M9 Assignment with Discussion National Ambient Air Quality Standards (NAAQS) can
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M9 Assignment with Discussion
National Ambient Air Quality Standards (NAAQS) can be found at the EPA’s website. Over the past 50 years the standard annual mean for fine particulate matter PM2.5 has been significantly tightened, starting out at 75 µg/m3 of air in 1971 and now only 12 µg/m3 of air (as of 2012 standards).
Work with the Data
Create a new tab in your Excel file (the same Excel file from your Module 7 and Module 8 Assignment and Discussion) and label it “Mod 9”. Copy the following three columns from your raw data tabs into this new worksheet: Daily Mean PM2.5 Concentration 2020, Daily AQI Values 2019, and Daily AQI Values 2020. Note that the number of rows may differ between 2019 and 2020.
Use StatCrunch to find a 90% confidence interval for the Daily Mean PM2.5 Concentration from your 2020 data. Note the two conditions for a valid confidence interval are met. Insert the StatCrunch results into your Mod 9 worksheet, to the right of the three columns of data.
Utilize Excel’s COUNTIF function to find how many days in your 2020 data had a Daily Mean PM2.5 Concentration over 12 µg/m3.
Learn more about the Air Quality Index (AQI) which is calculated for four major air pollutants regulated by the Clean Air Act in the AQI Brochure. Page 3 of the PDF file of this brochure (which is numbered page 2 on the brochure) includes a table noting levels of health concerns for various air quality index values. In your Mod 9 worksheet, create a table containing a row for each range of AQI values (as found in the brochure) and a column for each of the following: Levels of Health Concerns, # of days 2019, and # of days 2020. Utilize the COUNTIF function in Excel to find the number of days within each range of AQI values on the table, for each year of your data. For example, to find the number of days with AQI in the Moderate Level of Health Concern (AQI 51 to 100), use this command (adapt to reflect the appropriate cells in your data file): =COUNTIF(G2:G477,”<101")-COUNTIF(G2:G477,"<51"). The Discussion Assignment Your main discussion post should have a descriptive title/subject, one that includes the name of the county and state, along with an appropriate title for what you are presenting. Within that main discussion post, address all of the following (using complete, descriptive sentences). Attach your Excel file to this discussion post. What is the confidence interval for your 2020 PM2.5 Concentration data? The textbook noted that confidence intervals may be reported in two different ways (see page 348 of the textbook). Report your confidence interval in both formats, using appropriate mathematical notation. Which format do you find to be more useful or clearer? Is the 12 µg/m3 of air standard mean contained in your confidence interval? With standards getting stricter over time, it is possible that even if it the current standard is not contained in the confidence interval a future stricter standard might be. What concerns might you have if this were contained in your confidence interval? What can you interpret from this? Did your county have any days over the 12 µg/m3 of air standard annual mean for fine particulate matter, and if so how many? Note that the 12 µg/m3 is an annual mean, so that over the course of the year the AVERAGE for any given area should be under that value. As an average, one would expect some days to be higher and some days to be lower concentrations, but the overall average for the year should be below this value to meet the EPA's standards. If your county had days over this value, what might have caused these spikes (one thing to consider is time of year)? In addition to your main post, you are to respond to at least two other students’ main posts. Substantive responses to other students’ main posts might include the following: (1) a detailed comparison of your results to their results including proposing why the results might (or might not) differ between your two regions, or (2) detailed and polite recommendations for improvements should their work be incorrect or not fully meet the assignment's requirements.