三峡水库入库污染负荷研究(Ⅰ)--蓄水前污染负荷现状

分析蓄水前三峡水库入库污染负荷,包括库区污染负荷,如城市生活污水、工业废水、农业面源、船舶流动污染源;主要干支流长江、嘉陵江、乌江的入库背景污染负荷,包括上游天然背景负荷和上游污染贡献负荷,为三峡水库水污染防治提供理论依据。研究表明：①进入三峡库区的污染源主要来自长江、嘉陵江、乌江上游输入的背景负荷,包括上游贡献负荷和天然背景负荷,其中：CODCr的天然背景负荷与上游污染贡献负荷较为接近,BOD5、NH3-N的上游贡献负荷略大于天然背景负荷;TP的上游贡献负荷远大于天然背景负荷。因此,“三江”上游区域的污染治理工作应为今后三峡水库水污染防治的重点;②库区内排放的主要污染物是TP、BOD5、TN、CODCr等有机污染物,其累计等标污染负荷比达到98%以上。库区内的主要污染源为农田径流,其等标污染负荷比为77.85%;其次为城市污水,其等标污染负荷比为19.45%,工业废水的等标污染负荷比只占1.62%。因此,农田面源将是今后库区污染防治的重点。     

三峡水库入库污染负荷研究(Ⅱ)--蓄水后污染负荷预测

在文献\[1\]基础上,预测三峡水库2010年和2015年的入库污染负荷。采用包络线法预测排污得到有效控制的低负荷水平（最佳状态）,排污继续恶化到一定限度的高负荷水平（最坏状态）,以及按正常排污介于高、低负荷水平之间的中负荷水平（一般状态）。在预测入库污染负荷时,把长江、嘉陵江、乌江进入的背景水质污染负荷分为天然背景负荷和上游贡献负荷,天然背景负荷保持不变,上游贡献负荷根据上游水污染控制规划按高、中、低负荷水平预测。预测表明,库区内的污染负荷占入库总污染负荷的比例较小。中负荷水平下,库区污染源占入库总负荷的比例为8.50%～22.93％。污染负荷主要来自长江、嘉陵江、乌江上游的贡献和天然背景负荷。在低、中、高三种负荷水平下,扣除天然背景值时,2010年低负荷水平时BOD5库区负荷占28.8％、中负荷占32.5％、高负荷占35.04％。总磷出现反常,库区的总磷的污染负荷在低负荷水平下,所占入库负荷的比例高于中负荷水平、但小于高负荷水平。2010年、2015年库区的主要污染物质和污染负荷排放分布与现状（1998年）基本相同。主要排污区域为重庆主城区,2010年预测重庆主城区CODCr负荷占库区总负荷的比例,高、中、低负荷水平分别为：39.6%、36.2％、21.6％,低负荷比高负荷降低18％。库区的主要污染源为农业面源,2010年库区农业面源中CODCr负荷占总负荷的比例在高、中、低负荷水平下分别为：38.9%、47.5％、70.4％。同时,随着库区社会经济发展,污染负荷有逐步增大的趋势,到2015年所有污染物及负荷水平,均大于2010年和1998年。     

Pre-feasibility study of stand-alone hybrid energy systems for applications in eco-houses

In light of rising cost of fossil fuels and fears of its depletion, coupled with the increase in energy demand and the rise in pollution levels, governments worldwide have had to look at alternative energy resources. Combining renewable energy generation like solar power with superior storage and conversion technology such as hydrogen storage, fuel cells and batteries offers a potential solution for a stand-alone power system. The aim of this paper was to assess the techno-economic feasibility of using a hybrid energy system with hydrogen fuel cell for application in an eco-house that will be built in Sultan Qaboos University, Muscat, Oman. Actual load data for a typical Omani house of a similar size as the eco-house was considered as the stand-alone load with an average energy consumption of 40 kW/day and 5 kW peak power demand. The National Renewable Energy Laboratory's Hybrid Optimisation Model for Electric Renewable software was used as a sizing and optimisation tool for the system. It was found that the total annual electrical energy production is 42,255 kW and the cost of energy for this hybrid system is 0.582 $/kW. During daylight time, when the solar radiation is high, the photovoltaics (PV) panels supplied most of the load requirements. Moreover, during the evening time the fuel cell mainly serves the house with the help of the batteries. The proposed system is capable of providing the required energy to the eco-house during the whole year using only the solar irradiance as the primary source.     

Distribution of health costs of pesticide use by household economy

We observed skewed distribution across household of benefits of pesticide use in vegetable farming in Nepal. However, economic burden or harm of pesticide use and exposure by household economy is poorly studied. It is hypothesized that exaggerated and incompetent pesticide use is likely to affect human health that may lead to decline in human productivity, and economic loss––that may further marginalize farmers. Thus, a study was conducted in the Ansi khola watershed of Kavrepalanchowk District of central Nepal. The primary aim of the study was to value risks of pesticide use and to estimate health costs of exposure by household category. We grouped household into “large-scale” who owns more than 1 ha of agricultural land, “small-scale” having <0.5 ha and “medium-scale” in between >0.5 and <1 ha. Data were collected through (1) an initial household survey conducted from May to June 2008, (2) monthly visit surveys accomplished from June to November 2008 and (3) a final household survey conducted during November to December 2009. The cost of pesticide use and exposure was highest for medium-scale household; however, the economic burden in relation to incomes was the highest for small-scale household. On the basis of area under vegetables, small-scale household incurred 23 % higher economic burdens compared to the large-scale household. Overall, the cost of pesticide use and exposure amounted 15 % of agricultural income and/or 5 % of gross household income. For small-scale households, the cost was equivalent to 18 % of agricultural income and 6 % of gross income. Small-scale households are not only deprived from benefits of agriculture intensification, but also incurred highest burden of pesticide use.     

Present to future sediment transport of the Brahmaputra River: reducing uncertainty in predictions and management

The Brahmaputra River in South Asia carries one of the world’s highest sediment loads, and the sediment transport dynamics strongly affect the region’s ecology and agriculture. However, present understanding of sediment conditions and dynamics is hindered by limited access to hydrological and geomorphological data, which impacts predictive models needed in management. We here synthesize reported peer-reviewed data relevant to sediment transport and perform a sensitivity analysis to identify sensitive and uncertain parameters, using the one-dimensional model HEC-RAS, considering both present and future climatic conditions. Results showed that there is considerable uncertainty in openly available estimates (260–720 Mt yr^?1) of the annual sediment load for the Brahmaputra River at its downstream Bahadurabad gauging station (Bangladesh). This may aggravate scientific impact studies of planned power plant and reservoir construction in the region, as well as more general effects of ongoing land use change and climate change. We found that data scarcity on sediment grain size distribution, water discharge, and Manning’s roughness coefficient had the strongest controls on the modelled sediment load. However, despite uncertainty in absolute loads, we showed that predicted relative changes, including a future increase in sediment load by about 40 % at Bahadurabad by 2075–2100, were consistent across multiple model simulations. Nevertheless, for the future scenarios we found that parameter uncertainty almost doubled for water discharge and river geometry, highlighting that improved information on these parameters could greatly advance the abilities to predict and manage current and future sediment dynamics in the Brahmaputra river basin.     

Optimum design and evaluation of hybrid solar/wind/diesel power system for Masirah Island

This paper addresses the requirements of electrical energy for an isolated island of Masirah in Oman. The paper studied the possibility of using sources of renewable energy in combination with current diesel power plant on the island to meet the electrical load demand. There are two renewable energy sources used in this study, solar and wind energy. This study aimed to design and evaluate hybrid solar/wind/diesel/battery system in terms of cost and pollution. By using HOMER software, many simulation analyses have been proposed to find and optimize different technologies that contain wind turbine, solar photovoltaic, and diesel in combination with storage batteries for electrical generation. Four different hybrid power systems were proposed, diesel generators only, wind/diesel/battery, PV/diesel/battery, and PV/wind/diesel/battery. The analysis of the results shows that around 75 % could reduce the cost of energy by using PV/wind/diesel hybrid power system. Also, the greenhouse emission could be reduced by around 25 % compared with these by using diesel generators system that currently utilize in the Masirah Island. The solar/wind/diesel hybrid system is techno-economically viable for Masirah Island.     

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of ?1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the ‘most’ appropriate system when a review or upgrade of the network infrastructure is required.     

Long-term simulation of effects of energy crop cultivation on nitrogen leaching and surface water quality in Saxony/Germany

The production of energy crops in Germany is a growing agronomic sector and is expected to occupy a substantial share of farmland in the near future. At the same time, there are concerns that energy crops might cause increased nitrogen pollution of soil water, surface water and groundwater. Therefore, the Federal State of Saxony, Germany, funded a study on potential effects of an intensified cultivation of energy crops. In frame of this study, we used the Web GIS-based model STOFFBILANZ to simulate N leaching from the rooting zone and N loads of surface water for a reference scenario and an energy crop scenario. For the reference scenario, we used data representing the crop cultivation for the year 2005 at municipality level. We found that the total loads for N leaching from the rooting zone of cropland are highest for the loess region (8,067 t year^?1), followed by mountainous region (6,797 t year^?1) and lowland (5,443 t year^?1). However, highest N fluxes in the leachate from rooting zones have been simulated for lowland (40.6 kg ha^?1 year^?1) and mountainous region (37.1 kg ha^?1 year^?1), while nitrate concentrations of leachate were highest for the lowland (101.8 mg l^?1). In terms of diffuse N input into surface water, the mountainous region is the most important source area (total N load 6,380 t year^?1, flux 34.6 kg ha^?1 year^?1). Retention by in-stream processes accounts for 15 % (3,784 t year^?1) of the total N load leaving the study area (25,136 t year^?1). In the 2020 energy crop scenario, shares of rape and silage maize (id., ensiled corn) were limited for each municipality to a maximum of 25 and 33 %, respectively. The conversion of grasslands to crop farming was not allowed. Under these conditions, we found slight to substantial reductions of nitrogen loads for leachate from the rooting zone and for surface waters. The simulated reduction depends strongly on local conditions. Only small reductions (ca. 4–8 %) were found for the lowlands and mountainous regions of Saxony, while reductions for the loess region were substantial (ca. 22 %). A major outcome of our study is that the cultivation of energy crops might reduce N loss if certain preconditions are assumed, for example, without conversion of grasslands to crop farming. However, effects might vary widely depending on local conditions.     

Economic feasibility of autonomous hybrid wind–diesel power systems for residential loads in hot regions: a step to mitigate the implications of fossil fuel depletion

Today, energy occupies a pivotal position around which all socio-economic activities revolve. No energy means no life, and supply of energy in a cheap, plentiful, long-sustainable and environmentally safe form is a boon for everyone. In the light of rising cost of oil and fears of its exhaustion coupled with increased pollution, the governments worldwide are deliberating and making huge strides to promote renewable energy sources such as wind. Integration of wind machines with the diesel plants is pursued widely to reduce dependence on fossil-fuel-produced energy and to reduce the release of carbon gases that cause global climate change. The literature indicates that commercial/residential buildings in the Kingdom of Saudi Arabia (KSA) consume an estimated 10–40% of the total electric energy generated. The aim of this study is to analyse wind-speed data of Dhahran (East-Coast, KSA) to assess the economic feasibility of utilising autonomous hybrid wind–diesel power systems to meet the electrical load of 100 typical residential buildings (with annual electrical energy demand of 3512 MWh). The monthly average wind speeds range from 3.3 to 5.6 m/s. The hybrid systems simulated consist of different combinations of 600 kW commercial wind machines supplemented with diesel generators. The National Renewable Energy Laboratory's hybrid optimisation model for electric renewables software was employed to perform the techno-economic analysis.

The simulation results indicate that for a hybrid system comprising 600 kW wind capacity together with a 1.0 MW diesel system (two 500 kW units), the wind penetration (at 50 m hub-height, with 0% annual capacity shortage) is 26%. The cost of generating energy (COE, $/kWh) from this hybrid wind–diesel system was found to be 0.070 $/kWh (assuming diesel fuel price of 0.1 $/l). The study exhibits that for a given hybrid configuration, the number of operational hours of diesel generator sets (gensets) decreases with an increase in the wind-farm capacity. Concurrently, emphasis has also been placed on wind penetration, un-met load, effect of hub-height on energy production and COE, excess electricity generation, percentage fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost breakdown of wind–diesel systems, COE of different hybrid systems, etc.     

Freshwater stress on small island developing states: population projections and aridity changes at 1.5 and 2 °C

Small island developing states (SIDS) face multiple threats from anthropogenic climate change, including potential changes in freshwater resource availability. Due to a mismatch in spatial scale between SIDS landforms and the horizontal resolution of global climate models (GCMs), SIDS are mostly unaccounted for in GCMs that are used to make future projections of global climate change and its regional impacts. Specific approaches are required to address this gap between broad-scale model projections and regional, policy-relevant outcomes. Here, we apply a recently developed methodology that circumvents the GCM limitation of coarse resolution in order to project future changes in aridity on small islands. These climate projections are combined with independent population projections associated with shared socioeconomic pathways (SSPs) to evaluate overall changes in freshwater stress in SIDS at warming levels of 1.5 and 2 °C above pre-industrial levels. While we find that future population growth will dominate changes in projected freshwater stress especially toward the end of the century, projected changes in aridity are found to compound freshwater stress for the vast majority of SIDS. For several SIDS, particularly across the Caribbean region, a substantial fraction (~?25%) of the large overall freshwater stress projected under 2 °C at 2030 can be avoided by limiting global warming to 1.5 °C. Our findings add to a growing body of literature on the difference in climate impacts between 1.5 and 2 °C and underscore the need for regionally specific analysis.     

Pesticide handling practices by vegetable farmer in Kenya

Pesticide handling practices have a strong bearing on the exposure of toxic effects to target and nontarget organism. A clear understanding of determinants of pesticide handling practices is a precondition in the design and implementation of policy intervention. To accomplish this, a household survey of 425 respondents was conducted in 2008. Majority of the farmers (85 %) had inappropriately handled pesticides, mainly through, unsafe storage (23 %), unsafe disposal of leftover in either sprays solutions, or rinsate and empty pesticide containers (40 %), failure to wear the required minimum protective gear (68 %), or overdosed pesticides (27 %). However, majority of those farmers were aware of the risks of pesticide use, with over 81 % expressing the view that pesticides have harmful effects on human health, livestock, beneficial arthropods, and on water. Econometric models showed that pesticide handling practices were significantly influenced by variation in record keeping, main source advice on pesticide use, toxicity of pesticide, and geographical location. Pesticide risk perception and negative impacts experiences had no association with handling practices. The study recommends policymakers to design effective, participatory, and location targeted outreach programmes, which deal specifically on promotion of record keeping and reduction in use of harmful pesticides.     

Life cycle sustainability assessments (LCSA) of four disposal scenarios for used polyethylene terephthalate (PET) bottles in Mauritius

Improper disposal of post-consumer Polythylene Terephthalate (PET) bottles constitutes an eyesore to the environmental landscape and gives rise to numerous environmental and health-related nuisances. These problems impact negatively on the flourishing tourism industry in Mauritius. The present study was therefore undertaken to determine a sustainable disposal method among four selected disposal alternatives of post-consumer PET bottles in Mauritius. The disposal scenarios investigated were: 100 % landfilling (scenario 1); 75 % incineration with energy recovery and 25 % landfilling (scenario 2); 40 % flake production (partial recycling) and 60 % landfilling (scenario 3); and 75 % flake production and 25 % landfilling (scenario 4). Environmental impacts of the disposal alternatives were determined using ISO standardized life cycle assessment (LCA) and the SimaPro 7.1 software. Cost-effectiveness was determined using Life cycle costing (LCC) as described by the recent Code of Practice on LCC. An excel-based model was constructed to calculate the various costs. Social impacts were evaluated using Social Life Cycle Assessment (S-LCA) based on the UNEP/SETAC Guidelines for Social Life Cycle Assessment. For this purpose, a new and simple social life cycle impact assessment method was developed for aggregating inventory results. Finally, Life Cycle Sustainability Assessment (LCSA) was conducted to conclude the sustainable disposal route of post-consumer PET bottles in Mauritius. The methodology proposed to work out LCSA was to combine the three assessment tools: LCA, LCC and S-LCA using the Analytical Hierarchy Process. The results indicated that scenario 4 was the sustainable disposal method of post-consumer PET bottles. Scenario 1 was found to be the worst scenario.     

Socio-economic vulnerability of the megacity of Shanghai (China) to sea-level rise and associated storm surges

Sea-level rise (SLR) poses a significant threat to many coastal areas and will likely have important impacts on socio-economic development in those regions. Located on the eastern coast in China, the megacity of Shanghai is particularly vulnerable to SLR and associated storm surge risks. Using the municipality of Shanghai as a case study, the possible impacts of flooding risks caused by SLR and associated storm surges on socio-economic development in the region were analysed by a Source–Pathway–Receptor–Consequence (SPRC) conceptual model. The projections of flooding risk in the study area were simulated by MIKE21 (a two-dimensional hydrodynamic model) for the three time periods of 2030, 2050 and 2100. An index system for vulnerability assessment was devised, in which flooding depth, density of population, GDP per capita, GDP per unit land, loss rate under flooding and fiscal revenue were selected as the key indicators. A quantitative spatial assessment method based on a GIS platform was established by quantifying each indicator, calculating and then grading the vulnerability index. The results showed that in the 2030 projection, 99.3 % of the areas show no vulnerability to SLR and associated storm surges under the present infrastructure. By 2050, the areas with low, moderate and high vulnerabilities change significantly to 5.3, 8.0 and 23.9 %, respectively, while by 2100, the equivalent figures are 12.9, 6.3 and 30.7 %. The application of the SPRC model, the methodology and the results from this study could assist with the objective and quantitative assessment of the socio-economic vulnerability of other similar coastal regions undergoing the impacts of SLR and associated storm surges. Based on the results of this study, mitigation and adaptation measures should be considered, which include the controlling the rate of land subsidence, the reinforcement of coastal defence systems and the introduction of adaptation in long-term urban planning.     

Climate change impacts on a pine stand in Central Siberia

The objective of this paper is to analyse the impacts of climate change on a pine forest stand in Central Siberia (Zotino) to assess benefits and risks for such forests in the future. We use the regional statistical climate model STARS to develop a set of climate change scenarios assuming a temperature increase by mid-century of 1, 2, 3 and 4 K. The process-based forest growth model 4C is applied to a 200-year-old pine forest to analyse impacts on carbon and water balance as well as the risk of fire under these climate change scenarios. The climate scenarios indicate precipitation increases mainly during winter and decreases during summer with increasing temperature trend. They cause rising forest productivity up to about 20 % in spite of increasing respiration losses. At the same time, the water-use efficiency increases slightly from 2.0 g C l^?1 H₂O under current climate to 2.1 g C l^?1 H₂O under 4 K scenario indicating that higher water losses from increasing evapotranspiration do not appear to lead to water limitations for the productivity at this site. The simulated actual evaporation increases by up to 32 %, but the climatic water balance decreases by up to 20 % with increasing temperature trend. In contrast, the risk of fire indicated by the Nesterov index clearly increases. Our analysis confirms increasing productivity of the boreal pine stand but also highlights increasing drought stress and risks from abiotic disturbances which could cancel out productivity gains.     

Feasibility of PV–biodiesel hybrid energy system for a cement technology institute in India

This paper compares an existing unreliable grid supply with a proposed PV–biodiesel hybrid energy system in order to find the feasibility of the latter for improvement in reliability of power supply, lower pollutant emissions and saving of coal reserves. In the present study, the electrical load of a cement technology institute located in Bhilai, India, has been selected for the purpose of analysis. The results show that hybrid PV–biodiesel system comprising 25 kW PV array, 8 kW biodiesel generator-1, 20 kW biodiesel generator-2, 10 kW inverter and 10 kW rectifier will supply power to the institute avoiding addition of 27.744 tons of CO₂ in atmosphere and save 55,080 kg of coal per year with improvement in reliability from 93.15 to 100%.     

上海地区夏季气温变化对用电负荷的影响

利用上海地区2003~2007年6~9月日最高用电负荷和逐日气温资料，提取夏季日最高用电负荷气象变化量，分析了上海地区夏季气温变化对日最高用电负荷的影响。结果表明上海地区夏季日最高用电负荷气象变化量的变化趋势与日平均气温、日最高气温和日最低气温的变化趋势一致。日最高气温≥33℃为引起上海日最高用电负荷增加的初始气温敏感点，日最高气温≥35℃为强气温敏感点，日最高气温≥39℃则为极端气温敏感点。高温期间上海日最高用电负荷随气温增加的幅度较大，日最高用电负荷气象变化量的第95百分位数对应于38℃以上的高温日。上海日最高用电负荷气象变化量与月、日空调度日数成正比关系，当日空调度日数比常年偏多1倍以上时，上海处在强高温过程，日最高负荷随气象增幅较大，电力部门调电难度增加     

Stand-alone wind power system with battery/supercapacitor hybrid energy storage

This paper presents a stand-alone wind power system with battery/supercapacitor hybrid energy storage. A stand-alone wind power system mainly consists of a wind turbine, a permanent magnet synchronous generator, hybrid energy storage devices based on a vanadium redox flow battery and a supercapacitor, an AC/DC converter, two bidirectional DC/DC converters, a DC/AC converter and a variable load. Several control strategies for the stand-alone wind power system are involved such as a maximum power point tracking (MPPT) control, a vanadium redox flow battery charge/discharge control and a supercapacitor charge/discharge control. The proposed MPPT control combines a sliding mode control with an extreme search control to capture maximum wind energy. This strategy avoids the necessity of measuring wind velocity, obtaining models or parameters of the wind turbine and calculating the differentials of the power generated from the wind power system and from the speed of the generator. The battery charge/discharge control maintains a constant DC bus voltage. When the battery charging/discharging current reaches the setting threshold, the charge/discharge control of the supercapacitor is triggered to limit the charging/discharging current of the battery. The simulation results show that the proposed method can rapidly respond to variations in wind velocity and load power.     

Modelling livelihoods and household resilience to droughts using Bayesian networks

Over the last four decades, the Indian government has been investing heavily in watershed development (WSD) programmes that are intended to improve the livelihoods of rural agrarian communities and maintain or improve natural resource condition. Given the massive investment in WSD in India, and the recent shift from micro-scale programmes (<500 ha) to meso-scale (~5000 ha) clusters, robust methodological frameworks are needed to measure and analyse impacts of interventions across landscapes as well as between and within communities. In this paper, the sustainable livelihoods framework is implemented using Bayesian networks (BNs) to develop models of drought resilience and household livelihoods. Analysis of the natural capital component model provides little evidence that watershed development has influenced household resilience to drought and indicators of natural capital, beyond an increased area of irrigation due to greater access to groundwater. BNs have proved a valuable tool for implementing the sustainable livelihoods framework in a retrospective evaluation of implemented WSD programmes. Many of the challenges of evaluating watershed interventions using BNs are the same as for other analytical approaches. These are reliance on retrospective studies, identification and measurement of relevant indicators and isolating intervention impacts from contemporaneous events. The establishment of core biophysical and socio-economic indicators measured through longitudinal household surveys and monitoring programmes will be critical to the success of BNs as an evaluation tool for meso-scale WSD.     

Energy rating methodology for light-duty vehicles: geographical impact

The aim of this paper was to describe a new energy dependency score methodology and its consequent application to cars sold in twelve regions: Europe (EU-28) and eleven specific countries worldwide (Australia, Brazil, China, India, Japan, Norway, Portugal, Russia, Saudi Arabia, South Africa and USA). This methodology was developed as a potential tool to inform consumers of their choice impact on the country’s economy. This methodology is based on primary energy assessments and origins for each energy pathway associated with a gasoline-, diesel-, natural gas (used for H₂ production)- or electricity (balanced with country electricity mix)-powered vehicle. An energy dependency index was attributed to the best-case (100 % endogenous production) and worst-case (0 % endogenous production) scenarios and consequently weighted with vehicle fuel consumption. This enabled obtaining an energy dependency index (10–0). This index could be assigned to an environmental and social index to provide a sustainability index and therefore complement a road vehicle environmental rating system, providing a combined index rating. Internal combustion engine vehicles and hybrid vehicles (that have oil products as energy source) rate the lowest for almost all locations, with the exception of regions that are energy independent (Norway, Saudi Arabia or Russia). Electric vehicles rank higher when comparing to the other technologies analyzed for all locations in this study. The plug-in hybrid electric vehicle shows generally a rank in an intermediate place, except for Japan where it scores lower than all other technologies.     

Assessing and selecting interventions for river water quality improvement within the context of population growth and urbanization: a case study of the Cau River basin in Vietnam

In this study, a multi-criteria methodology is proposed to identify and prioritize interventions for water quality improvement with the aid of computer simulation models. The methodology can be used to elaborate and compare future socio-economic development scenarios to select the best interventions based on three criteria: (1) ideas of experts and stakeholders about the importance of scenarios, (2) impacts of each scenario on surface water quality in watershed, and (3) benefit–cost analysis for each scenario. A score is computed for each scenario based on a weighted sum technique which enables to take into consideration different level of importance for the three criteria. The methodology is applied to Cau River basin in Vietnam, with the aid of a computer tool, to assess interventions for river water quality improvement within the context of population growth and urbanization. The results show that fast future population growth in upstream has significant impacts. In 2020, an increase of 116 % of the population in Bac Kan town can lead to an increase of 120 and 135 % in BOD₅ and NH₄ ⁺ median concentrations, respectively, with the implementation of a treatment plant for 10,000 people in Bac Kan town. Therefore, the increase of the domestic wastewater treatment plant’s capacity in Bac Kan town, at least twice as the projection of local government, is necessary. These results will help decision makers to select the best interventions for Cau River basin management.