scholarly journals ADJUSTING THE STRUCTURE COMBINATIONS OF PLANT COMMUNITIES IN URBAN GREENSPACE REDUCED THE MAINTENANCE ENERGY CONSUMPTION AND GHG EMISSIONS

2018 ◽  
Vol 26 (4) ◽  
pp. 261-274 ◽  
Author(s):  
Yang Liu ◽  
Qiusheng Yang ◽  
Lichao Duan
Keyword(s):  
Energy Consumption ◽  
Plant Communities ◽  
Energy Use ◽  
Plant Density ◽  
Ghg Emissions ◽  
Average Energy ◽  
Maintenance Energy ◽  
Plant Structure ◽  
Urban Greenspace ◽  
Average Energy Consumption

Maintaining urban greenspace results in energy use and GHG emissions. To understand the change of the annual maintenance energy consumption and GHG emissions in varying combinations of plant structures (plant density or proportion of area covered) in urban greenspace, this study investigated 34 urban plant communities as sample plots (20×20 m), and divided them into woodland, shrub, herbaceous and grassland layers. The average energy use and GHG emissions in the woodland layer were 18.64 MJ/tree/y–1 and 0.23 kg/CO2-e/tree/y–1, respectively. In the shrub, herbaceous, and grassland layers, the average energy consumption was 3.73, 2.27, 7.23 MJ/m2/y–1, and the average GHG emissions were 0.06, 0.02, 0.09 kg/CO2-e/m2/y–1, respectively. The energy use and GHG emission curves had parabolic trends as the plant density in the woodland layer increased and increasing curves with two peaks as the plant area proportions of the shrub, herbaceous, and grassland layers increased. The annual maintenance of urban greenspace can divide into low, average and high levels of energy consumption and GHG emissions due to the change in the plant structure combinations. Furthermore, city managers and landscape designers can refer to the energy consumption and GHG emissions trends to understand the environmental impact of maintenance tasks. The future plant structures in greenspace can be better designed to improve ecosystem services based on limiting the maintenance environmental impacts.

scholarly journals Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Muhammad Imran ◽  
Orhan Ozcatalbas
Keyword(s):  
Energy Consumption ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Use ◽  
Ghg Emissions ◽  
Average Energy ◽  
Green Economy ◽  
Energy Output ◽  
Gas Emissions ◽  
Wheat Production

AbstractThis study aimed to model energy use, energy efficiency, and greenhouse gas emissions in rain-fed wheat production by using a nonparametric data envelopment analysis (DEA) method. Data were collected through face-to-face interviews with 140 wheat farmers in 4 districts of Antalya Province. The energy inputs (independent variables) were human labor, seeds, chemical fertilizers, herbicides, and diesel fuel, and the energy output was the dependent variable. The results showed that the average energy consumption and the output energy for the studied wheat production system were 21. 07GJ ha−1 and 50. 99 GJ ha−1, respectively, and the total GHG emissions were calculated to be 592.12 kg CO2eq ha−1. Chemical fertilizer has the highest share of energy consumption and total GHG emissions. Based on the results from DEA, the technical efficiency of the farmers was found to be 0.81, while pure technical and scale efficiencies were 0.65 and 0.76, respectively. The results also highlighted that there is a potential opportunity to save approximately 14% (2.93 GJ ha−1) of the total energy consumption and consequently a 17% reduction in GHG emissions by following the optimal amounts of energy consumption while keeping the wheat yield constant. Efficient use of energy and reduction in GHG emissions will lead to resource efficiency and sustainable production, which is the main aim of the green economy.

scholarly journals Modifying Building Energy-Saving Design Based on Field Research into Climate Features and Local Residents’ Habits

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 442
Author(s):  
Xiaoyue Zhu ◽  
Bo Gao ◽  
Xudong Yang ◽  
Zhong Yu ◽  
Ji Ni
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Residential Buildings ◽  
Average Energy ◽  
Field Tests ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Local Conditions ◽  
Building Energy Saving ◽  
Average Energy Consumption

In China, a surging urbanization highlights the significance of building energy conservation. However, most building energy-saving schemes are designed solely in compliance with prescriptive codes and lack consideration of the local situations, resulting in an unsatisfactory effect and a waste of funds. Moreover, the actual effect of the design has yet to be thoroughly verified through field tests. In this study, a method of modifying conventional building energy-saving design based on research into the local climate and residents’ living habits was proposed, and residential buildings in Panzhihua, China were selected for trial. Further, the modification scheme was implemented in an actual project with its effect verified by field tests. Research grasps the precise climate features of Panzhihua, which was previously not provided, and concludes that Panzhihua is a hot summer and warm winter zone. Accordingly, the original internal insulation was canceled, and the shading performance of the windows was strengthened instead. Test results suggest that the consequent change of SET* does not exceed 0.5 °C, whereas variations in the energy consumption depend on the room orientation. For rooms receiving less solar radiation, the average energy consumption increased by approximately 20%, whereas for rooms with a severe western exposure, the average energy consumption decreased by approximately 11%. On the other hand, the cost savings of removing the insulation layer are estimated at 177 million RMB (1 USD ≈ 6.5 RMB) per year. In conclusion, the research-based modification method proposed in this study can be an effective tool for improving building energy efficiency adapted to local conditions.

scholarly journals Energy-Efficient and Disjoint Multipath Using Face routing in Wireless Sensor Networks

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7823
Author(s):  
Hyunchong Cho ◽  
Seungmin Oh ◽  
Yongje Shin ◽  
Euisin Lee
Keyword(s):  
Energy Consumption ◽  
Average Energy ◽  
Packet Transmission ◽  
Destination Node ◽  
Path Generation ◽  
Data Packets ◽  
Hole Area ◽  
Face Routing ◽  
Multiple Routes ◽  
Average Energy Consumption

In WSNs, multipath is well-known as a method to improve the reliability of packet delivery by making multiple routes from a source node to a destination node. To improve reliability and load-balancing, it is important to ensure that disjoint characteristics of multipath do not use same nodes during path generation. However, when multipath studies encounter a hole area from which is hard to transmit data packets, they have a problem with breaking the disjoint features of multipath. Although existing studies propose various strategies to bypass hole areas, they have side effects that significantly accelerate energy consumption and packet transmission delay. Therefore, to retain the disjoint feature of multipath, we propose a new scheme that can reduce delay and energy consumption for a node near a hole area using two approaches—global joint avoidance and local avoidance. This scheme uses global joint avoidance to generate a new path centered on a hole area and effectively bypasses the hole area. This scheme also uses local joint avoidance that does not select the same nodes during new path generation using a marking process. In simulations, the proposed scheme has an average 30% improvement in terms of average energy consumption and delay time compared to other studies.

scholarly journals Food security of paddy farm households based on the proportion of food expenditure and energy consumption level in Jogorogo Ngawi

2021 ◽  
Vol 905 (1) ◽  
pp. 012077
Author(s):  
A D P M Larasati ◽  
Darsono ◽  
S Marwanti
Keyword(s):  
Food Security ◽  
Energy Consumption ◽  
Sample Selection ◽  
Average Energy ◽  
Farm Households ◽  
Household Food Security ◽  
Protein Consumption ◽  
Consumption Level ◽  
Food Expenditure ◽  
Average Energy Consumption

Abstract Ngawi is the sixth paddy producer in Indonesia and certainly has an influence on the food security of paddy farm households. This study aimed to analyze the proportion of food expenditure (PFE), energy and protein consumption, the relationship between food expenditure and energy consumption, and the condition of food security. The basic method used descriptive analytic. The number of respondents based on the slovin formula was 87 households. The sample selection used stratified random sampling. The data analysis method used correlation with SPSS 22 and cross indicator between PFE and energy consumption level. The results showed that the average of PFE was 58.81%. The average energy consumption was 4,272.2 kcal/household/day with an energy consumption level of 81.93% while the average protein consumption was 122.1 grams/household/day lower than the average household RDA consumption. Food expenditure had a significant relationship to energy consumption with a correlation coefficient of 0.925 including a very strong and unidirectional relationship. The contribution of household food security conditions were 28.7% secure; 32.2% vulnerable; 10.3% less secure; 28.8% insecure.

scholarly journals Modeling of Duty-Cycled MAC Protocols for Heterogeneous WSN with Priorities

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 467 ◽  
Author(s):  
Canek Portillo ◽  
Jorge Martinez-Bauset ◽  
Vicent Pla ◽  
Vicente Casares-Giner
Keyword(s):  
Performance Evaluation ◽  
Energy Consumption ◽  
Average Energy ◽  
Packet Delay ◽  
Evaluation Study ◽  
Duty Cycling ◽  
Quantitative Evidence ◽  
And Performance ◽  
Save Energy ◽  
Average Energy Consumption

Wireless Sensor Networks (WSN) have experienced an important revitalization, particularly with the arrival of Internet of Things applications. In a general sense, a WSN can be composed of different classes of nodes, having different characteristics or requirements (heterogeneity). Duty-cycling is a popular technique used in WSN, that allows nodes to sleep and wake up periodically in order to save energy. We believe that the modeling and performance evaluation of heterogeneous WSN with priorities operating in duty-cycling, being of capital importance for their correct design and successful deployment, have not been sufficiently explored. The present work presents a performance evaluation study of a WSN with these features. For a scenario with two classes of nodes composing the network, each with a different channel access priority, an approximate analytical model is developed with a pair of two-dimensional discrete-time Markov chains. Note that the same modeling approach can be used to analyze networks with a larger number of classes. Performance parameters such as average packet delay, throughput and average energy consumption are obtained. Analytical results are validated by simulation, showing accurate results. Furthermore, a new procedure to determine the energy consumption of nodes is proposed that significantly improves the accuracy of previous proposals. We provide quantitative evidence showing that the energy consumption accuracy improvement can be up to two orders of magnitude.

Thermal Performance of Electrochromic Smart Window with Nanocomposite Structure under Different Climates in Iran

2019 ◽  
Vol 11 (2) ◽  
pp. 154-164 ◽  
Author(s):  
Siamak Hoseinzadeh
Keyword(s):  
Energy Consumption ◽  
Thermal Energy ◽  
Average Energy ◽  
Climatic Conditions ◽  
Smart Window ◽  
Nanocomposite Layer ◽  
Energy Plus ◽  
Average Energy Consumption ◽  
Bandar Abbas ◽  
Different Climates

Objective: This study investigated the optimization of thermal energy consumption using electrochromic components with a new nanocomposite layer (WO3+Ag) in a larger size (window) for a room with an educational application for five cities with different climatic conditions in Iran (Yazd, Tehran, Bandar Abbas, Tabriz, and Sari). Materials & Methods: For this simulation platform, the software was implemented in Energy Plus. This feasibility study was modeled by DesignBuilder software which reported reduced thermal energy consumption across all climates in Iran (hot and dry, warm and semi-humid, warm and wet, moderate and dry, and mild and humid.). Four strategies were considered for better comparison. The first strategy used for common double-glazed windows, while the second to fourth strategies involved the use of the electrochromic window in three different modes; bleached mode (Off), colored mode (On), and switchable mode (controlled below comfort conditions). Results: The third and fourth strategies indicated a reduction in thermal energy consumption in different climates from 25 to 45% relative to typical windows. The best result of cooling energy consumption was observed in Tehran. Conclusion: For this climate, the average energy consumption dropped to 34% for the warm months of the year and even 42% for the warmest month of the year (August).

scholarly journals A Novel Approach to Reduce Energy Consumption By Clustering With Genetic Algorithm and Sleeping Time in The IoT

2021 ◽  
Author(s):  
Negin Babaei ◽  
Alireza Hedayati
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Novel Approach ◽  
Timing Mechanisms ◽  
Reduce Energy Consumption ◽  
Average Energy Consumption

Abstract Internet of things is one of the most important technologies in the last century which covers various domains such as wireless sensor networks. Wireless sensor networks consist of a large number of sensor nodes that are scattered in an environment and collect information from the surrounding environment and send it to a central station. One of the most important problems in these networks is saving energy consumption of nodes and consequently increasing lifetime of networks. Work has been done in various fields to achieve this goal, one of which is clustering and the use of sleep timing mechanisms in wireless sensor networks. Therefore, in this article, we have examined the existing protocols in this field, especially LEACH-based clustering protocols. The proposed method tries to optimize the energy consumption of nodes by using genetic-based clustering as well as a sleep scheduling mechanism based on the colonial competition algorithm. The results of this simulation show that our proposed method has improved network life (by 18%) and average energy consumption (by 11%) and reduced latency in these networks (by 17%).

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.

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