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AbstractWater scarcity has become a global severe challenge over the past few decades. Quantifying the impact of climate variability and land use on water resource availability is crucial for integrated water resource management. Many studies have focused on blue water but ignored green water which is important in the terrestrial ecosystem, especially on different temporal scales. In this study, we selected the Shanmei Reservoir, the most import drinking water resource for a rapidly development city of Southeast China, as a case for analysis of these impacts for the entire basin. We adopted the Soil and Water Assessment Tool (SWAT) to investigate the spatial and temporal distributions of blue water (BW), green water flow (GWF) and green water storage (GWS) in the Shanmei Reservoir Basin (SRB). The results of the blue and green water components (BW and GW) revealed that SRB is dominated by BW, accounting for 52.6% of the total water resources, while GW accounted for 47.4%. There was an insignificant upward trend of BW and a significant upward trend of GWF, with a tendency rate of 1.125 mm a−1. Precipitation was the key factor affecting BW on annual and monthly scales. The GWF was more sensitive to temperature at both the annual and monthly scales. The GWS was significantly correlated with precipitation at the monthly scale, while insignificant correlation occurred at the annual scale. The spatial distribution of BW was largely dominated by precipitation, and land-use types led to the differentiation of GW. It indicates that the BW of paddy fields is greater than that of forests, while the GWS of forests is greater than that of orchards and rainfed croplands.

This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions.

As issues concerning “circular economy” and “sustainable development” have been advocated globally, the recycling, reuse, recovery or disposal of end-of-life vehicles (ELVs) have gained more and more attention. Toxic substances and wasted resources within ELVs make evaluating the sustainability of ELV recycling enterprises to be especially important for sound ELV management. In this study, an improved emergy analysis with traditional and revised emergy indices was employed for evaluation of the efficiency and sustainability of ELV recycling enterprises. The constructed emergy indicator system not only reflected the ELV recycling system's resource, environmental, economic and technological efficiency, but also made a multi-scale and multi-dimensional evaluation of the system according to its industrial characteristics. An ELV recycling enterprise in Jiangxi Province, China, as a case, was studied employing the proposed method and indicator system. The results showed that the enterprise involved in the study had strong competitive ability with relatively high economic benefit, and had a moderate environmental impact compared with other industrial systems. The emergy sustainability index indicated that the recycling enterprise was both economically and environmentally sustainable in the long term. However, the emergy technical efficiency indices indicated that the technical level and operational efficiency of the ELV recycling enterprise were relatively low and more investment should be put into the improvement of the recycling technologies. The results of the study can provide useful information for the decision makers to manage ELV recycling enterprises considering not only economic benefits but also the environmental benefits in the long term.

This Article examines the genesis and context of SE4All, placing the effort within both itshistorical and international policy contexts. It highlights the voluntary nature of the initiative andargues that its effective implementation and the achievement of its goals require the articulation ofan applicable international legal framework that aids the transformation of SE4All’s policy actionsinto binding international legal commitments. The article contends that such a transformation doesnot depend on the creation of entirely new legal rules or institutions. Instead, an effective frame-work for successful implementation of SE4All can be derived from existing rules of internationalhuman rights law and sustainable development law. Reliance on these twin bodies of interna-tional law will increase the prospects for SE4All to achieve energy access and related goals thatits predecessor initiatives have failed to accomplish

The design and assessment of net-zero buildings commonly focus exclusively on the operational phase, ignoring the embodied environmental impacts over the building life cycle. An analysis is presented on the consequences of integrating embodied impacts into the assessment of the environmental advantageousness of net-zero concepts. Fundamental issues needing consideration in the design process - based on the evaluation of primary energy use and related greenhouse gas emissions - are examined by comparing three net-zero building design and assessment cases: (1) no embodied impacts included, net balance limited to the operation stage only; (2) embodied impacts included but evaluated separately from the operation stage; and (3) embodied impacts included with the operation stage in a life cycle approach. A review of recent developments in research, standardization activities and design practice and the presentation of a case study of a residential building in Norway highlight the critical importance of performance indicator definitions and system boundaries. A practical checklist is presented to guide the process of incorporating embodied impacts across the building life cycle phases in net-zero design. Its implications are considered on overall environmental impact assessment of buildings. Research and development challenges, as well as recommendations for designers and other stakeholders, are identified.

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic annual ruderal plant and native to Northern America, but now also spreading across Europe. Air pollution and climate change will not only affect plant growth, pollen production and duration of the whole pollen season, but also the amount of allergenic encoding transcripts and proteins of the pollen. The objective of this study was to get a better understanding of transcriptional changes in ragweed pollen upon NO2 and O3 fumigation. This will also contribute to a systems biology approach to understand the reaction of the allergenic pollen to air pollution and climate change. Ragweed plants were grown in climate chambers under controlled conditions and fumigated with enhanced levels of NO2 and O3. Illumina sequencing and de novo assembly revealed significant differentially expressed transcripts, belonging to different gene ontology (GO) terms that were grouped into biological process and molecular function. Transcript levels of the known Amb a ragweed encoding allergens were clearly up-regulated under elevated NO2, whereas the amount of allergen encoding transcripts was more variable under elevated O3 conditions. Moreover transcripts encoding allergen known from other plants could be identified. The transcriptional changes in ragweed pollen upon elevated NO2 fumigation indicates that air pollution will alter the transcriptome of the pollen. The changed levels of allergenic encoding transcripts may have an influence on the total allergenic potential of ragweed pollen.

Electric vehicles (EVs) offer an attractive long-term solution to reduce the dependence on fossil fuel and greenhouse gas emission. At the same time, charging a large fleet of EVs distributed across the residential area poses a challenge for the distribution network. In this paper, we formulate this problem by building on the optimal power flow (OPF) framework to model the network constraints that arises from charging EVs at different locations. To overcome the computational challenge when the control horizon is long, we study a nested optimization approach to decompose the joint OPF and EV charging problem. We characterize the optimal EV charging schedule to be a valley-filling profile, which allows us to develop an efficient offline algorithm with significantly lower computational complexity compared to centralized interior point solvers. Furthermore, we propose a decentralized online algorithm that dynamically tracks the valley-filling profile. Our algorithms are evaluated on the IEEE 14 bus system with real residential load profiles, and the simulations show that our online algorithm performs almost optimally under different settings.

A reasonable plan for charging stations is critical to the widespread use of electric vehicles. In this paper, we propose an optimal planning method for electric vehicle charging stations. First of all, we put forward a forecasting method for the distribution of electric vehicle fast charging demand in urban areas. Next, a new mathematical model that considers the mutual benefit of electric vehicle users and the power grid is set up, aiming to minimize the social cost of charging stations. Then, the model is solved by the Voronoi diagram combined with improved particle swarm optimization. In the end, the proposed method is applied to an urban area, simulation results demonstrate that the proposed method can yield optimal location and capacity of each charging station. A contrasting case is carried out to verify that improved particle swarm optimization is more effective in finding the global optimal solution than particle swarm optimization.