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This article presents a novel active-mode indirect solar dryer consisting of highly efficiency through-flow evacuated tube collector for air heating. A DC fan powered with solar photovoltaic (PV) module is provided for forced air flow through this dryer. The dehydration chamber is of tray type with loading capacity of 6 kg–45 kg depending on the drying product. The dryer was evaluated to dry fenugreek leaves (Trigonella foenum-graecum) and turmeric (Curcuma longa) in semi-continuous mode; and respective overall thermal efficiency was found to be 34.1% and 23.6%. The respective thermal efficiency in open sun drying (OSD) was 5.7% and 5.4%. The quality of dried fenugreek leaves and turmeric was found better than OSD. Economics of the solar dryer indicate the capital cost is negligible in comparison to cumulative present worth of life cycle savings. The values are 211,262 INR (1 US$ = 74.57 INR) and 229,152 INR respectively for fenugreek leaves and turmeric; and capital cost of the dryer is only 50,000 INR. The low value of payback period also confirms economic viability of this dryer. The generalized economic curves have also been plotted.

The impacts of climate change, largely fuelled by the consumption of fossil fuels and an unhealthy consuming lifestyle, are encouraging a wide and far ranging adoption of renewable energy sources. This is critical, and well received, for countries who are on the frontline of climate change, in particular Small Island Developing States (SIDS) and those with fragile, unique and complex natural ecosystems. While there has been research on the importance of renewable energy and on the increasing of its efficiency for bettering its adoption and resulting economic gain, there is however little literature on the design and its implementation in respect to the rich and fragile biodiversity of areas; which contribute greatly to local ecosystems, and even to liveability dimensions of fauna, flora as well as humans, regions and cities. To ensure optimal energy generation while preserving fragile ecosystems, a method for numerical Genetic Algorithm (GA) is proposed for wind farming optimization to determine both the sitting of wind turbines and the Levelised Cost of Energy (LCOE). Optimal sites were identified in the small island of Mauritius and the model was applied on a complex terrain around an airport to identify optimal sites for the sitting of wind turbines while analysing the energy offset in terms of demand and supply of the area to encourage decentralised and more stable energy networks. Based on a set of parameters including local regulations and guidelines, 3 scenarios with a layout of 12, 24 and 36 wind farming sitting arrangements were proposed with a minimal impact on the fauna and flora; including the pathways of migratory birds. This paper is aimed at energy, urban planners and policy makers looking at sustainable energy planning.

Ensuring energy, water and food security is a core challenge as well as an opportunity to national sustainable development. This paper aims to perform an in-depth analysis on demand-driven energy, water and land resource requirements by Chinese economy 2012 and corresponding energy-water-land nexus relationships in its supply chains by using the input-output analysis and the structural path analysis. Results show that Agriculture and Light industry, mainly related to household consumption, are critical aggregated sectors for water and land requirements, in contrast to Heavy industry and Construction, which are related to investment for energy requirements. 15.41% of the total energy requirement, 44.18% of water and 58.64% of land can be attributed to the top 20 supply chain paths. The energy-water-land nexuses are explored by industrial sector, supply chain path and final demand category from the perspective of embodiment. On the final demand side, Agriculture, Light industry, Construction and Service are critical nexus sectors. Major sectoral nexus paths in terms of energy-land, energy-water, water-land, and energy-water-land nexuses are further identified. The energy-water-land nexus in China's supply chains reflect a strong dependence relationship of energy, water and land resource requirements, which then demonstrate essential intervention points of demand-side resource management.

Agriculture is responsible for 7.2% of the final energy consumption in the Netherlands; most energy is used for heating and lighting in the greenhouse sector. Currently, the greenhouse sector faces major challenges in reducing its energy demand while increasing crop quality and quantity. One route to improve the performance of industrial greenhouses could be based on using climate adaptive shells. These shells are capable of changing their thermal and optical properties on an hourly, daily, or seasonal basis to optimize performance. The climate adaptive shell concept shows considerable potential for performance improvement in the building sector. However, its potential for the greenhouse sector is yet unknown. This paper quantifies this potential by predicting the energy savings and the increase in net profit using a new framework based on numerical simulation and optimization techniques. The simulation results show that climate adaptive greenhouse shells increase net profit between 7% and 20% for tomato producing Dutch greenhouses. Monthly and hourly adaptation resulted in considerable primary energy savings of 23% and 37%, respectively. It is expected that the predicted net profit increase and energy savings will drive the attention of the greenhouse industry towards the development of climate adaptive greenhouse shells.

International audience; Among the tools and processes that are used to inform decisions makers on the long-term challenges raised by energy transition, numerical models are at the forefront. Whether led at the global, continental, country or local level, they help projecting the future operational conditions of our energy systems. However the possibility of addressing the sustainability challenge by changes in our lifestyles rather than technical solutions often remains outside the scope of such models whereas lifestyles contain a set of key determinants of mobility, housing, spatial planning or the organization terms of the productive sectors (industry, agriculture, services). Energy is not consumed for itself and understanding how the future demand of energy services could be framed is an important issue. This paper makes proposals to improve the consideration of lifestyles in the quantitative foresight exercises. Our methodology includes the development of a statistical model of the dynamic of changes in lifestyle patterns to derive energy service demands. The use of this model provides a more coherent framework for the formulation of lifestyle change scenarios. A set of three lifestyles anticipated for France are then designed and discussed up to 2072.

Industry and agriculture in Malaysia are the main contributors to economic growth and employment. These sectors also play an important role in Malaysia's total exports. The question then is whether technological innovation, sectoral output, and exports growth have had a real impact on these two sectors, which are very important for policy-making. This paper attempts to empirically identify such relations using econometric methods, including an autoregressive distributed lag (ARDL) bounds testing method and a dynamic ordinary least squares (DOLS) during 1978–2018. The results confirmed that overall long-run economic growth is the main contributor to the increase in energy consumption with a greater magnitude than in the short-run. In the long-run, an increase of 1% in economic growth leads to an increase of 4.6% and 1.1% in energy demand in agriculture and industrial sectors, respectively. Exports are the second largest contributor to energy demand in the overall economy and the agriculture sector. Finally, the technological innovation that enhances energy efficiency is only effective in reducing energy consumption in the industrial sector, which ultimately reduces emissions.

This paper analyzed the energy saving potentials of China's agricultural sector by using an econometric approach and a scenario analysis. First a co-integration analysis and an error correction model are employed to analyze the long-term equilibrium relationship between agricultural energy consumption and its influencing factors such as agricultural output, mechanical power, agricultural industrial structure, fiscal expenditure and energy prices during the period 1980–2012. Then stability test, fitting effect test and Monte Carlo simulation method are applied to confirm the rationality of the prediction model. Further, the scenario analysis method is used to predict the energy-saving potentials in 2020 and 2025 under different scenarios. It is found that agricultural output and mechanical power have positive impacts on energy consumption, while agricultural industrial structure, fiscal expenditure and energy prices have negative influences. The results demonstrate that under BAU condition, the energy demand of China's agricultural sector will reach 128, 94 and 161,61million tons of standard coal by 2020 and 2025 respectively. Moreover, the energy savings potential will be 7, 967 million tons and 15,701 million tons under moderate and advanced scenarios by the year 2020, and 17, 225 million tons and 31,094 million tons by the year 2025. This study provides a reference for establishing energy saving policies for China's agricultural sector.

Power generation from biomass residues is an attractive option for supplying the rapidly increasing power demand of the Association of South East Asian Nations (ASEAN) in a sustainable and a cost-effective manner. In this paper, we assess the total quantity and location of biomass residues from agriculture, livestock and forestry activities in ASEAN, evaluate their technical power generation potential and estimate the cost of electricity production from these residues. A cost optimization model is developed to identify cost-effective options of power generation from biomass residues using various conversion technologies. We estimate the total available thermal energy from biomass residues in ASEAN to be approximately 1076 TWh. About 86% of the total energy potential is provided by agricultural residues, with rice, sugarcane and palm oil residues being the major contributors. We find the highest energy potentials to be located in Indonesia (407 TWh), Thailand (194 TWh) and Vietnam (153 TWh). The estimated maximum technical potential for electricity generation from biomass residues in ASEAN amounts to 360 TWh. Power generation costs vary within a wide range from less than 40 USD/MWh to more than 200 USD/MWh.

Biomass energy is one of the fundamental renewable energy sources. It decreases fossil fuel combustion and consequently net greenhouse gas emissions since no new carbons aren't released to the atmosphere. Generally, agricultural, forest, animal and urban wastes are considered as potential sources for biomass energy. Among these sources, agricultural wastes are the most suitable type to generate biomass energy in Turkey. Aegean Region has a great potential with respect to its lands and its diversity of agricultural products. In this paper, the most appropriate location for a biomass power plant has been investigated among the eight alternative locations in Aegean Region by examining both quantitative and qualitative criteria. It is the first time, an integrated model including fuzzy sets, analytic hierarchy process, opinion aggregation method, and information axiom method has been proposed to obtain a solution for such a problem. According to the results, Aydin is determined as the most appropriate location for a biomass power plant at Aegean Region. Furthermore, a sensitivity analysis has been performed to present the reliability of the obtained results.

With the rapid popularization of China’s agricultural mechanization, energy consumption in China’s agricultural activities has been increasing significantly. Based on the agricultural sample data from 2000 to 2017, this study explores the substitution effect and rebound effect of China’s energy consumption in agricultural sector. In order to characterize the asymmetric response, this paper applies asymmetric price decomposition method and seemingly unrelated regression model to conduct the research. Some important results are found as follows. First, own-price elasticity of energy, labor and capital in China’s agricultural sector are −0.25, −0.23, and −0.33 during the study period, showing all the inputs are lacking of price elasticity of demand. Second, the substitution rate of capital for energy is 0.21 while the substitution rate of energy for capital is 0.17, which indicates that reducing capital cost is a more effective way than raising energy price for agricultural energy-saving goal. Second, the rebound rate of energy consumption is 74.78%, meaning that the improvement of energy efficiency relying on technological progress can only achieve 25.22% of energy saving effect. Fourth, the energy rebound rate of China’s agricultural sector is much higher than those of other sectors and presents certain regional characteristics over the study period. Based on these research results, measures such as accelerating market-oriented reform of input factors, increasing agricultural subsidies, optimizing agircultrual energy structure, and weeding out backward agricultural machineries are put forward for the development of China’ agricultural sector.

This article analyses energy trends in Cambodia and Laos and constructs future scenarios. The target is (i) to compare different scenario methods, (ii) to construct scenarios with these methods, (iii) to analyse the future energy demand and the related CO 2 emissions and (iv) to analyse the potential role of renewable energy sources and their impact on CO 2 emissions. Decomposition scenarios have been constructed based on the trends of the drivers of the energy consumption and CO 2 emissions. More detailed scenarios have been constructed using combined LEAP/LINDA models to take into account the structural socio-economic and technological changes in the energy system. The paper provides a novel combination of bottom-up modelling and macroeconomic modelling. The constructed scenarios indicate rapid increase in energy consumption and related CO 2 emissions mainly due to the fast economic growth and industrialization. Increase in fossil fuel use in electricity production in the future increases the emissions considerably. The potential of different renewable agricultural residues is analysed to evaluate the possibilities to reduce the CO 2 emissions and fossil fuel import dependence. The reduction potential is considerably large in both countries.

Global warming is leading to a water resources decrease in the Mediterranean basin, where future farming resilience depends on incorporating alternative water sources and improving water-energy use efficiency. This paper assesses water and energy consumption when natural water sources are partially replaced by desalinated sea water. Initially, energy consumption, water supply and GHG (greenhouse gas) emissions were recorded for the current farming practices in SE (southeast) Spain. The results of our study indicate that citrus orchards have the lowest energy consumption and GHG emissions. Annual vegetables were the least energy efficient crops. Subsequently, two alternative water supply scenarios were analysed, in which the reduction of natural water resources associated to climate change was compensated with desalinated sea water. The use of 16.8% of desalinated seawater would increase energy consumption by 32.4% and GHG emissions by 19.6%, whereas for the use of 26.5% of desalinated seawater such increases would amount to 50.0% and 30.3%, respectively. Therefore maintaining irrigated agriculture in water-stressed regions by incorporating high energy demanding non-traditional water sources could negatively contribute to combat global warming.