DOI: 10.5061/dryad.zgmsbcckf
title: Data from: Current inequality and future potential of US urban tree cover for reducing heat-related health impacts

description: Excessive heat is a major and growing risk for urban residents. Here, we
 estimate the inequality in summertime heat-related mortality, morbidity,
 and electricity consumption across 5,723 US municipalities and other
 places, housing 180 million people during the 2020 census. On average,
 trees in majority non-Hispanic white neighborhoods cool the air by 0.19 ±
 0.05⁰C more than in POC neighborhoods, leading annually to trees in white
 neighborhoods helping prevent 190 ± 139 more deaths, 30,131 ± 10,406 more
 doctors’ visits, and 1.4 ± 0.5 terawatt-hours (TWhr) more electricity
 consumption than in POC neighborhoods. We estimate that an ambitious
 reforestation program would require 1.2 billion trees and reduce
 population-weighted average summer temperatures by an additional 0.38 ±
 0.01⁰C.  This temperature reduction would reduce annual
 heat-related mortality by an additional 464 ± 89 people, annual
 heat-related morbidity by 80,785 ± 6110 cases, and annual electricity
 consumption by 4.3 ± 0.2 TWhr, while increasing annual carbon
 sequestration in trees by 23.7 ± 1.2 MtCO2e yr-1 and decreasing annual
 electricity-related GHG emissions by 2.1 ± 0.2 MtCO2e yr-1. The total
 economic value of these benefits, including the value of carbon
 sequestration and avoided emissions, would be USD 9.6 ± 0.5 billion,
 although in many neighborhoods the cost of planting and maintaining trees
 to achieve this increased tree cover would exceeds these benefits. The
 exception is areas that currently have less tree cover, often majority
 POC, which tend to have a relatively high return-on-investment from tree
 planting.
description: Our analysis proceeded in four phases. First, we assembled
 spatial data from multiple sources and compiled them to a common analysis
 unit. Second, we developed an algorithm that would set a plausible
 ambitious reforestation target, given other land-use constraints. Third,
 we estimated the heat mitigation-related benefits of current tree canopy
 and of future planting scenarios, up to the ambitious planting scenario.
 Benefits evaluated were avoided mortality, avoided morbidity, avoided
 electricity consumption, avoided release of greenhouse gases from avoided
 electricity consumption, and carbon sequestration in aboveground tree
 biomass. Fourth, we valued these benefits in monetary terms. See McDonald
 et al. 2024 in npj Urban Sustainability for Details.
description: # Data from: Current inequality and future potential of US urban tree
 cover for reducing heat-related health impacts
 This data archives
 contains datasets generated the analysis of McDonald et al. 2024. Note
 that all input datasets to the analysis are publicly available (see the
 section on Data Sources in the Methods). ## Description of the data and
 file structure Figure 1- CSV file showing data corresponding to Figure 1
 of the paper. Column names are in the first row, and are self explanatory.
 Figure 1 caption from the paper: "**Figure 1. Mortality and urban
 tree canopy cover for our sample of 5,723 US municipalities.** Shown are
 the current annual reduction in mortality due to trees, as well as the
 additional reduction in mortality possible under the ambitious planting
 scenario. This quantity can be expressed not just in annual lives saved
 (left axis) but also the estimated annual value of avoiding this mortality
 (right axis)." Figure 2- Data corresponding to Figure 2 of the paper.
 The generated variables are shown in a CSV file. GISJOIN and GEOID are
 variable to link to the US Census Bureau blocks (included for convenience
 of users, in the Block_Data.gdb geodatabase generated from ArcGIS Pro),
 while the other column names are in the first row and are self
 explanatory. Figure 2 caption from the paper: "Figure 2. Inequality
 in the Washington, DC urbanized area. **a) Zoom-in of purple rectangle
 shown in other panels. Tree cover varies significantly from block to
 block. Neighborhoods that are predominately people of color (POC) are
 shown in grey and are primarily east of Rock Creek Park, while majority
 non-Hispanic white neighborhoods west of the park. Note that Rock Creek
 Park itself has no residents. b.) Land surface temperature in summer by
 census block, as observed by satellite imagery. For reference, the extent
 of the zoomed in panel in the upper left is outlined in purple. c.) The
 potential reduction in heat risk due to additional tree planting (increase
 in protective rate, in avoided annual deaths per million people). d.)
  Potential additional carbon sequestered due to new tree planting within
 census blocks. While tree planting in the city center occurs at higher
 population densities, and so benefits more people with heat reduction, the
 greatest number of potential trees can be planted in suburban areas."
 For convenience, we also supply the high-resolution tree cover rasters for
 all urbanized used in our analysis. These are publicly available as part
 of: McDonald, R. I. et al. The tree cover and temperature disparity in US
 urbanized areas: Quantifying the association with income across 5,723
 communities. PLoS ONE 16, e0249715 (2021). Figure 3- CSV file showing data
 corresponding to Figure 3 of the paper. Each row is an urbanized area.
 Column names are in the first row, and are self explanatory. Figure 3
 caption from the paper: "**Figure 3- Protective value of urban tree
 canopy for large US urbanized areas.** The size of the circle is
 proportional to the avoided annual mortality due to urban tree canopy in
 the urbanized area. The color of the circle indicates the difference in
 the protective rate (annual deaths avoided due to urban tree canopy per
 million population) between people-of-color (POC) majority neighborhoods
 and non-Hispanic white majority neighborhoods. Negative values indicate
 that POC neighborhoods have a lower protective rate than white
 neighborhoods." Figure 4- CSV file showing data corresponding to
 Figure 4 of the paper. Each row is an urbanized area. Column names are in
 the first row, and are self explanatory. Figure 4 caption from the paper:
 "**Figure 4. Ambitious reforestation potential for large US urbanized
 areas.** The size of the circles is proportional to the potential
 additional carbon storage under the ambitious reforestation scenario. The
 color of the circle indicates the increase in the protective rate (annual
 deaths avoided due to urban tree canopy per million population) under the
 same reforestation scenario." Figure 5- CSV file with data
 corresponding to Figure 5 of the paper. Column names are in the first row,
 and mean: POC= Whether the block is majority people of color (POC) or not
 priority = Whether the block is a priority or not, or all blocks.
 DelExcessDeaths_FC0 and similar = The avoided deaths due to achieving the
 target. FC0 is the current tree cover, and shows the number of avoided
 deaths due to current tree cover. FC5, FC10, etc. are the decrease in
 annual mortality due to the additional tree cover in the 5%, 10%, etc.
 target. DelExcessDeaths_FC0_error95 = The error in the estimation of the
 above DelExcessDeath calculation. TreesFC5 and similar = The number of
 trees planted in a given tree planting scenario. Figure caption for Figure
 5:"**Figure 5: Mortality reductions as a function of planting
 ambition.** Blocks are classified as either majority people of color (POC)
 or majority non-Hispanic white. For each census block, additions of tree
 cover of 5%, 10%, etc., up to an Ambitious Scenario, the maximum possible
 given our assumptions. Each point along the curve thus represents an
 additional 5% increase in tree cover, wherever this is possible. Error
 bars are the 95% confidence interval of reduction in annual heat-related
 mortality. a.) Results for all census blocks. For instance, planting 200
 million additional trees in white blocks for a 5% increase in tree cover
 reduces annual heat-related mortality by an additional 62 lives. b.)
 Results for high ROI census blocks, defined as in the top 5% of ROI (see
 methods for details). Note the very different scales in the two plots. For
 instance, planting 0.4 million additional trees in white blocks for a 5%
 increase in tree cover reduces annual heat-related mortality by an
 additional 2 lives." ## Code/Software Our code is archived on a
 linked Zenodo archive. The analysis is a series of codes for SAS 9.4, run
 in this order: 1.Basic_analysis_v2_urbanNCS_variant.sas
 2.UrbanNCS_v2_1.sas 3.Air_temperature_regression v2_14.sas
 4.benefits_v1_03.sas 5.Carbon_calculations_v2_10.sas
 6.electricity_v1_0.sas 7.carbon_plus_health_plus_electricity_v4_11.sas
 Input Data needed to run these scripts are in the InputData.zip file. To
 ease use, we have also included intermediate SAS data files that were used
 to pass data between the scripts. While there are extensive comments
 throughout the scripts detailing the analytic methods, the origin of the
 code (sometimes from previous manuscripts), and version changes, we
 caution that this code sequence is saved here for archival purpose. It
 will likely be complex for those not involved in writing the code to
 understand and use it, especially since the comments were written for our
 external use not to be used by others. Please email if you have questions
 and we will do our best to explain technical points as time allows:
 [rob_mcdonald@tnc.org](mailto:rob_mcdonald@tnc.o)