Buildings and Cities
Energy courses through buildings—in heating and air-conditioning systems, electrical wiring, water heating, lighting, information and communications systems, security and access systems, fire alarms, elevators, appliances, and indirectly through plumbing. Most large commercial buildings have some form of centralized, computer-based building management, used to monitor, evaluate, and control those systems. Adopting automated rather than manual building management systems can reduce energy consumption by 10 to 20 percent.
A building automation system (BAS) is a building’s brain. Equipped with sensors, BAS buildings are constantly scanning and rebalancing for greatest efficiency and effectiveness. Lights switch off when no one’s around, for example, and windows vent to improve air quality and temperature. New buildings can be equipped with BAS from the start; older ones can be retrofitted to incorporate it and reap its benefits.
Beyond energy savings and reduced operations and maintenance costs, BAS benefits the well-being and productivity of people inside the building. Improved thermal and lighting comfort and indoor air quality directly impact occupant satisfaction. BAS is especially useful to ensure and maintain efficiency in green buildings, so that their ratings on paper match their actual performance.
automated systems…[lower] energy consumption: IEA. Transition to Sustainable Buildings: Strategies and Opportunities to 2050. Paris: International Energy Agency, 2013; Siemens. Building Automation—Impact on Energy Efficiency. Zug, Switzerland: Siemens, 2009.
indoor air quality…increases in productivity: WGBC. Health, Wellbeing, and Productivity in Offices: The Next Chapter for Green Building. London: World Green Building Council, 2014.
buildings…energy use and…emissions: Lucon, O., D. Ürge-Vorsatz, A. Zain Ahmed, H. Akbari, P. Bertoldi, L. F. Cabeza, N. Eyre et al. “Buildings.” In Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, and New York: Cambridge University Press, 2015.
“neural networks”: Lux Research. Sensors and Controls for BEMS: Providing the Neural Network to Net-Zero Energy. Boston: Lux Research, 2012.
Project Drawdown defines building automation as: automated control systems that can regulate a building’s heating and cooling, lighting, appliances, and more to maximize energy efficiency and/or worker productivity. This solution would replace buildings with conventional pneumatic or electric control systems.
Because of their large share of energy consumption, residential and commercial buildings now account for nearly one-third of global carbon dioxide emissions. An efficiency technology that has historically been common in large commercial buildings is a building automation system (BAS). Though many large commercial buildings in the US and EU have some form of building automation or management system, these systems are often not based on the most recent technologies.
Recent trends in building system integration and automation have caused increased interest around the future of BAS technologies, but this is an area that remains under-studied. The benefits of these BAS for large commercial buildings and, increasingly, for small- and medium-sized buildings are significant, as they can reduce energy consumption in commercial buildings by up to 40 percent (IEA, 2013). The model presented examines the financial and emissions impact of high BAS adoption instead of conventional system use.
Total Addressable Market 
The total addressable market for BAS was considered to be the total floor area of commercial building space worldwide; adoption was therefore defined as the total commercial floor area managed by a BAS system. Current adoption  was estimated to be 35 percent of the market. This was estimated using sources for the US, EU, and China.  Sparse adoption data indicated very low adoption in other regions, which were therefore excluded from this current adoption estimate.
Adoption Scenarios 
Impacts of increased adoption of building automation from 2020-2050 were generated based on three growth scenarios, which were assessed in comparison to a Reference Scenario where the solution’s market share was fixed at the current levels.
- Plausible Scenario: Logistic s-curves were calculated for each Drawdown region, with assumptions on their expected adoption in 2050. These assumptions were: 100 percent adoption in Organisation for Economic Co-operation and Development (OECD) countries; current US adoption levels in China; half of current US and EU levels in Latin America and Eastern Europe, respectively; and 20 percent of current EU levels in the Middle East and Africa. These were summed to get the global adoption.
- Drawdown Scenario: Linear growth was applied to each Drawdown region, with assumptions on the adoption in 2050: 100 percent adoption in the OECD, 80 percent adoption in China, 50 percent everywhere else. These were summed to get the global adoption.
- Optimum Scenario: Linear growth was applied to each Drawdown region, with assumptions on the adoption in 2050: 100 percent adoption in the OECD, 80 percent everywhere else. These were summed to get the global adoption.
First costs for building automation were estimated at US$6.93  per square meter, based on 20 data points. Cost data for the conventional pneumatic control was very limited, so first costs were estimated by taking the ratio of the cost of upgrading a heating, ventilation, and air conditioning (HVAC) system with a pneumatic control to one with a direct digital control. This ratio (64 percent) was then applied to the BAS first cost to estimate the conventional first cost. Operating costs as well as emissions included: building heating and cooling energy (fuel and electricity), and other electricity use. Fuel and electricity prices were averaged over the ten years prior to the base year, and emissions factors were obtained from Intergovernmental Panel on Climate Change (IPCC) guidelines.
Drawdown’s building automation solution was integrated with others in the Buildings and Cities Sector by first prioritizing the solutions according to the point of impact on building energy usage. This meant that building envelope solutions were first, building applications like HVAC were second, and building systems were last. Thus, the building automation energy saving potential was reduced to represent the prior energy savings of higher-priority solutions.
Project Drawdown’s Plausible Scenario adoption of building automation avoids over 4.6 gigatons of carbon dioxide-equivalent greenhouse gas emissions by 2050. In addition, implementing BAS across the commercial building stock requires only a marginal investment of US$68 billion more than the Reference Scenario, but saves over US$881 billion in operating costs over 2020-2050. The Drawdown Scenario shows 9.1 gigatons avoided. In the Optimum Scenario, the emissions reduction is only slightly higher at 9.3 gigatons, owing to the low estimated building stock in Latin America, Africa and the Middle East, and Eastern Europe.
Based on both the financial and climate benefits of accelerated adoption of BAS across the commercial building sector, it seems that this solution can play a significant role in emissions mitigation while yielding savings for building owners. The high upfront costs of BAS, as well as the complexity of building systems and the lack of standardization for control approaches, have been barriers to the implementation of these systems beyond the large commercial buildings in the US and EU. But trends in automation and the growth of the Internet of Things, which connects many building devices, can accelerate adoption of BAS across the global commercial building stock by making smaller systems more cost-effective. This can improve the business case for smaller building owners as well as for those in developing countries.
 For more on the Total Addressable Market for the Buildings and Cities Sector, click the Sector Summary: Buildings and Cities link below.
 Current adoption is defined as the amount of functional demand supplied by the solution in the base year of study. This study uses 2014 as the base year due to the availability of global adoption data for all Project Drawdown solutions evaluated.
 The US EIA’s Commercial Building Energy Consumption Survey (CBECS), BSRIA Consultancy and the Pacific Northwest National Laboratory (PNNL).
 To learn more about Project Drawdown’s three growth scenarios, click the Scenarios link below. For information on Buildings and Cities Sector-specific scenarios, click the Sector Summary: Buildings and Cities link.
 All monetary values are presented in US2014$.
 For more on Project Drawdown’s Buildings and Cities Sector integration model, click the Sector Summary: Buildings and Cities link below.
Full models and technical reports coming in late 2017.