Framing of Geoengineering Affects Support for Climate Change Mitigation

The growing recognition that climate change mitigation alone will be inadequate has led scientists and policymakers to discuss climate geoengineering. An experiment with a US sample found, contrary to previous research, that reading about geoengineering did not reduce conservatives’ skepticism about the existence of anthropogenic climate change. Moreover, depending on how it is framed, geoengineering can reduce support for mitigation among both conservatives and non-conservatives. When geoengineering is framed as a major solution, people worry less about climate change, leading to reduced mitigation support. When framed as disastrous, people perceived geoengineering as riskier, also leading to a decrease in mitigation support. A more moderate framing of geoengineering as a partial solution is less susceptible to moral hazard effects. Overall, results suggest that geoengineering will not lessen political polarization over anthropogenic climate change, and could undercut support for mitigation efforts. Instead, framing geoengineering as a small piece to solving a big puzzle seems to be the best strategy to weaken this potential moral hazard.     

Investigation of titanium liquid/gas diffusion layers in proton exchange membrane electrolyzer cells

In a proton exchange membrane electrolyzer cell (PEMEC), liquid/gas diffusion layer (LGDL) is expected to transport electrons, heat, and reactants/products to and from the catalyst layer with minimum voltage, current, thermal, interfacial, and fluidic losses. In addition, carbon materials, which are typically used in PEM fuel cells (PEMFCs), are unsuitable in PEMECs due to the high ohmic potential and highly oxidative environment of the oxygen electrode. In this study, a set of titanium gas diffusion layers with different thicknesses and porosities are designed and examined coupled with the development of a robust titanium bipolar plate. It has been found that the performance of electrolyzer improves along with a decrease in thickness or porosity of the anode LGDL of titanium woven meshes. The ohmic resistance of anode LGDL and contact resistance between anode LGDL and the anode catalyst play dominant roles in electrolyzer performance, and better performance can be obtained by reducing ohmic resistance. Thin titanium LGDLs with straight-through pores and optimal pore morphologies are recommended for the future developments of low-cost LGDLs with minimum ohmic/transport losses.     

Plant blindness and the implications for plant conservation

Plant conservation initiatives lag behind and receive considerably less funding than animal conservation projects. We explored a potential reason for this bias: a tendency among humans to neither notice nor value plants in the environment. Experimental research and surveys have demonstrated higher preference for, superior recall of, and better visual detection of animals compared with plants. This bias has been attributed to perceptual factors such as lack of motion by plants and the tendency of plants to visually blend together but also to cultural factors such as a greater focus on animals in formal biological education. In contrast, ethnographic research reveals that many social groups have strong bonds with plants, including nonhierarchical kinship relationships. We argue that plant blindness is common, but not inevitable. If immersed in a plant‐affiliated culture, the individual will experience language and practices that enhance capacity to detect, recall, and value plants, something less likely to occur in zoocentric societies. Therefore, conservation programs can contribute to reducing this bias. We considered strategies that might reduce this bias and encourage plant conservation behavior. Psychological research demonstrates that people are more likely to support conservation of species that have human‐like characteristics and that support for conservation can be increased by encouraging people to practice empathy and anthropomorphism of nonhuman species. We argue that support for plant conservation may be garnered through strategies that promote identification and empathy with plants.     

A spatially explicit backcasting approach for sustainable land-use planning

General backcasting as a decision support and planning method starts from desired future states and simulates developments backwards until reaching the present state. Development pathways that reveal steps to be taken to reach a certain future state, and milestones that serve as interim goals, are created during the process. Backcasting has hitherto only been applied in workshops or as a theoretical framework and no spatially explicit backcasting model has previously been established. This paper presents the development of a spatially explicit backcasting model. The proposed model first creates a future scenario utilizing an agent-based model and then simulates backwards. It is implemented using the programming language Python. The model has been applied to a case study for sustainable land-use planning in Salzburg, Austria. The results of the model run show a successful backcasting of land-use classes from a future state back to the present, in 10 year time steps.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.     

采用支持向量机算法优化电化学处理油田污水的工艺参数

采用支持向量机(SVM)算法,将Box-Behnken设计法与支持向量回归算法(SVR)实验参数优化软件相结合,优化电化学去除油田污水COD的工艺参数。通过量子粒子群算法对SVM算法参数进行优化,从建立的回归模型中找到工艺参数的全局最佳点:电解时间60 min,电解电流3 A,三维电极填充料中石英砂质量695 g。模型得到的COD理论最优去除率为92.48%,验证实验得到的COD去除率为91.43%。     

膜电解法退镀废ABS电镀件及回收铜和镍

采用膜电解法对废丙烯腈-丁二烯-苯乙烯（ABS）电镀件进行退镀处理。以退镀废液作为阴极液和阳极液，在阳极室退镀ABS电镀件，在阴极室电解退镀废液，进行铜镍分离，回收铜粉和NiCl₂。实验结果表明：在阴极电流密度为500 A/m²、初始铜离子质量浓度为24.00 g/L的条件下电解160 min，阴极铜回收率可达97.65%，电流效率达86.60%，得到的铜粉纯度为97%~99%，处理1 L退镀废液可回收铜粉20.0 g，2 mol/L盐酸0.87 L，NiCl₂晶体43.8 g;在阳极电流密度为500 A/m²、液固比为6的条件下电解60 min， ABS电镀件的退镀率为77.22%。     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

4段式平板膜处理污泥的中试研究

4段式平板膜处理污泥及中水回用工艺是根据次临界通量的原理设计运行的.在中试装置运行25 d的过程中,发现污泥浓度逐级提升,在进泥浓度为3 g/L左右时,出泥平均可达35 g/L;同时发现,膜出水COD和氨氮浓度均在工艺运行18d内分别保持在50 mg/L和10 mg/L;最后,研究发现,从第1段到第4段过程中,污泥的粒径逐渐减少,而污泥的粘度和毛细脱水时间是逐渐增大的.     

曝气条件对浸没式膜生物反应器内流场的影响

为深入研究流场动力学特性对浸没式膜生物反应器系统内膜面污染的控制,应用fluent软件对浸没式膜生物反应器内气液两相流动进行了三维数值模拟研究。采用标准k-ε湍流模型和欧拉多相流模型,考察了改变曝气条件对膜面气液速度场及气含率分布的影响。模拟结果表明,在相同曝气强度下,1 mm曝气孔径下膜面气液两相的速度增加较孔径2mm、3 mm的快;曝气孔径为1 mm时,膜面的液相速度随着曝气强度的增加逐渐增大;曝气孔径为1 mm时,曝气量为5.5m3/h所形成的漩涡区较大,膜面气含率值较高且分布较均匀,气液两相接触面积较大,膜面冲刷效果较好;模拟观察到反应器底部靠近壁面局部气含率较低,不利于活性污泥中微生物的生长,需要进一步优化曝气和反应器结构。