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How has Air Quality changed over 2017 in the San Francisco Bay Area, and how was it affected by the October Sonoma Fires? Using Python libaries such as matplotlib.pyplot, seaborn, numpy, json and requests; and the AIR NOW API, we charted distributions over time and space of pollutant particulates across the Bay Area's counties.

HP-Nunes/airQualityInTheBayArea_October2017

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Air Quality in the San Francisco Bay Area and the 2017 Sonoma Fires, An Observation of Data Trends

04/07/18

The Northern California firestorm of October 2017 were a series of 250 wildfires which burned down over 245,000 acres over six counties, including Napa, Sonoma, and Solano county in the San Francisco Bay Area. These fires are the costliest wildfires on records, surpassing the 1991 Oakland firestorm, and the deadliest week of wildfires in California history with 44 fatalities.

Air pollution stemming from the fires reached hazardous levels, notably in the city of Napa on October 12th which was ranked poorest in the United States. Schools and outdoor activities were cancelled in many cities due to poor air quality, and the San Francisco Internation Airport canceled over 280 flights over a three days period due to visibility issues. Speaking from first-hand account, the city of San Francisco was enveloped in a smokey haze for several days, and a burned odor was clearly detectable even indoors for a couple of days.

Thus the theme of Air Quality is of interest due to the close proximity of the fires, its wide ranging impact over a major urban area, and the historical scope of its scale and impact.

Research Inquiry:

How has Air Quality changed over 2017 in the San Francisco Bay Area?

What are characteristic parameters which reveal trends in air quality?

What is the magnitude of the changes in air quality due to the events such as the Sonoma fires, compared to normal atmospheric condition in the Bay Area?

Prerequisites

Python/Anaconda version

  • Python 3.6.1 (64-bit)
  • conda 4.3.29

Libraries used

  • matplotlib.pyplot
  • requests
  • json
  • pandas
  • pprint
  • seaborn
  • numpy

API used

  • airnowapi.org

About

How has Air Quality changed over 2017 in the San Francisco Bay Area, and how was it affected by the October Sonoma Fires? Using Python libaries such as matplotlib.pyplot, seaborn, numpy, json and requests; and the AIR NOW API, we charted distributions over time and space of pollutant particulates across the Bay Area's counties.

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