A multilevel regression approach to understand effects of environment indicators and household features on residential energy consumption

Tso, Kwok Fai; Guan, Jingjing

doi:10.1016/j.energy.2014.01.056

Cited by 103 publications

(57 citation statements)

References 38 publications

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“…Age, educational level, gender, and nationality are all occupant characteristics that influence energy behavior [28,[152][153][154]. Such characteristics could greatly impact occupant energy-saving adoption and the relevant intervention methods.…”

Section: Overview Of Current Approachesmentioning

confidence: 99%

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

2015

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Abstract:Buildings currently account for 30-40 percent of total global energy consumption. In particular, commercial buildings are responsible for about 12 percent of global energy use and 21 percent of the United States' energy use, and the energy demand of this sector continues to grow faster than other sectors. This increasing rate therefore raises a critical concern about improving the energy performance of commercial buildings. Recently, researchers have investigated ways in which understanding and improving occupants' energy-consuming behaviors could function as a cost-effective approach to decreasing commercial buildings' energy demands. The objective of this paper is to present a detailed, up-to-date review of various algorithms, models, and techniques employed in the pursuit of understanding and improving occupants' energy-use behaviors in commercial buildings. Previous related studies are introduced and three main approaches are identified: (1) monitoring occupant-specific energy consumption; (2) Simulating occupant energy consumption behavior; and (3) improving occupant energy consumption behavior. The first approach employs intrusive and non-intrusive load-monitoring techniques to estimate the energy use of individual occupants. The second approach models diverse characteristics related to occupants' energy-consuming behaviors in order to assess and predict such characteristics' impacts on the energy performance of commercial buildings; this approach mostly utilizes agent-based modeling techniques to simulate actions and interactions between occupants and their built environment. The third approach employs occupancy-focused interventions to change OPEN ACCESSEnergies 2015, 8 10997 occupants' energy-use characteristics. Based on the detailed review of each approach, critical issues and current gaps in knowledge in the existing literature are discussed, and directions for future research opportunities in this field are provided.

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Section: Overview Of Current Approachesmentioning

confidence: 99%

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

2015

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“…This method has already been used in other fields but, to the authors' knowledge, has so far not been applied to mass valuation. Hierarchical linear models have been successfully used since the 80s in the fields of education (Aitkin et al 1981;Raudenbush and Bryck 1986;Singh 2014), public policy (Duncan et al 1993;Tso and Guan 2014), criminology (Gelman 2007;Fagan et al 2015), and politics (Wang et al 2015). This method overcomes some limitations of the traditional regression models, which are based on the hypothesis that the individuals in the sample are independent, however this assumption is not always correct.…”

Section: Introductionmentioning

confidence: 99%

Mass Appraisal of Residential Real Estate Using Multilevel Modelling

Arribas

García

Guijarro

et al. 2016

International Journal of Strategic Property Management

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ABSTRACT. Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. In this study HLM was applied to a large dataset of 2,149 apartments, which included 17 variables belonging to two hierarchical levels: apartment and neighbourhood. The model obtained high goodness of fit and all the estimated variances of the parameters in HLM were lower than those calculated by OLS. It can be concluded as well that no further neighbourhood variables need be added to the model to improve the goodness of fit, since almost all the residual variance can be attributed to the first hierarchical level of the model, the apartment level.

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“…The literature widely identifies an uptrend in citizens' concerns about the complexity of pollution sources worldwide [3][4][5]. Besides citizen concerns, there is evidence of more intense political activity on the topic, independent of national parliaments and governments [6,7] or the international space of multilateral agreements [8,9].…”

Section: Motorsports As a Source Of Comentioning

confidence: 99%

Smoking Gentlemen—How Formula One Has Controlled CO2 Emissions

Mourão

2018

Sustainability

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This article reports estimates of the level of CO 2 emissions created by Formula One (F1) cars on Sunday races. Supported by a variety of sources and using Monte Carlo iterations, we obtained values identifying important periods of change. These periods were identified using tests of structural breaks. We observe that the 1966-1970 period (related to the dominance of DFV/Cosworth engines) is associated with an increase in CO 2 emissions, whereas the 1992-1995 period (related to lighter and more efficient engines) is associated with a decrease in estimated levels of emitted CO 2 . Our results do not identify the deep modifications following more "green" regulations in 2009-2011 as a relevant change.

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A multilevel regression approach to understand effects of environment indicators and household features on residential energy consumption

Cited by 103 publications

References 38 publications

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

Mass Appraisal of Residential Real Estate Using Multilevel Modelling

Smoking Gentlemen—How Formula One Has Controlled CO2 Emissions

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