What if we cooled a ward?

Move the sliders to see an illustrative first-order estimate of daytime cooling from adding tree canopy, raising roof albedo or adding pocket parks, using coefficients from published research rather than a trained model. The coefficients cite their papers; the pocket-park scaling and the budget's albedo gain are our own stated assumptions.

Tree canopy cover

40% cover

Ziter et al. 2019 found negligible daytime cooling below ~40% canopy in a 60-90m radius; cooling only shows up above that threshold.

Cool-roof albedo increase

+0.10 albedo

Santamouris 2014's city-scale review range; Li, Bou-Zeid & Oppenheimer 2014 supports treating the relationship as roughly linear.

Pocket-park coverage

10% of ward area

Bowler et al. 2010's meta-analysis found parks average ~0.94°C cooler than their surroundings in the day; scaled here by the share of ward area converted. Capped at 60%: no ward can convert its roads, buildings, and hospitals into parkland.

Estimated daytime cooling

From tree canopy

0.00°C

From cool roofs

0.60°C

From pocket parks

0.09°C

Combined estimate: 0.69°C (cool-roof range: 0.57-2.30°C)

This is a cited coefficient estimator, not a trained model and not a validated climate simulation. The coefficients above are transferred from other cities' studies, not Mumbai-calibrated, and the three interventions are summed as independent illustrative terms, not a coupled physical model.

Where would 5 crore go?

One worked scenario, not a recommendation and not a funded programme. It spends a fixed budget on cool roof, white lime paint at ₹5.38/m², allocating by benefit per rupee.

Budget: 5 crore
Wards funded: 3
Person-degrees: 74,70,327
Unspent: ₹0

Wards funded under the vulnerability objective, with spend and estimated benefit
Ward	HVI rank	Spend	Roofs treated	Person-degrees
H/E	7 of 24	₹1,61,09,379	100%	25,26,519
M/W	9 of 24	₹1,93,51,699	100%	29,51,259
F/S	6 of 24	₹1,45,38,922	90%	19,92,549

The objective changes the answer

Maximise vulnerability-weighted cooling: degrees C x people exposed x ward HVI, allocated by benefit per rupee.

Allocated by fractional knapsack, provably optimal for a divisible intervention. The choice of objective moves the answer: on this budget the exposure objective funds wards ranked 17, 19, 22 and 24 of 24, and the vulnerability objective funds wards ranked 6, 7 and 9. Dense wards yield the most person-degrees per rupee whether or not they are the wards at risk, which is why the default weights by vulnerability and why the objective is recorded in the output rather than left implicit.

Assumptions

Albedo gain from a cool roof: +0.4. An assumption, not a measurement.
Cooling: 0.6 C per +0.1 albedo, the conservative end of Santamouris 2014's 0.57-2.3 K range.
Roof area: 40% of each ward's impervious surface. Imperviousness includes roads and paving, so this is a share of it rather than all of it, and it is an assumption rather than a roof survey.
Population from WorldPop density times ward area; the same modelled surface the index uses, not a census count.
Benefit is instantaneous person-degrees. It does not model intervention lifetime, maintenance, discounting, or health outcomes.

Limitations

Only cool roofs can be allocated. Cited cooling coefficients exist for tree canopy (Ziter 2019) and pocket parks (Bowler 2010), but no credible Indian unit COST was found for either, so they cannot enter a budget comparison.
Costs are 2020 prices and are not inflation-adjusted.
Even the vulnerability-weighted objective is an aggregate one: it maximises total weighted cooling, not the worst-off ward's outcome. A sparse but severely vulnerable ward can still lose to a dense moderately vulnerable one. A minimax or per-capita-floor objective would answer a different and equally legitimate question.

Cost and cooling sources

Unit cost: NRDC, 'Frequently Asked Questions (FAQs): Cool Roofs', 2020-05-27, question 11 and Table 1.

Cooling coefficient: Santamouris 2014, Solar Energy 103:682-703, doi:10.1016/j.solener.2012.07.003

Every rupee allocated here is priced from a published municipal-programme cost. The stage refuses to allocate budget to an intervention with no sourced cost.

Sources for this estimate

Ziter et al. 2019
PNAS 116(15):7575-7580
Canopy percent to LST reduction coefficients (simulator and NBS impact)
DOI
Li, Bou-Zeid & Oppenheimer 2014
Environ. Res. Lett. 9(5):055002
Cool-roof fraction to UHI reduction, structural support for a linear term
DOI
Santamouris 2014
Solar Energy 103:682-703
Albedo to peak-temperature coefficient (~0.6-2.3K per +0.1 albedo)
DOI
Bowler et al. 2010
Landscape and Urban Planning 97:147-155
Park cool-island effect (~0.94C average daytime, meta-analysis) for the pocket-park simulator term
DOI