Harms to lungs arise in many ways. A new global collaboration estimates about 2.5 million annual, early deaths from air pollution, which is defined in general as ozone and particulates. The study is freely available here in full text in a respected journal, and a ScienceDaily summary is here. The study is an effort at modeling using Monte Carlo analysis and other statistical methods, and so the numbers are variable, both higher and lower.
The conclusion states the specifics:
We estimate that in the present-day, anthropogenic changes to air pollutant concentrations since the preindustrial are associated annually with 470 000 (95% CI, 140 000 to 900 000) premature respiratory deaths related to ozone, and 2.1 (1.3 to 3.0) million CPD and LC deaths related to PM2.5. Our estimates differ from those of Lim et al (2012) in that we estimate mortality for changes in air pollution relative to the modeled preindustrial conditions, rather than using a counterfactual low concentration. Relative to Anenberg et al (2010), our results also differ mainly because of the different emissions used in the models for preindustrial and present-day conditions, and by using modeled concentrations from an ensemble of models rather than a single model.
There is significant variability in mortality estimates driven by different atmospheric models, even though these models used very similar anthropogenic emissions, highlighting the uncertainty in basing results on a single model. Variability among models is higher for ozone than for PM2.5, but for both pollutants, it contributes less to overall uncertainty than the uncertainty in CRFs. The uncertainty in CRFs is understated because it does not account for the full range over the literature—e.g., use of the CRF for PM2.5 from Lepeule et al (2012) would lead to higher mortality estimates. The relative magnitude of results using different CRFs and with low-concentration thresholds, analyzed by Anenberg et al (2010), would also apply here. As for previous studies that estimate the mortality burden of outdoor air pollution, our methods likely underestimate the true burden because we have limited the evaluation to adults aged 30 and older, and base the analysis on coarse-resolution models that likely underestimate exposure, particularly for PM2.5 in urban areas (Punger and West 2013). On the other hand, recent studies suggest that the relationship between PM2.5 and mortality may flatten at high concentrations (Pope et al 2011), suggesting that we may overestimate PM2.5 mortality in regions with very high concentrations. We also caution that there are large uncertainties in applying CRFs from the US globally.
Air pollution-related mortality due to past climate change is shown to be significantly smaller than the total anthropogenic burden—i.e., anthropogenic increases in emissions likely have had a much greater influence on air pollutant concentrations than past climate change. We estimate here that 1500 (−20 000 to 27 000) premature respiratory deaths related to ozone and 2200 (−350 000 to 140 000) CPD and LC deaths related to PM2.5 occur each year due to past climate change. The large uncertainties reflect significant variability among different atmospheric models, with some models estimating an overall decrease in mortality from past climate change. The multi-model averages for both ozone and PM2.5 mortality are very small by coincidence, as the results for individual models show a large range of positive and negative values.
Consequently, it cannot be clearly concluded that past climate change has increased air pollution mortality. This large variability among models suggests that using a single model to represent past climate change may have significant uncertainties. This conclusion agrees with that of Post et al (2012) who analyzed the effects of future climate change on air pollution mortality in the US from an ensemble of atmospheric models. As models continue to develop and more comprehensively represent the mechanisms by which climate change might influence air quality, we should expect that large differences between estimates based on different models will likely persist."