Potential carbon emission reductions in australian construction systems through bioclimatic principles

Sattary, Sattar; Thorpe, David

doi:10.1016/j.scs.2016.03.006

Cited by 31 publications

(30 citation statements)

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“…In this paper, we propose that there may be a significant interaction of carbon emissions between neighboring regions. Indeed, some scientists have argued that the determinants of carbon emissions, such as social and economic factors or public policies, not only have a direct effect on carbon emissions in the local region, but also have an indirect effect on carbon emissions in neighboring regions, namely the spatial spillover effect [13,14]. Therefore, in this paper we identify the determinants of carbon emissions, taking into account the spatial spillover effects.…”

Section: Introductionmentioning

confidence: 98%

The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

et al. 2020

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As the largest carbon emitter in the world, China is confronted with great challenges of mitigating carbon emissions, especially from its construction industry. Yet, the understanding of carbon emissions in the construction industry remains limited. As one of the first few attempts, this paper contributes to the literature by identifying the determinants of carbon emissions in the Chinese construction industry from the perspective of spatial spillover effects. A panel dataset of 30 provinces or municipalities from 2005 to 2015 was used for the analysis. We found that there is a significant and positive spatial autocorrelation of carbon emissions. The local Moran’s I showed local agglomeration characteristics of H-H (high-high) and L-L (low-low). The indicators of population density, economic growth, energy structure, and industrial structure had either direct or indirect effects on carbon emissions. In particular, we found that low-carbon technology innovation significantly reduces carbon emissions, both in local and neighboring regions. We also found that the industry agglomeration significantly increases carbon emissions in the local regions. Our results imply that the Chinese government can reduce carbon emissions by encouraging low-carbon technology innovations. Meanwhile, our results also highlight the negative environmental impacts of the current policies to promote industry agglomeration.

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Section: Introductionmentioning

confidence: 98%

The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

et al. 2020

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“…It can be observed that researchers are also paying attention to Scope 2 and Scope 3 (or indirect) GHGs. Sattary and Thorpe (2016) [208] investigated the level of GHG emissions reduction which can be obtained by use of bioclimatic principles in Australian buildings. Based on their results, bioclimatic principles can make up to 65 percent reduction in construction GHG emissions, for the whole building including floor, wall and roof.…”

Section: Previous Studiesmentioning

confidence: 99%

Sustainable asset and project management

Abdi¹

2021

Preprint

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There is a growing demand for companies to report and demonstrate their environmental credentials and corporate responsibility, which presents an opportunity for them to differentiate and gain a competitive advantage in the marketplace. They are now recognizing the limited capacity of the environment to endure the current level of development and economic growth, depletion of natural resources, increasing problem of waste, worrying carbon dioxide emissions, and other environmental impacts. In fact, for asset and project managers, financial criteria are no longer the sole considerations to achieve success and shareholder value. Therefore, environment is being considered as a future source of risk or opportunity. The present research proposes methodology and mathematical models for a sustainable asset and project management, with the focus on the environmental aspect of sustainable development and more specifically the issue of greenhouse gas (GHG) emissions. The following models have been presented in this dissertation. First, a mathematical fleet optimization model is developed, which incorporates the environmental impacts of a fleet of assets over a finite horizon, in addition to its total cost of ownership. As a unique feature of the model, it allows the assets to be kept in storage over any time period, in which such assets do not deteriorate as in-use assets do. The mathematical model optimizes the number of new, in-use, in-storage, and salvaged assets in each time period, so that the total economic costs and environmental impacts are minimized. The application of this work is illustrated in a fleet of excavators. Second, a hybrid Bayesian network (BN) is proposed for fleet availability analysis, focusing on the uncertainty of assets failure and repair rates. We model the common causes to individual rates, as well as the common causes that affect both failure and repair rates at the same time. The proposed model explicitly quantifies uncertainty in repair and failure rates of a fleet of assets and provides an appropriate method for modeling complex dependencies and factors affecting reliability, maintainability, or both, by considering influencing factors, either technical (such as working temperature, environment, quality, stress, etc.) or organizational (such as staff quality, management policies, etc.). We will then extend the model to consider extremely rare and/or previously unobserved risks (e.g. heavy storms, droughts, floods, etc.) that can significantly weaken reliability or maintainability levels. Third, a deterministic model for equipment repair-replacement (R/R) decision with both economic and environmental considerations is formulated. We converted the model into an algorithm and an automatic R/R Calculator. A probabilistic version of this model is then developed to factor in the quality of preventive maintenance, repair perfection, and risk events. We also model the causal relationship between equipment reliability and its GHG emissions during the operation phase. A plastic shredder case study was used to present the models’ results. Fourth, we aim to capture the uncertainty of carbon price in the Western Climate Initiative (WCI) market, by determining the causality between carbon price and its driving forces. A probabilistic model is developed using BNs to infer the possible ranges of each driving force that could have an escalation/depreciation effect on price as well as the magnitude of this effect. The model is developed and run based on a database of historical and projection on the selected driving factors in all the jurisdictions of the WCI market, providing the most probable price(s) over the next ten years. Finally, we developed two models to estimate and control project GHG emissions. The first model is developed based the earned value management (EVM) technique, a common practice in project cost and schedule performance measurement. The proposed model provides project managers with metrics to measure project GHG performance at any point in time over the life of a project and forecast the final emissions. In addition, we proposed a probabilistic model to quantify the uncertainty of project GHG emissions using Monte Carlo Simulation and BN techniques. The model provides a quantitative risk analysis mechanism to estimate the total emissions of the project as well as prediction of final emissions during the implementation process. The proposed models are applied to a work package of a real construction project.

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“…Given the role of the physical characteristics in enhancing the overall energy consumption of building industry, some reports and research works have stressed the impact of architectural composition principles and physical characteristics on the energy performance of building sector (UNEP SBCI, 2009;BZE, 2013;Allwood et al, 2012;Nasrollahi et al, 2013;Sattary and Thorpe, 2016;Chandel et al, 2016;Granadeiro et al, 2013). In Australia, for instance, BZE (2013) reported that the poor thermal performance of the building envelope that is a consequence of inadequate design consideration and poor choice of building materials and techniques has led to high amount of wasted energy in the housing sector.…”

Section: Literature Reviewmentioning

confidence: 99%

A collaborative image of energy efficient housing via a photo-based approach

Poor

Thorpe

Goh

2019

IJHMA

Self Cite

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Purpose Regarding the contribution of Australian small-size housing in the enhancement of total energy consumption of the country and the roles of the occupants’ preferences in successful implementation of action plans, the purpose of this study is to identify the Australian occupants’ collaborative image of housing energy efficiency. The two main objectives are, therefore, to address the main energy-related housing physical factors that have the potential in representing the housing image of Australian occupants and to explain the causal factors that make the physical factors critical to their energy efficiency perception. Design/methodology/approach This study has been developed through a qualitative approach. Given that the images encompass a wide range of information expressing human perceptions, an online photo-based qualitative survey was developed based on previous research works. The survey includes respondents’ demographic profiles and the evaluation of images, asking for their perception of overall housing energy efficiency, the impacts of building envelope physical attributes on the energy efficiency of the houses and the reasons behind the selection of different attributes. Findings This study has developed a set of attribute-based factors, explaining occupants’ collective perception of energy efficient small-size housing of Brisbane in the area of exterior aspects of the buildings. Specifically, the collaborative image of small-size housing of Brisbane is about the thermal performance of the buildings provided through passive climatic principles by using more efficient envelope features, e.g. material, colour, transparency, texture, openings, balconies and shadowing devices, while ignoring the impacts of architectural composition principles along neighbourhood quality. The key attributes in assessing the small-housing energy efficiency are ventilation, thermal performance and shadowing. The housing images in old traditional architectural style with rural face, built by stone, brick and concrete in high dense vegetation were evaluated to be more energy efficient than those with modern architecture, built by large glass panel and metal cladding with light or no vegetation. Research limitations/implications The main limitation of the paper is related to the nature of an image-based survey, which leads to ignoring some aspects of real spaces such as odour, temperature and noise. Practical implications This research has the potential for developing a practical methodology for assessing housing-resident fit using computer-based methodology and neural networks. Social implications This research has the potential for developing a methodology, assisting the end users in meeting their desires and motivations by helping them in assessing how a housing unit fits with their expectations and preferences. Originality/value This research provides a reliable conceptual platform for dealing with the complexity of occupants’ housing perceptions. This is achieved by establishing a collective conceptual picture of these environmental perceptions, namely, housing image, which is a platform for transferring abstract data related to human perception into measurable and quantitative scales.

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Potential carbon emission reductions in australian construction systems through bioclimatic principles

Cited by 31 publications

References 9 publications

The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

Sustainable asset and project management

A collaborative image of energy efficient housing via a photo-based approach

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