INTRODUCTION:
Air-emissions health assessments often apply uniform baseline incidence rates and one set of exposure–response functions (ERFs) across administrative areas, masking place-based vulnerability shaped by poverty, uneven service access, and concentrated burdens of HIV/TB, cardiometabolic disease, and respiratory illness. In such settings, baseline health is a geography of susceptibility that determines where emissions translate into realised harm and where mitigation yields the largest gains.

METHODS:
We propose a spatially explicit framework to develop an emission vulnerability map. First, we map baseline indicators at ward or facility-catchment scale (respiratory and cardiometabolic burden, HIV/TB burden, service access, and deprivation proxies). Second, we overlay these layers with emissions inventories and/or modeled concentration surfaces from major point sources to create a composite vulnerability index, identify local hotspots, and support prioritisation. The approach separates (a) baseline heterogeneity (local variation in underlying disease burden and health-system access) from (b) effect-estimation uncertainty (choice of relative risks/ERFs, exposure metrics, and co-pollutant confounding). We illustrate implementation using the Medupi–Matimba coal power corridor in Limpopo, South Africa, within a WHO-aligned health impact assessment structure.

RESULTS:
We assess sensitivity of spatial burden estimates to alternative ERFs and relative risks. Differences are most pronounced where updated evidence revises long-term particulate-matter mortality risks and where SO₂ is treated conservatively as an indicator within a broader combustion mixture. Acute morbidity ERFs (e.g., SO₂-related asthma and hospital admissions) reveal hotspots of health-system pressure that align with mapped baseline respiratory vulnerability.

CONCLUSIONS:
Relying on administrative averages can under-identify high-risk communities and misstate distributional benefits of compliance interventions. Combining baseline vulnerability mapping with transparent ERF sensitivity enables equitable decisions, better targeting of emission controls, and identification of health interventions that can mitigate impacts (asthma/COPD management, TB/HIV service continuity, strengthened primary care, screening, and risk communication).