Over the past 3 weeks we have been looking at different environmental data in different locations around the world in order to analyze the Capitalocene. In general, the Capitalocene analyzes how as countries become more economically advanced the worse their effect on the environment is. In our first lab we use EPI and World bank data to compare income level with region their environmental impact. Graphing this data showed us a possible trend in that less developed and lower income countries tended to have a worse EPI scores. Our second lab we wanted to look at more factors that contribute to the Capitalocene to potentially see further correlation. Using deforrestation and ubran growth I looked for trends that may connect these things to regions EPI scores. So, for our third lab we analyzed world values survey v.s income level. We specifically looked at citizens responses to Economic development v.s Environmental protection, by finding a hypothesis and a p value based on our data, we proved that the lower the countries income the higher they’ll prioritize economic growth over environmental protection. All these labs helped us analyze the ideas of the Capitalocene and how the world’s current environmental data correlates.
For this final Capitalocene lab we shifted our focus to environmental justice, EJ. The U.S EPA defines environmental justice as ““the fair treatment and meaningful involvement [emph. added] of all people regardless of race, color, national origin, or income with respect to the development, implementation and enforcement of environmental laws, regulations and policies”. We analyzed this data while relating it to the Capitalocene by looking at race v.s class, specifically we wanted to look at environmental injustice having to do with toxicities. We also utilized multiple Portland Air Toxicity Reports (PATS) in order to look at pollution that affects the Portland area. We specifically focused on polycyclic aromatic hydrocarbons, which is pollution from wood combustion. We chose this because based on PATS report, this is the pollutant they were most worried about. We did this in order to see spacial coincidences with waste and race/class. While it may connect to the Capitalocene in some ways, some issues with analyzing this type of data is that spatial correlation may not imply causation. We will further talk about factors that might affect our data when we discuss our maps. To begin this lab we imported data from ACS and PATS data. The ACS is a census community survey that regularly gathers information on different demographics. The PATS data is from the Portland Air Toxics Solutions. This is a database of toxic air pollutants recorded in the Portland region. For our lab we used the toxin PAH15, or Poly Aromatic Hydrocarbons. This toxin is an outcome from wood combustion and is the pollutant PATS is most concerned about. The ACS data contains information on income and race based on citizens residence. We were able to manipulate this data by combining income over $100,000 to make a high income group and combining low income (under $50,000) groups. Additionally we combined the black and hispanic groups to create a minority race group to compare to the residence location of white citizens. As you can see from the heat map, the toxin PAH15 is dispersed around Portland. The toxins are in highest concentration in the North Portland area as well as near Beaverton. We chose to break up the ACS data into four groups. These groups consisted of income over 100,000 dollars, income below 50,000 dollars, white residents, and black and hispanic residents. Doing so we sought to find out how these groups may be settled among the toxins map. The high income group seems to reside farther outside the city, away from these toxins. The exception would be a cluster in the center of the city which is also an expensive place to live. A lot of the low income group resides not in the center of the city but also not on the far out cleaner suburban areas. There is an even larger divide between white residents and black and hispanic ones. The white residents are settled more on the outside on the city in lower pollution areas. The minority residents seemed to be living in closer proximity to the city in higher toxin areas. We only have access to these groups residences and not where they are employed. It could be that the ACS groups we looked at may be more or less exposed based on where they work. This is a limitation of what our data allows us to look at. The results seem to indicate that low income and minority groups are more exposed to this type of air pollutant. I believe it would be interesting to look at low income minority groups and low income white groups to see if race is important or if it depends mostly on the income level. Additionally it may be interesting to see if minorities make up the majority of the low income sections. |
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