Baby’s First Quarto

CO₂ trends, 1958 - 2020

This report uses the NOAA ESRL dataset from Module 2 to highlight the increase in CO² concentrations over 7 decades. Source: National Environmental Pro

The dataset shows a steady increase in atmospheric CO₂ concentrations since 1958. Mean annual concentrations increased in every decade, and the magnitude of the increase generally became larger over time, particularly after 1990.

Plotting the annual CO₂ concentration, with an emphasis on decadal increases

co2 = read.table("co2_mm_mlo.txt", 
col.names = c("year", "month", "decdate", "average", "interpolated", "trend", "ndays"))

AnnualCO2 = tapply(co2$interpolated, co2$year, mean)
AnnualYear = as.numeric(names(AnnualCO2))

mycols = ifelse(AnnualYear < 1960, "purple",
         ifelse(AnnualYear < 1970, "blue",
         ifelse(AnnualYear < 1980, "darkcyan",
         ifelse(AnnualYear < 1990, "green",
         ifelse(AnnualYear < 2000, "orange",
         ifelse(AnnualYear < 2010, "red",
                "brown"))))))

plot(AnnualYear, AnnualCO2,
     col = mycols,
     pch = 16,
     xlab = "Year",
     ylab = expression("Mean" ~ CO[2] ~ "(ppm)"),
     main = expression("Annual Mean" ~ CO[2] ~  "Concentration"))   

legend("topleft",
       legend = c("1950s", "1960s", "1970s", "1980s",
                  "1990s", "2000s", "2010s"),
       col = c("purple", "blue", "darkcyan", "green",
               "orange", "red", "brown"),
       pch = 16,
       title = "Decade")

Annual mean atmospheric CO₂ concentration from 1958–2020, with points colored by decade.

Mean CO₂ concentration by decade

   1950s    1960s    1970s    1980s    1990s    2000s    2010s 
315.6076 320.2862 330.8544 345.5428 360.4614 378.5815 401.4693 

The dataset shows a steady increase in atmospheric CO₂ since 1958, with larger increases in later decades.

    1960s     1970s     1980s     1990s     2000s     2010s 
 4.678583 10.568250 14.688417 14.918583 18.120083 22.887818 

Module 3, Exercise 2 code

The assignment:

1. Create a vector containing all CO2 concentrations for all years up to and including 1985 (Use the column headed ‘interpolated’ for the CO2 values)
2. Create a vector containing all CO2 concentrations for all years following 1985
3. Estimate the mean CO2 concentration for each of these vectors
4. Convert the months in the CO2 data frame to factors and create a new column called ‘fmnth’ to store this in the data frame.
   1. Use the levels() and table() functions to a) make sure this worked, and b) see how many observations you have for each month.

co2 = read.table("co2_mm_mlo.txt", 
col.names = c("year", "month", "decdate", "average", "interpolated", "trend", "ndays"))

names(co2)
#co2 concentration after 1985

Conc1 = subset(co2, year <= 1985)
Conc1

Vec1 = Conc1$interpolated
Vec1

Conc2 = subset(co2, year > 1985)
Conc2
Vec2 = Conc2$interpolated
Vec2

mean1 = mean(Vec1, na.rm = TRUE)
mean1

mean2 = mean(Vec2, na.rm = TRUE)
mean2

fmnth = factor(co2$month)
fmnth
levels(fmnth)
table(fmnth)