BRICK CITY
The expedition to Newark, New Jersey
My first home, University Heights. Photo: Willem Frankfort
My First Home
The city of Newark, New Jersey has had a profound influence on my life. My parents met there in the late nineteen-seventies at Rutgers University's concrete campus. They married at a small church nearby. I was born at Clara Maas hospital, near Branch Brook Park, where the petals of cherry blossoms blow through the air like light flurries of snow. My father was the senior division operator of the Newark Airport Express Mail facility for the US Postal service for thirty-eight years. My first home was at 154 Washington Street, across the street from Rutgers Law school. Though my family moved a few miles up the hill, to the lush and green township of Montclair, I remained drawn to this urban center. I returned there to work and study at Rutgers, in the same buildings my mother attended classes, carrying me in a sling. I worked there for almost a decade in the law school computer labs. I am intimately familiar with the streets of Newark, its people, thriving art scene, and its districts.
Returning to Give Back
Route 280, Exit 13. Photo: Willem Frankfort
This is my first semester at Johns Hopkins. I joined this program because I want to do my part to help reverse climate change. I wanted to be sure to pick a topic with this goal in mind when I proposed my independent research project for my Principles and Methods of Ecology course. While pondering topics for my first post graduate research paper, my thoughts kept returning to this city, where I had spent so much time. Newark, NJ is a major shipping and transportation hub in the Northeastern United States. In past decades, this city became synonymous with urban decay. Newark had been ravaged by civil unrest, riots, poverty, and pollution. In the 21st Century, urban renewal programs, educational initiatives, and an influx of investment have begun to transform the greater Newark area.
I wanted to understand the connections between climate change and the economic activities behind up and coming cities like Newark. Where I live, in the town of Montclair, the air quality is much better. Considering the disparity in per capita affluence between these two municipalities, I began to research methods of modeling human environmental impact using population and economic data from the Census. My research led me to a family of equations arising from the IPAT [I = P x A x T] equation, formulated by Ehrlich and Holdren in 1971 (Ehrlich and Holdren, 1971). In the nineteen-nineties, a stochastic version of IPAT known as STIRPAT was created by Dietz and Rosa (Dietz and Rosa, 1994 & 1997). STIRPAT stands for Stochastic Impact by Regression of Population, Affluence, and Technology. IPAT is a simple multiplicative identity, whereas STIRPAT describes a more elastic relationship between these interlinked variables. Armed with this knowledge, I endeavored to find out whether the population and affluence of Newark residents could predict which neighborhoods would produce the most carbon emissions in order to inform the creation of a suitability model for the construction of carbon capture sites. Econometric analysis is an important tool in the field of industrial ecology.
Weequahic. Photo: Willem Frankfort
Newark Terrain (ESRI)
Newark was built on rugged terrain with varying elevations, which had an influence on the layout of the city. The industrial and commercial zones are located near the water, where the elevations are low and the terrain is flatter. I chose six neighborhoods across the city to test my hypothesis. I ranked these neighborhoods by population and affluence and attempted to predict which of them would have the highest CO2 emissions readings. These neighborhoods included Roseville, University Heights, Ironbound, Vailsburg, Central Business District, and Weequahic/Airport. Baseline readings were taken at Bear Mountain State Park in Stony Point, New York. The baseline CO2 concentration was determined to be 385 PPM in this region. The map below is equipped with a search window, with which to search for these neighborhoods to see their locations.
Newark Locations (ESRI)
The Hypothesis and the Data
Using the IPAT and STIRPAT equations as a basis, I made a prediction that populated residential areas would yield high carbon dioxide readings. If the affluent neighborhoods with the highest populations yield the highest readings, it would validate the IPAT model as an accurate predictor. If lower affluence neighborhoods yield higher readings than the high affluence neighborhoods, it would indicate that STIRPAT is the more accurate predictor. However, if a low population neighborhood yields the highest emissions readings, it would indicate that neither model could accurately predict the locations of high emissions readings.
61 Field Measurements
Results
Impact, Population, Affluence, and Technology 2010-2020. Willem Frankfort
Although my econometric analyses supported previous studies regarding the connection between affluence and environmental impact, I was unable to use the predictions of these formulae to locate regions with high carbon emissions. This could be due to the limitations of my hand held air quality tester, but the highest readings were located in the commercial districts, industrial districts, and transportation hubs. While less affluent individuals may cause more emissions than their wealthier neighbors, those emissions do not necessarily occur near their residences. I decided to take another approach using GIS technology.
Results
GIS
Newark NJ Zoning Districts. Source: ArcGIS Portal (ESRI)
Using zoning data, I determined that the highest readings occurred at Newark Liberty International Airport, Ironbound, and Central Business District. These are heavily trafficked areas. In future research, districts zoned mostly for commercial and industrial purposes will become the main areas of focus, although I may revisit predominantly residential areas with a more sophisticated measuring apparatus.
Panchromatic. Source: USGS
The panchromatic band (8) produces the highest resolution, but it is difficult to distinguish types of land cover.
5,3,8 Spectral Band Analysis. Source: USGS
I stumbled across this band combination in attempts to increase the contrast and resolution of the default vegetation analysis settings. The panchromatic band doubles the resolution, while the near infrared band clearly highlights plant cover. This allows one to quickly assess which areas contain industrial and commercial facilities, as well as their distance from plants which would mitigate their emissions. The airport, Central Business District, and Ironbound can be clearly identified here. Areas in these regions which also lack tree cover are sure to be high emissions zones.
Slope Raster. Source: USGS
The highest emissions regions were found in the districts with the flattest terrain, and low elevations.
Wrapping Up
The many faces of brick city. Photos: Willem Frankfort
Although I was unable to utilize econometric data in the way that I had hoped, this research has provided insights into the connection between economics and environmental degradation. As the affluence of Newark residents increases, it will become a cleaner city. My readings helped me to understand how to devise a better experiment, and took me one step closer to my goal of designing a suitability model for carbon capture sites. In the future, cities like Newark could build a thriving carbon capture industry, turning the pollutant into commodities for the market. In turn, this influx of money, if distributed evenly, could lead to a reduction in emissions... balancing the ledger on both ends. I believe that if can be proven to wealthy financiers that it's possible to make money by removing carbon from the atmosphere, it would have a three-pronged effect. First, overall CO2 concentration would experience a massive decrease because carbon capture facilities would be constantly removing it from the atmosphere. Second, proven profitability of carbon capture would attract financial and corporate interests, and incentivize them to build more facilities. Thus, the number of facilities would increase exponentially until the process ceases to be profitable (i.e. when CO2 concentration returns to pre-industrial levels and it costs more to operate a facility than it takes in). Third, the installation and operation of these facilities will create good paying jobs, which will boost the average yearly salary and raise the standard of living. Given the negative correlation between affluence and environmental impact, this should contribute to an overall reduction in emissions. Thank you for taking the time to review my presentation! Thank you to the City of Newark and its people for all they have done for me, and I hope to return the favor.