diff --git a/howTo/openGeogAPI/local_auth_ghg_plots.R b/howTo/openGeogAPI/local_auth_ghg_plots.R
index 26acc4679273503ad9ed5594c63862471ffd489a..d759f77e906915393b937628003c1ad77bb90a13 100644
--- a/howTo/openGeogAPI/local_auth_ghg_plots.R
+++ b/howTo/openGeogAPI/local_auth_ghg_plots.R
@@ -134,6 +134,11 @@ ghg_subset <- function(dt, auth_area = "Southampton"){
 }
 
 # Construct plots ----
+plotCaption = paste0("Emissions data: Department for Business, Energy & Industrial Strategy",
+                     "\nUK local authority and regional carbon dioxide emissions national statistics: 2005 to 2018",
+                     "\nVisualisation: t.w.rushby@soton.ac.uk | energy.soton.ac.uk")
+
+# Emissions by year for each local authority
 i <- 1
 plotNames <- list()
 
@@ -141,10 +146,6 @@ for (auth_area in las_to_load) {
   
 plotName <- paste0("laemissions_by_year_",gsub("[[:space:]]", "_", auth_area))
 
-plotCaption = paste0("Emissions data: Department for Business, Energy & Industrial Strategy",
-                     "\nUK local authority and regional carbon dioxide emissions national statistics: 2005 to 2018",
-                     "\nVisualisation: t.w.rushby@soton.ac.uk | energy.soton.ac.uk")
-
 plotTitle = paste0("Greenhouse gas emissions by source: ",auth_area)
 
 plot_data1 <-  ghg_subset(pc_detail_plot, auth_area = auth_area)
@@ -176,8 +177,9 @@ i <- i+1
 
 print(plotNames)
 
-# By local authority
+# Emissions by local authority
 years_to_plot <- c(2005,2018)
+plot_year <- 2018
 
 for(plot_year in years_to_plot) {
   
@@ -210,6 +212,34 @@ for(plot_year in years_to_plot) {
   
 }
 
+# Emissions for single local authority
+
+plot_data1 <-  pc_detail_plot %>% filter(Year == plot_year & Name == auth_area)
+plot_data2 <- pc_totals_plot %>% filter(Year == plot_year & Name == auth_area)
+
+x_min <- floor(min(plot_data2$value))
+x_max <- ceiling(sum(plot_data2$value))
+
+plot <- ggplot() +
+  geom_col(data = plot_data1, aes(x = Name, y = value, fill = variable), position = "stack") +
+  #geom_col(data = plot_data2, aes(x = Name, y = value, colour = variable), fill = NA, position = "stack") +
+  geom_hline(yintercept=0, lwd=0.4, colour="black", linetype = "dashed") +
+  coord_flip(ylim = c(x_min,x_max)) +
+  scale_y_continuous(breaks = x_min:x_max) +
+  scale_color_manual(values = totals_pal) +
+  scale_fill_manual(values = detailed_pal) +
+  theme_minimal() +
+  labs(y = "Emissions per capita (tonnes of carbon dioxide/person)") +
+  theme(axis.text.y = element_blank(),
+        axis.title.y = element_blank(),
+        axis.ticks.y = element_blank(),
+        #axis.title.x = element_blank(),
+        panel.grid.major.y = element_blank(),
+        legend.position = "none")
+
+ggplotly(plot)
+
+
 ggplot() +
   geom_col(data = plot_data1, aes(x = Name, y = value, fill = variable), position = "stack") +
   geom_col(data = plot_data2, aes(x = Name, y = value, colour = variable), fill = "none", position = "stack") +