An Integrated Assessment by Models for Energy Systems Analysis and Life-Cycle Assessment with a Case Study of Advanced Fossil-Fired Power Plants in China

We developed an integrated assessment (IA) using models for energy systems analysis and life-cycle assessment (LCA). Based on this assessment framework, we developed cost-benefit analysis (CBA) case studies for a hypothetical project designed to introduce advanced fossil-fired power generation technologies in China. Our MARKAL model for Japan confirmed that radical reductions (i.e., 80 % by 2050) of carbon dioxide (CO₂) could be attained from energy systems alone and that credit for emission allowances was required. We evaluated life-cycle costs and emissions of carbon dioxide, sulfur oxide, and nitrogen oxide gases for the energy technologies using an LCA model. Further, we applied a power generation planning model for six Chinese grids to provide a power mix structure, potentially producing credit by installing fossil-fired power generation technology and by using baseline grid emission factors with an average cost of electricity. Finally, by using dynamic emission reductions and additional costs from the two models, we conducted case studies of CBA for a hypothetical project to install the technologies in China. This was accomplished by evaluating emission reductions in monetary terms and by applying a life-cycle impact assessment model. A unique feature of our IA is its dynamic (time-varying) assessment of costs and benefits.     

SWOT analysis for the development of photovoltaic solar power in Africa in comparison with China

Development of solar power becomes a necessary measure to combat global climate change and local environmental pollution in the world. In Africa, solar power resource is abundant, and deployment of solar photovoltaic (PV) offers a new opportunity for both economic growth and low-carbon development. Using an approach of SWOT analysis, we investigate the internal strengths and weaknesses, and the external opportunities and threats for PV solar power development in Africa. Particularly, factors are examined and discussed for African countries in terms of their internal strengths of rich solar resource, vast land, suitable application for distributed PV power systems; their weaknesses of small scale of renewable energy investment, shortness of foundation for the PV industrial chain, insufficient awareness of social and environmental benefits of solar PV; their external opportunities of increasing gap between energy supply and demand, raising global awareness of Climate Change, rapid decrease of PV price, as well as their external threats of dominant position of the fossil fuels, potential environmental impacts related to the solar PV development, and discontinuity of energy policies. The analysis particularly emphasizes on a new opportunity for African countries to develop their solar power resource through mutually beneficial cooperation between Africa and China within the framework of the Belt and Road Initiative (BRI).     

Impacts of Decentralized Power Generation on Distribution Networks: a Statistical Typology of European Countries

The development of decentralized sources of power out of renewable sources of energies has been triggering far-reaching consequences for Distribution System Operators over the past decade in Europe. Our paper benchmarks across 23 European countries the impact of the development of renewables on the physical characteristics of power distribution networks and on their investments. It builds on a large spectrum of databases of quantitative indicators about the dynamics of installed capacity of renewable energy resources and the power generation out of them, electricity independence, quality of electricity distribution, smart grids investments, Network System Operators capital expenditures, length of the distribution networks, overall costs of power networks paid by private agents, and electricity losses, all in relation with the development of decentralized generation. The heterogeneity of these indicators across Europe appears to be wide notably because of physical constraints, historic legacies, or policy and regulatory choices. A cluster analysis allows for deriving six groups of countries that display statistically homogenous characteristics. Our results may provide decision makers and regulators with a tool helping them to concentrate on the main issues specific to their countries as compared to the European median, and to look for possible solutions in the experience of other clusters which are shown to perform better for some indicators.     

Advanced energy consumption system for smart farm based on reactive energy utilization technologies

Over the decades, both agriculture and energy grids have encountered significant challenges, such as the lack of power supply to agricultural farms and the difficulties of renewable energy use in the electricity sector. To overcome and address these issues, this paper presents an idea of merging smart farm and renewable energy, using surplus renewable energy for the agriculture sector using the smart farm for renewable energy supplies. First, demonstrate the framework to connect a smart farm energy system and analyze its feasibility and advantages. In this paper, Reactive Energy Utilization Technology (REUT) has been used as an efficient energy consumption system for the smart farm. It is used to predict the optimum wind power scenario in the smart farm by monitoring continuous control variables, with the lowest voltage reached in each scenario, and minimized actual total power losses. A combined system consisting of smart farming production, as well as renewable energy consumption, has been evaluated in experimental results. Experimental results and discussion shows that the proposed method has better renewable energy consumption, accuracy(96.7%), and efficiency(95.6%) for smart farming.     

IoT driven framework based efficient green energy management in smart cities using multi-objective distributed dispatching algorithm

Nowadays, the concept of smart cities evolves from conceptual models to various stages of development. The smart services of cities like smart buildings, smart hospitals, smart traffic, smart factories, and smart transportation are vital to energizing resilient, reliable, seamless energy and electrical flow. One of these smart services' critical challenges is anticipated to run without disruptions using smart energy and smart electrical grids. Hence, in this research, the Internet of Things (IoT) role in green energy resources incorporation into smart electrical grids has been introduced using the Multi-Objective Distributed Dispatching algorithm (MODDA). Efficient energy management includes a tradeoff between the cost linked with utility function and energy consumption. The utility function can be the living comfort of the consumers or the utility firm's gross income. The interchanges between utility and energy consumption must, therefore, be recognized. The algorithm is intended to transmit the renewable green energy available to the battery, thermal, and load storing while preserving a thermal and battery storage limit. The experimental results at the lab-scale show the proposed dispatching algorithm minimizing the system cost and energy consumption. It is shown that substantial energy waste can be reduced by equipping a smart building with the proposed IoT system for effective green energy management.     

重庆城市电网工频电磁环境现状及安全性分析

在现场实测的基础上,分析研究了重庆城市电网中各种电压等级、各种类型变电站周边环境,多种形式架空线路下方区域以及地下电缆周围工频电磁环境的现状,对比国家现行标准限值,评价重庆城市电网的工频电磁环境的安全性,同时也指出随着架空线密度的增加,周围工频电场不但不增加,反而有降低的现象.目前擅自在输电线路下建房或增加房屋高度是危及电磁环境安全的主要问题,应加大监管力度,减少日后不必要的环保纠纷.     

Economic and environmental impacts of photovoltaic power with the declining subsidy rate in China

Photovoltaic (PV) power is expected to play an important role in reducing global warming and improving energy security. China promotes PV power development by implementing feed-in tariff policies. However, the economic and environmental impacts of substituting coal-fired electricity with PV power, particularly as the subsidy rate declines, are not well-known. This study estimates the economic and environmental impacts in different cases and scenarios by combining life-cycle assessment with input-output analysis. Results indicate that substituting PV power for coal-fired electricity has negative impacts on employment, household income, and tax revenue. Although this substitution can promote economic growth when PV power generation is subsidised, the impact of the substitution on GDP will gradually decline as the subsidy rate is reduced and finally becomes negative. Assuming that the levelized cost of PV power declines following the learning curve, the same results will hold even if PV power generation becomes profitable in the future. Despite its negative impacts on employment, household income and tax revenue, the substitution has huge external values. Therefore, policies are needed to internalise the external value and address the economic impacts of the substitution.     

Land Sharing vs Land Sparing to Conserve Biodiversity: How Agricultural Markets Make the Difference

In this paper, we model the supply and demand for agricultural goods and assess and compare how welfare, land use, and biodiversity are affected under intensive and extensive farming systems at market equilibrium instead of at exogenous production levels. As long as demand is responsive to price, and intensive farming has lower production costs, there exists a rebound effect (larger market size) of intensive farming. Intensive farming is then less beneficial to biodiversity than extensive farming is, except when there is a high degree of convexity between biodiversity and yield. On the other hand, extensive farming leads to higher prices and smaller quantities for consumers. Depending on parameter values, it may increase or decrease agricultural producer profits. Implementing “active” land sparing by zoning some land for agriculture and other land for conservation could overcome the rebound effect of intensive farming, but we show that farmers have then incentives to encroach on land zoned for conservation, with higher incentives under intensive farming. We also show that the primary effect of the higher prices associated with extensive farming is a reduction of animal feed production, which has a higher price elasticity of demand, whereas less of an effect is observed on plant-based food production and almost no effect is observed on biofuel production if there are mandatory blending policies.     

Nuclear Versus Coal plus CCS: a Comparison of Two Competitive Base-Load Climate Control Options

In this paper, we analyze the relative importance and mutual behavior of two competing base-load electricity generation options that each are capable of contributing significantly to the abatement of global CO₂ emissions: nuclear energy and coal-based power production complemented with CO₂ capture and storage (CCS). We also investigate how, in scenarios developed with an integrated assessment model that simulates the economics of a climate-constrained world, the prospects for nuclear energy would change if exogenous limitations on the spread of nuclear technology were relaxed. Using the climate change economics model World Induced Technical Change Hybrid, we find that until 2050 the growth rates of nuclear electricity generation capacity would become comparable to historical rates observed during the 1980s. Given that nuclear energy continues to face serious challenges and contention, we inspect how extensive the improvements of coal-based power equipped with CCS technology would need to be if our economic optimization model is to significantly scale down the construction of new nuclear power plants.     

The effect of absorbent grid preparation method on precision and accuracy of ambient nitrogen dioxide measurements using Palmes passive diffusion tubes

A few studies have suggested that the precision and accuracy of measurement of NO(2) by Palmes-type passive diffusion tube (PDT) are affected by the method of preparation of the triethanolamine (TEA) absorbent coating on the grids. Theses studies have been quite limited in extent and have tended to evaluate PDT accuracy as zero bias between PDT NO(2) value and the exposure-averaged NO(2) determined by co-located chemiluminescence analyser. This ignores the well-documented intrinsic systematic biases on PDT-derived NO(2), such as within-tube chemistry and exposure-duration nitrite loss, which may lead to non-zero bias values irrespective of effects of TEA absorbent preparation method on PDT accuracy. This paper reports on a statistical analysis of a large dataset comprising 680 duplicated PDT exposures spanning 146 separate exposure periods, spread over five urban exposure locations and a number of years. In each exposure period, PDTs prepared by between four and six different grid preparation methods were simultaneously compared. The preparation methods used combinations of the following: acetone or water as the TEA solvent; 20% or 50% as %TEA in the solution; and application of TEA solution by dipping grids for several minutes in the solution before drying and tube assembly, or by pipetting 50 microL of solution directly onto grids already placed in the PDT cap. These represent the range of preparation procedures typically used. Accuracy was evaluated as maximised nitrite capture within an exposure. Data were analysed by general linear modelling including examination of interaction between different aspects of grid preparation method. PDT precision and accuracy were both significantly better, on average, when the PDT grids were prepared by dipping in TEA solution, and neither solvent or %TEA used for the dipping solution were important. Where PDT preparation by pipetting TEA solution onto grids is to be used, better performance was obtained using 20% TEA in water. A systematic positive bias in PDT measure of NO(2), consistent with within-tube oxidation of NO to NO(2) and independent of preparation method, was again evident in this work.     

Deficit analysis: service capacity assessment and planning in developing countries – case study in the Philippines

Current demand analysis methods do not formally cover the case of chronic deficits in quantity or quality of water and sanitation services. These services include drinking water supply (DWS), wastewater and sewage treatment (WST), and municipal solid waste management (MSW). Formal analysis of this case would, at minimum, define the deficit state and evaluate appropriate options for reducing it. This paper proposes for a formal analytical model for municipal sanitation systems (MSS) that operate with deficits in at least one of the constituent services of DWS, WST, or MSW. The model introduces definitions and notation for describing the deficit state for conducting demand analysis on municipal sanitation systems. This model of demand analysis for systems with chronic deficits will hereinafter be referred to as deficit analysis. A case study for Bacoor, Philippines is presented as an example.     

Advancing Energy Access Modelling with Geographic Information System Data

One of the main goals in pursuing sustainable development is to provide universal access to modern energy services, notably through the use of off-grid renewable energy technologies. To date, integrated assessment models (IAMs) poorly address energy access targets. In the context of research dedicated to energy scenarios and climate change mitigation in Africa, we attempt to advance the representation of energy access in one such IAM by using GIS data. In a case study for Ethiopia with the TIAM-ECN model, we demonstrate that by enriching an IAM with information derived from GIS databases, insights are obtained that better capture the dynamics of energy access developments, in comparison to conventional IAM analysis of energy technology deployment pathways. When duly accounting for the geographical spread in demography and technology costs in a developing country, we find that many people may gain access to electricity in remote areas thanks to the availability of affordable off-grid power production options that render expensive grid extensions unnecessary. This effect is not explicitly accounted for in most traditional IAMs. By the middle of the century, off-grid technologies could provide affordable electricity to 70% of the Ethiopian population, based almost entirely on renewable sources such as wind, solar and hydropower.     

Wind energy and Turkey

The global energy requirement for sustaining economic activities, meeting social needs and social development is increasing daily. Environmentally friendly, renewable energy resources are an alternative to the primary non-renewable energy resources, which devastate ecosystems in order to meet increasing demand. Among renewable energy sources such as hydropower, biopower, geothermal power and solar power, wind power offers distinct advantages to Turkey. There is an increasing tendency toward wind globally and the European Union adjusted its legal regulations in this regard. As a potential EU Member state, Turkey is going through a similar process. The number of institutional and legal regulations concerning wind power has increased in recent years; technical infrastructure studies were completed, and some important steps were taken in this regard. This study examines the way in which Turkey has developed support for wind power, presents a SWOT analysis of the wind power sector in Turkey and a projection was made for the concrete success expected to be accomplished in the future.     

Modelling and assessing inter-regional trade of CO2 emission reduction units

A cost-efficient way to allocate carbon dioxide (CO₂) emission reductions among countries or regions is to harmonise their marginal reduction costs. This could be achieved by a market of emission reduction units (ERUs). To model such a market, we use a multi-regional MARKAL-MACRO model. It gives insights into the consequences of co-ordinating CO₂ abatement on regional energy systems and economies. As a numerical application, we assess the establishment of a market of ERUs among three European countries for curbing their CO₂ emissions.     

A dynamic analysis of the global warming potential associated with air conditioning at a city scale: an empirical study in Shenzhen,China

Heating, ventilation and air conditioning (HVAC) systems are a major source of energy consumption in buildings, directly and indirectly contributing to greenhouse gas (GHG) emissions. In the urban environment, and depending on local climatic conditions, air conditioning units attribute to these high energy demands. This study analyzes the use of residential air conditioning units and their associated global warming potential (GWP) between 2005 and 2030 for the city of Shenzhen, a fast-growing megacity located in Southern China. A life cycle assessment approach was adopted to quantify the GWP impacts which arise from both direct (refrigerant release) and indirect (energy consumption) sources, in combination with a materials flow analysis approach. The results show that the total GWP (expressed as carbon dioxide equivalents, CO₂ eq.) from residential air conditioning systems increased from 2.2 ± 0.2 to 5.1 ± 0.4 million tonnes (Mt) CO₂ eq. between 2005 and 2017, with energy consumption and refrigerant release contributing to 72.5% and 27.5% of the total demands, respectively. Immediate measures are required to restrict refrigerant release and reduce the energy consumption of air conditioning units, to help mitigate the predicted additional total emissions of 36.4 Mt. CO₂ eq. potentially released between 2018 and 2030. This amount equals to approximately New Zealand's national CO₂ emissions in 2017. The findings proposed in this study targets air conditioning units to reduce the GWP emissions in cities, and provide useful data references and insights for local authorities to incentivise measures for improving building energy efficiency management and performance.     

Assessing Development Pressure in the Chesapeake Bay Watershed: An Evaluation of Two Land-Use Change Models

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations.     

Evaluation of the best compromise between the urban air quality monitoring resolution by diffusive sampling and resource requirements

The need to collect data representative of overall urban pollution is all-important in order to monitor the population exposure. High spatial resolution monitoring using diffusive samplers allows studying of the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost. In this study we point out how to find the best compromise between the number of necessary measurements and the affordable costs for monitoring campaigns. We also describe an innovative method for the proper design of a fixed urban monitoring network by means of preliminary high spatial resolution campaigns using diffusive samplers. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO(2) concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km. The statistical processing of data produced a twofold result: the creation of isoconcentration maps with geostatistical procedures, and an algorithm aimed at locating the minimum number of sampling sites where the fixed monitoring stations should be placed. Average urban levels estimated on the basis of these selected sites differ by less than 8% from those calculated on the whole populations of the sampled points. The aim of this work is to investigate how far the resolution of a monitoring campaign of urban pollution by diffusive sampling can be reduced, thus making the monitoring less expensive in terms of human and financial resources, while preserving the same quality of the results that could be achieved with a higher resolution. We found that there is no significant loss of information when the resolution of the monitoring grid for BTEX is lowered to a mesh size of 1.85 km, that is a sampling site each 3.4 km(2), and that the minimum number of sampling sites to be used is N = 0.29 A, where A is the urban surface to be monitored (in km(2)). As the spatial distribution of NO(2) is less sensitive to the distance from the emission source than that of BTEX, this relationship could be retained as a valid lower limit for the mesh grid size also for NO(2) monitoring.     

重庆电网环境噪声监测与分析

通过对重庆电网环境噪声的监测与分析,揭示了重庆电网环境噪声的整体状况,分析了主要噪声源的特性,以及在不同状况下的大小变化规律、达标状况,并提出了降低电网环境噪声的建议和意见,其目的在于促进电网环保技术水平的不断提高,缓解企业面临的环保压力,促进社会的和谐与稳定。     

Eco-Efficiency of Electric and Electronic Appliances: A Data Envelopment Analysis (DEA)

Several papers have studied the eco-efficiency of manufacturing systems to address strategic socioeconomic issues in the context of sustainability analysis. Their goal has been to take into account not only environmental impact aspects throughout the whole life cycle but also to incorporate the associated economic value as well, thus, giving a comprehensive vision of both factors. This paper focuses on different commonplace household electric appliances, comparing their eco-efficiency computed using a data envelopment analysis model. We consider the retail price as a measure of the product’s economic value and the ecopoint LCA score as the assessment of its environmental impact. We conclude that cell phones and the bulky analyzed appliances have the highest eco-efficiency scores, whereas the rest would require a more environmentally friendly redesign and/or an increase in their perceived value to improve their eco-efficiency.