• Energy Research
• 11. Sustainability close
• 15. Life on land close
• 2. Zero hunger close
• 1. No poverty close
• FI close
• PK close

With increasing concern over global climate change and rapid rise in energy consumption on the data-driven market, data centres are an important renewable energy target. As cooling contributes a substantial portion of the energy use of data centres, minimising the cooling energy demand in data centres is one of the main objectives for improving renewable energy. This paper investigates overall energy consumption and the energy efficiency of the cooling system for a data centre in Finland as a case study. The temporal energy consumption characteristics, cooling infrastructure and operation of the data centre are analysed. The main problems associated with cooling energy efficiency and the factors that may contribute toward higher efficiency are identified and further suggestions are put forward. Results are presented of an extensive evaluation of the energy performance of the study data centre with a view to energy recovery. The conclusion we can draw is that even though the analysed data centre demonstrat...

Microplastics are a growing concern in the environments and especially agricultural soil due to numerous negative impacts on the ecosystems and human health. This study aimed to investigate the properties of microplastics (including quantity, shape, size, and polymer types) in five samples (DA1-5) taken from agriculture soil in Dong Anh district, Hanoi using Nicolet iN10 MX Fourier transform infrared (µFTIR) microscope. The study found that the microplastic content in these soils ranging from 494 ± 292 items/kg dry weight to 1031 ± 379 items/kg dry weight. In terms of shape, microplastic fragments accounted for the majority of microplastics found in soil (65% - 86% of the total microplastics). Fifteen types of microplastic polymers were identified in the soil samples, with PET being the most common polymer of 38%, followed by urea-formaldehyde resin of 15%, and nylon of 13%. Microplastics with sizes ranging from 50-150 µm were the dominant group (39% - 57% of the total microplastics). This study provides an initial assessment of the presence of microplastics in the agricultural soil of the suburban area of Hanoi, highlighting the potential risk of contamination that may effect on environment and pose a threat to human health.

The phenotypic and genotypic characterization of eight rhizobial isolates obtained from Arachis hypogaea nodules grown under stress environment was performed. Isolates were screened for their ability to tolerate different abiotic stresses (high temperature (60° C), salinity (1–5% (w/v) NaCl), and pH (1–12). The genomic analysis of 16S rRNA and housekeeping genes (atpD, recA, and glnII) demonstrated that native groundnut rhizobia from these stress soils are representatives of fast growers and phylogenetically related to Rhizobium sp. The phenotypic characterization (generation time, carbon source utilization) also revealed the isolates as fast-growing rhizobia. All the isolates can tolerate NaCl up to 3% and were able to grow between 20 and 37 °C with a pH between 5 to 10, indicating that the isolates were alkali and salt-tolerant. The tested isolates effectively utilize mono and disaccharides as carbon source. Out of eight, three rhizobial isolates (BN-20, BN-23, and BN-50) were able to nodulate their host plant, exhibiting their potential to be used as native groundnut rhizobial inoculum. The plant growth promoting characterization of all isolates revealed their effectiveness to solubilize inorganic phosphate (56–290 µg mL−1), synthesize indole acetic acid (IAA) (24–71 µg mL−1), and amplification of nitrogen fixing nifH gene, exploring their ability to be used as groundnut biofertilizer to enhance yield and N2-fixation for the resource poor farmers of rainfed Pothwar region.

The European Union has set ambitious targets of raising the share of EU energy consumption produced from renewable resources from 20% by 2020 to 27% by 2030. The aim of this paper is to assess the role of woody biomass in renewable energy as gross final energy consumption in the European Union (the EU-28). The paper identifies leading and lagging countries in biomass development by focusing on their current biomass use and forecasts future perspectives. The research compares and evaluates the role of biomass in renewable energy in the EU-28 focusing on countries' potential resources and policy support. The study shows that all countries are making efforts to reach the 20% target in 2020 and exhibit a trend of increasing renewable energy as gross final energy consumption towards the new target of 2030. Solid biomass plays an important role in reaching the EU's renewable energy targets. The majority of the EU-28 countries are close to reaching their national renewable energy targets and show a very attractive biomass development. Unless energy consumption decreases however, some member states will face serious problems in reaching their renewable energy target in 2020. Following our analysis, the largest problems occur in those MS having a relative high-energy consumption pattern: France, Germany and the United Kingdom. It is unlikely that they can comply with expected renewable energy demand, unless they mobilize more woody biomass from their available domestic potential (France, Germany) or considerably increase their woody biomass imports (mostly wood pellets) from elsewhere (United Kingdom).

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.

AbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

The purpose of this study is to investigate the potential of airborne particulate matter (PM10 and PM2.5) and its impact on the performance of the photovoltaic (PV) system installed in the Sargodha region, being affected by the crushing activities in the hills. More than 100 stone crushers are operating in this region. Four stations within this region are selected for taking samples during the summer and winter seasons. Glass–fiber papers are used as a collection medium for particulate matter (PM) in a high-volume sampler. The concentration of PM is found above the permissible limit at all selected sites. The chemical composition, concentration, and the formation of particulate matter (PM10 and PM2.5) layers on the surface of the photovoltaic module varies significantly depending on the site’s location and time. The accumulation of PM layers on the PV module surface is one of the operating environmental factors that cause significant reduction in PV system performance. Consequently, it leads to power loss, reduction of service life, and increase in module temperature. For the PV system’s performance analysis, two PV systems are installed at the site, having higher PM concentration. One system is cleaned regularly, while the other remains dusty. The data of both PV systems are measured and compared for 4 months (2 months for the summer season and 2 months for the winter season). It is found that when the level of suspended particulate matter (PM10 and PM2.5) increases, the energy generation of the dusty PV system (compared to the cleaned one) is reduced by 7.48% in May, 7.342% in June, 10.68% in December, and 8.03% in January. Based on the obtained results, it is recommended that the negative impact of PM on the performance of the PV system should be considered carefully during the decision-making process of setting solar energy generation targets in the regions with a high level of particulate matter.

Abstract Energy poverty has evolved as an important issue of research from academic and policy perspectives during the last two decades. The energy poverty estimates exhibit widespread variations across regions, methodologies and datasets, making the task of energy and development policies challenging. The variations in energy poverty estimates necessitate a systematic and rigorous analysis of these empirical studies to obtain a true measure of energy poverty. The present study conducts a meta-analysis of 30 studies and 103 estimates of energy poverty. On average, 71.1 percent of the population in the overall sample studies has been identified as energy poor. High I-square statistic values suggest heterogeneity bias in the sample studies; therefore, analysis at the subgroup level has been conducted. Meta-regression analysis of overall sample and subgroups has identified type of methodology, citations, impact factor of the journal, regional dummies, average key crude oil price and gross domestic product as significant factors that explain heterogeneity in the energy poverty effect sizes. We recommend inclusion of local and regional factors in assessment of energy poverty for developing a uniform methodology to assess energy poverty across developing economies.

Two chickpea genotypes viz. Bhakar-2011 (desi) and Noor-2013 (kabuli) were sown in soil filled pots supplied with low (0.3 mg kg-1) and high (3 mg kg-1 soil) zinc (Zn) under control (70% water holding capacity and 25/20 °C day/night temperature), drought (35% water holding capacity) and heat (35/30 °C day/night temperature) stresses. Drought and heat stresses reduced rate of photosynthesis, photosystem II efficiency, plant growth and Zn uptake in chickpea. Low Zn supply exacerbated adverse effects of drought and heat stresses in chickpea, and caused reduction in plant biomass, carbon assimilation, antioxidant activity, impeded Zn uptake and enhanced oxidative damage. However, adequate Zn supply ameliorated adverse effect of drought and heat stresses in both chickpea types. The improvements were more in desi than kabuli type. Adequate Zn nutrition is crucial to augment growth of chickpea plants under high temperature and arid climatic conditions.