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Bioplastics are alternatives of conventional petroleum-based plastics. Bioplastics are polymers processed from renewable sources and are biodegradable. This study aims at conducting an environmental impact assessment of the bioprocessing of agricultural wastes into bioplastics compared to petro-plastics using an LCA approach. Bioplastics were produced from potato peels in laboratory. In a biochemical reaction under heating, starch was extracted from peels and glycerin, vinegar and water were added with a range of different ratios, which resulted in producing different samples of bio-based plastics. Nevertheless, the environmental impact of the bioplastics production process was evaluated and compared to petro-plastics. A life cycle analysis of bioplastics produced in laboratory and petro-plastics was conducted. The results are presented in the form of global warming potential, and other environmental impacts including acidification potential, eutrophication potential, freshwater ecotoxicity potential, human toxicity potential, and ozone layer depletion of producing bioplastics are compared to petro-plastics. The results show that the greenhouse gases (GHG) emissions, through the different experiments to produce bioplastics, range between 0.354 and 0.623 kg CO2 eq. per kg bioplastic compared to 2.37 kg CO2 eq. per kg polypropylene as a petro-plastic. The results also showed that there are no significant potential effects for the bioplastics produced from potato peels on different environmental impacts in comparison with poly-β-hydroxybutyric acid and polypropylene. Thus, the bioplastics produced from agricultural wastes can be manufactured in industrial scale to reduce the dependence on petroleum-based plastics. This in turn will mitigate GHG emissions and reduce the negative environmental impacts on climate change.

In this study, Myriophyllum elatinoides growth under different nitrogen (N) concentrations (2, 250, 300, 350 and 400 mg L-1) and changes in rhizosphere bacterial community structure were investigated. High N (>300 mg L-1) concentrations caused reduction in M. elatinoides biomass. Growth tended to stabilize at 49 days. N concentration in roots were higher than that in stems and leaves under high N conditions. TN and NH4+ removal efficiencies reached 84.0% and 87.2%, respectively, in M. elatinoides surface flow constructed wetlands (SFCWs). Rhizosphere bacterial diversity increased over time. Proteobacteria, Firmicutes, Cyanobacteria, and Bacteroidetes dominated at the phylum level. Genera Turicibacter, Allochromatium, and Methylocystis increased at low N (<300 mg L-1) concentrations, while Pseudomonas increased at high N concentrations over the experimental period. Redundancy analysis showed that pH was strongly correlated with changes in rhizosphere bacterial community structure. These findings helped to insight into N removal mechanism in M. elatinoides.

Societal relations in rural areas have entered into a new stage of adjustment over the past decade. However, the adjustment, which might bring about profound societal changes in countryside as well as in China as a whole, have not been paid much attention and very few studies have been conducted from the perspective of ecological resource crises. We use the case of a village as an example to show how water pollution, as one of the contributory factors, possibly affect the transition of clans and societal changes in Chinese villages. Through observation and interviews, we find that there is an apparent rise of “New Clanism” within clans, which gradually abandons the tradition of supremacy of clan interests and places family or individual interests at top priority. We also find that clan boundaries get increasingly obscure since the integrity of clans is undermined by the rise of new interest groups across clans, but the boundaries remain relatively clear due to the consistency (albeit incomplete) of clan interests. Some new clan élites and representatives of new interest groups get involved in village governance, which indicates that their goals have shifted from natural resources to social or political capital. The significance of our findings is that they provide not only a unique perspective for the interaction between society and resources, but also some new ideas for the future study of rural China at the environment-social interface.

Abstract Scenedesmus obliquus biomass was used as a feedstock for comparing the biological production of hydrogen by two different types of anaerobic cultures: a heat-treated mixed culture from a wastewater treatment plant and Clostridium butyricum DSM 10702. The influence of the incubation temperature and the carbon source composition were evaluated in order to select the best production profile according to the characteristics of the microalgal biomass. C. butyricum showed a clear preference for monomeric sugars and starch, the latter being the major storage compound in microalgae. The highest H 2 production reached by this strain from starch was 468 mL/g, whereas the mixed culture incubated at 37 °C (LE37) produced 241 mL/g. When the mixed culture was incubated at 58 °C (LE58), a significant increase in the H 2 production occurred when xylose and xylan were used as carbon and energy source. The highest H 2 yield reached by the LE37 culture or in co-culture with C. butyricum was 1.52 and 2.01 mol/mol of glucose equivalents, respectively. However, the ratio H 2 /CO 2 (v/v) of the biogas produced in both cases was always lower than the one produced by the pure strain. In kinetic assays, C. butyricum attained 153.9 mL H 2 /L h from S. obliquus biomass within the first 24 h of incubation, with a H 2 yield of 2.74 mol/mol of glucose equivalents. H 2 production was accompanied mainly by acetate and butyrate as co-products. In summary, C. butyricum demonstrated a clear supremacy for third generation bioH 2 production from S. obliquus biomass.

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

Abstract Uncertainties of cooling load may make cooling system oversized. Most of previous studies implement probabilistic-based uncertainty analysis, intending to achieve optimization and reliability simultaneously. However, how to reduce the load uncertainty has received little attention. This paper investigates the impact of water storage on the design of cooling system considering load uncertainty. Information entropy is used as a convergence index of load uncertainty and used to determine how many random simulations should to be performed. A cooling system configured with water storage (system B) and another system without water storage (system A as a comparation system) are investigated in this paper. In this paper, the configure of system A and system B are optimized respectively. The result shows that the capacity distribution of system A is consistent with the distribution of extreme loads. But, the capacity distribution of system B is more concentrated as the water storage can reshape the load curve. Water storage improves the flexibility of system B. Therefore, system B is more reliable and economical than system A.

Nowadays, the issues related with environment preservation assume an increasing importance. Progressively, more sustainable solutions/techniques are being developed to combat environmental destruction. The decision to include themes related to the environment in the curriculum of technological courses in higher education aims to promote more sustainable behaviors and in an indirect way, increase the environmental literacy of the population. Thus, this study aims to evaluate the environmental literacy focusing on four topics, i.e., air pollution, water pollution, global warming, and energy resources. For this purpose, a questionnaire was developed and applied to a convenience sample, formed by individuals of both genders, aged between 20 and 81 years old. The questionnaire intended to collect data to characterize the sample and assess the literacy regarding environmental issues. In order to carry out the environmental literacy assessment, the respondents were asked to express their degree of agreement with some statements related with the environmental themes mentioned above. The data collected was analyzed using data mining tools. The results suggest that the population’s literacy is satisfactory in relation to some issues, but insufficient in relation to others, equally important, but less disseminated.

This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch problem of distributed generators. A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, and support plug-and-play functionalities. The optimal economic dispatch is achieved by allowing the iterative coordination of local agents (consumers and distributed generators). As coordination information, the local estimation of power mismatch is shared among distributed generators through communication networks and does not contain any private information, ultimately contributing to a fair electricity market. Additionally, the proposed distributed algorithm is particularly designed for easy implementation and configuration of a large number of agents in which the distributed decision making can be implemented in a simple proportional-integral (PI) or integral (I) controller. In MATLAB/Simulink simulation, the accuracy of the proposed distributed algorithm is demonstrated in a 29-node system in comparison with the centralized algorithm. Scalability and a fast convergence rate are also demonstrated in a 1400-node case study. Further, the experimental test demonstrates the practical performance of the proposed distributed algorithm using the VOLTTRON platform and a cluster of low-cost credit-card-size single-board PCs. Comment: 16 Pages, 13 figures Figures order and references are corrected!