Scoping In: From Environmental Racism to the Effects of Zoning Designations in Northern Manhattan
Catherine & Jennifer
Background:
Through our research we have come to learn firsthand the challenges of data research, data cleaning, and map making. We have spent countless hours trying to make maps, properly save maps, remake maps, make sense of maps, and felt frustrated by the process of making maps that already exist in order to build our map making and data cleaning muscles. However, we have also had some interesting moments of learning through our map making. As previously mentioned, some of the serendipitous process of learning through making led us to the rabbit hole of zoning which we knew we were bound to fall into given our thesis topic. Despite recognizing the relationship between zoning designations/policies and environmental racism, we lacked a deeper understanding of how zoning truly functions. This encapsulates: types of zoning designations (residential, commercial, and manufacturing), how the process of rezoning occurs, and a rezoning’s effects on community members and the environmental health of their neighborhood.
Our conversations with Northern Manhattan community members, who experienced the East Harlem and are experiencing the recent Inwood rezoning, prepared us to come into this project recognizing how fraught the topic of zoning is. Through our secondary research, map making, and lectures we attended regarding the role of anchor institutions, like Columbia, in protecting community interests, we learned about the 2012 West Harlem Rezoning which was contentious and faced great community backlash.
Knowing what we know about the relationship between environmental racism and zoning designations. given the disproportionate number of polluting manufacturing facilities placed in low income communities of color, and the resulting high levels of air pollution and subsequent asthma hospitalization, we feel it is urgent to learn as much as we can about the effects that rezoning has on both health and economic wellbeing of existing community members, using West Harlem as the primary case study given the greater length of time that has passed; and look at the shifts in rent burden rates, poverty rates, racial and economic demographics, housing code violations/maintenance complaints, and availability of affordable housing overtime pre and post rezoning.
We believe that understanding the effects of rezoning within Northern Manhattan is critical in better understanding the phenomenon of energy insecurity, which we hypothesize will be worsened due to rezoning initiatives and extreme heat’s increasing occurrence.
Objective:
We have continued to gather different datasets that we believe will help us to better explain and understand the changing in zoning and its effects on the Northern Manhattan community. We made visualizations of these datasets (spatial and temporal), so we can understand how they can be layered and combined to measure how zoning potentially impact the community’s energy insecurity.
The types of datasets that we visually explored: zoning (mostly manufacturing this week), racial demographics, fine particulate matter, public schools, poverty, and rent burden.
Process (sprinkled with outcomes and lessons learned):
We learned a lot last week about Northern Manhattan (East Harlem, Central Harlem, West Harlem, Washington Heights, Inwood) as a whole compared to the rest of Manhattan. This week we continued to test things out and try mapping new information we found and started to overlap and layer things to begin to better understand what’s happening in Northern Manhattan.
This is an overview of our process thus far. More details will be given below.
- Understanding the current state of Northern Manhattan’s resident’s health, environmental exposures, and economic wellbeing in comparison to the rest of Manhattan
- Understanding the environmental racism in Northern Manhattan
- Understanding how these environmental hazards affect the health of Northern Manhattan community members and their daily lives
- Understanding how zoning designations affect the present environmental, health, and lifestyle (like energy burden) hazards in Northern Manhattan
- Looking further into how zoning and rezoning efforts play a role in energy burden
- Understanding the current state of Northern Manhattan’s resident’s health, environmental exposures, and economic wellbeing in comparison to the rest of Manhattan
We began this week’s research by continuing to look at the map we created last week regarding the zoning of New York City. After a discussion with our professor and conducting more secondary research, we decided to look further into manufacturing zoning, instead of focusing on commercial zoning. We chose to look at manufacturing zones because of their high, negative environmental impact.
Manufacturing zone designation numbers correspond with negative environmental impact on the surrounding uses, with M3 emitting the greatest amount of pollutants and M1 zones posing less risk to the community. Through secondary research, we found that there’s supposed to be a buffer zone between M3 zones and residential zones. However based on our map making we found that this was often not the case, particularly in some parts of Northern Manhattan.
We continued to look at the maps that we created last week and we decided that it was important for us to work to make edits to the racial demographic spatial map we created. Upon revisiting how the map was crafted, we realized that we had created the spatial map with the incorrect column from the dataset. Now the map portrays the correct information regarding the percentage of people of color. This map is beneficial as we begin to overlay different maps and information on top of it. We can see that Northern Manhattan, as expected, has high percentages of people of color, compared to other parts of Manhattan.
We also thought it might be helpful to better understand the number of school, by school type, that exist in each neighborhood. Which are colored by poverty level
We wanted to create a map that would allow for us to easily see the dispersion of poverty levels in Manhattan–specifically comparing Northern Manhattan communities to the rest of Manhattan. When we first built this map, it took us a while to figure out some of the technical skills. Because of the different datasets we wanted to combine, we could not spatially join the two datasets, because the names of the neighborhoods are not the same. When we built the map below, the spatial join only joined some of the neighborhoods (as the names of those neighborhoods perfectly matched on both datasets), creating a very skewed and incorrect map.
Over the course of doing some other research, we found a dataset that had the same neighborhood labeling as the poverty rate dataset we had, so we swapped this new file into the map and all neighborhoods could be spatially joined. So the map’s information is now correct. It’s very evident that the poverty rates are higher in Northern Manhattan compared to Manhattan overall.
2. Understanding the environmental racism in Northern Manhattan
When thinking about toxic facility placement we also wanted to better understand the major roads that run through manhattan. On this map we colored the different roads that run through Manhattan by roadway type. However, we have not been able to identify what each type is. Based on the amount of #1s that we saw on the map, we chose to exclude it, because it looks like #1 might be city streets. We wanted to focus more on the major highways, parkways and streets that make up Manhattan.
3. Understanding how these environmental hazards affect the health of Northern Manhattan community members and their daily lives
After our research regarding toxic facility placement, racial demographics, along with other factors tied into environmental vulnerability, we mapped Fine Particulate Matter levels in Manhattan. The map is broken up into NTAs and the color of each neighborhood is determined by the mean (mcg per cubic meter) particulate matter levels. As we had hypothesized, there’s higher levels of particulate matter, which contributes to air pollution, around midtown Manhattan, while there is increased particulate matter in parts of Northern Manhattan. We hypothesize that Inwood and Washington Heights have lower levels of particulate matter, because of its numerous parks, green spaces and distance from midtown Manhattan.
When we first started working with the Particulate Matter dataset we had difficulty finding another dataset that would allow for a spatial join in Tableau, so we created a chart that helped us to quickly see the levels of particulate matter in each Manhattan neighborhood. We created a chart that displays the mean levels of particulate matter (mcg per cubic meter) in a bar chart format. It’s a quick visual representation. It’s easy to notice that midtown has high levels of particulate matter.
While thinking about the environmental hazards that exist in Northern Manhattan, we began to think about how these factors could increase vulnerability in children. We already came into this project with the knowledge that children in Northern Manhattan have increased asthma rates. This map is filtered by NTA to only include public schools in Manhattan and color coded by the type of school (early childhood, elementary, high school, junior high-intermediate school, K-8, K-12, secondary schools). This is not a true spatial map, as we had difficulty spatial joining the school data points with the NTA shapefile. However, because the school data points do have X and Y coordinates, so they maintain their “shape” when placed as a graph. The data points still look like Manhattan!
This week we started to test overlapping some of the maps we created. We tried to build these in Tableau, but we couldn’t figure out the complexities of the dual-axis needed. Therefore, we took simple screenshots and put them into Photoshop where we were able to play with the opacity of the screenshots to be able to layer them. We noticed a couple of things: toxic facilities and manufacturing zones are placed where they’re higher percentages of people of color, the most heat vulnerable locations are in neighborhoods where there’s high percentages of people of color, and there’s higher rates of PM 2.5 in areas where there’s toxic facilities placed.
- Racial demographics + toxic facility placement
- Racial demographics + Manufacturing zoning
- Racial demographics + Heat vulnerability
- Racial demographics + PM 2.5
- Toxic facility placement + PM 2.5
4. Understanding how zoning designations affect the present environmental, health, and lifestyle (like energy burden) hazards in Northern Manhattan
After meeting with our professor, we realized that we really wanted to use this project to explore things that we didn’t learn about before. Since we started to learn so much about zoning through our previous maps, we thought it would be interesting to take a look at how the zoning of Manhattan has changed overtime. One technical issue we’re running into with these maps is that the coloring is not the same for each zoning district type map to map. This makes the maps hard to compare visually. We found a work-around for this issue to make the different types of zoning more apparent to viewers–we colored all of the different zone types by grouping them into residential, manufacturing, or commercial. We also placed these maps side by side, to simplify the visual comparison.
5. Looking further into how zoning and rezoning efforts play a role in energy burden
This is a next step. We’re getting there!
Key Learnings:
There is a lack of consistency in units of measurement throughout different datasets. https://data2gohealth.nyc/faq.pdf
- Census Blocks
- Census Tracts
- CDs Community Districts
- UHF United Health Fund
- NTA Neighborhood Tabulation Areas
- PUMAs Public Use Microdata Areas (US Census created)
We created a Tableau dashboard that allows us to see the nuance between each of these types of units of measurement.
We also learned that there’s a bridge to these many levels of geographic measurement! (https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-nynta.page)
Zoning Research
- After there is a rezoning or major development project, the community can respond through a 197-a plan, which is essentially basically an assessment of what the community members concerns are, as well as what they want and need. There’s also an environmental review that every zoning proposal needs to create. One of the most challenging aspects to navigate, is that neither of these documents are legally binding. However, these documents are powerful and organizations like WE ACT and community members can work together with New York City council to craft a report.
- Most rezonings deal with FAR, which is Floor Area Ratio (the formula is total sq footage of all the floors of a building/total square footage of all the lot it’s on) and either trying to “upzone” which means increasing FAR or “downsize” which means decreasing FAR to protect the existing neighborhood scale. Most rezoning includes increasing FAR in some parts and decreasing FAR in other areas.
- Our last interesting and complicated learning is that most rezonings have recently been working to convert Manufacturing (M) zones to Mixed use zones (MX). MX is when manufacturing zones move to allow residential and commercial zoning in the same zone). We hypothesize that it may feel as though (potentially from an environmental perspective) that decreasing manufacturing zones would have a positive impact on the neighborhood, because less pollutants have the potential to be emitted, however this may leave communities fighting to keep manufacturing jobs We hypothesis that rezoning makes it harder for people to keep jobs; and developers see a decline in the manufacturing industry and believe rezoning will allow for new developments and the creation of more housing (but as we know, housing for other folks that are wealthier and probably white).
- A question we have is whether things are moving from M1 to MX or M3 to MX because that would mean there is a reduction in the number of sewage plants in low income communities of color, which seems like a positive finding. If this is the case, the development would have a mandatory affordable housing provision. However, removing industry bakeries and machine shops where people work, and where these are low polluting facilities, seems negative. We are left contemplating the complexity of recognizing the economic well being of a community along with environmental/ public health wellbeing. If all of these dimensions are not considered we run the risk of greenwashing.
- Learning through data analysis and map making
- Continued to learn about the difficulties of joining datasets that have different level of geographic measurement, and the importance of bridging these levels visually.
- Learning how data scientists come to use proxies
- It’s one thing to read about Cathy O’Neil’s book, Weapons of Math Destruction and come away thinking that proxies can be extremely problematic, and question why people use proxies, and then realize through this process that it is challenging to find publicly available data regarding energy cost per household with the exception of NYCHA buildings because they are public and must legally post that. The decision to not make that a proxy for all low income households was one made because we were aware of the potential issues with making this a proxy.
- Learned that heavy polluting M3 zone designations are supposed to have a lower polluting M1/2 zone in between heavy manufacturing zones and residential zones and we saw that this was not the case after map making.
Next steps based on this week’s learnings/research:
- What is the relationship between rezoned areas and rent burden over time in West Harlem (rezoned in 2012) and East Harlem ( rezoned in 2017)? (map)
- In our next round of work and research, we’d like to research Inwood’s recently passed rezoning proposal.
- What has the change in racial demographics and economic demographics been overtime post rezoning in Northern Manhattan? (map)
- What has been the change in affordable housing in Northern Manhattan overtime in West and East Harlem overtime post rezoning? (map)
- What rezoned areas in West and East Harlem had an increase in FAR? (visual but not map?)
- Why were they targeted for more development? What improvements were made to address increased population?
- What is being proposed in the Inwood rezoning?
- How large was the FAR increase? If this increased by 50% or more there is more pressure to demolish and build larger buildings. Did this happen?
- What rezoned areas in West and East Harlem had a decrease in FAR? (visual but not map?)
- Did FAR help preserve the neighborhood?
- Create a map that looks at M1 to MX and M3 to MX changes overtime.
- Was it contextual rezoning (regulates buildings created in a neighborhood to match the context of existing buildings)? (In West and East Harlem, Inwood proposal)
