Methodology - Asset-Specific Vulnerability Framework (2/2)

An asset's financial exposure to a climate hazard is a function of its specific physical characteristics and operational purpose. For example, a sustained period of extreme heat will have a profoundly different financial consequence for a data center, which relies on constant, energy-intensive cooling, than it will for a transportation bridge. To quantify these differences, we use an Asset Sensitivity Matrix.

The coefficients in the matrix are on a 0-to-5 scale, representing the degree to which an asset's financial performance is sensitive to the climate drivers for a given metric. A higher score indicates a more pronounced financial impact.

Asset Type	Maintenance Increase	Operational Downtime	Efficiency Loss	Additional CapEx (Retrofit)	Climate-Adjusted Discount Rate	Insurance Premium Increase	Insurability Index	Utility Demand Increase
Residential Buildings	3	2	1	3	2	4	3	5
Commercial Buildings	4	3	2	4	3	4	3	5
Power Plants	4	4	5	4	4	4	3	1
Electricity T&D	4	4	4	4	4	4	3	0
Water & Wastewater	4	5	3	5	3	3	3	1
Transport (Road & Rail)	5	3	1	4	2	2	1	0
Airports	4	4	3	5	4	4	4	2
Seaports	5	5	2	5	4	5	5	1
Data Centers	4	5	5	4	5	5	4	5

Illustrative Example: Data Center Maintenance Increase

This matrix is used to scale the baseline, geography-only metrics. This two-layer process provides a more accurate and actionable financial risk estimate.

• Step 1: Calculate Baseline Metric. Based on climate projections for a location, the geography-based model calculates a baseline Maint_Increase of 3.0%.

• Step 2: Identify Asset Type and Sensitivity Score. The asset is a "Data Center." We consult the matrix and find the sensitivity score for "Maintenance Increase" is 4 (High).

• Step 3: Apply Sensitivity Coefficient. The score of 4 is converted into a multiplier. Using an illustrative scaling factor of , the calculation is 1 + (4 × 0.25) = 2.0. The resulting multiplier is 2.0x.

• Step 4: Calculate Final Asset-Specific Impact. The baseline metric is multiplied by the sensitivity-derived scaling factor: Final_Maint_Increase = 3.0% × 2.0 = 6.0%.

Methodological Limitations

The two-layer framework presented in this document is designed to balance scientific rigor with scalability and transparency. However, like any model, it involves certain trade-offs and limitations that users should understand. The most significant methodological choice is the application of Sensitivity Coefficients at the aggregate metric level, rather than at the level of each underlying climate feature or risk component.

For example, the Maintenance Increase metric is calculated from five climate features (heat, humidity, etc.). Our framework calculates a single, blended Maintenance Increase score for a location and then applies one sensitivity coefficient to that total score for a given asset.

An alternative, more granular approach would be to develop a unique sensitivity coefficient for each asset against each of the five climate features. In this hypothetical approach, a "Seaport" might have an extreme sensitivity to humidity (corrosion) but a low sensitivity to freeze-thaw cycles, whereas for "Transport (Road & Rail)" the opposite might be true.

While a more granular, component-level model appears more precise, we have chosen the aggregate approach for three key reasons:

• Scalability and Transparency: A component-level approach would create a combinatorial explosion of coefficients (hundreds), rendering the model opaque and impractical to scale. The current 9x8 matrix is transparent and manageable.

• Avoiding False Precision: Defining and defending hundreds of micro-level coefficients could introduce more error and uncertainty than it resolves, as the required data often does not exist.

• Maintaining Clear Directionality: The current framework provides clear, defensible insights (e.g., "Data Centers have an extreme sensitivity to efficiency loss"). A component-level approach risks obscuring this primary insight in a sea of complexity.

The primary limitation is that this simplification may mask nuance in cases where an asset has extreme and opposing sensitivities to different components of a single metric. In cases where an asset has a truly extreme and opposing sensitivity to different components of a single metric, this simplification may mask some nuance. However, we contend that this is a necessary and justifiable trade-off to create a model that is robust, explainable, and fit for the purpose of strategic financial decision-making.

Appendix: Rationale for Sensitivity Coefficients

This appendix provides the summarized, evidence-based justification for each coefficient in the Asset Sensitivity Matrix.

A.1 Residential Buildings

• Maintenance Increase (3 - Moderate): Accelerated degradation of roofing, sealants, and concrete from heat, humidity, and freeze-thaw cycles.

• Operational Downtime (2 - Low): Temporary displacement of occupants is driven by acute events like severe floods or power outages.

• Efficiency Loss (1 - Very Low): Metric for productive output is not directly applicable to residential shelter.

• Additional CapEx (3 - Moderate): Material costs for upgrades like improved insulation or elevating structures.

• Discount Rate (2 - Low): Risk is typically reflected in insurance costs and property values rather than a direct discount rate adjustment.

• Insurance Premium Increase (4 - High): A primary financial impact, as insurers aggressively raise premiums in response to rising hazard frequency (wildfire, flood, storm).

• Insurability Index (3 - Moderate): Growing risk of private insurance withdrawal in the most extreme zones.

• Utility Demand Increase (5 - Extreme): A direct, significant financial impact as rising cooling costs (driven by CDD) outweigh savings from reduced heating.

A.2 Commercial Buildings

• Maintenance Increase (4 - High): Complex systems (HVAC, facades) are highly susceptible to degradation from heat and humidity, leading to pronounced financial impact.

• Operational Downtime (3 - Moderate): Translates directly into lost revenue, driven primarily by power outages and flood-related access issues.

• Efficiency Loss (2 - Low): Primarily an indirect cost related to workforce productivity, borne by tenants.

• Additional CapEx (4 - High): Significant investment is driven by market pressure for resilient and "green" buildings (e.g., HVAC upgrades, flood barriers).

• Discount Rate (3 - Moderate): Climate risk is actively being integrated into commercial real estate valuation, supporting a risk premium.

• Insurance Premium Increase (4 - High): A direct and material blow to net operating income (NOI).

• Insurability Index (3 - Moderate): Inability to secure insurance in high-risk zones can render a property un-leasable and un-financeable.

• Utility Demand Increase (5 - Extreme): A direct and exceptionally large impact on operational expenses due to high energy consumption for heating and cooling.

A.3 Power Plants

• Maintenance Increase (4 - High): Mechanical strain on cooling systems and turbines from extreme heat; corrosion from humidity.

• Operational Downtime (4 - High): Forced outages from heatwaves (violating thermal limits), drought (reducing cooling water/hydropower), or storm damage.

• Efficiency Loss (5 - Extreme): A primary impact. Higher ambient temperatures reduce the efficiency of thermal generation cycles, directly cutting power output.

• Additional CapEx (4 - High): Substantial investment needed for upgrading cooling systems, flood defenses, and grid hardening.

• Discount Rate (4 - High): As critical, long-lived infrastructure, their high sensitivity justifies a significant climate risk premium.

• Insurance Premium Increase (4 - High): High-value assets with significant exposure to physical damage from extreme weather (hurricanes, floods, wildfires).

• Insurability Index (3 - Moderate): Growing risk that coverage for specific perils (e.g., coastal flooding) may become unavailable for the most vulnerable assets.

• Utility Demand Increase (1 - Very Low): A plant's internal electricity use is negligible compared to its output.

A.4 Electricity Transmission & Distribution (T&D)

• Maintenance Increase (4 - High): Mechanical fatigue on towers from high winds; catastrophic damage from ice storms; expensive vegetation management to mitigate fire risk.

• Operational Downtime (4 - High): A primary point of failure during extreme weather (lines down from wind/ice, substation flooding); preemptive shutdowns (PSPS) are a form of climate-driven downtime.

• Efficiency Loss (4 - High): A critical, physics-based vulnerability. Higher temperatures increase electrical resistance (line losses) and cause lines to sag, forcing capacity reductions ("derating").

• Additional CapEx (4 - High): Massive investment required to "harden" the grid (e.g., replacing poles, undergrounding lines, using advanced conductors).

• Discount Rate (4 - High): The systemic risk to economic productivity from large-scale outages warrants a significant risk premium.

• Insurance Premium Increase (4 - High): Driven largely by massive liabilities associated with T&D infrastructure starting catastrophic wildfires.

• Insurability Index (3 - Moderate): The market for wildfire liability is hardening, potentially making full coverage challenging.

• Utility Demand Increase (0 - No Sensitivity): Not applicable; T&D infrastructure is a conduit for energy, not a consumer.

A.5 Water & Wastewater Treatment

• Maintenance Increase (4 - High): Physical damage from storms; accelerated sewer corrosion from higher temperatures; more intensive filtration needed due to sediment loads.

• Operational Downtime (5 - Extreme): Extremely high risk of failure from intense rainfall causing massive infiltration and inflow (I&I), overwhelming system capacity and causing overflows (CSOs/SSOs).

• Efficiency Loss (3 - Moderate): Higher source water temperatures can promote algae growth, making water more difficult and costly to treat.

• Additional CapEx (5 - Extreme): Massive investment required to separate combined sewers, increase plant capacity, and build flood barriers for coastal facilities.

• Discount Rate (3 - Moderate): The risk of costly failures and unfunded adaptation liabilities represents a material risk to municipal creditworthiness.

• Insurance Premium Increase (3 - Moderate): Upward pressure on premiums from physical damage and liability risk from overflow events.

• Insurability Index (3 - Moderate): Threat of permanent inundation in high-risk coastal zones may make affordable flood insurance difficult to obtain.

• Utility Demand Increase (1 - Very Low): Energy cost is not primarily driven by the building's heating and cooling needs.

A.6 Transport (Road & Rail)

• Maintenance Increase (5 - Extreme): Extreme heat softens pavement and buckles rails; intense precipitation causes erosion; freeze-thaw cycles are exceptionally destructive to asphalt and concrete.

• Operational Downtime (3 - Moderate): Downtime from localized and temporary road/rail closures due to flooding, landslides, or wildfires.

• Efficiency Loss (1 - Very Low): Not directly applicable to static infrastructure.

• Additional CapEx (4 - High): Enormous investment required to adapt the vast network (e.g., elevating roadways, enlarging culverts, using resilient materials).

• Discount Rate (2 - Low): Typically publicly owned, so not subject to the same market-based valuation pressures.

• Insurance Premium Increase (2 - Low): Most public infrastructure is self-insured by government entities.

• Insurability Index (1 - Very Low): The concept is not a primary risk for publicly self-insured assets.

• Utility Demand Increase (0 - No Sensitivity): Not applicable.

A.7 Airports

• Maintenance Increase (4 - High): Damage to asphalt runways from extreme heat; accelerated wear on terminal HVAC systems.

• Operational Downtime (4 - High): Highly sensitive to weather; downtime (delays/cancellations) from runway flooding, extreme heat preventing takeoff, or wildfire smoke.

• Efficiency Loss (3 - Moderate): Extreme heat reduces air density, forcing aircraft to reduce weight (fewer passengers/cargo), directly cutting economic efficiency.

• Additional CapEx (5 - Extreme): Massive investments required, especially for coastal airports (seawalls, elevating runways) and inland airports (stormwater systems).

• Discount Rate (4 - High): As critical, high-value infrastructure with high exposure, they warrant a significant climate risk premium.

• Insurance Premium Increase (4 - High): Huge concentration of value leads insurers to raise premiums for property damage and business interruption.

• Insurability Index (4 - High): Particularly acute risk; a major coastal airport may find it difficult to obtain full coverage for flood damages.

• Utility Demand Increase (2 - Low): While terminals have significant HVAC needs, the relative sensitivity is lower than for a commercial building.

A.8 Seaports

• Maintenance Increase (5 - Extreme): Constant, intensified assault from the elements; saltwater corrosion of steel and concrete is accelerated by higher tides; heat damages pavements.

• Operational Downtime (5 - Extreme): Primary threat from hurricanes/typhoons forcing port closures for weeks; flooding from storm surge or intense rain also halts all operations.

• Efficiency Loss (2 - Low): Primary functions of heavy equipment are less sensitive to climate variables; major impacts manifest as catastrophic downtime.

• Additional CapEx (5 - Extreme): Monumental expenditures required to defend against sea-level rise and storm surge (e.g., raising wharves, building massive breakwaters).

• Discount Rate (4 - High): Extreme vulnerability and systemic economic importance justify a substantial climate risk premium.

• Insurance Premium Increase (5 - Extreme): At the pinnacle of climate risk for insurers due to location and concentration of value; premiums are extremely sensitive.

• Insurability Index (5 - Extreme): Potential for catastrophic losses strains global insurance capacity; risk of key perils becoming uninsurable is very real.

• Utility Demand Increase (1 - Very Low): Electricity consumption is not primarily driven by building heating/cooling.

A.9 Data Centers

• Maintenance Increase (4 - High): Driven by the constant, heavy load on cooling systems, which work harder as ambient temperatures rise, leading to accelerated wear.

• Operational Downtime (5 - Extreme): Downtime is a catastrophic event, triggered by power grid failures (a critical dependency) or cooling system failure.

• Efficiency Loss (5 - Extreme): A primary measure of efficiency is Power Usage Effectiveness (PUE). Higher ambient temperatures worsen PUE as cooling systems consume more energy.

• Additional CapEx (4 - High): Significant capital required for more efficient cooling systems, physical hardening, and on-site power generation.

• Discount Rate (5 - Extreme): As critical infrastructure for the digital economy with extreme sensitivity to climate, they justify an extreme risk premium.

• Insurance Premium Increase (5 - Extreme): Enormous concentration of value and business interruption risk leads to extreme sensitivity in insurance pricing.

• Insurability Index (4 - High): A challenging class for insurers; facilities in high-risk zones may find it difficult to obtain full, affordable coverage.

• Utility Demand Increase (5 - Extreme): Cooling demand is immense, continuous, and a primary operational cost that increases directly and significantly as CDD rises.