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Article

Urban Heat and Cooling Demand: Tree Canopy Targets for Equitable Energy Planning in Baltimore

by
Chibuike Chiedozie Ibebuchi
1,2,* and
Clement Nyamekye
3
1
Department of Mathematics, Morgan State University, Baltimore, MD 21251, USA
2
Center for Urban and Coastal Climate Science Research, Morgan State University, Baltimore, MD 21251, USA
3
Department of Civil Engineering, Koforidua Technical University, Koforidua 03420, Ghana
*
Author to whom correspondence should be addressed.
Urban Sci. 2026, 10(1), 61; https://doi.org/10.3390/urbansci10010061 (registering DOI)
Submission received: 16 December 2025 / Revised: 9 January 2026 / Accepted: 14 January 2026 / Published: 18 January 2026

Abstract

Urban heat and hardscapes increase cooling electricity demand, stressing power grids and disproportionately burdening deprived neighborhoods. While previous studies have documented the cooling benefits of urban tree canopy, most analyses remain at coarse spatial scales and do not isolate the canopy’s marginal effect from built surfaces, limiting their utility for equitable neighborhood-level planning. We introduce a novel neighborhood-scale (census block-group, CBG) model to estimate cooling-season energy demand across Baltimore City and Baltimore County, Maryland. We quantify demand drivers and actionable tree-canopy targets while controlling for built surfaces. Correlation analysis shows demand increases with developed fraction and imperviousness, and decreases with tree canopy and other vegetated or water cover. Using an explainable monotone gradient-boosted tree model (SHAP) with controls for imperviousness and development, we isolate the canopy’s marginal effect. Demand reductions begin once the canopy exceeds ~11% in Baltimore City and ~23% in Baltimore County, with diminishing returns beyond ~18% (City) and ~24% (County). This flattening is strongest in highly impervious CBGs, while low-impervious county areas show renewed reductions at very high canopy (>55–60%), consistent with forest-dominated microclimates. Spatial hotspots cluster in Baltimore City and southern Baltimore County, where low canopy and high hardscapes coincide with elevated demand; 61% of City CBGs fall below the 18% threshold. We translate these findings into priority intervention tiers combining demand, hardscapes, jurisdiction-specific canopy thresholds, and an equity overlay, identifying 21% of City and 1.2% of County CBGs as high-priority targets for greening and energy-relief interventions.
Keywords: cooling demand; urban heat island; tree canopy; Baltimore; machine learning; land cover; extreme heat; energy cooling demand; urban heat island; tree canopy; Baltimore; machine learning; land cover; extreme heat; energy

Share and Cite

MDPI and ACS Style

Ibebuchi, C.C.; Nyamekye, C. Urban Heat and Cooling Demand: Tree Canopy Targets for Equitable Energy Planning in Baltimore. Urban Sci. 2026, 10, 61. https://doi.org/10.3390/urbansci10010061

AMA Style

Ibebuchi CC, Nyamekye C. Urban Heat and Cooling Demand: Tree Canopy Targets for Equitable Energy Planning in Baltimore. Urban Science. 2026; 10(1):61. https://doi.org/10.3390/urbansci10010061

Chicago/Turabian Style

Ibebuchi, Chibuike Chiedozie, and Clement Nyamekye. 2026. "Urban Heat and Cooling Demand: Tree Canopy Targets for Equitable Energy Planning in Baltimore" Urban Science 10, no. 1: 61. https://doi.org/10.3390/urbansci10010061

APA Style

Ibebuchi, C. C., & Nyamekye, C. (2026). Urban Heat and Cooling Demand: Tree Canopy Targets for Equitable Energy Planning in Baltimore. Urban Science, 10(1), 61. https://doi.org/10.3390/urbansci10010061

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