Plot two different axis in ggplot

dual_axis.R

# set the limits of each axis
# these will need to be changed for each data 
# use summary(df) to get metrics
ylim_prime <- c(0.35, 0.76)
ylim_sec <- c(6200, 12000)

# calculate values for use in plot
b <- diff(ylim_prime)/diff(ylim_sec)
a <- ylim_prime[1] - b*ylim_sec[1]

# grab color variable
col1 <- unname(cadmus_palettes$cool2)[1]
col2 <- unname(cadmus_palettes$cool2)[2]

load_emssions %>% 
  arrange(Month, Day, HourBeginning) %>% 
  group_by(Month, HourBeginning) %>% 
  summarise(co2_per_mwh = mean(co2_per_mwh),
            load = mean(load),
            co2 = mean(co2)) %>% 
  mutate(Month = as.factor(month.abb[Month])) %>% # match month names to number 
  ggplot(aes(x = HourBeginning, y = co2_per_mwh)) +
  geom_line(color = col1) +
  geom_line(aes(y = a + load * b), color = col2) +
  # Create the second axis and name it
  scale_y_continuous(sec.axis = sec_axis(~(. - a) / b, name = "Demand", labels = comma)) +
  facet_wrap(~ Month) +
  labs(x = "Hour Beginning",
       y =  bquote(~'CO'^2~'/MWh'),
       col = "Value") +
  # Set the labels to color coordinate with the lines
  theme(
    axis.line.y.right = element_line(colour = col2),
    axis.ticks.y.right = element_line(colour = col2),
    axis.text.y.right = element_text(colour = col2),
    
    axis.line.y.left = element_line(colour = col1),
    axis.ticks.y.left = element_line(colour = col1),
    axis.text.y.left = element_text(colour = col1),
)