Bio-Ethanol Production from Non-Food Parts of Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

Global climate issues and a looming energy crisis put agriculture under pressure in Sub-Saharan Africa. Climate adaptation measures must entail sustainable development benefits, and growing crops for food as well as energy may be a solution, removing people from hunger and poverty without compromising the environment. The present study investigated the feasibility of using non-food parts of cassava for energy production and the promising results revealed that at least 28% of peels and stems comprise dry matter, and 10 g feedstock yields >8.5 g sugar, which in turn produced >60% ethanol, with pH ≈ 2.85, 74-84% light transmittance and a conductivity of 368 mV, indicating a potential use of cassava feedstock for ethanol production. Thus, harnessing cassava for food as well as ethanol production is deemed feasible. Such a system would, however, require supportive policies to acquire a balance between food security and fuel.     

城市能源利用与环境保护的综合管理初探

能源短缺和环境污染已成为中国推行全面协调可持续发展的重要制约因素,作为能源消耗的主体和环境污染的控制重点,在城市层面推动能源发展战略的转变和强化环境保护是发展的基本要求.鉴于能源与环境之间的高度关联性,在管理方面要求对能源发展和环境保护进行统筹考虑和综合管理,充分强调能源经济效率和环境制约因素在能源发展中的作用.通过制定合理的产业能效标准和排放绩效标准,为城市经济、能源和环境的可持续性发展提供科学性、系统性决策支持.     

Biogeochemical model (BGC-ES) and its basin-level application for evaluating ecosystem services under forest management practices

It is important for humans to live in harmony with ecosystems. Evaluation of ecosystem services (ES) may be helpful in achieving this objective. In Japan, forest ecosystems need to be re-evaluated to prevent their degradation due to lack of forest management.In order to evaluate the effects of forest management on forest ES, we developed a process-based biogeochemical model to estimate water, carbon, and nitrogen cycles in forest ecosystems (BGC-ES). This model consists of four submodels: biomass, water cycle, carbon-nitrogen (CN) cycles, and forest management. The biomass submodel can calculate growth of forest biomass under forest managements.Several parameters of the model were calibrated using data from observations of evapotranspiration flux and quality of stream flow in forests. The model results were compared with observations of runoff water from a dam catchment site and with carbon flux observations.Our model was coupled with a basin-level GIS database of forests. Evaluations under various forest management scenarios were carried out for forests in a basin contained in the Ise Bay basin (Chubu region, Japan), where plantations (artificial forests) seemed to have degraded from poor forest management.Comparing our simulation results with those of forests without management in the basin, we found that the amounts of absorbed carbon and runoff were larger in managed forests. In addition, the volume of harvested timber was larger and its quality (diameter) was better in managed forests. Changes of ES within the various scenarios were estimated for their economic value and were compared with the cost of forest management.     

Efficient photoelectrochemical oxidation of rhodamine B on metal electrodes without photocatalyst or supporting electrolyte

We designed photoelectrochemical cells to achieve efficient oxidation of rhodamine B (RhB) without the need for photocatalyst or supporting electrolyte. RhB, the metal anode/cathode, and O₂ formed an energy-relay structure, enabling the efficient formation of O ₂ ^– species under ultraviolet illumination. In a single-compartment cell (S cell) containing a titanium (Ti) anode, Ti cathode, and 10 mg·mL^–1 RhB in water, the zero-order rate constant of the photoelectrochemical oxidation (k_PEC) of RhB was 0.049 mg·L^–1·min^–1, while those of the photochemical and electrochemical oxidations of RhB were nearly zero. k_PEC remained almost the same when 0.5 mol·L^–1 Na₂SO₄ was included in the reactive solution, regardless of the increase in the photocurrent of the S cell. The k_PEC of the illuminated anode compartment in the two-compartment cell, including a Ti anode, Ti cathode, and 10 mg·mL^–1 RhB in water, was higher than that of the S cell. These results support a simple, eco-friendly, and energysaving method to realize the efficient degradation of RhB.

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Cracking the Achilles’ heel of energy performance contracting projects: the credit risk identification method for clients

ABSTRACT

A credit risk identification model is established to examine the credit status of Energy performance contracting (EPC) project clients (i.e., energy-using companies) in China based on rough set theory. The model is verified with data from 120 listed companies at different times. Study shows that lack of credit is one of the main obstacles to the implementation of EPC projects, and information asymmetry is the main reason for this lack of credit among potential clients in China. The credit risk identification method based on rough set theory can make up for the shortcomings of existing EPC projects in terms of credit risk identification, including redundant information and indicators, and unclear decision rules. Credit risk identification indicators of clients are dynamic. The research results can help energy service companies (ESCOs) determine the credit status of clients, facilitate cooperation between ESCOs and clients, and help explain the various dynamics of clients’ credit risk identification indicators over time.     

Investigation of sustainable energy alternatives for powering remote communities in northern Ontario

ABSTRACT

Remote communities in the North of Ontario survive in isolation as their proximity to the southern industrial sector of the province limits their accessibility to the major grid. The lack of grid connection has led to antiquated methods of power generation which pollute the environment and deplete the planet of its natural resources. Aside from the primary means of electricity generation being by diesel generators, generation infrastructure is deteriorating due to age and the stagnation of the power supply has led to communities facing load restrictions. These challenges may be resolved by introducing clean energy alternatives and providing a fuel blend option. The primary energy sources investigated in this research are solar, wind, and hydrogen. To assess the viability of these energy production methods in Northern communities, an exergy analysis is employed as it utilizes both the first and second law of thermodynamics to determine systems’ efficiency and performance in the surroundings. Local weather patterns were used to determine the viability of using wind turbines, solar panels and/or hydrogen fuel cells in a remote community. Through analysis of the resources available at the community, it was determined that the hydrogen fuel cell was best suited to provide clean energy to the community. Wind resulted in low efficiency in the range of 2–3% while solar efficiencies resulted in ranges of 18 – 19%, as the seasonal variations between the three years is not very great. Due to the higher operating efficiencies observed of the PV panels it would also be an attractive alternative to diesel generators however, the lack of consistent operation above 30% efficiency throughout the year, resulted in hydrogen fuel cells being a better alternative.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Prediction of Leachate Level in Kimpo Metropolitan Landfill Site by Total Water Balance

Kimpo metropolitan landfill has received various kinds of wastessince January 1992. The leachate level was measured to be 10.3 m in May 1995 and the level increased to 12.2 m in August 1996. Therefore, to prove the reason for the increasing leachate level, we calibrated hydraulic conductivity of each waste andintermediate layer using the HELP (Hydrologic Evaluation ofLandfill Performance) model. The leachate generation data measured from February 1993 to October 1995 was used in the model calibration. As a result of a model calibration, we obtained anaverage infiltration ratio and used this in analysis of the total water balance to predict elevation of leachate level. Main causes of the elevation of the leachate level were the high water content of the waste and the degradation of the leachate-drainage system caused by the subsidence of a naturalbarrier layer.     

Bioanalytical characterisation of multiple endocrine- and dioxin-like activities in sediments from reference and impacted small rivers

A comprehensive evaluation of organic contamination was performed in sediments sampled in two reference and three impacted small streams where endocrine disruptive (ED) effects in fish have been evidenced. The approach combined quantitative chemical analyses of more than 50 ED chemicals (EDCs) and a battery of in vitro bioassays allowing the quantification of receptor-mediated activities, namely estrogen (ER), androgen (AR), dioxin (AhR) and pregnane X (PXR) receptors. At the most impacted sites, chemical analyses showed the presence of natural estrogens, organochlorine pesticides, parabens, polycyclic aromatic hydrocarbons (16 PAHs), bisphenol A and alkylphenols, while synthetic steroids, myco-estrogens and phyto-estrogens were not detected. Determination of toxic-equivalent amounts showed that 28-96% of estrogenic activities in bioassays (0.2-6.3 ng/g 17β-estradiol equivalents) were explained by 17β-estradiol and estrone. PAHs were major contributors (20-60%) to the total dioxin-like activities. Interestingly, high PXR and (anti)AR activities were detected; however, the targeted analysed compounds could not explain the measured biological activities. This study highlighted the presence of multiple organic EDCs in French river sediments subjected to mixed diffuse pollution, and argues for the need to further identify AR and PXR active compounds in the aquatic environment.     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.