The Economics Of Energy Retrofitting: Calculating Roi For Boston Businesses – The Moderating Effect of Golden Parachute on the Association between CSR and Firm Value: Does Innovation Matter by Gender?
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- 1 The Economics Of Energy Retrofitting: Calculating Roi For Boston Businesses
- 2 Installing Leds Gives Warehouses Cheaper, Cleaner Lighting, Experts Say
- 3 Here’s How To Scale Energy Saving Commercial Building Retrofits
- 4 Minutes Timescale 3d Isotropic Imaging Of Entire Organs At Subcellular Resolution By Content Aware Compressed Sensing Light Sheet Microscopy
- 5 Solving Challenges In Renewable Energy Storage
The Economics Of Energy Retrofitting: Calculating Roi For Boston Businesses
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Installing Leds Gives Warehouses Cheaper, Cleaner Lighting, Experts Say
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By Tharindu Prabatha Tharindu Prabatha Scilit Preprints.org Google Scholar , Kasun Hewage Kasun Hewage Scilit Preprints.org Google Scholar * and Rehan Sadiq Rehan Sadiq Scilit Preprints.org Google Scholar
Here’s How To Scale Energy Saving Commercial Building Retrofits
Received : 28 January 2023 / Revised : 16 March 2023 / Accepted : 16 March 2023 / Published : 20 March 2023
Building energy retrofits can reduce emissions and increase cost savings. Some retrofits that can provide higher emissions savings are not popular due to a lack of economic justification. Financial incentives can be used to change buyers’ attitudes towards such retrofits. This study proposes a framework for identifying the best retrofit strategies for a given cluster of buildings and the best incentive amounts to promote the chosen strategies, accounting for uncertainties, stakeholder priorities, and budget constraints. The proposed framework was illustrated using a case study complemented with policy insights. Life-cycle cost savings and capital cost significantly influence retrofit purchase decisions. Case study results have shown that significant cost savings can be achieved by retrofitting electrically heated homes. However, by adopting energy-conscious behaviors in natural gas-heated homes and by injecting renewable natural gas into the gas supply, any retrofitting strategy can double the emissions savings applied to a house heated by electricity. This highlights the need to adopt performance-based incentives beyond the prescriptive approach to reward occupier efforts as well as asset performance. Despite potential life-cycle cost savings, incentives must be complemented with low-interest loans to promote retrofit strategies that carry higher capital costs.
Climate change is no longer recognized as a future crisis. Leading scientific bodies such as NASA acknowledge that climate change is already affecting the world . The intergovernmental panel on climate change (IPCC) indicates that the associated environmental consequences would be preventable if the global temperature increased by 1.5 °C over pre-industrial temperatures . The IPCC recommends limiting anthropogenic greenhouse gas (GHG) emissions to avoid the projected climate dangers and identifies the construction sector as a key area that can support this as it accounts for 12% of anthropogenic GHGs and 40% of energy use worldwide responsible for [2, 3, 4].
In response to these increasing challenges, climate leaders such as British Columbia (BC), Canada have developed innovative policy tools such as the BC Energy Step Code to reduce the environmental impacts of new construction . However, improving the performance of existing buildings built to less stringent energy efficiency standards remains a challenge .
Building Retrofits: The Underrated Weapon In The Fight To Decarbonise Cities
Retrofitting is commonly used to improve the energy performance of existing buildings. Energy retrofits lead to improvements in economic, environmental and indoor environmental quality (IEQ) performance . Occupants can benefit from operational cost savings and improved IEQ . In addition, building owners can benefit from the increases in property value. Overall, retrofitting projects can support national climate change mitigation initiatives and local economies through emissions savings and job creation. However, financial pressures such as high life cycle costs (LCC) and capital costs (CC) and lack of economic justification may reduce public acceptance of retrofitting [7, 8]. Therefore, building owners need to be guided and trained, but they also need to be provided with an economic rationale to adopt these interventions.
A carbon tax and capping of emissions are used to minimize the use of energy generated by using higher emission sources . However, regionally implemented penalties such as provincial carbon taxes can create challenges for local industries competing in the global market due to increased production costs . In addition, energy affordability issues arising from penalties can create social difficulties that can cause a backlash against clean energy promotion and government-led initiatives to mitigate climate change [11, 12]. Therefore, bringing forward the penalties as a first step can hinder the success of energy retrofit promotion campaigns. Furthermore, penalties and emission caps fail to promote energy conservation opportunities associated with cleaner energy sources. Therefore, it is more appropriate to promote performance improvements with financial incentives to drive industries and the public towards energy-efficient technologies and cleaner energy sources in the initial stages [13, 14]. When the community is ready for cleaner energy adoption and equipped with energy efficiency practices, penalties can be introduced slowly in an incremental approach. Given the importance of incentives/rebates in promoting building energy retrofits (BERF), this article focuses on planning financial incentives for energy retrofits.
A search of the Compendex database in January 2022 yielded seventy-three research articles using “residential”, “building”, “energy”, “retrofit”, and “incentive” as keywords. Diakaki et al. developed a retrofit selection algorithm considering annual energy use, annual emissions, and capital cost using a multi-objective solution methodology . Bonomolo et al. an approach is proposed to identify cost-optimal lighting retrofits that account for daylighting opportunities . Zhang et al. proposed a Pareto optimization approach for the selection of residential retrofits . Ruparathna et al. developed an economic evaluation approach for retrofit evaluation . All of the reviewed literature contributed to improving retrofit selection processes. However, current approaches have not addressed one or several of the following aspects of community retrofit planning: life cycle costing and emissions, addressing uncertainties, conflicting decision priorities, and retrofitting promotion through financial incentives.
The results of the literature review prompted the authors to investigate the need for a comprehensive strategy to identify the best retrofit strategies and the best incentive levels to promote the best retrofit packages/strategies under uncertain conditions. In addition to the literature review, the authors communicated with experts from local municipalities, construction companies, building management agencies, utility providers, and Natural Resources Canada to determine the need for a retrofit planning mechanism and energy incentives. All stakeholder groups echoed the need for a decision support tool that would enable standardized incentives and an energy retrofit planning strategy to achieve the existing buildings sector’s climate action targets. The research gaps identified related to building energy retrofits and incentive planning are summarized below:
Minutes Timescale 3d Isotropic Imaging Of Entire Organs At Subcellular Resolution By Content Aware Compressed Sensing Light Sheet Microscopy
No comprehensive models have been developed to quantitatively determine incentive amounts for building energy retrofits, and the multi-stakeholder nature of the problem is ignored [13, 19, 20].
Life cycle emissions (LCE) are considered in retrofit planning and financial incentives. Corporate emissions are often neglected due to the singular focus on operational emissions .
Previous studies on retrofitting strategy and incentive planning [13, 22] have largely neglected uncertainties related to building retrofitting and the external environment. Furthermore, the sensitivity of residential energy retrofit project results to operating conditions and macroeconomic parameters has not been adequately investigated.
This study addresses the research gaps discussed above for its academic merit by proposing an incentive/rebate planning strategy for BERs to maximize environmental and economic benefits under uncertainty while taking into account budgetary constraints and stakeholder priorities. More importantly, it provides a much-needed quantitative decision-making model that can be used by various levels of government and non-governmental organizations to identify the best incentive levels with the limited budget at hand. Additionally, individual building owners/contractors can use the proposed retrofit selection framework to determine the best retrofit strategies under uncertainty for their buildings.
Solving Challenges In Renewable Energy Storage
The proposed approach was illustrated using a Canadian case study. The sensitivity of the different retrofit strategies to uncertainties in energy supply and building operating conditions, macroeconomic parameters, and alternative decision preference scenarios was evaluated based on the case study results. However, the proposed approach can be used globally by changing the inputs. Inputs to the model include the energy saving potential of different retrofit strategies (generated from the energy simulation software), energy cost and emission factors, retrofit cost factors (e.g. capital costs and maintenance), decision priorities, and constraints. These inputs can be selected according to local conditions and the retrofit selection and incentives planning algorithm can be applied regardless of location or building type.
The opportunities and challenges of BERs can be better understood using the eco-efficiency classification presented in Table 1.
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