Table 1.

Distribution of air pollution concentrations, CPS-II cohort, United States ($\mathit{n}=\mathrm{623,048}$).

Air pollutant (units)	Time period	Mean (SD)	Minimum	Percentiles					Maximum	Increment
				5th	25th	50th	75th	95th		5th percentile–mean
${\text{PM}}_{2.5}$ (${\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$)	1999–2004	12.6 (2.8)	1.4	8.2	10.6	12.5	14.4	17.0	27.9	4.4
${\text{NO}}_2$ (ppb)	2006	11.6 (5.1)	1.0	5.1	8.1	10.8	14.1	21.2	37.6	6.5
${\mathrm{O}}_3$ (ppb)	2002–2004	38.2 (4.0)	26.7	31.3	36.2	38.1	40.1	44.9	59.3	6.9
Near-source ${\text{PM}}_{2.5}$ (${\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$)a	1999–2004	12.0 (0.9)	8.6	10.4	11.6	12.0	12.5	13.5	19.7	1.6
Regional ${\text{PM}}_{2.5}$ (${\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$)a	1999–2004	0.5 (2.7)	$-7.9$	$-4.0$	$-1.4$	0.5	2.5	4.6	13.0	4.5

Note: CPS-II, Cancer Prevention Study II; ${\text{NO}}_2$, nitrogen dioxide; ${\text{O}}_3$, ozone; ${\text{PM}}_{2.5}$, particulate matter with aerodynamic diameter $<2.5\mathrm{\mu }\mathrm{m}$.

^aThe land use regression Bayesian maximum entropy (LURBME) ${\text{PM}}_{2.5}$ model was created in three main steps: a) A base LUR model predicted ${\text{PM}}_{2.5}$ concentrations based on traffic within $1\mathrm{km}$ (based on modeled traffic counts) and the cube of green space within $100\mathrm{m}$; b) A BME interpolation model was then used to interpolate residual spatiotemporal variation in ${\text{PM}}_{2.5}$ concentrations; c) The two estimates were then combined. Regional ${\text{PM}}_{2.5}$ concentrations therefore represent a residual with some observations less than zero.