SCs, focusing on the implications of the pandemic for the SC constructs related to risk, resilience, and sustainability. A method applies text mining of general newspapers as well as SC and logistic newspaper articles employing the open-source software R. This paper shows that certain SC topics like risk, resilience, disruption, and sustainability vary in their news coverage on the type of newspaper and the number of coronavirus disease 2019 (COVID-19) infections. It reassures trends and observations from individual experiences on a broader and global picture and discusses the limitations and possibilities of using text mining in this field. The time period was split into three phases regarding the course of the number of infections and differences in the news coverage of the phases that can be distinguished already: (1) the onset of the crisis, (2) the peak and lockdown, and (3) managing SCs during the crisis. As this pandemic is highly dynamic, is new, and has not yet ended, research implications are too early to make. This research rather serves as a base for further, more detailed research into certain topics and identifies limitations and improvements of the applied method. Due to the method chosen and the timeliness of data, this empirical research is unique and can be of great help to see trends and patterns to further deep dive into specific areas.

Description: The amount of waste generation has been increasing with a significant amount being landfilled. These non-recyclable wastes contain large number of fiber and plastic wastes which can be treated with thermal processes to turn them into energy sources since they have high calorific values, are abundant and usually tipping fees are paid to handle them. This paper studied the torrefaction of non-recyclable paper (fiber) wastes, mixed plastic wastes (MPW) and their blends at different ratios in the temperature range of 250–400°C through thermogravimetric analysis (TGA). The solid residues after the experiments were analyzed by nuclear magnetic resonance (NMR) spectroscopy. Significant synergy between fiber and MPW were observed at the range 250–300°C, showing both increase in the reaction rate as well as the overall mass loss. At 250°C, the maximum mass loss rate was more than two times higher and the mass loss at the end of the experiments were also much higher compared to the expected results. In addition, synergy was weakened with an increase of temperature, disappearing at 400°C. The existence of such interactions between fiber and plastic wastes indicates that the natural energy barriers during the individual torrefaction in paper waste or plastic waste could be bypassed, and the torrefaction of fiber and plastic blend can be achieved at lower temperatures and/or shorter residence times. The MPW and fiber wastes were also compounded by extrusion (to produce pellets) at 220°C with different blend ratios. The fiber-MPW pellets from extrusion were characterized by IR spectroscopy, rheology, thermal analysis and flexural properties and showed significant chemical changes from the non-extruded blends at the same ratios. From IR characterization, it was found that there was significant increase in hydroxyl (OH) group on account of the carbonyl (C = O) and etheric (C-O-C) groups. The interaction between paper and MPW can be attributed to the plastic polymers acting as a hydrogen donor during the reactive extrusion process. Synergistic effects were also found from mechanical and rheological properties.

Description: Measuring the expected impact of China’s energy transition on carbon dioxide (CO2) mitigation and identifying the key influencing factors in different economic sectors will help to provide better policy recommendations for CO2 emission reduction. Based on the prediction results of China’s CO2 emissions in 2030 under the baseline scenario and the target scenario, this study constructs the control group and the treatment group of the energy transition policy quasinatural experiment and then uses the difference in difference (DID) model to evaluate the CO2 emission reduction effect of China’s energy transition policy. The results reveal that the energy transition policy has a significant impact on CO2 emission reduction and helps to achieve China’s 2030 carbon emission reduction target. The impact of energy structure transition on CO2 emission reduction has significant sectoral heterogeneity, which has a positive reduction effect in the industry sector, wholesale and retail sectors, and accommodation and catering sectors, but its reduction effect is not obvious in transportation, storage, and postal sectors. It is suggested that China should implement the sector-differentiated CO2 mitigation strategy, focus on improving the industrial sector’s energy efficiency, and promote the clean, low-carbon transition of energy consumption structure in construction, transportation, storage, and postal industries.

Description: The electrocatalytic CO2 reduction reaction (CO2RR) is considered as one of the most promising approaches to synthesizing carbonaceous fuels and chemicals without utilizing fossil resources. However, current technologies are still in the early phase focusing primarily on identifying optimal electrode materials and reaction conditions. Doped graphene-based materials are among the best CO2RR electrocatalysts and in the present work we have performed a computational screening study to identify suitable graphene catalysts for CO2RR to CO under alkaline conditions. Several types of modified-graphene frameworks doped with metallic and non-metallic elements were considered. After establishing thermodynamically stable electrodes, the electrochemical CO2RR to CO is studied in the alkaline media. Both concerted proton-coupled electron transfer (PCET) and decoupled proton and electron transfer (ETPT) mechanisms were considered by developing and using a generalization of the computational hydrogen electrode approach. It is established that the CO2 electrosorption and associated charge transfer along the ETPT pathway are of utmost importance and significantly impact the electrochemical thermodynamics of CO2RR. Our study suggests an exceptional performance of metal-doped nitrogen-coordinated graphene electrodes, especially 3N-coordinated graphene electrodes.

Description: Coronavirus disease 2019 (COVID-19) is seriously threatening and altering human society. Although prevention and control measures play an important role in preventing the transmission of severe acute respiratory syndrome coronavirus, signals of climate impact can still be detected globally. In this paper, the data of 265 cities in China were analyzed. The results show that the correlations between COVID-19 and air quality index (AQI) and PM2.5 concentration were very weak and that the correlations between COVID-19 and meteorological factors were significantly different in different climate backgrounds. So, a fixed model is not enough to describe the correlations. Overall, high humidity, low wind speed, and relatively lower air temperature are conducive to the spread of COVID-19. The climate background suitable for the spread of COVID-19 in China is air temperature 0~15°C, specific humidity

Description: Due to the irreversibility of heavy metal pollution, the presence of heavy metals in farmland soil is associated with severe ecological risks that endanger both the environment and human health. Cadmium (Cd) and mercury (Hg) are two toxic heavy metals found widely in polluted soil. Cd is not readily fixed in the soil and is therefore easily accumulated by plants, while Hg has a wide range of pollution sources. The aims of this study were to explore the spatial variation in Cd and Hg concentrations in farmland soil in Poyang Lake Plain, China, and to assess their potential ecological risks as influenced by natural and human factors. A total of 283 soil samples were obtained from Fengcheng city, central Jiangxi Province. Data were then analyzed using geostatistics, the potential ecological risk index, Pearson’s correlation analysis, and Geodetector. The results showed moderate variation in soil Cd and Hg concentrations, with a remarkable difference in their spatial distribution. Cd concentrations in the northwest and northeast of Fengcheng were below the regional background level in Jiangxi; in most remaining areas, Cd concentrations were between the regional background level and national risk screening value. Areas with Hg concentrations lower than the regional background level were largely concentrated in the south, east and north of Fengcheng, and gradually increased towards the central, where they exceeded the regional background level but were below the national risk screening value. Overall, the potential ecological risk level of Cd was predominantly low, while that of Hg was moderate. The comprehensive potential ecological risk was low in most areas for both Cd and Hg, with some scattered areas of moderate risk. Moreover, the comprehensive potential ecological risk index of both Cd and Hg was significantly correlated with soil pH, total phosphorous, elevation, distance from a river (p 〈 0.01), and distance from a road (p 〈 0.05). The most significant factor influencing the comprehensive potential ecological risk index of these two heavy metals was soil pH of 5.2–5.6, followed by total p ≤ 0.52 mg kg−1. In conclusion, moderate pollution of Cd and Hg occurred in farmland soil in Poyang Lake Plain where their comprehensive potential ecological risk level was generally low and mainly influenced by soil pH and total phosphorous.

Description: The rapid development in data science and the increasing availability of building operational data have provided great opportunities for developing data-driven solutions for intelligent building energy management. Data preprocessing serves as the foundation for valid data analyses. It is an indispensable step in building operational data analysis considering the intrinsic complexity of building operations and deficiencies in data quality. Data preprocessing refers to a set of techniques for enhancing the quality of the raw data, such as outlier removal and missing value imputation. This article serves as a comprehensive review of data preprocessing techniques for analysing massive building operational data. A wide variety of data preprocessing techniques are summarised in terms of their applications in missing value imputation, outlier detection, data reduction, data scaling, data transformation, and data partitioning. In addition, three state-of-the-art data science techniques are proposed to tackle practical data challenges in the building field, i.e., data augmentation, transfer learning, and semi-supervised learning. In-depth discussions have been presented to describe the pros and cons of existing preprocessing methods, possible directions for future research and potential applications in smart building energy management. The research outcomes are helpful for the development of data-driven research in the building field.

Description: This article presents a case study of distributed generation and flexibility potential for a multienergy system in an urban district in Singapore. The analysis incorporates real-life data of a local energy system consisting of flexible loads (i.e., district cooling demand from air-conditioned buildings) and distributed generators (DGs) (i.e., waste-to-energy (W2E) generators and photovoltaic (PV) generators) from a representative study area. The demand-side flexibility (DSF) potentials from air-conditioned buildings are derived based on a state-space model and its underlying base load estimation. Besides the conventional consideration of PV system integration in the urban environment, we conducted a feasibility study of the distributed W2E technology deployment and estimated the generation potentials for the study area. Furthermore, to facilitate flexibility and energy exchange, market frameworks are proposed to harvest energy and flexibility from distributed energy resources (DERs) and in the real-time market context in Singapore.

Description: Due to the important role of ammonia as a fertilizer in the agricultural industry and its promising prospects as an energy carrier, many studies have recently attempted to find the most environmentally benign, energy efficient, and economically viable production process for ammonia synthesis. The most commonly utilized ammonia production method is the Haber-Bosch process. The downside to this technology is the high greenhouse gas emissions, surpassing 2.16 kgCO2-eq/kg NH3 and high amounts of energy usage of over 30 GJ/tonne NH3 mainly due to the strict operational conditions at high temperature and pressure. The most widely adopted technology for sustainable hydrogen production used for ammonia synthesis is water electrolysis coupled with renewable technologies such as wind and solar. In general, a water electrolyzer requires a continuous supply of pretreated water with high purity levels for its operation. Moreover, for production of 1 tonne of hydrogen, 9 tonnes of water is required. Based on this data, for the production of the same amount of ammonia through water electrolysis, 233.6 million tonnes/yr of water is required. In this paper, a critical review of different sustainable hydrogen production processes and emerging technologies for sustainable ammonia synthesis along with a comparative life cycle assessment of various ammonia production methods has been carried out. We find that through the review of each of the studied technologies, either large amounts of GHG emissions are produced or high volumes of pretreated water is required or a combination of both these factors occur.

Description: High-throughput roll-to-roll (R2R) manufacturing of perovskite solar cells (PSCs) is currently limited by thermal processes that take tens of minutes each, translating to impractically long annealing tools at high web speeds. In addition, PSCs are usually made with metal oxide transport layer materials that require high temperatures for thermal annealing. Here, we demonstrate the fabrication of PSCs using photonic curing, instead of thermal annealing, to convert NiOx directly from sol-gel precursors for hole transport layers and to crystallize methylammonium lead iodide (MAPbI3) active layers on flexible Willow® Glass substrates. Photonic curing uses short, intense pulses of light to process materials at a high speed, hence it is compatible with R2R manufacturing. We achieved power conversion efficiencies (PCEs) of 11.7% in forward-scan and 10.9% in reverse-scan for PSCs made with photonic cured NiOx and MAPbI3 films. Furthermore, both NiOx and MAPbI3 films could be processed with a single photonic curing pulse, with a web speed of 5.7 m/min, and still produce PCEs comparable to thermally annealed control samples. Based on the single-pulse photonic curing condition for each film, we project a web speed of 26 m/min, laying a pathway to high-throughput production of perovskite solar modules.

Description: The integrity of data is an essential basis for analyzing power system operating status based on data. Improper handling of measurement sampling, information transmission, and data storage can lead to data loss, thus destroying the data integrity and hindering data mining. Traditional data imputation methods are suitable for low-latitude, low-missing-rate scenarios. In high-latitude, high-missing-rate scenarios, the applicability of traditional methods is in doubt. This paper proposes a reconstruction method for missing data in power system measurement based on LSGAN (Least Squares Generative Adversarial Networks). The method is designed to train in an unsupervized learning mode, enabling the neural network to automatically learn measurement data, power distribution patterns, and other complex correlations that are difficult to model explicitly. It then optimizes the generator parameters using the constraint relations implied by true sample data, enabling the trained Generator to generate highly accurate data to reconstruct the missing data. The proposed approach is entirely data-driven and does not involve mechanistic modeling. It can still reconstruct the missing data in the case of high latitude and high loss rate. We test the effectiveness of the proposed method by comparing three other GAN derivation methods in our experiments. The experimental results show that the proposed method is feasible and effective, and the accuracy of the reconstructed data is higher while taking into account the computational efficiency.

Description: Energy is a crucial development indicator of production, consumption, and nation-building. However, energy diversification highlighting renewables remains salient in economic development across developing economies. This study explores the economic impact of renewables (RE) and fossil fuel (NRE) utilization in 17 emerging nations. We use annual data with timeframe between 1980 and 2016 and propose a bootstrap panel causality approach with a Fourier function. This allows the examination of multiple structural breaks, cross-section dependence, and heterogeneity across countries. We validate four main hypotheses on the causal links attached to the energy consumption (EC)-growth nexus namely neutrality, conservation, growth, and feedback hypotheses. The findings reveal a causal relationship running from RE to GDP for Brazil, Egypt, Indonesia, Korea, Pakistan, and the Philippines, confirming the growth hypothesis. Besides, the results validate the conservation hypothesis with causality from GDP to RE for China, Colombia, Egypt, Greece, India, Korea, South Africa, and Turkey. We identify causality from NRE to GDP for Pakistan, Mexico, Malaysia, Korea, India, Greece, Egypt, and Brazil; and from GDP to NRE for Thailand, Peru, Malaysia, India, Greece, Egypt, and Colombia. We demonstrate that wealth creation can be achieved through energy diversification rather than relying solely on conventional energy sources.

Description: Nitrogen (N) is the most critical element limiting agricultural production at a global scale. Despite many efforts, the N use efficiency (NUE) in agriculture remains in a range of less than 50%. Reaching targeted crop yields has resulted in N overuse, which is an economic and environmental concern worldwide. The continuous exploration of innovative solutions has led to the synthesis of novel nanomaterials, resulting in a powerful tool for the development of new technological products. Nanofertilizers are one of the most promising engineered materials that are being tested, either for soil or foliar applications. Encouraging results have been obtained using nanofertilizers in different plant species, however, limited information has been reported about its use in grasslands. Commonly, N is applied to grassland soils as granular fertilizers, which may result in significant losses via surface runoff or leaching, ammonia (NH3) volatilization and N oxides (N2O, NO, NOx) emissions. Nitrogen nanofertilizers are expected to increase NUE by improving the effectiveness of N delivery to plants and reducing N losses to the environment. Information on the efficiency of the use of N nanofertilizers in grasslands species is scarce and the application strategies that can be used to avoid N losses are poorly understood. New scenarios of increasing economic and environmental constraints may represent an opportunity for N nanofertilizers application in grasslands. This article reviews its potential use as an innovative approach to improve NUE and reduce N losses to the wider environment, analyzing potential shortcomings and future considerations for animal food chains.

Description: Adaptive capacity determines the extent to which exposure to natural hazards and extreme events translates into impacts. This study traces the effectiveness of adaptive capacity of two different sugarcane contract farming schemes (so-called outgrower schemes)—Phata and Kasinthula—in Chikwawa district in southern Malawi which, due to their proximity, are similarly exposed to extreme events, but have shown different impacts in terms of sugarcane production. We develop a framework to explore and compare the adaptive capacity at scheme management level, and relate the findings to the historical changes in yield, the occurrence of extreme events in the district and the lived experiences of the scheme management over the last ten years (2010–2019) using qualitative data from interviews with scheme managers. The total level and components of adaptive capacity differ in several aspects. Phata had much better prerequisites to mitigate the impacts of the extreme events (i.e., maintain production), particularly related to the Asset base, Knowledge and information, Innovation, and Forward-looking decision-making. Kasinthula on the other hand, was impacted by compound events whilst having low financial capacity, weak governance and reduced human capacity. Kasinthula had limited capacity to recover from the severe 2015 floods, the adaptive capacity thus drawn upon and were not restored when next event occurred (drought). This novel, comparative approach to assessing adaptive capacity, linking to past events, has been shown useful in order to determine the components that are missing and need to be built in order to reduce risk from extreme events and climate change. These findings are important to ensure future adaptation of sugarcane outgrowers, and relevant also to other contract farming arrangements or similar kinds of agricultural organizations.

Description: It is now widely recognized that in order to reach the target of limiting global warming to well below 2°C above pre-industrial levels (as the objective of the Paris agreement), cutting the carbon emissions even at an unprecedented pace will not be sufficient, but there is the need for development and implementation of active Carbon Dioxide Removal (CDR) strategies. Among the CDR strategies that currently exist, relatively few studies have assessed the mitigation capacity of ocean-based Negative Emission Technologies (NET) and the feasibility of their implementation on a larger scale to support efficient implementation strategies of CDR. This study investigates the case of ocean alkalinization, which has the additional potential of contrasting the ongoing acidification resulting from increased uptake of atmospheric CO2 by the seas. More specifically, we present an analysis of marine alkalinization applied to the Mediterranean Sea taking into consideration the regional characteristics of the basin. Rather than using idealized spatially homogenous scenarios of alkalinization as done in previous studies, which are practically hard to implement, we use a set of numerical simulations of alkalinization based on current shipping routes to quantitatively assess the alkalinization efficiency via a coupled physical-biogeochemical model (NEMO-BFM) for the Mediterranean Sea at 1/16° horizontal resolution (~6 km) under an RCP4.5 scenario over the next decades. Simulations suggest the potential of nearly doubling the carbon-dioxide uptake rate of the Mediterranean Sea after 30 years of alkalinization, and of neutralizing the mean surface acidification trend of the baseline scenario without alkalinization over the same time span. These levels are achieved via two different alkalinization strategies that are technically feasible using the current network of cargo and tanker ships: a first approach applying annual discharge of 200 Mt Ca(OH)2 constant over the alkalinization period and a second approach with gradually increasing discharge proportional to the surface pH trend of the baseline scenario, reaching similar amounts of annual discharge by the end of the alkalinization period. We demonstrate that the latter approach allows to stabilize the mean surface pH at present day values and substantially increase the potential to counteract acidification relative to the alkalinity added, while the carbon uptake efficiency (mole of CO2 absorbed by the ocean per mole of alkalinity added) is only marginally reduced. Nevertheless, significant local alterations of the surface pH persist, calling for an investigation of the physiological and ecological implications of the extent of these alterations to the carbonate system in the short to medium term in order to support a safe, sustainable application of this CDR implementation.

Description: Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.

Description: Resilience thinking is increasingly promoted to address some of the grand challenges of the 21st century: providing water, energy, and food to all, while staying within the limits of the Earth system that is undergoing (climate) change. Concurrently, a partially overlapping body of literature on the water–energy–food (WEF) nexus has emerged through the realization that water, energy, and food systems are intricately linked—and should therefore be understood and managed in conjunction. This paper reviews recent scientific publications at the intersection of both concepts in order to i) examine the status quo on resilience thinking as it is applied in WEF nexus studies; ii) map the research landscape along major research foci and conceptualizations; iii) and propose a research agenda of topics distilled from gaps in the current research landscape. We identify key conceptualizations of both resilience and nexus framings that are used across studies, as we observe pronounced differences regarding the nexus’ nature, scope, emphasis and level of integration, and resilience’s scope, type, methodological and thematic foci. Promising research avenues include i) improving the understanding of resilience in the WEF nexus across scales, sectors, domains, and disciplines; ii) developing tools and indicators to measure and assess resilience of WEF systems; iii) bridging the implementation gap brought about by (governing) complexity; iv) integrating or reconciling resilience and nexus thinking; v) and considering other development principles and frameworks toward solving WEF challenges beside and beyond resilience, including control, efficiency, sustainability, and equity.

Description: Subsidy policy to electric vehicles in China was initially launched in 2001. This study uses the perspective of the characteristics of subsidy policy and applies generalized propensity score matching (GPS) to estimate the impact of different subsidy policy intensities on the change in consumer demand for EVs and find the interval to optimize. The study shows that the optimization interval of the policy is in the 40%–70% treatment level, which maximizes the effect of the subsidy on China’s EVs. For a treatment effect lower than 40%, it is difficult to effectively create an incentive to enter the EVs market in China because consumers think that the product is difficult to satisfy the demand of too low technology; by contrast, for the treatment level higher than 70%, the cost of the high endurance mileage power battery increases exponentially, and the complementary effect of subsidies is insufficient. Consequently, we propose three suggestions: The government should 1) use big data technology to supervise subsidies and design a real-time reporting mechanism and punishment mechanism for subsidy-misuse; 2) adopt the incentive regulation to promote the battery range of new energy vehicles (e.g., optimizing the subsidy ladder, innovating the form of subsidies) and gradually eliminate low-technology product; and 3) reasonably design a targeted regulatory mechanism that increases the cost of fraud and breach of contract to encourage firms to truthfully report technical indicators.

Description: Molecular crystals have attracted increasing attention as a candidate for innovative solid electrolytes with solid-state Mg-ion conductivity. In this work, we synthesized a novel Mg-ion-conducting molecular crystal, Mg{N(SO2CF3)2}2(CH3OC5H9)2 (Mg(TFSA)2(CPME)2), composed of Mg bis(trifluoromethanesulfonyl)amide (Mg(TFSA)2) and cyclopentyl methyl ether (CPME) and elucidated its crystal structure. We found that the obtained Mg(TFSA)2(CPME)2 exhibits solid-state ionic conductivity at room temperature and a high Mg-ion transference number of 0.74. Contrastingly, most Mg-conductive inorganic solid electrolytes require heating above 150–300°C to exhibit ionic conductivity. These results further prove the suitability of molecular crystals as candidates for Mg-ion-conducting solid electrolytes.

Description: Production of safe food in the densely populated areas of the developing countries is the most challenging issue due to the speedy urbanization, fragile food transportation facilities, and reduced farmlands. Given this background, a study was conducted to evaluate the agronomic properties and economic viability of lettuce grown vertically in the wall of building in Dhaka city, Bangladesh. Two lettuce cultivars (V1: Green wave and V2: New red fire) and three organic growing media (P1: 40% soil + 40% vermicompost + 20% coir; P2: 50% soil + 50% vermicompost; P3: 20% soil + 40% vermicompost + 40% spent mushroom compost) along with control (P0:100% soil) were used. The results revealed that plant height, leaf area, fresh weight, dry weight, and total yield of leaf lettuce were significantly increased when the green-leafed cultivar (VI) was grown in the P1 compared to all other treatments, but V2 got maximum sensory attribute scores when grown in the P1. Lettuce leaves grown in the formulated growing media (P1, P2, and P3) had higher microbial infestation whereas, a lower content occurred in the P0. The higher economic return was observed in V1P1. These results provided baseline information for further study on urban commercial vertical farming on the building walls. These demonstrate the agronomic and economic potential for vertical farming in densely populated areas but emphasize the need for optimized food safety strategies.

Description: Microplastic pollution is omnipresent in biota around the globe, and concerns are rising that humans are exposed to microplastics (MP) through food. Investigations of MP in wild animals relevant for human consumption and the effects in exposed birds and mammals is warranted. We investigated the concentrations of MP in organs and tissues of fish, seabirds, terrestrial and marine mammals from a plastic polluted area near Bergen, Norway. A standardized autopsy included evaluation of condition, bacteriological and histopathological analyzes. Tissues were analyzed for MP (〉10 µm) by pyrolysis Gas Chromatography Mass Spectrometry (py-GCMS) and inspected by polarized light microscopy. We analyzed samples of stomach and intestinal wall, liver and muscle/fillet from three flounders, three cod, three seabirds, three otters and one seal, kidneys from seabirds, otters and the seal, and gills from the fishes. No large plastic items were observed in the gastrointestinal tracts. Eight of 13 animals had MP in one or several tissues. MP was found in intestine (5), stomach (4), liver (3), muscle (3). No MP was found in the seal, and only in the stomach wall of one otter. In seabirds, MP was found in the intestine, stomach and liver, but not muscle. The highest concentration was 3.4 µg/g wet weight in cod liver. Three of the nine investigated polymers were found above the Limit of Quantification (LOQ): Polyvinylchloride〉polystyrene〉〉polyethylene terephthalate. MP was quantified in one of four replicates of cod muscle and one of two replicates of cod liver. No MP was observed by microscopy. The results show levels under or close to the current LOQ. Replicates indicate uneven MP distribution in tissues and resulted in higher prevalence of MP for cod. No adverse effects could be related to MP. The sample size was small, and conclusions cannot be drawn regarding effects or risks. The animals were by-catch, and mostly in good condition when caught. Procedural blanks and air-controls showed very low MP, and support that the MP come from environmental sources. Further studies are needed to determine levels of microplastic in edible tissues and the current wildlife exposure through the food web.