• Energy Research
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To meet international efforts to prevent climate change, the South Korean government is seeking to transform its main power source from coal to natural gas (NG), which emits less carbon dioxide (CO2) than coal. The government needs information about public preferences for increasing NG-fired generation. Therefore, the purpose of this paper is to provide the government with this information by gathering the data on public preferences for increasing NG-fired generation for reducing CO2 emissions, analyzing these data, and obtaining the implications from the analysis. To this end, a survey of 1000 people, after explaining the merits and demerits of NG-fired power, were asked to determine the proper ratio of NG-fired generation by choosing one of six examples: lower than 10%, 10%–20%, 20%–30%, 30%–40%, 40%–50%, and higher than 50%. An interval data model was employed to deal with the data. The average value of the ratio was estimated to be 26.7% with statistical significance, which is greater than the actual value of 22.2% from 2017. Finally, whether and how much some variables such as education level, age, gender, and income level of the respondent affected their preferences for NG-fired generation were investigated.

This research aimed to examine the willingness to pay (WTP) of the young generation (the age group from 18 to 29) for the participatory solutions and actions on fine particulate matter (PM2.5) pollution control and abatement in Daegu, Korea, and Beijing, China. This study found out that Korean respondents and Chinese respondents shared a wide range of similarities, both in terms of socio-demographic characters like age, family size, and house/apartment ownership, as well as a number of perceptions related to environmental and social responsibilities. Around one-third of the Korean respondents and one-fifth of the Chinese respondents expressed negative WTP due to primary reasons such as lack of trust in the effectiveness of PM2.5 control measures (Korea) and limitation of budget (China). The mean estimated values of WTP with and without explanatory variables in Korea were merely slightly higher than those in China. The mean WTP without control variables in Korea was 11,882.97 KRW/month (10.61 USD/month) and the one in China was 65.09 CNY/month (9.48 USD/month). The mean WTP with explanatory variables for Daegu, Korea, was KRW 11,982.33 (USD 10.70) per person per month, and the one for Beijing, China, was CNY 64.84 (USD 9.40) per person per month. The annual total WTP for Daegu, Korea, was assessed around KRW 47572 million (USD 42.45 million), whereas the estimated total WTP for Beijing, China, was around CNY 3260.14 million (USD 474.94 million) per year. Based on the results and the findings, this study proposes to further strengthen the comprehensive cooperation between China and Korea in the field of air quality improvement, with a particular focus on PM2.5 control and abatement and cooperation in academic circles and among the general public.

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.

This study aimed to conduct a techno-economic performance and optimisation analysis of grid-connected PV, wind turbines, and battery packs for Syiah Kuala University, situated at the tip of Sumatra island in the tsunami-affected region. The simulation software Hybrid Optimisation Model for Electric Renewables (HOMER) was used to analyse and optimise the renewable energy required by the institution. The methodology began with the location specification, average electric load demand, daily radiation, clearness index, location daily temperature, and system architecture. The results revealed that the energy storage system was initially included in the simulation, but it was later removed in order to save money and optimise the share of renewable energy. Based on the optimisation results, two types of energy sources were chosen for the system, solar PV and wind turbine, which contributed 62% and 20%, respectively. Apart from the renewable energy faction, another reason for the system selection is cost of energy (CoE), which decreased to $0.0446/kWh from $0.060/kWh. In conclusion, the study found that by connecting solar PV and wind turbines to the local grid, this renewable energy system is able to contribute up to 82% of the electricity required. However, the obstacle to implementing renewable energy in Indonesia is the cheap electricity price that is mainly generated using cheap coal, which is abundantly available in the country.

Biomass co-firing in coal-fired power plants has been widely accepted to reduce the environmental burden. In this study, food waste (FW) and sewage sludge (SS), which are the main types of municipal organic waste, were selected as solid refuse fuel (SRF). To compensate for the limitations of FW and SS, a mixture of FW and SS with varying ratios was processed using pyrolysis and desalination. The fuel properties such as the calorific value, chlorine content, alkali and alkaline earth metallic species (AAEMs) content, and heavy metal content were determined. The calorific values of all biochars were greater than 12.6 MJ/kg, which satisfies the national threshold of Bio-SRF in Korea. Chlorine and AAEMs contents exhibited clear trends for the FW ratio and pyrolysis temperature. Increasing concentrations of heavy metals were observed with increasing SS ratio and pyrolysis temperature. These results provide important insights into the practical application of municipal waste-based biochar in coal-fired plants, as well as the influence of mixing ratio and pyrolysis temperature.

The upsurges in population, internal migration, and various development works have caused significant land use and land cover (LULC) changes in the Bagmati Basin of Nepal. The effects of climate change such as increased precipitation and temperature are affecting the provision of ecosystem services (ES). In this regard, this study particularly treated water yield (WY), soil loss, nitrogen export, and carbon fluctuation in the basin. Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) tools were used to carry out a comparative analysis of ES based on LULC data for 2000 and 2010 and corresponding climate data. To analyze the future period (2010–2099), we have used climate data from the multi-model ensemble (MME) of statistically downscaled and bias-corrected 12 best global climate models (GCMs). A raw GCM analysis (based on historical observational data) from 29 GCMs was done first. The results shows with a subsequent degradation of ES providers like forests and an increment in agricultural and urban areas, ES are on a verge of degradation. Furthermore, a projection of future climate patterns depicts increased precipitation and temperature. Thus, urgent measures are required for the sustainable provision of ES. Outcomes of the study are expected to help in the incorporation of ES in development policies promoting low-impact development along with maintaining ecological and economic goals. The study closes by presenting a recommendation for model application and future study needs.

A solution to reduce the emission and generation cost of conventional fossil-fuel-based power generators is to integrate renewable energy sources into the electrical power system. This paper outlines an efficient hybrid particle swarm gray wolf optimizer (HPS-GWO)-based optimal power flow solution for a system combining solar photovoltaic (SPV) and wind energy (WE) sources with conventional fuel-based thermal generators (TGs). The output power of SPV and WE sources was forecasted using lognormal and Weibull probability density functions (PDFs), respectively. The two conventional fossil-fuel-based TGs are replaced with WE and SPV sources in the existing IEEE-30 bus system, and total generation cost, emission and power losses are considered the three main objective functions for optimization of the optimal power flow problem in each scenario. A carbon tax is imposed on the emission from fossil-fuel-based TGs, which results in a reduction in the emission from TGs. The results were verified on the modified test system that consists of SPV and WE sources. The simulation results confirm the validity and effectiveness of the suggested model and proposed hybrid optimizer. The results confirm the exploitation and exploration capability of the HPS-GWO algorithm. The results achieved from the modified system demonstrate that the use of SPV and WE sources in combination with fossil-fuel-based TGs reduces the total system generation cost and greenhouse emissions of the entire power system.

The optimization of outdoor thermal comfort has become the keystone to guarantee the healthy and comfortable use of outdoor spaces. This study aims to optimize the outdoor thermal comfort through vegetation parameterization in a boulevard located in Guelma city, Algeria during summertime. However, two main parameters were investigated, species and tree layout, through a numerical simulation. We first collected microclimate data of a sunny summer day. Second, we used real microclimate data in different simulations using the Envi-met atmospheric model. The findings reveal that Ficus Nitida is the most significant species to intercept solar radiation and provide shade over the day in Souidani Boudjemaa Boulevard, with a maximum reduction of Ta = 0.3 °C and UTCI = 2.6 °C at 13:00 p.m. Tree layout is a determining parameter in the creation of shaded paths, based on the quality of the shadows cast by the trees, namely, their size. Thereby, planting the washingtonia palm trees along the center of the boulevard is the best option to maximize the shaded area within the boulevard, with maximum reduction of Ta = 1.8 °C and UTCI = 3.5 °C at 16:00 p.m.