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Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework.

ABSTRACT: Decarbonizing the building sector depends on choices made at the household level, which are heterogeneous. Agent-based models are tools used to describe heterogeneous choices but require data-intensive calibration. This study analyzes a novel, cross-country European household-level survey, including sociodemographic characteristics, energy-saving habits, energy-saving investments, and metered household electricity consumption, to enhance the empirical grounding of an agent-based residential energy choice model. Applying cluster analysis to the data shows that energy consumption is not straightforwardly explained by sociodemographic classes, preferences, or attitudes, but some patterns emerge. Income consistently has the largest effect on demand, dwelling efficiency, and energy-saving investments, and the potential to improve a dwellings' energy use affects the efficiency investments made. Including the various sources of heterogeneity found to characterize the model agents affects the timing and speed of the transition. The results reinforce the need for grounding agent-based models in empirical data, to better understand energy transition dynamics.

SUBMITTER: Edelenbosch OY

PROVIDER: S-EPMC8891977 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework.

Edelenbosch Oreane Y OY Miu Luciana L Sachs Julia J Hawkes Adam A Tavoni Massimo M

iScience 20220211 3

Decarbonizing the building sector depends on choices made at the household level, which are heterogeneous. Agent-based models are tools used to describe heterogeneous choices but require data-intensive calibration. This study analyzes a novel, cross-country European household-level survey, including sociodemographic characteristics, energy-saving habits, energy-saving investments, and metered household electricity consumption, to enhance the empirical grounding of an agent-based residential ener ...[more]

PMID: 35252811

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Project description:Sustainability has endured as a global topic in terms of quality of life and energy-saving for an equalized system. Households represent one of the most energy-consuming sectors globally and are expected to increase tremendously in the future. Women have higher responsibility in the household energy use in most societies. However, their participation and impacts have been less prioritized in the sustainability concept regarding energy perspective. In contrast, most development studies reveal that women's participation in managing resources can positively impact women and policy management. However, women's active participation and influences on social, economic, and environmental contexts are mostly ignored in energy-related decisions, disregarding women's productive activities. Thus, this study evaluates the gender role in urban household energy in three contexts of economic, social, and environmental aspects of sustainability pillars. This study is exploratory research based on questionnaire survey, interviews, observation, and air quality tests to apprehend appropriate data. The study revealed that the lower-income group uses a larger share of their monthly income for household energy with unclean cooking fuel. It has an impact on low-willingness to participate in new energy technology purchases. The use of electrical appliances and income has a moderate correlation (r = .48). However, Kathmandu urban households are eager to use electric cooking, but urban women have insufficient knowledge, information, and less affordability for new technology. The city's sustainability level is still low (47 scores) from a gender perspective, and it suggests the city needs a long way on the sustainability route. The study concluded that innovative technical interventions and women's financial power are essential, including the subsidy policy to reduce inequality between low and high energy household share variation and elevate gender participation. The gender mainstreaming approach in energy policy can increase women's participation in energy technology to get a clean environment and reduce the nation's financial burden of importing fuel.Supplementary informationThe online version contains supplementary material available at 10.1007/s43621-021-00027-w.

Project description:BackgroundThe ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed.ResultsWe have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research.ConclusionsThe Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community.

Dataset Information

Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework.

Publications

Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework.

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