Homework-2, 8610
metricsdawg
2023-01-20
Atmospheric Environmental Conditions in the New York City
To understand the environmental conditions in the NY, we use environmental dataset inbuilt in R. The data comes from the New York City during 05-09, 1973.
Original Source of data: Bruntz, S. M., W. S. Cleveland, B. Kleiner, and J. L. Warner. (1974). The Dependence of Ambient Ozone on Solar Radiation, Wind, Temperature, and Mixing Height. In Symposium on Atmospheric Diffusion and Air Pollution, pages 125–128. American Meterological Society, Boston.
1) Data Summary
library(lattice)
data(environmental)
str(environmental)## 'data.frame': 111 obs. of 4 variables:
## $ ozone : num 41 36 12 18 23 19 8 16 11 14 ...
## $ radiation : num 190 118 149 313 299 99 19 256 290 274 ...
## $ temperature: num 67 72 74 62 65 59 61 69 66 68 ...
## $ wind : num 7.4 8 12.6 11.5 8.6 13.8 20.1 9.7 9.2 10.9 ...summary(environmental)## ozone radiation temperature wind
## Min. : 1.0 Min. : 7.0 Min. :57.00 Min. : 2.300
## 1st Qu.: 18.0 1st Qu.:113.5 1st Qu.:71.00 1st Qu.: 7.400
## Median : 31.0 Median :207.0 Median :79.00 Median : 9.700
## Mean : 42.1 Mean :184.8 Mean :77.79 Mean : 9.939
## 3rd Qu.: 62.0 3rd Qu.:255.5 3rd Qu.:84.50 3rd Qu.:11.500
## Max. :168.0 Max. :334.0 Max. :97.00 Max. :20.700There are 111 observations, 0 missing values and the following 4 variables:
ozone: Average ozone concentration (of hourly measurements) of in ppb.
radiation: Solar radiation (from 08:00 to 12:00) in langleys.
temperature: Maximum daily temperature in degree F.
wind: Average wind speed (at 07:00 and 10:00) in mph.
This description is based on Picostat Website (2022): click here
The variables will be useful to understand how ozone concentration is affected by radiations and how it inturn changes our atmospheric temperature.
2) Frequency Table for our temperature variable:
tab1(environmental$temperature, cum.percent = TRUE)
## environmental$temperature :
## Frequency Percent Cum. percent
## 57 1 0.9 0.9
## 58 1 0.9 1.8
## 59 2 1.8 3.6
## 61 3 2.7 6.3
## 62 2 1.8 8.1
## 63 1 0.9 9.0
## 64 2 1.8 10.8
## 65 2 1.8 12.6
## 66 2 1.8 14.4
## 67 3 2.7 17.1
## 68 4 3.6 20.7
## 69 2 1.8 22.5
## 70 1 0.9 23.4
## 71 3 2.7 26.1
## 72 3 2.7 28.8
## 73 4 3.6 32.4
## 74 2 1.8 34.2
## 75 2 1.8 36.0
## 76 6 5.4 41.4
## 77 4 3.6 45.0
## 78 4 3.6 48.6
## 79 3 2.7 51.4
## 80 3 2.7 54.1
## 81 10 9.0 63.1
## 82 7 6.3 69.4
## 83 3 2.7 72.1
## 84 3 2.7 74.8
## 85 3 2.7 77.5
## 86 5 4.5 82.0
## 87 3 2.7 84.7
## 88 2 1.8 86.5
## 89 2 1.8 88.3
## 90 3 2.7 91.0
## 91 1 0.9 91.9
## 92 3 2.7 94.6
## 93 2 1.8 96.4
## 94 2 1.8 98.2
## 96 1 0.9 99.1
## 97 1 0.9 100.0
## Total 111 100.0 100.03) Diagrammatic Representation of how ozone concentration changes with solar radiations:
library(MASS)
library(ggplot2)##
## Attaching package: 'ggplot2'## The following object is masked from 'package:epiDisplay':
##
## alphaplot(environmental$radiation, environmental$ozone,
main = "Ozone vs Solar Radiation",
xlab = "Solar Radiation (in langleys)",
ylab = "Ozone Concentration (in ppb)")
abline(lm(environmental$ozone ~ environmental$radiation), col = "red")
4) Diagrammatic Representation of how maximum atmospheric temperature changes with solar radiations:
plot(environmental$radiation, environmental$temperature,
main = "Temperature vs Solar Radiation",
xlab = "Solar Radiation (in langleys)",
ylab = "Maximum Atmospheric Temperature (degree F)")
abline(lm(environmental$temperature ~ environmental$radiation), col = "blue")
library("ggpubr")
corr <- cor(environmental$ozone, environmental$temperature, method = "pearson")5) Conclusion from these plots:
With the increase in solar radiation from 8-12 AM, the average ozone concentration increases which also increases the NY City maximum daily temperature. The pearson correlation between ozone and temperature is also positive (0.6985414), which suggests that they increase together.