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The purpose of this paper is to show that building stock is currently one of the largest energy consumers. It is thus imperative that buildings are optimally planned, constructed, and used from both the environmental and the economic point of view. Cost models are relevant tools for achieving this objective as they can be used to estimate the occupancy costs in early project phases including energy costs.

In the paper a regression model for predicting the energy consumption and energy costs of office buildings is developed based on the results of a survey conducted in 80 Swiss office properties.

The proposed energy cost model shows good agreement with the observed field data. The mean absolute percentage error resulted in 12 per cent. Validation tests using five properties not used for the model development revealed percentage errors ranging between −17 per cent and 7 per cent. The proposed concept and the presented cost model can be used as a basis for future studies.

The energy consumption and energy cost model can be improved as the database for developing them is further extended (including properties from different owners with different strategies, for example energy contracting, outsourcing, and maintenance strategies).

The objective of the study was to develop and validate a predictive model to facilitate the estimation of occupancy costs in early project phases. A procedure is presented on how quantitative energy consumption and cost models can be developed. Provided that sufficient empirical data are available, this proecdure can be used in further studies as a suitable and practicable concept to advance occupancy cost models.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

In debates related to energy poverty, the link to questions of residential segregation remains somewhat peripheral. Because, usually, only energy-poor households are at the focus and residential mobility is not addressed, the interdependencies between households’ energy costs and the residential segregation of cities remain out of sight. Concern that energy efficiency measures could foster socio-spatial segregation in cities has recently emerged in Germany. If only households with higher incomes can afford housing with high energy efficiency standards, whereas low income households tend to choose non-refurbished but, in sum, more affordable housing stock, an increasing concentration of poor households in poor housing conditions would result. German energy efficiency and CO2 reduction policies are relatively insensitive to such questions.

Using survey data from a small shrinking city in Germany, we explore how energy costs are interrelated with residential location decisions and, thus, with segregation processes and patterns. Shrinking cities represent an interesting case because, here, a decreasing demand for housing stimulates residential mobility and paves the way for dynamic reconfigurations of socio-spatial patterns.

We found that energy-related aspects of homes play a role in location decisions. Low income households seek to minimize housing costs in general, paying specific attention to heating systems, thermal insulation and costs. Resulting segregation effects depend very much on where affordable and, at the same time, energy-efficient housing stock is spatially concentrated in cities. These findings should be taken into consideration for future policies on energy in existing dwellings.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Many institutions of higher education have committed to carbon neutrality. Given this goal, the main economic issue is minimizing cost. As for society as a whole, dominant decarbonization strategies are renewable electricity generation, electrification of end uses and energy efficiency. The purpose of this paper is to describe the optimum combination of strategies.

There are four questions for eliminating the primary institutional greenhouse gas emissions: how much renewable electricity to produce on-site; where and at what price to purchase the balance of renewable electricity required; how to heat and cool buildings without fossil fuels; and how much to invest in energy efficiency. A method is presented to minimize decarbonization costs by equating marginal costs of the alternates.

The estimated cost of grid-purchased carbon-free energy is the most important benchmark, determining both the optimal level of campus-produced renewable energy and the optimum efficiency investment. In the context of complete decarbonization, greater efficiency investments may be justified than when individual measures are judged only by fossil-fuel savings.

This paper discusses a theoretically ideal plan and implementation issues such as purchasing carbon-free electricity, calculating marginal costs of conserved energy, nonmarginal cost changes, uncertainty about achieving efficiency targets, and dynamic pricing. The principles described in this study can be used to craft a cost-minimizing decarbonization strategy.

While previous studies discuss decarbonization strategies, there is little economic guidance on which strategies are optimal, on how to combine strategies to minimize cost or how to identify a preferred path to decarbonization.

Rising energy expenditures due to more intensive use of energy in modern agriculture and increasing energy prices may affect rural households’ agricultural incomes, particularly the incomes of the rural poor in developing countries. However, the exact link between energy costs and income among the rural poor needs further empirical investigation. The purpose of this paper is to develop a deeper understanding of the relationship between energy use and family income, using household-level panel data collected from 500 potato farmers in a poor region of Northern China, where eliminating poverty by 2020 is now the top government priority.

The paper uses household survey data collected from six counties in a poor region in northern China in 2013 to measure the relationship between energy cost and family income. A fixed effect model is employed to estimate the relationship.

The findings indicate that potatoes play an important role in the surveyed families’ incomes, and that the energy costs of potato production have a significant negative relationship with family income. However, this negative relationship is only significant for farmers with low economic standing, such as those living below or just above the poverty line. The negative relationship between energy costs and family income is only significant for those cultivating a certain size of potato-sown area; it is insignificant for those cultivating smaller areas.

These findings indicate that, in general, reducing energy costs helps the poor increase their income but is not necessarily helpful to those with high economic standing or a relatively small potato-sown area. If rural development policies are to support poverty reduction and energy savings (at least in major potato production regions), interventions aimed at energy cost reduction may be effective only for the poor whose family income depends, to a relatively high degree, on potato production.