Cumulative Burden and Uncertainty in Environmental Justice Screening

Environmental justice screening increasingly relies on indicator-based tools to identify disadvantaged places and to inform permitting, mitigation, and investment. Yet “cumulative burden” is operationalized inconsistently across tools, and modelling choices can materially alter who is flagged, where burdens cluster, and how results are interpreted. A related open question is how cumulative-burden definitions interact with statistical uncertainty across communities, particularly where designations hinge on threshold rules. This study first evaluates how sampling uncertainty in survey-derived socioeconomic indicators affects the designation of overburdened communities and, by extension, the statistical certainty of threshold-based eligibility for funding or regulatory protections. Using margin-of-error information for derived measures, the analysis quantifies when communities are confidently above or below statutory-style cutoffs and identifies an uncertainty zone where designations are sensitive to sampling variability, with the strongest instability expected near thresholds. In a second step, the study assesses cumulative burden across multiple burden categories under alternative screening approaches commonly used in environmental justice tools. Scenario families include indicator- and category-threshold counting as well as index-based aggregation with additive and multiplicative combination rules. A global sensitivity analysis is then used to compare the relative importance of cumulative-burden modelling choices against other core design decisions, clarifying which assumptions most strongly affect rankings and designations. Finally, spatial modelling and machine learning are used to characterize where uncertainty is systematically elevated beyond what population size alone would predict and to identify contextual and demographic correlates of these patterns, supporting an intersectional interpretation of who is most affected by uncertain classifications. Together, the results provide a transparent assessment of how uncertainty and cumulative-burden definitions jointly shape indicator-based environmental justice screening outcomes.