Many urban health outcomes are shaped by environmental stressors that occur together rather than in isolation, yet methods for measuring such co-occurrence at the neighbourhood scale remain underdeveloped. We developed a multi-metric framework for joint co-exposure assessment and applied it to characterise the joint spatial distribution of summer surface heat and fine particulate matter (PM2.5) across 42,304 census tracts in 48 large US metropolitan areas during summers 2015 to 2020, covering approximately 174.6 million residents. The framework combines a composite co-exposure index, a joint exceedance indicator, a conditional exceedance ratio that compares observed joint occurrence to within-group statistical independence, and an upper tail dependence parameter estimated using both the non-parametric Caperaa-Fougeres-Genest estimator and a Gumbel copula, with bias-corrected and accelerated (BCa) confidence intervals obtained from a 5,000-replicate metropolitan-area block bootstrap. Among residents of predominantly Black tracts, 13.21% lived in neighbourhoods that simultaneously exceeded the within-metropolitan-area 80th percentile for both heat and PM2.5, compared with 3.33% of residents of predominantly White tracts; the corresponding heat-only and PM2.5-only ratios were 2.88 and 2.48. Residents of Home Owners Loan Corporation grade D tracts had 3.97 times the odds (95% confidence interval 2.79 to 5.66) of joint hotspot residence compared with grade A residents after adjustment for contemporary tract racial composition, poverty, renter-occupancy, and pre-1960 housing. The within-group conditional exceedance ratio at the 80th percentile was 2.29 in predominantly White tracts (95% BCa CI 1.81 to 2.78), 1.27 in predominantly Black tracts (0.71 to 1.56), and 1.13 in predominantly Hispanic tracts (0.70 to 1.41); the White interval excluded one while the Black and Hispanic intervals included one, which we interpret as power-limited given fewer contributing CBSAs. Magnitudes attenuated under near-surface air temperature surfaces but the direction and statistical significance of the primary findings were preserved. The framework is portable to other compound-exposure questions and supports cumulative-impact assessment.