Janssen et al. cohorts, analyzed using the same exposure assessment strategy, and two papers on lung function growth in two cohorts of Southern California children [Brauer et al. 2002, 2006, 2007; Gauderman et al. 2002, 2004; Gehring et al. 2002; Morgenstern et al. 2007, 2008; see Supplemental Material, Tables F1, F2 (http://dx.doi.org/10.1289/ehp.1003369)]. For most of the studies, PM2.5 and BCP were highly correlated (R > 0.9). Overall, consistent with other types of studies, estimated effects of a 1-μg/m 3 increase in BCP were greater than estimated effects of a 1-μg/m 3 increase in PM2.5, whereas effects estimated for IQR increases were similar for BCP and PM2.5. Exposure contrast in BCP compared with PM mass. Street:background ratios were higher and more variable for BCP than for PM mass concentrations [Figure 2; see also Supplemental Material, Table G1 (http:// dx.doi.org/10.1289/ehp.1003369)]. On aver- age, BCP concentrations near busy roads were twice as high as urban background BCP con- centrations, whereas PM concentrations near busy roads were only about 20% higher than background levels. For all single sites, the street:background ratio for BCP was higher than the corresponding ratio for PM mass. For the studies included in Figure 2, the average roadside increment of EC relative to PM2.5 was 55% (95% CI: 46%, 63%) when the conversion 10 gμ/m 3 BS = 1.1 gμ/m 3 EC was used. Using the lower and upper conver- sion factors of 0.5 and 1.8 resulted in an aver- age percentage of 41% (95% CI: 29%, 54%) and 70% (95% CI: 59%, 82%), respectively [see Supplemental Material, Table G2 (http:// dx.doi.org/10.1289/ehp.1003369)]. Comparison of calculated health bene- fits of traffic abatement measures using PM2.5 or BCP. The estimated percentage 6 PPMM12.05or PM4 nd 5 × PM 1 u Abs o r BS kg 4 EC c a b : te 3 e r t s tio 2 a × R × 1 PM mass BCP Figure 2. Study-specific street:background ratios for PM mass and BCP concentrations. Blue, ≥ 24-hr average along highways; green, ≥ 24-hr average along inner-city roads; red, daytime and ≤ 12-hr measurements (all inner-city roads). Data from Boogaard et al. (2011), Cyrys et al. (2003), Fischer et al. (2000), Fromme et al. (2005), Funasaka et al. (2000), Harrison et al. (2004), Janssen et al. (1997, 2001, 2008), Kinney et al. (2000), Lena et al. (2002), Riediker et al. (2003), Roemer and van Wijnen (2001b), Roorda-Knape et al. (1998), Roosli et al. (2001), and Smargiassi et al. (2005). 1696 EC in the roadside increment in PM2.5 of 40–70% implies that every 1-μg/m 3 reduc- tion in traffic-related PM2.5 along busy roads will result in a 0.4- to 0.7-μg/m 3 reduction in EC. When the average conversion factor of 10 gμ/m 3 BS = 1.1 gμ/m 3 EC is used to derive the RR for a 1-gμ/m 3 increase in EC and the percentage of EC in a roadside increment of PM2.5, the increase in life expectancy per per- son is five times higher for EC than for PM2.5 (3.6 months vs. 21 days; Table 4). When the maximum and minimum conversion factors of 1.8 and 0.5 gμ/m 3 EC per 10 gμ/m 3 BS are used, the increase in estimated life expectancy is four to nine times higher. Therefore, esti- mated health benefits are much larger when expressed in terms of EC compared with an equivalent change in PM mass. Discussion Our review shows that health effect esti- mates from mortality and morbidity time- series studies as well as cohort studies were higher for BCP than for PM10 or PM2.5 when expressed for a 1-μg/m 3 increase in exposure and similar when expressed for an IQR increase in exposure. A relatively large part (40–70%) of the roadside increment in PM2.5 mass concentrations can be attributed to BCP. Based on the calculated RRs for all- cause mortality from cohort studies as well as the estimated percentage EC in the road- side increment in PM2.5 mass, the estimated increase in life expectancy associated with a hypothetical traffic abatement policy meas- ure was four to nine times higher than when expressed per achievable reduction in BCP compared with the estimated effect of an equivalent reduction in PM2.5 mass. Health effects of BCP compared with PM mass. Single-pollutant effect estimates for daily mortality or hospital admissions generally were an order of magnitude higher for BCP than for PM10 and PM2.5 when expressed per 1 gμ/m 3 . When differences in IQRs were accounted for, effect estimates were generally similar. It should be noted that there was a moderate to moderately high correlation between PM10 and BS measurements reported by the indi- vidual studies included in the pooled estimates (Pearson correlations of 0.5–0.8), consistent with correlations between daily wintertime PM10 and BS concentrations from a study in 14 European study areas (Hoek et al. 1997). Although this raises concerns about the ability to distinguish effects due to PM10 versus BS, there is at least some variation in the temporal patterns of these exposures. In studies examining a variety of different PM components, BCP generally showed sig- nificant associations, especially with cardiovas- cular health end points, both before and after adjusting for other components. For cohort studies, pooled estimates for all-cause mortal- ity per 1 μg/m 3 were 5–14 times higher for BCP than for PM2.5, but IQRs for PM 2.5 were higher than those for BCP by a similar factor. The implication of similar effects per IQR is that for policies that reduce all relevant components of PM proportional to current levels, estimated health benefits would be sim- ilar based on either indicator. The IQR-based comparison is also the relevant comparison for health impacts assessments of general air quality. However, for assessments of exposure conditions dominated by combustion sources, or policies directed toward specific combus- tion sources, the comparison of RRs expressed per unit change in mass is relevant. The available evidence from two-pollutant models for time-series studies suggests that the effect of BCP is more robust than the effect of PM mass. However, two-pollutant models with BCP and PM mass were not conducted in any of the cohort studies. Although overall the results of multipollutant analysis includ- ing BCP, sulfate, and ozone in the ACS study suggest that sulfate has the most robust asso- ciation with all-cause and cardiopulmonary mortality, Smith et al. (2009) indicate that this can also be caused by differential amounts of measurement error. In the ACS study, where exposure was assessed at the metropolitan area level, estimates of the spatial distribution of EC likely have more measurement error than the assigned sulfate exposures because EC is more locally generated than is sulfate, which is a secondary pollutant with little spatial vari- ation. When measurement error is present, variables measured with high precision will tend to dominate model-based predictions rel- ative to variables measured with less precision Table 4. Comparison of the estimated effect on life expectancy of reductions in PM2.5 mass and EC resulting from a traffic management plan. Reduction Increase in life expectancy Component Conversion of BS to ECa RRb [μg/m3 (95% CI)]c per persond PM2.5 1.007 1.00 21 days EC 10 μg/m3 BS = 1.1 μg/m3 EC 1.06 0.55 (0.46, 0.63) 3.6 months (3.0, 4.1 months) 10 μg/m3 BS = 1.8 μg/m3 EC 1.05 0.70 (0.59, 0.82) 3.1 months (2.6, 3.6 months) 10 μg/m3 BS = 0.5 μg/m3 EC 1.11 0.41 (0.29, 0.54) 4.5 months (3.2, 5.9 months) aBS was converted to EC for two of the four studies that were used to calculate the RR for EC and for 8 of 16 studies that were used to calculate the percentage EC in the roadside increment of PM2.5 over background. bRR per 1-μg/m3. cA traffic abatement measure is evaluated that reduces EC proportional to the percentage EC in the roadside increment of PM2.5 over background [Supplemental Material, Table G2 (http://dx.doi.org/10.1289/ehp.1003369)]. dValues in parentheses are based on the 95% CI for the reduction. ovlume 119 | number 12 | December 2011 • Environmental Health Perspectives