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The rapid urbanization of Indian cities and the population surge in cities has steered a massive demand for energy, thereby increasing the carbon emissions in the environment. Information and technology advancements, aided by predictive tools, can optimize this energy demand and help reduce harmful carbon emissions. Out of the multiple factors governing the energy consumption and comfort of buildings, indoor room temperature is a critical one, as it envisages the need for regulating the temperature. This paper aims to propose a mathematical model for short-term forecasting of indoor room temperature in the Indian context to optimize energy consumption and reduce carbon emissions in the environment.

A study is conducted to forecast the indoor room temperature of an Indian corporate building structure, based upon various external environmental factors: temperature and rainfall and internal factors like cooling control, occupancy behavior and building characteristics. Expert insight and principal component analysis are applied for appropriate variables selection. The machine learning approach using Box–Jenkins time series models is used for the forecasting of indoor room temperature.

ARIMAX model, with lagged forecasted and explanatory variables, is found to be the best-fit model. A predictive short-term hourly temperature forecasting model is developed based upon ARIMAX model, which yields fairly accurate results for data set pertaining to the building conditions and climatic parameters in the Indian context. Results also investigate the relationships between the forecasted and individual explanatory variables, which are validated using theoretical proofs.

The models considered in this research are Box–Jenkins models, which are linear time series models. There are non-linear models, such as artificial neural network models and deep learning models, which can be a part of this study. The study of hybrid models including combined forecasting techniques comprising linear and non-linear methods is another important area for future scope of study. As this study is based on a single corporate entity, the models developed need to be tested further for robustness and reliability.

Forecasting of indoor room temperature provides essential practical information about meeting the in-future energy demand, that is, how much energy resources would be needed to maintain the equilibrium between energy consumption and building comfort. In addition, this forecast provides information about the prospective peak usage of air-conditioning controls within the building indoor control management system through a feedback control loop. The resultant model developed can be adopted for smart buildings within Indian context.

This study has been conducted in India, which has seen a rapid surge in population growth and urbanization. Being a developing country, India needs to channelize its energy needs judiciously by minimizing the energy wastage and reducing carbon emissions. This study proposes certain pre-emptive measures that help in minimizing the consumption of available energy resources as well as reducing carbon emissions that have significant impact on the society and environment at large.

A large number of factors affecting the indoor room temperature present a research challenge for model building. The paper statistically identifies the parameters influencing the indoor room temperature forecasting and their relationship with the forecasted model. Considering Indian climatic, geographical and building structure conditions, the paper presents a systematic mathematical model to forecast hourly indoor room temperature for next 120 h with fair degree of accuracy.

Buildings/infrastructure are recognised to have a significant impact on the environment and the community, and hence there is pressure on industry practitioners to incorporate environmental and social considerations in addition to the traditional cost, time and quality. The development of sustainability reporting tools (SRTs) to assist in the management of “green” building/infrastructure projects is pivotal in informing on progress in sustainability practices. However, the rapid growth of SRTs in the last decade, with different criteria and methodology, has created complications for stakeholders.

The paper provides a comprehensive review of tools to guide practitioners, property investors, policy makers and developers towards making informed choices in “green” building/infrastructure projects. Comparative analyses, benefits and limitations of these tools are discussed in the paper.

Some of the findings from the analysis of SRTs include: an emphasis on environmental issues; scoring which does not account for uncertainty or variability in assessors’ perceptions; lack of published reasoning behind the allocation of scores; inadequate definition of scales to permit differentiation among projects; and the existence of non-scientific benchmarks.

The paper departs from earlier reviews to include a discussion on infrastructure SRTs, life cycle tools, and issues broader than the environment. Changes and additions, subsequent to earlier reviews, have been made to SRTs, making the updated review provided here useful.

Improving energy efficiency is considered one of the most desirable and effective short‐term measures to address the issue of energy security, and also reduce the emission of greenhouse gases. However, lack of access to domestic finance is the major hindrance in achieving the potential in China and India. This paper aims to report the experience of a three‐country United Nations Environment Programme/World Bank Energy Efficiency Project (involving China, India and Brazil) that is set up to address the financial barrier and identifies the lessons that can be learnt from the project.

The paper follows the post‐completion review approach of a project and presents the activities undertaken and results obtained from the project.

The project seeks to remove the financial barrier through the development of a commercial banking window for energy efficiency, energy service company development and support, exploring the need for setting up guarantee facilities and need for facilitating equity financing to the sector. The project succeeds in creating awareness and better understanding among the financial institutions in both India and China on potential of energy efficiency and need to make financing available for this. The banks in India in created specialized schemes for energy efficiency financing, and in China, the project has a positive impact on the new initiatives with the on‐lending facility and the guarantee fund for energy management companies. Experience sharing on these issues through cross‐exchange workshops proves to be very useful. The project successfully creates a platform on which further energy efficiency work can be carried out in the participating countries.

By disseminating the experience of energy efficiency financing in two developing countries, the paper contributes to knowledge that can be helpful in a wider context.

The assessment of building performance in terms of environmental impact and overall sustainability approach is carried out by several methods, different in terms of structure, application and parameters involved. A review of the most frequently used tools available at the moment is presented and a comparison of the tools in terms of general characteristics and environmental parameters is undertaken. Moreover, suggestions are made with regards to a future, easy to use, sustainable building Mediterranean assessment tool.

The methods are investigated in terms general parameters such as their applicability and also in terms of their primary environmental issues of concern involved. A comparative analysis is undertaken.

The investigation showed that none of the methods seem to incorporate all the parameters involved. Especially, the economic and social factors as well as comfort, which are all significant parameters directly involved to sustainability, are assessed only by half of the tools presented. The focus of the methods seems to be on issues regarding energy, landscape‐site, resources and quality of indoor environment.

The paper encourages the development of a more complete tool, which will include as many parameters as possible and would be applicable at a macro‐regional scale (e.g. the Mediterranean region).

The paper can be used as the starting point for future research as well as a reference paper.

The purpose of the paper is to marshal the carbon sources, and explore a computational model to calculate the buildings’ carbon emissions by using building information modeling (BIM) techniques. The study aims to integrate the BIM techniques with the carbon emission and energy analysis tools, which can provide a more exact quantification result.

To define the scope of this study, several standards or regulations have been comparatively analyzed. The BIM technique has also been used to establish the computational model of carbon emissions, including the calculation principle, the basic database, and each process of modeling. Finally, a case study is given to test the theoretical study.

The paper provides a quantitative calculation method for the carbon emissions of buildings, and suggests an approach to integrate the BIM techniques with the low carbon research. This allows the quantity of material consumption and carbon emission to be calculated in real time during the whole construction process.

Because of the chosen American database, the calculation results may lack generalizability. Therefore, the approach of establishing a universal database of carbon emission coefficients will be the next key point.

As this research shows, there is a need for an advanced calculation method to evaluate the buildings’ carbon emission exactly by BIM techniques, which also provides a basis to establish the regulation of carbon transaction tax in the future.

This paper fulfils an identified need to calculate the carbon emission during the buildings’ construction stage, so that better decisions can be made to optimize the construction plan and choose the low emission materials properly.

The key purpose of this paper is to quantify the size of the energy-efficiency gap (EEG) for air conditioners at the household level in Delhi. Most of the studies in the EEG tradition broadly define EEG as the difference between the actual and optimal level of energy efficiency. The optimal level of energy efficiency is defined at the societal level (that weigh social costs against social benefits) and the private level (that weigh private costs against private benefits).

The authors base the empirical results in this study on the basis of the primary data collected through in-person interviews of the high-income urban households in Delhi in 2014-2015. The sample of 101 households was collected through purposive random sampling. The survey data include information on type and number of AC possessed, hours of operations, socioeconomic characteristics and awareness and habits of households.

Using primary data of 101 high-income urban household, the paper finds that average EEG is about 10 per cent of total electricity demand of ACs at the household level. The maximum current saving potential measured as a difference between hypothetical energy consumption, if everyone adopts five star ACs, and actual energy consumption is estimated about 14 per cent of the total electricity demand of ACs. Results from the ordinary least squares regressions demonstrate that individual’s habits, attitude, awareness of energy-efficiency measures and perceptions significantly determine the size of the EEG. Among other things, authors’ empirical analysis shows that information can play a central role in guiding investment in energy-efficient technologies. From the analysis of improving access to understandable information about cost savings, payback period and emission reduction, it is found that full information leads to the significant reduction in the size of the expected private energy-efficiency gap from 10 to 2.98 per cent at the household level.

This paper tests the significance of non-economic and non-social factors in determining the size of the EEG. Apart from socioeconomic factors such as income, occupation and education, individual’s energy-conserving habits and attitudes, awareness of energy-efficiency measures and perceptions are other important factors found to have a significant negative impact on the size of the EEG. This is particularly important for the designing of information programs by policymakers for promoting energy-efficiency choices in view of the change that is required in the behavior and attitudes of the households.

In this study, authors try to estimate the size of the EEG of ACs for the high-income urban households in Delhi. The private energy-efficiency gap estimated at 10 per cent of the household demand for ACs indicates existing saving opportunity for the private households. It is found that provision of comprehensive information about cost savings, payback period and emission reduction reduces the size of the EEG significantly from 10 to 2.72 per cent at the private level. This highlights the existence of limited and incomplete information in the market about the possible costs and benefits of energy-efficiency investments. This paper tests the significance of non-economic and non-social factors in determining the size of the energy-efficiency gap. Apart from socioeconomic factors such as income, occupation and education, individual’s energy-conserving habits and attitudes, awareness of energy-efficiency measures and perceptions are other important factors found to have a significant negative impact on the size of the EEG. This is particularly important for the designing of information programs by policymakers for promoting energy-efficiency choices in view of the change that is required in the behavior and attitudes of the households.

In light of climate change, the design and construction of buildings needs to shift from conventional to lower-carbon practices to maximise carbon reduction. Over the past few years, the zero carbon buildings (ZCBs) approach has been promoted worldwide as an effective way to reduce environmental impacts and mitigate climate change. Although zero-carbon policies, technologies, processes and products are widely available in the construction market, construction stakeholders play an important part in adopting relevant strategies to implement ZCBs successfully. This study investigates the knowledge of construction stakeholders involved in the design and construction of buildings regarding zero carbon initiatives in New Zealand.

The research was conducted using a literature review and an online questionnaire survey with various New Zealand's construction stakeholders.

The findings indicate a low level of knowledge regarding the design and construction of ZCBs. To successfully deliver ZCBs, the study suggests that construction stakeholders must have their self-awareness increased, especially in improving knowledge of whole-of-life embodied carbon reduction. The governments and construction sectors should devote more effort to establishing training programmes and knowledge-sharing platforms to improve stakeholder knowledge in carbon literacy, building assessment methods, energy modelling and life cycle assessment.

The research implications may assist the real-world uptake of the ZCBs approach by offering academics and practitioners an insight into the ZCBs knowledge gaps.

Today, the need for renewable energy is rising steadily. Various steps are being taken by nations to address the rising need. The developments occurring in proportion to the industrial structures and economic levels of the countries, these efforts, the political structure of the country, some established patterns from the past, and many other external factors affect the use of renewable energy and therefore sustainable development, which has been one of the most important agendas since the early 1990s. In this study, it is examined whether certain characteristics of the Scandinavian Welfare Model affect the background of this successful image of Finland, Denmark, and Sweden, which rank in the top three positions in both the Global Energy Innovation Index and the Sustainable Development Report. As a result, although the use of fossil fuels increases the ecological footprint in the Scandinavian countries, which are evaluated as in the rest of the world, continuing the principles of innovation, trust, equality, openness, and sustainability with determination, the Nordic approach has not departed from the welfare state principle compatible with its own codes, unlike the transformations experienced by other welfare regimes, and has become a distinctive factor.

Drawing upon Alfred Sohn-Rethel's work, we argue that, just as capitalism produces abstract labor, it coproduces both abstract mind and abstract life. Abstract mind is the split between mind and nature and between subject/observer and observed object that characterizes scientific epistemology. Abstract mind reflects an abstracted objectified world of nature as a means to be exploited. Biological life is rendered as abstract life by capitalist exploitation and by the reification and technologization of organisms by contemporary technoscience. What Alberto Toscano has called “the culture of abstraction” imposes market rationality onto nature and the living world, disrupting biotic communities and transforming organisms into what Finn Bowring calls “functional bio-machines.”