R: Aligning/Sizing for plot_grid in cowplot?

Question

I'm having trouble with the sizing and aligning of one my plots using the plot_grid function in the cowplot package. The bottom left plot always seems to be a tad bit smaller then the others. I did some researching and couldn't seem to find anything that works. I'm new to R, so any help would be greatly appreciated! Thanks!

Attached is my code as well as what the plot is looking like and what I want it to look like

'#Data frame with huc results for each parameter
parameter_results <- readRDS("param_results_2014.RDS") %>% select(1:84)
#list of parameter names
parameters <- sort(readRDS("parameters.RDS"))

 blank_theme <- theme_minimal()+ theme(
  axis.title.x = element_blank(),
  plot.margin = unit(c(0,0,0,0), "pt"),
  axis.title.y = element_blank(),
  panel.border = element_blank(),
  legend.position=c(.5,.02),
  legend.direction="horizontal",
  legend.key=element_rect(colour="black",size=0.5,linetype="solid"),
  panel.grid=element_blank(),
  axis.ticks = element_blank(),
  plot.title= element_text(size=8, vjust=-4.0, face="bold")
)


#Function for creating poroportions table for parameters
parameter_summary <-function(parameter) {
  parameter_df <- parameter_results %>%
    select(results = parameter) %>%  #keep only column for the parameter you want to plot
    filter(results != "Not Applicable") %>%  #filters out 'not applicable' results
    count(results) %>%               #
    mutate(prop = prop.table(n), perc = paste0(round(prop * 100),"%"))
  return(parameter_df)
}


parameter_pie_chart <- function(parameter,title="",nudgex=5,nudgey=-10) {
  # parameter: the parameter you want to create a pie chart for, example: 'DO'
  # title: plot title, default is the name of the parameter

  parameter_df <- parameter_summary(parameter) 
  #data frame of proportions less than 10%. necessary because for these values, labels are implemented with an arrow
  small_perc <- parameter_df %>% filter(prop < .10)
  #dataframe of proportions greater than 10%
  signif_perc <- parameter_df %>% filter(prop >= .10)

  pie_chart <- ggplot(parameter_df, aes(x = "", y = n, fill = fct_inorder(results))) +
    geom_bar(stat = "identity", width = 1,colour='black') + 
    coord_polar(theta = "y") +
    blank_theme +
    theme(axis.text.x=element_blank()) + 
    theme(legend.title=element_blank()) +
    #ggtitle(title)+
    theme(plot.title = element_text(hjust = 0.5))   +
     geom_text(data = signif_perc, aes(label = perc), 
                position = position_stack(vjust = .5), size = 5, show.legend = F) +
    scale_fill_manual(values = c("Attaining" = "#99FF99","Insufficient Information" = "#FFFF99", "Non Attaining" = "#FF9999", "Not Applicable" = "orange"),labels=c("Attaining     ",
                                                                                                                                                                    "Insufficient Information    ",
                                                                                                                                                                    "Non Attaining      "))

  if (sum(parameter_df$prop < .10) > 0) {
    pie_chart <- pie_chart + geom_text_repel(data = small_perc, aes(label = perc), size= 5, show.legend = F, nudge_x = nudgex,nudge_y = nudgey)
  }


  pie_chart
  }


#Indivdual pie charts to create combined pie charts
pie_do <- parameter_pie_chart('DO') 
pie_TP<-parameter_pie_chart('Total Phosphorus')
pie_temp<-parameter_pie_chart('Temperature')
pie_pH<-parameter_pie_chart('pH')
pie_arcs<-parameter_pie_chart('Arsenic-HH')
pie_TDS<-parameter_pie_chart('Total Dissolved Solids')
pie_causebio<-parameter_pie_chart('Biological (Cause Unknown)')
pie_human_lead<-parameter_pie_chart('Lead-HH - DWS')
pie_mercury<-parameter_pie_chart('Mercury-HH')
pie_nitrate<-parameter_pie_chart('Nitrate')
pie_aluminum <- parameter_pie_chart("Aluminum")
pie_temp_trout<-parameter_pie_chart('Temperature Trout')
pie_do_trout<-parameter_pie_chart('DO Trout')
pie_fish_merc<-parameter_pie_chart('Fish-Mercury')
pie_fish_ddt<-parameter_pie_chart('Fish-DDx')
pie_fish_dioxin<-parameter_pie_chart('Fish-Dioxin')
pie_fish_chlordane<-parameter_pie_chart('Fish-Chlordane')
pie_fish_pcb<-parameter_pie_chart('Fish-PCB')
pie_human_arsenic<-parameter_pie_chart('Arsenic-HH')
pie_TDS<-parameter_pie_chart('Total Dissolved Solids')
pie_arsenic_dws<-parameter_pie_chart('Arsenic HH - DWS')
pie_trout_do<-parameter_pie_chart('DO Trout')
pie_unknown_trout<-parameter_pie_chart('Biological Trout (Cause Unknown)')
pie_ecoli<-parameter_pie_chart('e.Coli')
pie_enterococcus<-parameter_pie_chart('Enterococcus')
pie_beach_enterococcus<-parameter_pie_chart('Beach Closing (Enterococcus)')
##Figure 2.10
combined_plot1 <- plot_grid(pie_human_arsenic + theme(legend.position="none"), 
                           pie_TDS + theme(legend.position = "none"),
                           pie_human_lead + theme(legend.position = "none"),
                           pie_mercury + theme(legend.position = "none"),
                           pie_nitrate + theme(legend.position = "bottom"),
                           nrow = 2,ncol=3,align="hv",labels=c("Arsenic,human health","TDS","Lead,human health","Mercury,human health","Nitrate"),label_fontface="bold",label_size=10,hjust=-0.3,vjust=9)+
                          draw_label("Figure 2.10:Assessment Results for Key Parameters Associated with Water Supply Use,\nPercent(%) of 826 AUs",fontface="bold",hjust=0.5,vjust=-14.5)
ggsave(filename="Figure2.10-Water Supply Use.pdf",path="V:/lum/WM&S/BEAR (Bureau of Environmental Analysis and Restoration)/Envpln/Hourly Employees/KevinZolea/Rwork/2014IR/PieCharts",width=11.5,height=11)
`

Plot that I have:

Plot I Want: