Data Analysis of Lead Contamination in New York

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Water is one of the most precious resources on the Earth. It is shared by man, animals, and plant life. Up until the Flint Michigan water crisis in 2012, many Americans were ignorant to the legitimacy of their public water systems. As infrastructure continues to age, and with more advance mining techniques such as fracking continue to deliver unsavory elements into our water supply, it is imperative that we maintain a keen eye on our water systems. This paper looks at the lead contamination levels of schools in the state of New York. Over 43,000 pipes were flagged as having more than 15 ppb of lead contamination. 4,041 are flagged as out of service, and there exist 8,300 lead free buildings in the state. We extended the school level analysis to county level analysis to test the hypothesis to know whether there exists some factor that governed the distribution of lead levels across the counties. Results indicate that there is not any single factor, that governs the distribution of the lead across the counties. While the analysis shows improvement, however more steps need to be taken at a national level to secure the safety of our nation's water supply. Results and future actions are described in this paper.
Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Place of Publicationusa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1614-1619
Number of pages6
ISBN (Electronic)9781728125473
DOIs
StatePublished - Dec 1 2020
Event2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Canberra, Australia
Duration: Dec 1 2020Dec 4 2020

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Country/TerritoryAustralia
CityVirtual, Canberra
Period12/1/2012/4/20

Keywords

  • Contamination
  • Lead
  • New York Schools
  • R statistical analysis
  • Water

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