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AI-driven approaches can expedite building decarbonization: McKinsey | Dump Trucks Charlotte NC

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A young man works on a software looking at the design of a solar panel array. Given what is possible with AI and evolving data, integrating electrification measures with energy efficiency actions is part of a credible building decarbonization plan, McKinsey says. Laurence Dutton via Getty Images

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Columbus Ohio Dump Truck Company Brief:

  • Building portfolio owners can identify building decarbonization opportunities more quickly by applying machine learning, artificial intelligence and physics-based modeling, according to a Nov. 29 report released by McKinsey.
  • By using data from satellites, geospatial analytics, regulations, labor and columbus oh dump trucks costs, and assessing heating and cooling systems, insulation levels and the feasibility of solar or geothermal power, algorithms can analyze and propose solutions for building portfolios to reach net-zero emissions. 
  • With this new approach, financially optimized plans, which account for the regulatory environment and the building’s unique characteristics and leasing structure, can be developed for an entire portfolio within weeks, experts said in the report. 

Dump Trucks Columbus OH Insight:

Given that buildings are responsible for 40% of global combustion-related emissions, it is essential to cut 50% of direct building emissions and 60% of indirect emissions by 2030 to achieve net-zero carbon building stock by 2050, the McKinsey experts said. Traditional methods of decarbonization, involving physical energy audits and building-by-building net-zero strategies, are considered laborious and expensive, McKinsey said. Additionally, a lack of centralized inventory and standardization contributes to the perception that decarbonizing buildings is unprofitable.

Compared to traditional energy audits and net-zero studies, AI-driven approaches provide a more than 100-fold increase in the pace and scale of decarbonization planning, eliminating the need to rely on vague building archetypes, the report stated. 

The authors highlighted the potential for an AI-based approach to generate neutral to positive returns on investment for real estate portfolios, assuming the absence of factors like incremental future regulations, carbon pricing and green premiums on rent or property valuation.Implementing energy efficiency and electrification measures for each building, while optimizing renewable energy procurement at the portfolio level, enables building owners and occupants to recoup their investment by realizing energy savings, optimizing their capital costs and avoiding regulatory penalties, the paper emphasized. 

Features of an optimal building decarbonization plan

McKinsey emphasized that achieving the most effective building decarbonization plans involves seven components that can be optimized through the use of AI and machine learning methods:

  1. Efficient net-zero planning: Owners can ensure coordinated, comprehensive plans for their entire portfolio through joint procurement and strategic sequencing, unlike traditional decarbonization plans that often target select buildings based on emissions or existing regulations. 
  2. Asset-specific plans: Tailored plans that consider aspects like building layout and type of insulation are needed for cost-effective decarbonization. Each building requires a unique strategy that considers its starting point, local conditions and asset specifics like tenant composition and lease structures.
  3. Complete pathways to net-zero: This involves avoiding partial plans that compromise long-term outcomes. Companies must take comprehensive, forward-looking decisions as short-term strategies risk increased costs and overlook synergies like insulation measures that affect future HVAC requirements.  
  4. Integrated Scope 1 and Scope 2 plans: Disjointed approaches toward energy efficiency and electrification hinder efficiency, the report said. The failure to exploit interdependencies can lead to slower and costlier renewable power procurement.
  5. Actionable steps: Building plans must provide precise instructions for facilities managers and enable easy communication between vendors and facilities management teams to ensure swift execution.
  6. Quantification: Plans must be specific enough to offer detailed insights for financial planning, encompassing net-zero goals, capital investment challenges, operating costs, potential debt and the allocation of costs and benefits between building owners and tenants, so that leaders can understand the exact costs of achieving net-zero emissions.
  7. Net-zero-oriented decision-making: Owners and operators can integrate decarbonization plans into organizational operations by adjusting processes, incentives and governance structures. This involves updating capital plans, budgeting for low-emission systems and incorporating decarbonization analyses into new asset acquisitions. 

Decarbonization challenges related to scaling supply chains to meet new demand and training skilled workers to deploy retrofits and undertake other electrification efforts also impact the industry, the report said. 

Fortunately, adopting an AI-backed, full-life-cycle approach to decarbonization simplifies planning, accelerates processes, and reduces costs, enabling significant progress in addressing building-related emissions, McKinsey said.

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