Di vs Krewski: Two Cohorts, Different Age Coverage
The concentration–response function (CRF) maps PM2.5 exposure to mortality risk. Two studies dominate the field. They differ in slope, but the sharper difference is who they include:
Di et al. (2017) — 61 million Medicare enrollees, ages ≥65 only. HR = 1.073 per 10 µg/m³ (β = 0.00705). Higher slope, but the cohort cannot speak to anyone under 65.
Krewski et al. (2009) — ACS CPS-II, 500K participants, ages ≥30. HR = 1.056 per 10 µg/m³ (β = 0.00545). Lower slope, but covers 14.7 million additional Californians in the 30–64 bracket where Di is silent.
Both CRFs are peer-reviewed, both are used by EPA in regulatory impact analyses, and under each one independently the optimal transport portfolio is the same: T2 accelerated electrification. The difference between them is not the ranking of policies — it is the absolute burden each implies, driven primarily by who the cohort covers.
Same Ranking, Different Magnitudes
Under both CRFs independently, T2 accelerated electrification tops the ranking. T4 equity-targeted comes second. T3 delayed phase-out is consistently last. The CRF choice is not a structural lever over the policy decision — it is a multiplier on the estimated benefit.
| Policy | Di Net Benefit ($B) | Krewski Net Benefit ($B) | Di Optimal? | Krewski Optimal? |
|---|---|---|---|---|
| T1 Baseline | $5.62 | $17.77 | — | — |
| T2 Accelerated | $5.81 | $22.52 | Yes | Yes |
| T3 Delayed | $2.85 | $7.96 | — | — |
| T4 Equity | $5.78 | $22.51 | — | — |
| T5 Heavy-Duty | $4.58 | $16.73 | — | — |
Under Di (ages ≥65 only), T2 wins by a narrow $0.19B over T1 baseline, with T4 a close second. Under Krewski (ages ≥30), T2 wins by a wider $4.75B over T1, with T4 again close behind. The ranking of all five portfolios is preserved across the two CRFs — the policy decision is structurally robust to the CRF choice.
Burden Magnitude: 4× Driven by Age-Threshold
The CRFs do not disagree about the policy. They disagree about how big the problem is to begin with. Under Di (Medicare ≥65 only) the CA-wide annual PM2.5-attributable baseline is 11,689 deaths. Under Krewski (ACS ≥30) it is 17,660 — a 1.5× increase in attributable burden. The underlying cohort baseline mortality pool over which the CRF applies differs by 4× (31,407 vs 125,897 annual all-cause deaths), tracking the cohort age floor, not the CRF slope.
Both CRFs are scientifically credible. Di covers Medicare ≥65; Krewski covers ACS ≥30. They answer different questions on different cohorts — neither replaces the other. The cohort you report against sets the burden; it does not set the policy. Rankings hold; the scale of benefits does not.
Building Ranking Is Also Preserved
The building electrification decision is stable across both CRFs in the same way. B1 baseline is preferred over B2 aggressive electrification under both Di and Krewski. The CRF changes the magnitude of the benefit, but not the ranking. B2 does not justify its incremental cost under either cohort, because fossil space- and water-heating already contribute a small share of ambient PM2.5 compared with transport and wildfire.
No policy under study reorders under the Di ↔ Krewski CRF switch. The CRF is an uncertainty on the scale of benefit, not on which portfolio to deploy.
What this changes about the decision. Because the ranking holds under both CRFs, California does not need to pick one before acting — T2 accelerated is optimal either way. The CRF choice is a burden-reporting decision, not a policy-selection one. An age-stratified meta-analysis ($0.5M, 6 months) is still worth running to narrow the $5.8B ↔ $22.5B reported-benefit range before CARB files GFO-25-304.
10,000-draw Monte Carlo · Di (Medicare ≥65, β = 0.00705) vs Krewski (ACS ≥30, β = 0.00545) run independently · Sobol global sensitivity analysis · ISRM source–receptor matrix · 5 transport + 4 building policies · Burden ratio from age-decomposition of ambient CA population against each cohort’s age floor · Residual EVSI anchored on the Inv 21 hierarchical posterior over the CA-pooled CRF