Contra Torres, equity is the wrong criteria for tree-planting, experts say
Nobody serious doubts the importance of healthy urban forests, but the process for deciding where and what to plant is much more complex than knee-jerk social justice soundbites. SJ CM Omar Torres supports demanding an "equity lens" to tree planting across districts, while expert Ethan Bodnaruk, environmental and geotechnical engineer at Atlantic Testing Laboratories, suggests a much more scientific and health-based model in Deeproot.com.
We wanted to look at where trees can remove the most air pollution, where they can best reduce air pollution burdens for people in particular, and locations where trees are most needed to reduce extreme temperatures.
One consideration was to be aware and explicit through the modeling itself that there can be a big difference between where the hottest and most polluted locations are versus where people who can experience the benefits of mitigation are. That’s why we needed Census data to know where people are, and also demographic data because we know that the elderly and very young are more susceptible to extreme heat. For instance. I created different planting scenarios that:
Maximized air pollution removal,
Maximized human benefits of air pollution removal,
Prioritized plantings based on locations with the worst heat index (combination of temperature and humidity)
Prioritized plantings based on a combination of the worst heat index, population size, and relative risk due to age (elderly and very young)
Prioritized plantings based on a combination of the previous point plus the modeled effectiveness of trees in reducing the heat index.
We want to use science and mathematical models to supplement local knowledge of where we need more green space, where issues of concern can be addressed, and so forth.
In terms of modeling where new potential tree cover could go, I used the simplification that impervious areas such as buildings and roads would not be replaced by tree cover. To a certain extent this makes a lot of sense because people would laugh at a model that says to tear down buildings or get rid of roads to obtain more benefits from trees. We basically assumed that any land with bare soil or grasses could potentially be turned into tree cover.
Downtown areas are of course mostly buildings and roads so there is not much of what we defined as “potential plantable” area either according to the assumptions used in the model or in real life. But for future work we wanted to utilize map-based data that includes estimates of how much paved surface area could be removed and replaced with trees. We generally know that removing impervious surfaces where and when possible and replacing them with green space is good across many different types of ecosystem services. It’s often possible to squeeze some trees into parking lots, or remove portions of sidewalks for trees.
Of course, local communities and people who have direct experience in their locale would know much more about such “potential impervious plantable” areas than a modeler who doesn’t live in the area. So that’s why we ultimately want to gear the tools toward the people who can use them combined with local knowledge.
Read the whole thing here.
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