Buildings and Cities

Introduction

Dense urban human settlement – the cities of the world and the buildings and infrastructure that comprise them – account for a significant percentage of human energy use, mostly for heating and cooling; ergo, they are a significant source of greenhouse gas emissions. The rapid urbanization of humanity ushered in inefficient design of buildings and infrastructure, and Project Drawdown identified, measured, mapped and modeled several solutions that address the operating inefficiencies of dwelling in and using buildings, and of living in cities.

Solutions

Buildings

For Buildings, 10 solutions were identified (8 of which were modeled) as listed here:

Building automation – through controls and sensors, automation systems turn appliances and other energy uses on and off according to need and use, increasing utilization and reducing space heating and cooling waste.

Green roofs (cool roofs and green roofs) – cool roofs reflect solar radiation and reduce air temperature, which leads to reduction in cooling loads. Green roofs have a similar effect as well as reducing heating loads in regions of high heat demand. Collectively, green roofs mitigate carbon emissions by reducing fossil fuel use in heating and cooling.

Heat pumps – high efficiency heat pump systems are radically more efficient than conventional HVAC systems. The use of heat pumps reduces building heating and cooling loads.

Insulation – insulating building envelopes reduces space heating and cooling loads, which in turn mitigates carbon emissions.

LED lighting (commercial) – replacing conventional lighting solutions (bulbs, ballasts and systems) with more efficient commercial light-emitting diodes.

LED lighting (household) – replacing conventional lighting solutions (bulbs) with more efficient household light-emitting diodes.

Net zero buildings – not counted/calculated - composite

Retrofitting – not counted/calculated – composite

Smart glass – specially designed glass that can be implemented in buildings to control the infiltration and emissions of solar radiation, leading to reductions in space heating and cooling loads which, in turn, mitigate carbon emissions.

Smart thermostats – internet-connected devices in households that reduce the heating and cooling demand of homes by using sensors and intelligent settings to maintain building comfort.

Additionally, Project Drawdown modeled another key solution that depends on and interacts with buildings, but is categorized in the Energy Sector.

Solar hot water – the use of solar radiation to pre-heat or heat water for residential and commercial use within buildings, which reduces the need for conventional fossil fuel-based water heating.

Cities

Five additional solutions were studied and modeled for Cities, as listed here:

Bike infrastructure – modifying or augmenting urban right of ways to have specific infrastructure reserved for bicycle commuting and segregated physically or by marking from car and pedestrian right of ways.

District heating – centralized heating systems and distribution of generated heat to the buildings of a defined community, through a network of buried piped, to satisfy the demand for space and water heating.

Landfill methane – capturing methane generated from anaerobic digestion of municipal solid waste in landfills and incinerating the captured biogas to generate electricity, reducing the need for fossil fuel-powered electricity production and associated emissions.

Walkable cities – designing and retrofitting urban environments to encourage walking for commute or transportation, thereby reducing transportation via internal combustion engine powered vehicles and their associated emissions.

Water distribution – reducing water leakage or oversupply of regional water, which reduces pumping and pressurization electricity, which, in turn, reduces greenhouse gas emissions.

Methodology and Integration

Modeling Methodology

Each solution in the Buildings and Cities Sector was modeled individually, and then integration was performed to ensure consistency across the sector and with the other sectors. Information gathered and data collected were used to develop solution-specific models that evaluate the potential financial and emission-reduction impacts of each solution when adopted globally from 2020-2050. Models compare a Reference Scenario that assumes current adoption remains at a constant percent of current electricity generation, with high adoption scenarios assuming a reasonably vigorous global adoption path. In doing so, the results reflect the full impact of the solution, i.e. the total 30-year impact of adoption when scaled beyond the solution’s current status.

Figure 1: Project Drawdown Buildings Solutions and Cluster Schematic

Total Addressable Market

Buildings solutions that impact the building envelope were developed with shared assumptions and similar market constructions from common datasets such as the Global Building Performance Network and the IEA. These solutions include insulation, green roofs, and smart glass. Other Buildings solutions, specifically district heating, were classified as systems solutions. These solutions, along with appliance solutions such as heat pumps, building automation, and smart thermostats, needed to be segregated into the commercial or residential building stock markets (or both), as that distinction has consequences for which space heating and cooling variables and inputs were used in modeling. LED lighting, which is classified as appliances but correlated with the market for lumens instead of heating and cooling, also needed to be modeled considering commercial and household markets. Bike infrastructure and walkable cities were modeled using a Transport Sector approach: forecasting modal shifting in transportation behavior (in this case within cities). Landfill methane was modeled using a forecast of municipal solid waste going to landfills of a dynamic fractionation: the degradable carbon content that would be anaerobically broken down was measured, and assumptions were made as to when and what portion of resultant methane could and would be captured and combusted for electricity generation.

Adoption Scenarios

Three scenarios were developed:

• Plausible Scenario: this scenario represents incremental growth of the solutions along medium best fit adoption projections, using a variety of data sets extrapolated from several data points and literature sources. Each solution has specific boundaries and assumptions which constrain the projection. For building heating and cooling-related solutions, the Plausible Scenario most closely tracks the difference between the International Energy Agency (IEA)’s 6°C Scenario and 2°C Scenario.
• Drawdown Scenario: this scenario is optimized to reach drawdown by 2050 using more ambitious projections from existing sources. E.g., for Buildings solutions related to heating and cooling, the Drawdown Scenario tracks slightly ahead of the IEA 2°C Scenario for most solutions.
• Optimum Scenario: this scenario represents the most optimistic case, where humanity achieves nearly a net-zero built environment by 2050.

Many of the Buildings solutions interact with each other in determining the total impact of any one solution on space heating and cooling mitigation or efficiency. These interactions were handled through an integration process.

Integration

Not all the solutions in the Buildings and Cities Sector are subject to significant integration effects. The Buildings and Cities solutions require an integration analysis to avoid double counting, as they primarily relate to either reducing demand for space heating and cooling (for residential and/or commercial buildings), commercial lighting, or water heating. Certain solutions deal more with the building envelope, and these needed to be assessed first as they are in some cases relatively low cost with immediately measurable benefits. Other solutions impact the delivery of heating and cooling as a system or an appliance, which were integrated in that order. Special attention was given to commercial as opposed to residential applications of the solutions.

Buildings Solutions

Integration across the Buildings Sector were addressed through sequential adjustments to the   heating and cooling demand, and lighting markets according to the impact of solutions on the total addressable markets. Solution clusters were identified and integrated according to the following order: building envelope à appliances and systems (i.e. heating & cooling / lighting generation) à controls and system management. Solutions within clusters were given priority based on the assumed ease in adoption for new buildings and retrofits. Integration of the building envelope cluster began with insulation. In the Reference Scenario, exajoules of space heating and cooling was chosen as the market the solutions would address/mitigate. The results from the insulation model were subtracted from the reference case heating and cooling demand forecast. Next, green roofs were integrated by taking the percent of heating and cooling already mitigated by insulation for each year and, with some assumptions, discounting the impact of cool roofs and green roofs (each of which are less effective in overall heating and cooling impact on well-insulated buildings). The same process was followed for smart glass (also a building envelope solution, but with lighting impacts) to derive a post-building envelope integration forecast market/consumption of heating and cooling energy for the built environment (segregated into commercial and residential as needed). This post-integration market was then used as the starting point to subtract the systems and appliance solutions and appropriately discount the impact of solutions that are integrated after the envelope solutions. First, district heating was subtracted, then heat pumps, then building automation (which requires a split of impact between heating and cooling and lighting energy reduction), then smart thermostats.

Separately, the lighting solutions (commercial only) took a similar approach, starting with smart glass (an envelope solution) to discount the impact of LED lighting (commercial), which was subtracted to factor a discounting of the impact on lighting energy of building automation.

Cities Solutions

Cities solutions, except for district heating, are implicated in the integration of other Drawdown sectors. Landfill methane is factored based on the integration of the Materials solutions, and walkable cities and bike infrastructure are integrated in the Transport Sector.

Results

Mitigation Impact

Drawdown’s Buildings and Cities Sector solutions are ranked sixth after Food, Energy, Land Use, Women and Girls, and Materials in their global impact on greenhouse gas emissions mitigation. They are responsible for 5.18 percent of the mitigation impact in the Plausible Scenario (i.e. 54.5 gigatons of carbon dioxide-equivalent greenhouse gases), 5.78 percent in the Drawdown Scenario (83.33 gigatons), and 6.35 percent in the Optimum Scenario (102.41 gigatons).

Figure 2: Mitigation Impact by Sector, 2020-2050 (in Gigatons of Carbon Dioxide-Equivalent)

© 2017 Project Drawdown

Figure 3: Buildings and Cities Sector Plausible Scenario Emissions and Adoption Results, 2020-2050

Looking at individual solutions (Figure 4), one sees that a number of solutions have similar weight in comprising the overall mitigation impact. If combined, LED lighting would be the largest mitigating solution relative to the other solutions in this sector.

Figure 4: Mitigation Impact by Solution, 2020-2050 (in Gigatons of Carbon Dioxide-Equivalent)

© 2017 Project Drawdown

Table 1: Mitigation Impact of Buildings and Cities Sector Solutions in the Three Studied Scenarios

Financial Impact

Adopting the Buildings and Cities solutions in the Plausible Scenario from 2020-2050 would, collectively, cost $4,778 billion and result in a lifetime savings of $17,906 billion.[1] Adopting more efficient design in buildings and cities offers humanity the promise of prodigious financial savings over the long term.

Table 2: Financial Impact of Buildings and Cities Sector Solutions

Sector-Level Benchmarks

Whereas there are a number of studies that report on the impact of the built environment on climate change with reported emissions, and there are some “decarbonization” studies that isolate the mitigation potential of the built environment, many studies use different boundaries and definitions of “built environment,” so direct comparison of those results with Project Drawdown’s results is not always relevant.  Results from the IEA’s Energy Technology Perspectives (ETP, 2016) has both the scope and granularity to be an effective benchmark for the Buildings and Cities Sector of Project Drawdown. 

The IEA forecasts, among other prognostications, energy use and associated emissions with a 6°C Scenario and a 2°C Scenario, where total greenhouse gas concentrations in each scenario are correlated with the radiative forcing mean global temperature warming effect described in the titular numbers (i.e., either 2 degrees warming or 6 degrees warming).  The 6°C Scenario correlated well in many ways to Project Drawdown’s Reference Scenario, which is used to compare to the Plausible Scenario in order to derive the results.  The measured differences between the 6°C and 2°C Scenarios are comparable to the differences between Project Drawdown’s mitigation results for the Reference and Plausible Scenarios.  IEA reports their mitigation results for Buildings with similar, but different clusters than Project Drawdown.  Taking IEA’s results of the difference between 2°C and 6°C for every five years between 2015 and 2050, interpolating those results, and then summing the interpolated year-over-year results provides the following estimated benchmark values for IEA’s Buildings sector and the sub-clusters within that area:

Table 3: Estimated IEA ETP Buildings 6°C-2°C Difference Benchmark Compared to Plausible Scenario

© 2017 Project Drawdown

NOTE: Benchmarks are estimates based on reported data from the IEA, they are not actual values.

Because the 6°C and the Project Drawdown Reference Scenario use different starting points, different prognostications, and different grid emissions factors, we should expect differences.  To further benchmark building envelope solutions related to heating and cooling, and to benchmark lighting solutions, we compared the exajoules of energy saved from solutions that impact commercial heating and cooling and commercial lighting to the differences in exajoules forecast by the IEA for those clusters. 

To account for some of these differences, we subtracted the Plausible Scenario’s integrated energy reductions from insulation, green roofs, smart glass (in part – part of the energy reduction from smart glass impacts space heating and cooling and part impacts lighting), district heating, heat pumps, building automation (in part – part of the energy reduction from building automation impacts space heating and cooling and part impacts lighting), and smart thermostats from the exajoules of end-use energy used year over year from 2020-2050 for the 6°C Scenario, and compared that to the year-over-year exajoules of space heating and cooling end-use energy in the 2°C Scenario.  The results are similar (within 10 percent of each other) until 2046, when the Drawdown Plausible Scenario measures a greater reduction from the 6°C than the 2°C does. The same methodology was used for solutions related to lighting energy use, and the results are similar: within 10 percent variance until 2030 and then within 30 percent variance to 2050. 

Conclusions and Limitations

Conclusions

Readers may be surprised to see Buildings and Cities play a smaller role in the pathway to drawdown than might be expected. This might have much to do with where Project Drawdown has drawn the boundaries for assessment of the sectors. Many other studies include the impact of transitioning the grid to more diversified renewable sources as part of the built environment. In this case, we have allocated that mitigation potential to the Energy Sector.  

Limitations

Many of the solutions lack global adoption prognostications and/or global current adoption values, including insulation and green roofs. Market and adoption forecasts needed to be created and certain assumptions used based on variables selected from peer-reviewed literature.