Development of renewable, densified biomass for household energy in China

AbstractThe IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.

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Rural household energy consumption and its implications for eco-environments in NW China: A case study

Renewable Energy ◽

10.1016/j.renene.2013.07.045 ◽

2014 ◽

Vol 65 ◽

pp. 137-145 ◽

Cited By ~ 39

Author(s):

Hewen Niu ◽

Yuanqing He ◽

Umberto Desideri ◽

Peidong Zhang ◽

Hongyi Qin ◽

...

Keyword(s):

Energy Consumption ◽

Rural Household ◽

Household Energy ◽

Nw China ◽

Household Energy Consumption

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CNN-Bi-LSTM Based Household Energy Consumption Prediction

2021 3rd International Conference on Signal Processing and Communication (ICPSC) ◽

10.1109/icspc51351.2021.9451797 ◽

2021 ◽

Author(s):

Kshitij Gaur ◽

Sandeep Kumar Singh

Keyword(s):

Energy Consumption ◽

Household Energy ◽

Household Energy Consumption ◽

Energy Consumption Prediction ◽

Consumption Prediction

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The Geographical Distribution and Correlates of Pro-Environmental Attitudes and Behaviors in an Urban Region

Energies ◽

10.3390/en12081540 ◽

2019 ◽

Vol 12 (8) ◽

pp. 1540 ◽

Cited By ~ 5

Author(s):

Áróra Árnadóttir ◽

Michał Czepkiewicz ◽

Jukka Heinonen

Keyword(s):

Urban Form ◽

Online Survey ◽

Environmental Concern ◽

International Travel ◽

Urban Region ◽

Environmental Attitude ◽

Environmental Behaviors ◽

Household Energy ◽

Carbon Footprints ◽

Current Perspective

A lot of emphasis has been put on the densification of urban form to reduce greenhouse gas emissions from transportation. However, many recent studies have found that central urban dwellers, even though their carbon footprints of daily transportation may be lower, might be responsible for higher total emissions than those that reside in suburban areas. Similarly, as with the urban form, higher environmental concern is often considered as an indicator of lower emissions, but several studies have found that pro-environmental attitude (PEA) does not always correlate with less energy intensive behavior. This study analyzes how urban zones, PEA, and several sociodemographic variables are associated with annual travel emissions and pro-environmental behaviors (PEB), using a dataset collected with a map-based online survey (softGIS) survey, contributed by 841 participants from the Helsinki Metropolitan Area (HMA), Finland. Although PEA can affect PEBs related to household energy consumption (β = 0.282, p < 0.001), clothing (β = 0.447, p < 0.001) and produce purchases (β = 0.449, p < 0.0001), their relationship with emissions from local (β = −0.067), national (β = −0.019) and international (β = −0.016) travel was not significant. Clusters of low emissions from local travel and high international travel emissions were found in pedestrian-oriented urban zones and residents of car-oriented zones were more likely to conserve household energy (β = 0.102, p < 0.05). These results might help broaden the current perspective of city planners, as well as identify opportunities for more effective mitigation policies.

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