Resources Environment and Sustainability最新文献

An energy-efficient disintegration approach used to produce biohydrogen from marine macroalgae biomass (Chaetomorpha antennina) was demonstrated in this study. The suggested research aimed to explain the function of macroalgae disintegration by sonication (DS) and disintegration by a sonic surfactant (DSS) in biohydrogen production. Biosurfactant dosage (3 $\mu$L/g TS), sonic intensity (50%) and disintegration duration (30 min) were found to be an optimum conditions for DSS with respect to dissoluted organics release (DOR). Volatile fatty acids (VFA) generation was higher in DSS (1845 mg/L) than DS (864 mg/L) When DS and DSS were compared, DSS had a substantially higher disintegration efficiency (DE) and biohydrogen yield (26%, 147 mL $H_2$/gCOD) than DS (21.5%, 121 mL $H_2$/gCOD). Net energy (NE) obtained in DSS (0.044 kWh/kg of biomass) was more than the DS (−0.02 kWh/kg of biomass). DSS had a higher energy ratio of 1.8, while DS had a lower energy ratio of 0.7. Overall, DSS was found to be an energetic way to produce biohydrogen.

Switzerland is a country that has ambitious agri-environmental objectives, but its targets are continuously missed. The paper at hand examines this contradiction by describing and analysing three recent attempts to transform agricultural policies and change the unfortunate situation. The three cases were compared in a qualitative multimethod research design and along dimensions that are potentially relevant for explaining reform failures. While the attempts depicted involved distinctive governance pathways, they all failed to meet their objectives because of the large disadvantages their realisation would have generated. These included, above all, a reduction of the national self-sufficiency rate. It is concluded that the strategy of providing incentives for mere extensification has reached a dead end. New strategies to tackle food consumption patterns appear to be more promising.

Green waste is a diverse mixture of biomass mainly generated through site clearing and landscape maintenance in inhabited areas, which requires appropriate management to address sustainability concerns. However, the recycling potential and technological applicability of green waste remain poorly understood possibly due to limited knowledge of its complicated generation and composition characteristics. This review provides a comprehensive overview of the scope, generation, characteristics, and mainstream recycling technologies of green waste. Based on our synthesis, the average annual green waste generation is around 47 kg/person, but differences in performance vary between countries. The green waste generation is mainly related to green space area, radiation, and rainfall. In the light of the characteristics of nutrient and lignocellulose contents, separately recycling the green (grass and leaves) and brown parts (branches) is identified as a promising approach. From both environmental and economic perspectives, the brown part is suitable for energy recovery, while composting for nutrients recovery is more preferred for the green part. This study highlights that proper combination of recycling technologies would turn green waste into a valuable resource, which would help move towards a more resource-efficient and circular economy to address future sustainability challenges.

About 12% of the EU’s greenhouse gas emissions derive from construction of and energy use in buildings. To decrease energy use in buildings, more energy-efficient technologies must be implemented. However, there are barriers to the implementation of energy-efficient technologies. In this study, interviews were conducted with different stakeholders within a city district development project to find barriers towards the implementation of energy-efficient technologies in buildings. First, an investigation of barrier theory followed by three pre-interviews was conducted, which helped in forming questions for the interview study, which involved a total of 18 respondents. The respondents were from the client, facility manager, developer, consultants, project planners, contractor, and the local energy supplier. The barriers mentioned in the interviews were connected to different phases of a building project. There is a scarcity of studies where barriers in various phases of the construction process are explored. In conclusion, the most frequently mentioned barriers were connected to the Planning Program phase and the Project Planning phase. Two new barrier categories are suggested: Lack of Knowledge and Fear. The most prominent barriers to implementation of energy-efficient technologies were Inertia, Risk, Access to Capital and Lack of Knowledge. To increase the implementation of energy-efficient technologies in buildings, knowledge needs to be increased throughout the whole industry, and stakeholders need to step out of their comfort zone and not always do as they have done before. A key policy implication is the importance of capacity building in the early phases of the building process.

Microplastics (MPs) were considered as emerging pollutants in soil. Cadmium (Cd) is the typical heavy metal contaminant in paddy soil in China. It was not unraveled that the effects of the existence of MPs on soil properties and Cd adsorption after rice growth in paddy soil, one of the most important soil types in China. In this study, several typical MPs in dosage of 0.5% (w/w) with different particle sizes, including polyethylene (PE, $200\mu m$), polyacrylonitrile (PAN, $200\mu m$), and polyethylene terephthalate (PET, 200 and $10\mu m$), were selected and aged for a rice season ($\sim$6 months) in paddy soil by column experiments. Some essential physicochemical properties of paddy soil collected from different treatments and the adsorption performance of typical metal contaminants (cadmium, Cd) in paddy soil with MPs coexisting were compared. The results indicated that the 6-month existence of $200\mu m$ MPs increased water content (15.94% to 26.08-30.30%), pH value (7.05 to 7.16–7.33), organic matter (OM) content (15.1 g$$kg ⁻¹ to 18.2–22.9 g$$kg ⁻¹), the percentage of soil sand and Cd adsorption capacity of paddy soil, whereas decreased soil cation exchange capacity (CEC), the percentage of soil clay and silt. The adsorption experiments of Cd in soil showed that the adsorption behavior was consistent with the pseudo-second order and Langmuir isotherm model, and the addition of MPs would increase the adsorption capacity of Cd in soil. Besides, the particle size of MPs was found to be one of the dominant factors, in which MPs with smaller particle size ($10\mu m$) favored the increase of water content, pH, OM content, CEC, and adsorption performance with Cd. The results of this study could provide a supplemental understanding of the effect of MPs input on the paddy soil ecosystem, including the soil properties and the bioavailability and transport of metal in paddy soil.

High fidelity gridded temperature datasets are difficult to obtain for areas with sparse coverage of meteorological stations given that sparsity of stations is known to introduce uncertainty in the interpolation of climatic variables generally. Inspired by their potential for optimal results especially for small sample datasets, we assessed and compared the accuracy of interpolation results of Empirical Bayesian Kriging (EBK) and EBK-Regression Prediction (EBKRP) spatial prediction techniques under varying sampling density scenarios, using monthly maximum temperature normals (1991–2020) for the entire area of Sweden. The objectives of the study were to understand how EBK and EBKRP interpolation techniques perform in different sampling density scenarios and particularly in a sparse data setting, and the possible difference in the prediction accuracy between the two techniques. The 708 sampled stations obtained from the historical climatology database of the Swedish Meteorological and Hydrological Institute (SMHI) were split into seven sampling density subsets, ranging from 1 sample per 63,614 km² to 1 sample per 634,350 km² and representing both low and high sampling density scenarios. EBK interpolation technique was implemented using temperature data while land use land cover (LULC) and digital elevation model (DEM) were used as temperature covariates for the EBKRP interpolation models. The prediction accuracy assessment was based on five robust prediction performance indicators – mean error, mean absolute error, mean square error, root mean square error and Pearson correlation (R) – obtained from independent validation/cross-validation operations. Prediction accuracy was found to be generally positively related to sampling density, and sampling density accounted for about 85%–87% of interpolation accuracy for both EBK and EBKRP techniques. Although sampling density increased linearly, the rate of change in accuracy from one sampling density step to the next was not particularly proportional. For equivalent sampling density set-ups, EBKRP consistently outperformed EBK in all the accuracy metrics and EBKRP proved to be approximately 40% better than EBK. However, the two interpolation techniques produced generally low prediction biases for all the sampling density scenarios investigated. Our study suggests that potential effects of low sampling density and non-stationarity of temperature data can be significantly reduced by applying EBK but especially EBKRP when coupled with relevant covariates. This is especially true for continuous and slowly varying phenomena such as temperature and similar variables.

Farmland ecosystems are the most active carbon pool and contribute significantly to the global carbon cycle. Since these ecosystems are influenced by both natural and human factors it is important to study their roles as carbon sources and sinks in order to reach “peak carbon emissions” and “carbon neutrality” goals. This review provides a systematic summary of research in this area and explores the deficiencies in current research approaches by addressing common carbon flux accounting methods and mainstream carbon cycle measurement models. Natural and human factors that affect the functions of farmland ecosystems as sinks and sources of carbon are discussed and prospects for addressing existing problems and suggestions for future directions are presented. The factors affecting carbon sources and sinks in farmland ecosystem have great heterogeneity and complexity due to differences in management practices and natural conditions with the former being more important. However, due to differences in assessment models and accounting methods, there is still great uncertainty in the assessment of carbon sources and sinks in farmland ecosystems. Therefore, more emphasis is needed on the optimization of models and the improvement of accounting methods in the future. This review provides a comprehensive reference for further study on carbon sources and sinks of farmland ecosystems, rational adjustment of farmland management measures, and strategies for the reduction of agricultural non-point source pollution.