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Abstract Date biomass is a carbon-rich renewable resource that can be considered a potential carbon-rich substrate for energy generation over anaerobic digestion (AD). However, due to its complex nature, appropriate pretreatment is necessary to achieve a higher methane yield. Hence, the current study was envisioned to evaluate the influence of three different pretreatment strategies, namely acid, alkali, and hydrothermal pretreatment on biochemical methane potential (BMP) of seven diverse sorts of Algerian date biomass, namely Pedicels, Fibrilium, Petiole, Fruit bunch, Spath, Palm, and its mixture. Among all the pretreatment conditions, alkaline pretreatment highly influenced the lignin composition of date biomass and showed higher BMP. Among all sorts of biomass, higher BMP was detected through Palm as 295.9 mL CH4/g-TS, whereas the lowest BMP values were recorded with Petiole as 226.74 mL CH4/g-TS. Among all the experimental variations, ammonium pretreated Palm biomass documented the highest substrate conversion efficiency (63.80%), which correlates well with the observed higher BMP values. Nevertheless, there was a very marginal improvement in BMP detected in the case of other pretreatment strategies compared to alkaline pretreatment. This might be due to the efficacy of the applied pretreatment method on delignification of date biomass.

Abstract The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities’ electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model.

An anaerobic moving bed membrane bioreactor (AnMBMBR) fed with synthetic domestic wastewater was investigated under hydraulic retention time (HRT) shocks to assess the effects on the microbial (bacteria and archaea) community and reactor performance. 16S rDNA targeted polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) approach was optimized to relate the metabolic and community composition with biogas generation, methane content and COD removal efficiency. From the drastic decrease of HRT (from 8 h to 4 h), the methane production was significantly reduced due to the HRT shock, while the COD removal efficiency was not affected. The enhanced growth of homoacetogenic bacteria, Thermoanaerobacteraceae competes with methanogens under shock period. When the HRT was recovered to 8 h, the methane generation rate was higher than the initial operation before the shock HRT changes, which would be ascribed to the activity of new emerging hydrogenotrophic archaea, Methanocella sp. and Methanofollis sp.

This paper presents a study the change of the load profile on the power system by the charging impact of electric vehicles (EVs) in 2020. The impact of charging EVs on the load demand is determined not only by the number of EVs in usage pattern, but also by the number of EVs being charged at once. The charging load is determined on an hourly basis using the number of the EVs based on different scenarios considering battery size, model, the use of vehicles, charging at home or work, and the method of charging, which is either fast or slow. Focusing on the impact of future load profile in Korea with EVs reaching up 10 and 20 percentage, increased power demand by EVs charging is analyzed. Also, this paper analyzes the impact of a time-of-use (TOU) tariff system on the charging of EVs in Korea. The results demonstrate how the penetration of EVs increases the load profile and decreases charging demand by TOU tariff system on the future power system.

Abstract This study proposes an effective thermal control method for thermally comfortable and energy-efficient environments in buildings with double skin envelopes. Four rule-based control logics and an artificial neural network (ANN)-based control logic were developed for the integrated control of openings and cooling systems in summer. Using numerical computer simulations, the performance of the proposed control logics was comparatively tested in terms of thermal performance and energy efficiency. Analysis results imply that the more detailed rules of thermal control logic were effective to maintain the indoor temperature conditions within comfortable ranges. The ANN-based predictive and adaptive control logic presented its potential as an advanced temperature control method with an increased temperature comfort period, decreased standard deviation of temperature from the center of the comfortable range, and decreased number and ratio of overshoots and undershoots out of the comfort range. The additional rules embedded for control logic or ANN applications yielded a more comfortable temperature environment in an integrated manner according to the properly designed operations of envelope openings and the cooling system. However, logics with additional rules and ANN models consumed more energy for space cooling. Therefore, the rule-based controls with advanced logics or an ANN model are required in case occupant comfort is a primary factor to be satisfied. In other cases, the simple rule-based logic is effectively applied.

This article aims to identify occupations at risk of climate change, and explore their spatial distribution by investigating their spatial concentration and cluster patterns in Korea. In order to identify professions vulnerable to climate change, we used three criteria: (1) exposure to the risks of job activities; (2) sensitivity to work environments; and (3) adaptive capacities based on the socioeconomic conditions of a person’s occupation. We identified 26 vocations as vulnerable, which corresponds to 16.5% of the total number of careers. Then, we used exploratory spatial data analysis (ESDA) techniques to examine the spatial distribution of jobs at risk of climate change effects. Endangered occupations show the extremely uneven spatial distributions across regions, indicating that there is a wide range of values for the proportion of endangered occupations across regions. The regions with high proportions of professions in jeopardy show clear spatial clustering based on the large geographic belt from the southwest to the northeast. Our results suggest that policymakers should consider the specific geographies of vulnerable occupations. The current work provides helpful hints on regional policy coordination to promote a virtuous circle of sustainable regional development.

This study investigated lifecycle CO2 (LCCO2) emission reductions through application of double-window casement systems (DWCS) in residential units in Korea, compared with conventional single windows (SWs). The DWCS is a double window system that is energy-efficient, reducing energy consumption during operation. However, this system incorporates increased embodied CO2 emissions. We evaluated LCCO2 reductions associated with use of the DWCS by calculating CO2 emissions during space conditioning as well as the embodied CO2 emissions of the DWCS. The results showed that use of DWCS in a residential unit during the cooling season had 26.2 and 27.4 t CO2 fewer emissions than SWs in the natural ventilation and minimum ventilation modes, respectively. Although implementation of DWCS is expected to substantially reduce LCCO2 emissions, the large embodied CO2 emissions of the aluminum frame reduce the benefits of the DWCS.

Abstract The reliable benchmarks are required to evaluate building energy efficiency fairly. This study aims to develop the energy benchmarks and relevant process for a multi-family housing complex (MFHC), which is responsible for huge CO 2 emissions in South Korea. A database, including the information on building attributes and energy consumption of 503 MFHCs, was established. The database was classified into three groups based on average enclosed area per household (AEA) through data mining techniques. The benchmarks of site energy use intensity (EUI), source EUI, and CO 2 emission intensity (CEI) were developed from Groups 1, 2, and 3. Representatively, the developed benchmarks of CEI for Groups 1, 2, and 3 were 28.17, 24.16, and 20.96 kg-CO 2 /m 2 y, respectively. A comparative analysis using the operational rating identified that the developed benchmarks could solve the irrationality of the original benchmarks from overall database. In the case of the original benchmarks, 93% of small-AEA-groups and 16% of large-AEA-groups received lower grades. In the case of the developed benchmark, the upper and lower grades in Groups 1–3 were both adjusted to 50%. The proposed process for developing energy benchmark is applicable to evaluate the energy efficiency of other buildings, in other regions.

This study examined the influence of heat recovery ventilators (HRVs) on energy savings and indoor air quality (IAQ) in high-rise residential buildings. Field measurements were performed in four residential units, which were validated by computer simulations and estimated the total annual energy consumption. The operation schedules for HRVs were determined by a survey of residents. Field measurement results indicate that HRVs could effectively improve IAQ and afford effective energy savings. The indoor concentrations of formaldehyde were reduced by 54.6% after HRVs were operated for 24 h. The initial concentration was reduced by 82% after 168 h. Toluene was the dominant volatile organic compounds (VOCs) in the indoor air. Its initial concentration was reduced by 50% and other VOCs were also reduced by 40.1% to 53.1% after HRVs were operated. Annual energy savings of up to 20.26% were predicted when HRVs were operated for 24 h continuously, exchanging sensible and latent heat. HRVs could save energy more effectively in winter than in summer due to the greater temperature difference between outdoor and indoor air. Based on the preferred operation schedules of homes surveyed, an annual energy savings could be as high as 8.52%.