Bernardi Environmental Risk Index

Our Methodology and Positioning for Natural Disaster Resiliency within Municipal Bond Portfolios

White Paper, April 2026

Created By:

Matt Bernardi
Tom Bernardi
Zach Cronin
Jeremy Williams

Overview
Our firm has developed a proprietary Environmental Risk Index (“ERI” or the “Index”) to both measure and mitigate relative environmental risk within municipal bond portfolios. The Index assesses a county’s exposure to natural disasters and aspects of its financial resiliency – factoring in insurance non-renewal risk. We believe that a municipality’s overall resilience to natural disasters is a function of both this Index and its underlying fiscal health. ERI scores do not independently determine municipal credit risk and are complementary to our internal, single security credit analysis process.

We believe incorporating the Index into our credit analysis process is of growing importance as the cost of natural disasters continues to increase; in 2024, the US incurred approximately $182.7 billion in damages from 27 separate billion-dollar weather related disasters.¹ While the cost of disasters declined in 2025, damages still totaled approximately $115 billion across 23 billion-dollar events.² Based on these figures, the average annual cost of natural disasters has increased by approximately 3.60%-6.10% per year³ – outpacing the 2.40% rate of inflation since 2005.

Stress in the insurance market in particular regions poses a growing risk to municipal credit quality. Constrained coverage availability, rising premiums, and higher deductibles can pressure household and business balance sheets, weakening the local tax base and slowing post-disaster economic recovery. Non-renewal rates are especially alarming and deteriorating insurance conditions often signal increasing levels of underinsurance. This can materially impede rebuilding efforts and prolong fiscal strain on state and local governments following a disaster.

Lastly, the importance of measuring natural disaster risk and resiliency is further intensified by the potential for waning federal support for disaster recovery and a ballooning federal debt load. These factors could place significant fiscal pressure on state and local governments during future rebuilding efforts. A lack of federal support may also temper the pace of post-disaster economic recovery, straining tax revenues. It is important to note that the Index is a backward looking tool based on historical data, not a predictor of future events. Our primary data sources are FEMA’s National Risk Index4 and a Senate Budget Committee report5 on insurance non-renewal rates. The ERI score ranges from 0 (lowest risk) to 10 (highest risk).

Average State ERI

0.67

4.17

1 https://coast.noaa.gov/states/stories/
2 https://www.climatecentral.org/climate-matters/2025-in-review/
3 This data is sourced from the National Oceanic and Atmospheric Administration (NOAA), which only covers events with at least $1 billion in damages. The annual growth rate is based on their average data from 2005-2015 vs. the 2024 and 2025 figures. This data can be found here: https://www.ncei.noaa.gov/access/billions/summary-stats/US/2000-2010. These calculations deserve a caveat, in that though the growth of the cost of natural disasters has outpaced inflation, this NOAA-based data could be biased towards a higher relative growth rate. Given the price level has increased drastically due to inflation, it is more likely a billion dollar event will occur today than ten, let alone, twenty years ago. As the value of property increases, so does the probability of billion dollar events used in NOAA’s data.
4 https://www.fema.gov/sites/default/files/documents/fema_national-risk-index_technical-documentation.pdf
5 https://www.budget.senate.gov/imo/media/doc/next_to_fall_the_climate-driven_insurance_crisis_is_here__and_getting_worse.pdf

Bernardi Environmental Risk Index Findings

ERI National Average of States: 2.48 Below is the average ERI score, by state, calculated by averaging the scores of all counties within the given state. According to the Index, Florida leads the nation in environmental risk followed by Oklahoma, Arizona, California, and Hawaii. These five states represent the highest risk levels according to our blended Index of environmental risk and insurance non-renewal rates. Notably, Midwestern states – led by Michigan, Wisconsin, Ohio, Indiana – generally have lower Index scores (less risk), averaging a score of 1.82.⁶

Rank	State	Average ERI
1	FL	4.17
2	OK	4.11
3	AZ	3.93
4	CA	3.82
5	HI	3.77
6	DE	3.68
7	NV	3.42
8	NJ	3.33
9	SC	3.19
10	MA	3.16
11	CT	3.13
12	RI	3.13
13	TX	3.04
14	KS	3.04
15	MD	3.02
16	ID	2.98

6 Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin

Rank	State	Average ERI
17	NM	2.97
18	ME	2.96
19	LA	2.95
20	NC	2.89
21	UT	2.81
22	CO	2.74
23	AL	2.57
24	WY	2.52
25	AR	2.41
26	MS	2.39
27	NE	2.33
28	GA	2.33
29	MO	2.29
30	IA	2.15
31	SD	2.15
32	VA	2.15
33	OR	2.12
34	NH	2.07
35	IL	1.89
36	MT	1.78
37	MN	1.78
38	KY	1.78
39	NY	1.73
40	WA	1.70
41	AK	1.70
42	PA	1.68
43	TN	1.67
44	IN	1.62
45	ND	1.59
46	OH	1.38
47	WV	1.28
48	VT	1.15
49	WI	1.05
50	MI	0.67

Coastal and Gulf states consistently show elevated ERI values, primarily driven by hurricanes, coastal flooding, and riverine flooding. These regions not only face frequent hazards but are susceptible to compounding risks from sea level rise and increasing storm severity. In the interior western states and Pacific region, wildfire, drought conditions, and seismic activity drive higher ERI scores, where destructive storm potential is most prevalent. Counties with the highest ERI scores are concentrated in Southern California, the interior western states, and Oklahoma, with additional hot spots along the coastlines of North Carolina, Louisiana, and Florida.

The western United States exhibits a distinct risk profile, with elevated ERI scores largely driven by wildfires, earthquakes, and drought conditions. Counties in California, Oregon, and Washington face the highest exposure to earthquake and wildfire hazards, while mountain and arid Bernardi ERI | 5 regions are more susceptible to drought and fire frequency. Northern states deal primarily with winter storms and cold waves, though these events typically carry lower destructive potential than high-consequence hazards such as wildfires, tornadoes, and hurricanes.

Bottom Five | States with Highest ERI Score

Rank	State	Average ERI	Key Considerations
1	FL	4.17	High hurricane frequencies in coastal counties Highest insurance non-renewal rate
2	OK	4.11	Multiple hazards specifically tornado, hail, drought, and flooding Ranked 5th in insurance non-renewals
3	AZ	3.93	Multiple hazards with elevated frequency including wildfire, drought, heat wave, riverine flooding
4	CA	3.82	Ranked 3rd in insurance non-renewals Prevalence of hazards including wildfire, drought, heat wave, earthquake, flooding
5	HI	3.77	Multiple hazards with elevated frequency including volcanic and tsunami activity, as well as earthquake and flooding. Ranked 14th in insurance non-renewals

Top Five \| States with Lowest ERI Score
Rank	State	Average ERI	Key Considerations
46	OH	1.38	Ranked 23rd in insurance non-renewal Less frequent severe hazards
47	WV	1.28	Ranked 47th in insurance non-renewals Less frequent severe hazards
48	VT	1.15	Ranked 36th in insurance non-renewals Less frequent severe hazards
49	WI	1.05	Ranked 40th in insurance non-renewals Less frequent severe hazards
50	MI	0.67	Ranked 41st in insurance non-renewals

ERI National Average of all Counties: 2.34
Our analysis attributed an ERI score to 3,147 counties in the United States, with a national county-level average score of 2.34. The charts below show the twenty-five highest and lowest rankings by county. The higher the number, the more risk the county has within the ERI Index.

It is important these values are interpreted correctly. ERI scores are min-max normalized, and nonlinear. This means the scale is ordinal rather than ratio-based. For example, a score of 6.0 does not represent twice the risk as a score of 3.0. Instead, a higher score indicates higher rates of insurance non-renewals, more potential hazards, more frequency, or both. Furthermore, these scores are not probabilistic and should not be used to calculate the likelihood of a specific event in a given year.

Highest ERI Scores
State	County	ERI
CA	San Bernardino	10.00
CA	San Diego	10.00
CA	Riverside	10.00
ID	Twin Falls	8.37
ID	Elmore	7.82
CO	Weld	7.82
OK	Pittsburg	7.12
NC	Carteret	6.90
AK	Aleutians West	6.81
FL	Collier	6.53
UT	Washington	6.51
CA	Los Angeles	6.49
CO	Washington	6.47
NV	Elko	6.47
LA	St. Bernard	6.43
OK	Haskell	6.38
FL	Palm Beach	6.37
OK	Latimer	6.37
OK	Osage	6.31
SC	Charleston	6.28
OK	LeFlore	6.27
FL	Hendry	6.25
AZ	Mohave	6.20
CA	Ventura	6.14
NV	Humboldt	6.14

Highest ERI Scores
State	County	ERI
CA	San Bernardino	10.00
CA	San Diego	10.00
CA	Riverside	10.00
ID	Twin Falls	8.37
ID	Elmore	7.82
CO	Weld	7.82
OK	Pittsburg	7.12
NC	Carteret	6.90
AK	Aleutians West	6.81
FL	Collier	6.53
UT	Washington	6.51
CA	Los Angeles	6.49
CO	Washington	6.47
NV	Elko	6.47
LA	St. Bernard	6.43
OK	Haskell	6.38
FL	Palm Beach	6.37
OK	Latimer	6.37
OK	Osage	6.31
SC	Charleston	6.28
OK	LeFlore	6.27
FL	Hendry	6.25
AZ	Mohave	6.20
CA	Ventura	6.14
NV	Humboldt	6.14

Property Insurance Policy Non-Renewal Rates Across the Country

Not surprisingly, insurance market stress is emerging in regions with the highest environmental risk. In 2023, county-level non-renewal rates spiked in parts of Florida and North Carolina, led by Glades County, FL (16.2%), aptly named Dare County, NC (12.9%), and Washington County, NC (12.2%). As shown in the tables below, several additional coastal counties in North Carolina and Florida recorded non-renewal rates in the 9–11% range. Smaller, yet significant, clusters also appeared in pockets in Massachusetts and California. The correlation between high ERI scores and elevated non-renewal rates underscores the compounding challenge: the dual pressure of rising hazard severity and declining insurance availability (or surging premiums making insurance cost prohibitive) in the most exposed counties.

Our ERI takes this into account if the insurance non-renewal for a specific county is higher than the national average. As a result, the ERI score is assigned a 10% penalty.

Average National Insurance Non-Renewal Rate: 1.17%

Rank	State7	Average Non-Renewal
1	FL	3.24%
2	NC	2.81%
3	CA	2.65%
4	MA	2.61%
5	OK	2.40%
6	NM	1.57%
7	LA	1.55%
8	SD	1.47%
9	RI	1.47%
10	MS	1.37%
11	NE	1.35%
12	CO	1.24%
13	CT	1.22%
14	HI	1.20%
15	KS	1.17%
16	ID	1.17%
17	SC	1.16%
18	IA	1.16%
19	UT	1.14%
20	ND	1.12%
21	MO	1.09%
22	TX	1.02%
23	OH	0.97%
24	TN	0.97%
25	NV	0.96%

Rank	State	Average Non-Renewal
26	GA	0.96%
27	IN	0.96%
28	AR	0.95%
29	MT	0.94%
30	VA	0.94%
31	KY	0.93%
32	AL	0.92%
33	AZ	0.89%
34	WA	0.89%
35	OR	0.88%
36	VT	0.87%
37	WY	0.86%
38	IL	0.83%
39	NJ	0.81%
40	WI	0.78%
41	MI	0.75%
42	WV	0.74%
43	DE	0.73%
44	NH	0.67%
45	MD	0.66%
46	ME	0.63%
47	NY	0.50%
48	AK	0.47%
49	PA	0.44%
50	MN	0.41%

Rising non-renewal rates indicate insurers’ growing reluctance to underwrite natural disaster risk, reflecting their internal assessments of heightened disaster frequency and severity. This has also led to a surge in insurance premiums which creates a challenging environment where even if coverage is available, it has become increasingly cost prohibitive. Declining insurance coverage increases the potential for financial stress following a disaster and likely indicates constituents are under insured on a broader scale. Declining insurance availability and affordability materially reduce the attractiveness of these locations for both existing residents and prospective taxpayers .

FEMA Risk Index Shortfalls in Measuring Natural Disaster Risk & Resiliency

FEMA provides highly granular, county-level data on natural disaster risk, which serves as the foundational input to our Index. This data plays a critical role in enhancing the public’s understanding of disaster exposure across the United States. We hope FEMA continues to measure and maintain this data over long time horizons, as it will enable deeper analysis and more informed risk assessments of environment and financial risk over time. From a municipal credit perspective, however, the FEMA framework requires refinement. The FEMA National Risk Index incorporates an economic value component, that systematically assigns higher risk scores to larger and more economically valuable counties. While this construction is intuitive from a damage-estimation standpoint – higher concentrations of economic assets imply greater absolute potential losses – it can be misleading when applied to municipal credit analysis, in our opinion.

In our view, retaining the economic value input misrepresents credit risk and distorts relative risk rankings among municipal obligors.

When evaluated through the lens of municipal credit risk, this approach conflates exposure with credit vulnerability. Higher economic value is frequently associated with larger, more diversified, and economically dynamic jurisdictions. These characteristics are not weaknesses from a credit standpoint; rather, they are key drivers of fiscal resilience. In addition, larger counties tend to have broader geographic footprints, allowing disaster impacts to be absorbed across a wider economic base. These characteristics enhance resilience and support a municipality’s ability to recover from the damage of a natural disaster. To better align the index with municipal credit fundamentals, we removed the economic value component of FEMA’s National Risk Index and rely exclusively on FEMA’s natural disaster probability variable. In our view, retaining the economic value input misrepresents credit risk and distorts relative risk rankings among municipal obligors. In the context of municipal credit analysis, higher underlying economic value is more appropriately interpreted as an indicator of resilience, for several reasons: • Greater aggregate wealth enhances a jurisdiction’s capacity to levy taxes or fees to finance disaster recovery and maintain essential operations • Wealthier jurisdictions typically exhibit broader economic and revenue diversification, reducing reliance on any single industry or taxpayer, which improves shock absorption. Bernardi ERI | 10 • Larger, economically significant regions carry heightened national and regional importance, increasing the likelihood of federal or state assistance after a major disaster. • Higher economic value often reflects entrenched commercial activity, strategic location, or natural advantages that support faster and more durable post-disaster recovery. Conversely, smaller and less wealthy obligors generally operate with narrower and more concentrated economic footprints. In these cases, disaster damage is more likely to impair a materially larger share of the tax base, resulting in disproportionate fiscal stress, weaker recovery capacity, and elevated credit risk. This distinction is illustrated by recent California wildfire events. The 2025 Los Angeles–area wildfires were geographically extensive and economically destructive, with estimated losses in the tens to hundreds of billions of dollars. While these events created near-term fiscal pressure on the City of Los Angeles and surrounding jurisdictions, the region’s scale, wealth, and highly diversified revenue base materially enhanced its capacity to absorb losses and fund recovery costs over time. By contrast, the 2018 Camp Fire in Paradise, California destroyed approximately 95% of the town’s structures, effectively eliminating most of its economic base. Although the absolute dollar losses were significantly lower than those incurred in Los Angeles, the proportional economic and fiscal impact on Paradise was far more severe, resulting in substantially higher credit impairment. This comparison underscores why absolute economic damage is an insufficient proxy for municipal credit risk, and why isolating disaster probability—rather than asset value— provides a more analytically sound framework for evaluating long-term municipal resilience and creditworthiness. Any environmental score, however, must be paired with a fiscally oriented credit assessment to fully evaluate an obligor’s overall credit quality and financial resilience. Removing the wealth variable in FEMA’s risk framework materially alters the relative risk ranking. For example, this change moves Los Angeles down from the riskiest county in the FEMA National Risk Index to the ERI’s 12th riskiest. Of the top ten riskiest ERI scored counties, the average population8 is 883,861 with a median of 209,514 vs. FEMA’s average population of 3,213,614 and median of 2,299,920. These differences illustrate how the ERI partly mitigates the size and wealth bias embedded in FEMA’s index, resulting in a more appropriate assessment of natural disaster risk for municipal credit analysis.

1	CA	San Bernardino	10.00
2	CA	San Diego	10.00
3	CA	Riverside	10.00
4	ID	Twin Falls	8.37
5	ID	Elmore	7.82
6	CO	Weld	7.82
7	OK	Pittsburg	7.12
8	NC	Carteret	6.90
9	AK	Aleutians West	6.81
10	FL	Collier	6.53
11	UT	Washington	6.51
12	CA	Los Angeles	6.49
13	CO	Washington	6.47
14	NV	Elko	6.47
15	LA	St. Bernard	6.43
16	OK	Haskell	6.38
17	FL	Palm Beach	6.37
18	OK	Latimer	6.37
19	OK	Osage	6.31
20	SC	Charleston	6.28
21	OK	Le Flore	6.27
22	FL	Hendry	6.25
23	AZ	Mohave	6.20
24	CA	Ventura	6.14
25	NV	Humboldt	6.14

1	CA	Los Angeles	100.00
2	TX	Harris	99.97
3	CA	Riverside	99.94
4	CA	San Bernardino	99.90
5	CA	Alameda	99.87
6	CA	Santa Clara	99.84
7	FL	Miami-Dade	99.81
8	CA	Orange	99.78
9	FL	Broward	99.75
10	FL	Palm Beach	99.71
11	CA	San Diego	99.68
12	WA	King	99.65
13	IL	Cook	99.62
14	CA	Contra Costa	99.59
15	FL	Hillsborough	99.55
16	TX	Galveston	99.52
17	FL	Lee	99.49
18	SC	Charleston	99.46
19	CA	Ventura	99.43
20	CA	Santa Barbara	99.40
21	FL	Brevard	99.36
22	CA	San Mateo	99.33
23	NV	Clark	99.30
24	TX	Collin	99.27
25	TN	Shelby	99.24

Each scoring framework will inherently attribute more risk to larger counties given the increased chance of a natural disaster due to their larger size. Furthermore, there is an increased risk multiple disasters could occur in a larger land mass vs. smaller. Los Angeles County, CA is nearly 2.5x larger than Butte County, CA (location of the Camp Fire) and geographically more exposed to more risks. It has more coastal flooding, drought, earthquake, heatwave, landslide, riverine flooding, wind, tornado, tsunami, and wildfire risk due to its location and size. Therefore, before any weights are ascribed to disaster risk, Los Angeles County is going to have a higher risk score. Cook County presents another great example of a county that is unfairly penalized by FEMA for its wealth and size. It is ranked as the 13th riskiest county within the FEMA risk framework. Within the Bernardi ERI, Cook is ranked the 4th riskiest among all State of Illinois counties, and 704th nationwide. Within Illinois, the counties of Alexander, Jackson, and White all rank higher (riskier) within our ERI framework. The table below presents the twenty-five counties with the highest risk according to the ERI and FEMA Index. For each county, the table also shows its ranking under the other index and the difference between the two rankings. This difference is reported in the fifth column of each Bernardi ERI | 12 section. A higher ranking indicates greater assessed risk under the respective index. You will see significant risk ranking differences between the two indexes. This is primarily due to the ERI removing the size/wealth factor which FEMA incorporates. Generally, larger counties score higher (riskier) within the FEMA rankings vs. the ERI. Twelve different states are represented in the ERI’s top twenty-five riskiest counties, while FEMA has only eight. The median population of the ERI top twenty-five riskiest counties is 70,400 vs. 1,080,000 for FEMA’s top twenty-five.

Evaluating an obligor’s exposure to natural disaster risk requires analysis beyond the headline ERI score. This is particularly important for large counties, where a single county-level score may mask meaningful variation among the dozens—or even hundreds—of underlying municipal obligors within its boundaries. In addition to assessing an issuer’s distinct financial and management profile, investors should incorporate more granular hazard indicators – such as wildfire risk maps and floodplain data – to form a more complete view of natural disaster risk
San Diego County’s wildfire risk is one example of why any headline score requires closer examination. San Diego County scores the highest risk (10) within our framework, but given the multitude of municipalities located within the county and disparate risk, a deeper analysis is required.
Fire hazard maps help narrow down intra-county risk. We primarily utilize the CAL FIRE – Fire Hazard Severity Zone maps to address fire risk. The Fire Hazard Severity Zone classifies area as moderate, high, and very high fire risk. See below from CAL FIRE:

PUBLIC RESOURCE CODE 4202; THE STATE FIRE MARSHAL SHALL CLASSIFY LANDS WITHIN STATE RESPONSIBILITY AREAS INTO FIRE HAZARD SEVERITY ZONES. EACH ZONE SHALL EMBRACE RELATIVELY HOMOGENEOUS LANDS AND SHALL BE BASED ON FUEL LOADING, SLOPE, FIRE WEATHER, AND OTHER RELEVANT FACTORS PRESENT, INCLUDING AREAS WHERE WINDS HAVE BEEN IDENTIFIED BY THE DEPARTMENT AS A MAJOR CAUSE OF WILDFIRE SPREAD. GOVERNMENT CODE 51178; THE STATE FIRE MARSHAL SHALL IDENTIFY AREAS IN THE STATE AS MODERATE, HIGH, AND VERY HIGH FIRE HAZARD SEVERITY ZONES BASED ON CONSISTENT STATEWIDE CRITERIA AND BASED ON THE SEVERITY OF FIRE HAZARD THAT IS EXPECTED TO PREVAIL IN THOSE AREAS. MODERATE, HIGH, AND VERY HIGH FIRE HAZARD SEVERITY ZONES SHALL BE BASED ON FUEL LOADING, SLOPE, FIRE WEATHER, AND OTHER RELEVANT FACTORS INCLUDING AREAS WHERE WINDS HAVE BEEN IDENTIFIED BY THE OFFICE OF THE STATE FIRE MARSHAL AS A MAJOR CAUSE OF WILDFIRE SPREAD.9

Bernardi Environmental Risk Index

Our Methodology and Positioning for Natural Disaster Resiliency within Municipal Bond Portfolios

US state heat map of Average ERI scores, ranging from green (low) through yellow and orange to red (high)

Bernardi Environmental Risk Index Findings