Understanding Socio-Economic Driving Factors of Indonesian Households Electricity Consumption in Two Urban Areas

2012 ◽  
pp. 55-60 ◽  
Author(s):  
Muhammad Ery Wijaya ◽  
Tetsuo Tezuka
Keyword(s):  
Urban Areas ◽  
Electricity Consumption ◽  
Driving Factors

scholarly journals Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986–2017

2020 ◽  
Vol 12 (16) ◽  
pp. 2615
Author(s):  
Jie Zhang ◽  
Le Yu ◽  
Xuecao Li ◽  
Chenchen Zhang ◽  
Tiezhu Shi ◽  
...  
Keyword(s):  
Growth Rate ◽  
Hong Kong ◽  
Urban Areas ◽  
Urban Expansion ◽  
Driving Factors ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Spatial And Temporal Scales ◽  
Urban Dynamics ◽  
Bay Area

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the largest bay areas in the world. However, the spatiotemporal characteristics and driving mechanisms of urban expansions in this region are poorly understood. Here we used the annual remote sensing images, Geographic Information System (GIS) techniques, and geographical detector method to characterize the spatiotemporal patterns of urban expansion in the GBA and investigate their driving factors during 1986–2017 on regional and city scales. The results showed that: the GBA experienced an unprecedented urban expansion over the past 32 years. The total urban area expanded from 652.74 km2 to 8137.09 km2 from 1986 to 2017 (approximately 13 times). The annual growth rate during 1986–2017 was 8.20% and the annual growth rate from 1986 to 1990 was the highest (16.89%). Guangzhou, Foshan, Dongguan, and Shenzhen experienced the highest urban expansion rate, with the annual increase of urban areas in 51.51, 45.54, 36.76, and 23.26 km2 y−1, respectively, during 1986–2017. Gross Domestic Product (GDP), income, road length, and population were the most important driving factors of the urban expansions in the GBA. We also found the driving factors of the urban expansions varied with spatial and temporal scales, suggesting the general understanding from the regional level may not reveal detailed urban dynamics. Detailed urban management and planning policies should be made considering the spatial and internal heterogeneity. These findings can enhance the comprehensive understanding of this bay area and help policymakers to promote sustainable development in the future.

scholarly journals Comparative Thermal Analysis of Different Cool Roof Materials for Minimizing Building Energy Consumption

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Y. Anand ◽  
A. Gupta ◽  
A. Maini ◽  
Avi Gupta ◽  
A. Sharma ◽  
...  
Keyword(s):  
Thermal Analysis ◽  
Urban Areas ◽  
Electricity Consumption ◽  
Building Envelope ◽  
Comfort Level ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Cool Roof ◽  
Cool Roofs ◽  
The Impact

The roof and walls in the urban areas contribute to major share in the absorption of solar radiations and also retard the outflow of the absorbed radiation from the building envelope, thereby increasing the global warming by inducing the heat island effect. The impact of using cool roof technologies on the thermal comfort of the office buildings has been estimated. Cool roofs reduce electricity consumption for maintaining the temperature of the air-conditioned buildings in the comfort level and also increase comfort in buildings merely not relying completely on cooling equipment. The cool roofs and cool pavements, however, can mitigate summer urban heat islands by improving indoor air quality and comfort. The thermal analysis of different materials has been carried out to analyze the impact of the rate of heat transfer on the building envelope and the results obtained indicate that different cool roof techniques are beneficial in maintaining the comfort level of the building which purely depends on the ambient temperature conditions.

scholarly journals Optimization to water supply system design and operation scheme in high rise buildings

2018 ◽  
Vol 12 (3) ◽  
pp. 123-131
Author(s):  
Nguyen Lan Huong ◽  
Nguyen Viet Anh ◽  
Dang Thi Thanh Huyen ◽  
Tran Hoai Son ◽  
Dinh Viet Cuong
Keyword(s):  
Water Supply ◽  
Urban Areas ◽  
Greenhouse Gas Emission ◽  
Electricity Consumption ◽  
Structural System ◽  
Electrical System ◽  
Pump System ◽  
High Rise ◽  
Reduce Electricity Consumption ◽  
Scale Experiment

Greenhouse Gas emission from high-rise buildings has been increasing mainly due to excessive energy consumption of the HVAC system, structural system and electrical system. Electricity consumption for pump system accounts for 15% of total electricity usage in building. Therefore the reduction of electricity in operation is crucial to the overall reduction of GHGs in urban areas. In this study, a lab-scale experiment was conducted to test the electricity consumption in applying different design approaches; the energy efficiency of the system was calculated. Finally, this study proposes the advanced water supply design scheme to reduce electricity consumption of the pump system. Article history: Received 12 March 2018, Revised 03 April 2018, Accepted 27 April 2018

scholarly journals Greenhouse Gas Pollution Based on Energy use and its Mitigation Potential in the City of Surakarta, Indonesia

2020 ◽  
Vol 52 (1) ◽  
pp. 1
Author(s):  
Prabang Setyono ◽  
Widhi Himawan ◽  
Cynthia Permata Sari ◽  
Totok Gunawan ◽  
Sigit Heru Murti
Keyword(s):  
Energy Consumption ◽  
Greenhouse Gas ◽  
Urban Areas ◽  
Energy Use ◽  
Carbon Sink ◽  
Ghg Emissions ◽  
Electricity Consumption ◽  
Vegetation Density ◽  
Rate Of Increase ◽  
The City

Considered as a trigger of climate change, greenhouse gas (GHG) is a global environmental issue. The City of Surakarta in Indonesia consists mainly of urban areas with high intensities of anthropogenic fossil energy consumption and, potentially, GHG emission. It is topographically a basin area and most likely prompts a Thermal Inversion, creating a risk of accumulation and entrapment of air pollutants or GHGs at low altitudes. Vegetation has been reported to mitigate the rate of increase in emissions because it acts as a natural carbon sink. This study aimed to mitigate the GHG emissions from energy consumption in Surakarta and formulate recommendations for control. It commenced with calculating the emission factors based on the IPCC formula and determining the key categories using the Level Assessment approach. It also involved computing the vegetation density according to the NDVI values of the interpretation of Sentinel 2A imagery. The estimation results showed that in 2018, the emission loads from the energy consumption in Surakarta reached 1,217,385.05 (tons of CO2e). The key categories of these emissions were electricity consumption, transportation on highways, and the domestic sector, with transportation on highways being the top priority. These loads have exceeded the local carrying capacity because they create an imbalance between emission and natural GHG sequestration by vegetations.

scholarly journals Study on Household Energy Usage Patterns in Urban and Rural Areas of Nepal

2020 ◽  
Vol 15 (3) ◽  
pp. 402-410
Author(s):  
Dinesh Kumar Shahi ◽  
Hom Bahadur Rijal ◽  
Masanori Shukuya
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Urban Areas ◽  
Energy Demand ◽  
Energy Use ◽  
Family Income ◽  
Electricity Consumption ◽  
Income Level ◽  
Electricity Production ◽  
Electricity Use

In the last decades, the household’s energy demand has increased significantly in various countries including Nepal. In the case ofNepal, 94% of energy use is in the domestic sector. There is a possibility of a huge increase in electricity production, but we are stillsuffering from load shedding due to the high electricity demand. Electricity use is an important factor for the quality of life anddevelopment of a nation. There is not a sufficient number of researches done about electricity consumption in different climaticregions of Nepal which are analyzed by the income level of residents. This study gives descriptive information on the household’senergy uses patterns and investigates the electricity use rate, using electrical appliances in households. This study also identifies themajor source of energy use and awareness of energy use. The data were collected from 442 households in three regions in the winterseason of 2018. Kalikot is a rural area, Chitwan is a semi-urban, and Kathmandu is an urban area. We have collected electricity bills,family income, and family size, electricity using appliances, expenditure for energy and energy use for heating/cooling, cooking, andlighting. The electricity was used only for lighting purposes in the rural area, but other electrical appliances were used in semi-urbanand urban areas. The amount of electricity use has not affected by household income level in the rural area, but it has affected in semi-urban and urban areas. The level of education affects the use of the LED significantly. This study would be helpful to know theelectricity use patterns which is useful for energy saving and energy management of the rural and urban areas of Nepal.

scholarly journals Performance of Floating Raft Fertigation System on Water Spinach Plants (Ipomea reptans Poir.) Cultivation

2019 ◽  
Vol 6 (2) ◽  
pp. 165-179
Author(s):  
Rizal Hadyan Fadhlillah ◽  
Sophia Dwiratna ◽  
Kharistya Amaru
Keyword(s):  
Water Consumption ◽  
Urban Areas ◽  
Descriptive Analysis ◽  
Electricity Consumption ◽  
Growth Period ◽  
Electrical Energy ◽  
Water Spinach ◽  
Plant Weight ◽  
Floating Raft ◽  
Spinach Plant

The increase of human population impact to more land needed for residence and has an impact on the decreasing land for agriculture, especially in urban areas. One of solution for farming in urban areas is by utilizing rooftop farming by hydroponic cultivation. The hydroponic system that used in this research is floating raft system. This study aims to determine the performance of the floating raft fertigation system which includes the amount of energy consumption, water, nutrient solution, growth uniformity and yield productivity in water spinach cultivation using floating raft fertigation system for one period of growth. This research was carried out on the rooftop of the building of the Food Industry Technology Department of Padjadjaran University with descriptive analysis method. The parameters measured in this study were the amount of water consumption, nutrition and electrical energy from the floating raft fertigation system that was used and uniformity of the results of plant growth including plant height, root length and plant weight at harvest determined in this study, 16 days after transplanting. Result showed that water consumption for one time growth period water spinach was 300,63 liters; consumption of nutrients was 3860 ml and electricity consumption was 31,816 kW. The uniformity of water spinach plant results of the study was in the category of good. The efficiency of water use was 99.6 kg/m3 and plant productivity based on research results is 72.8 kg/m2.

scholarly journals Temporal and Spatial Variation of NDVI and Its Driving Factors in Qinling Mountain

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3154
Author(s):  
Chenlu Huang ◽  
Qinke Yang ◽  
Hui Zhang
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Urban Areas ◽  
Vegetation Index ◽  
Positive Impact ◽  
Google Earth ◽  
Driving Factors ◽  
Qinling Mountains ◽  
Qinling Mountain ◽  
The Impact

Qinling Mountains is the north–south boundary of China’s geography; the vegetation changes are of great significance to the survival of wildlife and the protection of species habitats. Based on Landsat products in the Google Earth Engine (GEE) platform, Pearson’s correlation coefficient method, and classification and regression models, this study analyzed the changes in NDVI (Normalized Difference Vegetation Index) in the Qinling Mountains in the past 38 years and the sensitivity of its driving factors. Finally, residual analysis method and accumulate slope change rate are used to identify the impact of human activities and climate change on NDVI. The research results show the following: (1) The NDVI value in most areas of Qinling Mountains is at a medium-to-high level, and 99.76% of the areas correspond to an increasing trend of NDVI, and the significantly increased area accounts for more than 20%. (2) From 1981 to 2019, the NDVI of the Qinling Mountains increased from 0.63 to 0.78, showing an overall upward trend, and it increased significantly after 2006. (3) Sensitivity analysis results show that the western high-altitude area of Qinling Mountain area dominated by grassland is mainly affected by precipitation. The central and southeastern parts of the Qinling Mountains are significantly affected by temperature, and they are mainly distributed in areas dominated by forest. (4) The contribution rates of climate change and human activities to NDVI are 36.04% and 63.96%, respectively. Among them, the positive impact of human activities on the NDVI of the Qinling Mountains accounted for 99.85% of the area. The area with significant positive effect accounted for 36.49%. The significant negative effect area accounts for only 0.006%, mainly distributed in urban areas and coal mining areas.

scholarly journals Urban Expansion Simulation Based on Various Driving Factors Using a Logistic Regression Model: Delhi as a Case Study

2021 ◽  
Vol 13 (19) ◽  
pp. 10805
Author(s):  
Muhammad Salem ◽  
Arghadeep Bose ◽  
Bashar Bashir ◽  
Debanjan Basak ◽  
Subham Roy ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Urban Areas ◽  
Logistic Regression Model ◽  
Urban Expansion ◽  
Driving Factors ◽  
Sustainable Urban Development ◽  
Landsat Images ◽  
Relative Operating Characteristic ◽  
Simulation Based

During the last three decades, Delhi has witnessed extensive and rapid urban expansion in all directions, especially in the East South East zone. The total built-up area has risen dramatically, from 195.3 sq. km to 435.1 sq. km, during 1989–2020, which has led to habitat fragmentation, deforestation, and difficulties in running urban utility services effectively in the new extensions. This research aimed to simulate urban expansion in Delhi based on various driving factors using a logistic regression model. The recent urban expansion of Delhi was mapped using LANDSAT images of 1989, 2000, 2010, and 2020. The urban expansion was analyzed using concentric rings to show the urban expansion intensity in each direction. Nine driving factors were analyzed to detect the influence of each factor on the urban expansion process. The results revealed that the proximity to urban areas, proximity to main roads, and proximity to medical facilities were the most significant factors in Delhi during 1989–2020, where they had the highest regression coefficients: −0.884, −0.475, and −0.377, respectively. In addition, the predicted pattern of urban expansion was chaotic, scattered, and dense on the peripheries. This pattern of urban expansion might lead to further losses of natural resources. The relative operating characteristic method was utilized to assess the accuracy of the simulation, and the resulting value of 0.96 proved the validity of the simulation. The results of this research will aid local authorities in recognizing the patterns of future expansion, thus facilitating the implementation of effective policies to achieve sustainable urban development in Delhi.

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