Paulsboro, NJ
Paulsboro wildfire risk explained
Paulsboro sits at the 48th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 2,644 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Paulsboro at the 49th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Paulsboro's building exposure, zone by zone
Most of Paulsboro's buildings (96.6% of 2,644) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How Paulsboro compares
Paulsboro's risk sits at a similar level relative to New Jersey (55th percentile statewide) as it does nationally (48th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Paulsboro ranks 16,270 for wildfire risk (1 is highest) and 6,027 by building count (1 is largest). Within New Jersey alone, it ranks 317 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Paulsboro and the insurance market
Paulsboro's elevated rating (48th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Even with 96.6% of Paulsboro outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Paulsboro's figures come from
Paulsboro's 48th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Paulsboro's dominant minimal exposure actually means, with real examples from across the dataset.