A ride-sharing company has budget for one carbon reduction initiative. Three options are available: Option A: Temporal shifting of the pricing model retraining (5-hour nightly batch job) within a solar-heavy region (intensity range 120 to 400 gCO₂e/kWh). Option B: Spatial shifting of the same pricing model to a hydro-powered region (35 gCO₂e/kWh steady), requiring transfer of 200 gigabytes nightly. Option C: Migrating the real-time rider-driver matching algorithm (50,000 requests per minute) from a coal-heavy region (580 gCO₂e/kWh) to the hydro-powered region (35 gCO₂e/kWh, but 120 milliseconds additional latency to the user base). Which option is the most feasible and why?

Question

A ride-sharing company has budget for one carbon reduction initiative. Three options are available:    Option A: Temporal shifting of the pricing model retraining (5-hour nightly batch job) within a solar-heavy region (intensity range 120 to 400 gCO₂e/kWh).    Option B: Spatial shifting of the same pricing model to a hydro-powered region (35 gCO₂e/kWh steady), requiring transfer of 200 gigabytes nightly.    Option C: Migrating the real-time rider-driver matching algorithm (50,000 requests per minute) from a coal-heavy region (580 gCO₂e/kWh) to the hydro-powered region (35 gCO₂e/kWh, but 120 milliseconds additional latency to the user base).    Which option is the most feasible and why?

Accepted Answer

Option A, because the solar region’s large intensity variation creates a meaningful clean window, the job is flexible with deadline slack, and no data transfer is required

Answer

Option B, because the hydro region has the lowest absolute intensity

Answer

All three options are equally feasible because they all target carbon reduction

Answer

Option C, because the matching algorithm consumes the most energy and the hydro region has the lowest intensity

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A ride-sharing company has budget for one carbon reduction initiative. Three opt...

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