Over 2.8 billion people are chronic ally exposed to hazardous levels offine particulate
matter air pollution. This paper provides novel evidence that workers in such settings
partially adapt to chronic exposure but that adaptation does not offset cumulative harm.
We estimate the effect of PM2.5 on labor productivity using individual-level performance
data from 14 years of professional cricket in India (2008–2022), paired with a machine
learning data product providing daily PM 2.5 estimates at 10 km resolution. Leveraging
variation in day-to-day exposure generated by league scheduling rules, we find that
a 10 μgm−3 increase in same-day PM 2.5 (half a standard deviation) reduces bowler
performance by about 1 percent relative to batters, consistent with bowlers’ heightened
exposure via higher respiration rates. Effects are non-linear, with the largest marginal
damages above approximately 50 μgm−3—levels common in developing countries
but uncommon in causal studies. Using variation in chronic exposure from player
assignment to teams according to salary cap rules, we find that acute shocks harm
those with the highest past exposure approximately 40 percent less than those with
median exposure histories, indicating adaptation over both 30-day and career-spanning
horizons. Nevertheless, chronic exposure degrades performance by more than adaptation
offsets, except under extremely rare pollution conditions. These findings underscore the
importance of regulating these cond moment of the pollution distribution: non-linearity
implies that marginal damages are largest when pollution is in the uppertail, while
partial adaptation implies that spikes above mean levels amplify marginal damages.
