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. 2021 Jul 1;5(7):e2021GH000414. doi: 10.1029/2021GH000414

Table 4.

Comparison of Methods for Estimating Excess Respiratory and Cardiovascular Hospital Admissions and Fire‐Originated PM2.5 Exposure, October 8–20, 2017

Impact assessment method # Admissions (95% CI) Fire‐originated PM2.5 (µg/m3) a
Total PM2.5 estimation Background PM2.5 estimation CRF type Respiratory Cardiovascular Population‐weighted average (Std. Dev.) Spatial average (Std. Dev.) 95th percentile
1 b BME data fusion CMAQ % attributable WF c 240 (114, 404) 68 (−10, 159) 10.05 (6.58) 7.05 (9.81) 26.59
2 CC‐CMAQ CMAQ % attributable WF 251 (77, 620) 70 (−10, 211) 9.84 (6.10) 6.56 (9.63) 27.47
3 BME kriging CMAQ % attributable WF 280 (124, 512) 78 (−12, 192) 11.02 (7.08) 8.19 (11.17) 26.40
4 BME data fusion October 2016 WF 299 (126, 544) 84 (−13, 208) 8.77 (7.50) 6.56 (8.48) 22.65
5 BME data fusion CMAQ % attributable NF d 177 (87, 305) 163 (95, 261) 10.05 (6.58) 7.05 (9.81) 26.59
a

The population‐weighted average and standard deviation, spatial average and standard deviation, and 95th percentile of the 1‐km resolution fire‐originated PM2.5 estimations across central California.

b

Base case impact assessment.

c

Wildfire‐specific CRFs (rate ratio per 10 μg/m3 increase in 2‐day average PM2.5)—respiratory: 1.028 (95% CI: 1.014, 1.041); cardiovascular: 1.008 (95% CI: 0.999, 1.018) (Delfino et al., 2009).

d

Nonwildfire‐specific CRFs (rate ratio per 10 μg/m3 increase in 2‐day average PM2.5)—respiratory: 1.021 (95% CI 1.012, 1.030); cardiovascular: 1.019 (95% CI: 1.013, 1.025) (Zanobetti et al., 2009).