Abstract Black carbon (BC) is an essential short‐lived climate pollutant and a critical component of health‐damaging fine particulate matter (PM 2.5 ), posing significant risks to public health and the climate system. Despite its dual impact, comprehensive assessments of population‐level BC exposure, its associated mortality burden, and its disparities across population subgroups remain limited in India. We used an advanced machine learning algorithm to estimate annual BC mass concentration at a 1‐km × 1‐km spatial scale from 2016 to 2021. Following the global burden of disease (GBD) framework, we integrated the meta‐analysis‐derived risk estimates with demographic and epidemiologic attributes and estimated BC‐attributable all‐cause, cardiovascular disease, and respiratory mortality (per 100,000 population). Further, utilizing the socio‐demographic information from the National Family Health Survey, we assessed the disparity in BC exposure and attributable burden across sub‐populations. Annual population‐weighted BC exposure varied from 0.4 to 13.7 μg/m 3 in India between 2016 and 2021. While BC exposure remained stagnant over the years, its disparity across most demographic subgroups has diminished in recent years. We estimated annual BC‐attributable all‐cause, cardiovascular disease, and respiratory mortality (per 100,000 population) to be 133 (95% uncertainty intervals: 113–155), 7 (5–9), and 9 (5–14), respectively. BC‐attributable mortality was found to be higher among females, other backward classes, and economically deprived subgroups than their demographic counterparts. Our results demonstrate that prioritizing BC emission reduction would improve ambient air quality, result in a larger health benefit (for every unit reduction in concentration), and slow down regional warming, thereby creating a win‐win situation for India.
Gupta et al. (Fri,) studied this question.