Greenhouse gas emissions for Northern Ireland by source sector for the years 1990 to 2021. Further information available from
https://www.daera-ni.gov.uk/articles/northern-ireland-greenhouse-gas-inventory
Reader Information
These statistics are based on the NI bulletin of the greenhouse gas inventory. The greenhouse gas inventory data are produced annually by Ricardo Energy and Environment, on behalf of the Department for Business, Energy & Industrial Strategy, the Scottish Government, the Welsh Assembly Government and the Northern Ireland Department of Agriculture, Environment and Rural Affairs. Each year the greenhouse gas inventory is extended and updated. The entire historical data series, from base year to 2021, is revised to incorporate methodological improvements and new data. This takes into account revisions to the datasets used in its compilation.
Emissions are reported for seven greenhouse gases: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Depending on their molecular weights, radiative properties and residence times in the atmosphere, each greenhouse gas has a different capacity to cause global warming. The base year is 1990 for carbon dioxide, methane and nitrous oxide, and 1995 for the fluorinated gases. The fluorinated gases are hydrofluorocarbons, perfluorocarbons, sulphur hexafluoride and nitrogen trifluoride. Emissions are reported according to the National Communication sectors in accordance with international reporting guidelines from the United Nations Framework Convention on Climate Change (UNFCCC).
The greenhouse gas emission estimates are based on a wide range of data sources and sources of uncertainty include statistical differences, assumptions, proxy datasets and expert judgement. In addition, the natural variability in the processes that are being modelled introduce uncertainty. For example, carbon content of fuels and farming practices under different climatic conditions and soil types. The uncertainties presented are a close approximation of the 95% confidence interval. The width of the interval provides a measure of the accuracy of the estimates. Uncertainty estimates for Northern Ireland emissions are available for the base year, the latest year (2021) and for the percentage change between the two years. For the base year, uncertainty is ±8%, and for 2021 it is ±5%. For the percentage reduction between the base year and 2021, the uncertainty interval ranges from 16% to 33%. There remains greater uncertainty around emissions in Northern Ireland compared to other parts of the United Kingdom due to the relative importance of methane and nitrous oxide emissions in the agriculture sector. Emissions of this gas are more difficult to estimate than carbon dioxide, and the agriculture sector makes up a larger share of Northern Ireland’s emissions than in other parts of the UK.
The UK greenhouse gas inventory National Statistics user guide provides a simple guide to the origins and use of data in the compilation of the UK Greenhouse Gas Inventory. This guide can be accessed through the Department for Business, Energy & Industrial Strategy website https://www.gov.uk/government/publications/uk-greenhouse-gas-emissions-statistics-user-guidance.
Contact Details
DAERA Statistics & Analytical Services Branch is keen to hear your feedback.
Please e-mail comments to env.stats@daera-ni.gov.uk
Further information can be found on the DAERA Statistics website https://www.daera-ni.gov.uk/landing-pages/statistics
```
---
title: "Northern Ireland greenhouse gas inventory 1990 - 2021"
output:
flexdashboard::flex_dashboard:
orientation: rows
theme: cerulean
source_code: embed
navbar:
- { title: "Cookies", href: "https://www.nisra.gov.uk/cookies", align: right }
---
<!--html_preserve-->
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new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
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<!--/html_preserve-->
```{r setup, message=F}
knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)
#LOAD PACKAGES
library(flexdashboard)
library(knitr)
library(crosstalk)
library(DT)
library(tidyverse)
library(plotly)
library(stringr)
library(reshape2)
# READ IN THE DATA
GHG <- read.csv("ghg emissions 2021.csv", header = T, stringsAsFactors = F)
# TIDY THE DATA UP
GHG$Year[GHG$Year == 'BaseYear'] <- 1989
kpis <- names(GHG)[c(3)]
GHGall <- melt(GHG, id=1:2)
GHGall$Sector[GHGall$Sector == "Agriculture"] <- "Agriculture"
GHGall$Sector[GHGall$Sector == "Business"] <- "Business"
GHGall$Sector[GHGall$Sector == "Energy Supply"] <- "Energy Supply"
GHGall$Sector[GHGall$Sector == "Industrial processes"] <- "Industrial Process"
GHGall$Sector[GHGall$Sector == "Land use, land use change and forestry"] <- "Land Use Change"
GHGall$Sector[GHGall$Sector == "Public"] <- "Public"
GHGall$Sector[GHGall$Sector == "Residential"] <- "Residential"
GHGall$Sector[GHGall$Sector == "Transport"] <- "Transport"
GHGall$Sector[GHGall$Sector == "Waste Management"] <- "Waste Management"
GHGall$Sector[GHGall$Sector == "Northern Ireland"] <- "Northern Ireland"
GHGall$Sector[GHGall$Sector == "agri-combustion"] <- "agri-combustion"
GHGall$Sector[GHGall$Sector == "enteric fermentation"] <- "enteric fermentation"
GHGall$Sector[GHGall$Sector == "manure management"] <- "manure management"
GHGall$Sector[GHGall$Sector == "fertilization"] <- "fertilisation"
GHGall$Sector[GHGall$Sector == "manufacturing industries and construction"] <- "manufacturing industries and construction"
GHGall$Sector[GHGall$Sector == "substitutes for ozone depleting substances"] <- "substitutes for ozone depleting substances"
GHGall$Sector[GHGall$Sector == "other business"] <- "other business"
GHGall$Sector[GHGall$Sector == "energy-combustion"] <- "energy-combustion"
GHGall$Sector[GHGall$Sector == "other energy"] <- "other energy"
GHGall$Sector[GHGall$Sector == "industrial processes"] <- "industrial processes"
GHGall$Sector[GHGall$Sector == "forest land"] <- "forest land"
GHGall$Sector[GHGall$Sector == "cropland"] <- "cropland"
GHGall$Sector[GHGall$Sector == "grassland"] <- "grassland"
GHGall$Sector[GHGall$Sector == "wetlands"] <- "wetlands"
GHGall$Sector[GHGall$Sector == "settlements"] <- "settlements"
GHGall$Sector[GHGall$Sector == "HWP and indirect N2O emissions"] <- "HWP and indirect N2O emissions"
GHGall$Sector[GHGall$Sector == "public"] <- "public"
GHGall$Sector[GHGall$Sector == "residential combustion"] <- "residential combustion"
GHGall$Sector[GHGall$Sector == "residential other"] <- "residential other"
GHGall$Sector[GHGall$Sector == "domestic aviation"] <- "domestic aviation"
GHGall$Sector[GHGall$Sector == "road transport "] <- "road transport "
GHGall$Sector[GHGall$Sector == "railways and shipping"] <- "railways and shipping"
GHGall$Sector[GHGall$Sector == "transport other"] <- "transport other"
GHGall$Sector[GHGall$Sector == "landfill sites"] <- "landfill sites"
GHGall$Sector[GHGall$Sector == "Wastewater treatment"] <- "Wastewater treatment"
GHGall$Sector[GHGall$Sector == "other waste"] <- "other waste"
# format variables
GHGall$Sector <- factor(GHGall$Sector)
GHGall$variable <- factor(GHGall$variable)
#GHGall$Year <- factor(GHGall$Year)
GHGall$value <- as.numeric(GHGall$value)
# CREATE FINAL DATAFRAME FOR SHARING
dat <-
GHGall %>%
arrange(desc(Year))
# CREATE A COPY OF dat FOR GRAPHING THAT DOESN'T USE big.mark ","
dat_graph <- dat
dat$value <- sapply(dat$value, format, big.mark = ",")
# CROSSTALK
GHGkpis <-
GHGall %>%
filter(variable %in% kpis) %>%
select(Year, Sector, variable, value)
shared_dat <- SharedData$new(GHGkpis)
sd_df <- SharedData$new(GHGkpis, group = shared_dat$groupName())
# CREATE DATAFRAMES TO USE WITH PLOTLY
tidy_dat <-
dat_graph
###############################################
################# Total ####################
###############################################
Total <-
GHGall %>%
filter(variable == "Total") %>%
select(Year, Sector, value) %>% spread(Sector, value)
pre1997 <-
Total[as.numeric(as.character(Total$Year)) < 1997, ]
post1997 <-
Total[as.numeric(as.character(Total$Year)) > 1997, ]
ticklabs <- list()
for(i in 1:length(Total$Year)){
ticklabs[[i]] <- 1988+i
}
ticklabs[[1]] <- "Base year"
ticklabs[[3]] <- " "
ticklabs[[4]] <- " "
ticklabs[[5]] <- " "
ticklabs[[6]] <- " "
ticklabs[[8]] <- " "
ticklabs[[9]] <- " "
ticklabs[[31]]<-"2019"
ticklabs[[32]]<-"2020"
tickval <- list()
for(i in 1:length(Total$Year)){
tickval[[i]] <- 1988+i
}
tickval[[31]]<-2019
tickval[[32]]<-2020
pre1997<-pre1997 %>% mutate_if(is.numeric, round, digits=1)
post1997<-post1997%>% mutate_if(is.numeric, round, digits=1)
```
```{r logo, out.width = "175px", echo=FALSE, fig.align='centre'}
```
Charts {data-icon="fa-chart-line"}
===========================================================
**Greenhouse gas emissions for Northern Ireland by source sector for the years 1990 to 2021. Further information available from **
**https://www.daera-ni.gov.uk/articles/northern-ireland-greenhouse-gas-inventory**
Row {.tabset .tabset-fade}
-------------------------------------
### **Northern Ireland**
```{r Northern Ireland greenhouse gas inventory 1990 - 2021}
plot_ly(pre1997, x = ~Year, y = ~Agriculture, legendgroup = "agri", name = 'Agriculture', type = 'scatter', mode = 'markers', visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$Business, name = 'Business', legendgroup = "bus", mode = 'markers', visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Energy Supply`, name = 'Energy Supply', legendgroup = "energy", mode = 'markers', visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Industrial Process`, name = 'Industrial Process', legendgroup = "indi", mode = 'markers', visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Land Use Change`, name = 'Land Use Change', legendgroup = "land", visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Public`, name = 'Public', legendgroup = "public", visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Residential Total`, name = 'Residential', legendgroup = "res", visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$Transport, name = 'Transport', legendgroup = "tran", visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Waste Management`, name = 'Waste Management', legendgroup = "waste", visible = T, showlegend = F) %>%
add_trace(y = ~pre1997$`Northern Ireland`, name = 'Northern Ireland', legendgroup = "NI", visible = 'legendonly', showlegend = F) %>%
add_trace(x = ~post1997$Year, y = ~post1997$Agriculture, legendgroup = "agri", name = 'Agriculture', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$Business, legendgroup = "bus", name = 'Business', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Energy Supply`, legendgroup = "energy", name = 'Energy Supply', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Industrial Process`, legendgroup = "indi", name = 'Industrial Process', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Land Use Change`, legendgroup = "land", name = 'Land Use Change', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Public`, legendgroup = "public", name = 'Public', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Residential Total`, legendgroup = "res", name = 'Residential', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$Transport, legendgroup = "tran", name = 'Transport', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Waste Management`, legendgroup = "waste", name = 'Waste Management', mode = 'lines', visible = T, showlegend = T) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Northern Ireland`, legendgroup = "NI", name = 'Northern Ireland', mode = 'lines', visible = 'legendonly', showlegend = T) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",hoverinfo="text",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
range = c(0, max(Total$Value)),
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Agriculture**
```{r Agri}
plot_ly(pre1997, x = ~Year, y = ~`Enteric Fermentation`, legendgroup = "enteric", name = 'Enteric Fermentation', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Manure Management`, legendgroup = "manure", name = 'Manure Management', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Agri-combustion`, legendgroup = "agricomb", name = 'Agri-combustion', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(107,174,214)')) %>%
add_trace(y = ~pre1997$`Fertilization`, legendgroup = "fert", name = 'Fertilisation', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(158,202,225)')) %>%
add_trace(y = ~pre1997$`Agriculture`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Enteric Fermentation`, legendgroup = "enteric", name = 'Enteric Fermentation', mode = 'lines',
visible = T, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Manure Management`, legendgroup = "manure", name = 'Manure Management', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Agri-combustion`, legendgroup = "agricomb", name = 'Agri-combustion', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(107,174,214)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Fertilization`, legendgroup = "fert", name = 'Fertilisation', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(158,202,225)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Agriculture`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Business**
```{r Bus}
plot_ly(pre1997, x = ~Year, y = ~`Manufacturing Industries and Construction`, legendgroup = "manu", name = 'Manufacturing Industries and Construction', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Substitutes for Ozone Depleteing Substances`, legendgroup = "subs", name = 'Substitutes for Ozone Depleting Substances', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Other Business`, legendgroup = "other", name = 'Other Business', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(107,174,214)')) %>%
add_trace(y = ~pre1997$`Business`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Manufacturing Industries and Construction`, legendgroup = "manu", name = 'Manufacturing Industries and Construction', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Substitutes for Ozone Depleteing Substances`, legendgroup = "subs", name = 'Substitutes for Ozone Depleting Substances', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Other Business`, legendgroup = "other", name = 'Other Business', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(107,174,214)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Business`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Energy Supply**
```{r energy}
plot_ly(pre1997, x = ~Year, y = ~`Energy Combustion`, legendgroup = "encomb", name = 'Energy-combustion', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Other Energy`, legendgroup = "other", name = 'Other Energy', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Energy Supply`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Energy Combustion`, legendgroup = "encomb", name = 'Energy-combustion', mode = 'lines', visible = T, showlegend = TRUE, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Other Energy`, legendgroup = "other", name = 'Other Energy', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Energy Supply`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Industrial processes**
```{r IndP}
plot_ly(pre1997, x = ~Year, y = ~`Industrial Process`, legendgroup = "indp", name = 'Industrial Processes', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Industrial processes Total`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Industrial Process`, legendgroup = "indp", name = 'Industrial Processes', mode = 'lines', visible = T, showlegend = TRUE, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Industrial processes Total`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Land use change**
```{r LULUCF}
plot_ly(pre1997, x = ~Year, y = ~`Forestland`, legendgroup = "forest", name = 'Forestland', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,69,148)')) %>%
add_trace(y = ~pre1997$`Cropland`, legendgroup = "crop", name = 'Cropland', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(33,113,181)')) %>%
add_trace(y = ~pre1997$`Grassland`, legendgroup = "grass", name = 'Grassland', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(66,146,198)')) %>%
add_trace(y = ~pre1997$`Wetlands`, legendgroup = "wet", name = 'Wetlands', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(107,174,214)')) %>%
add_trace(y = ~pre1997$`Settlements`, legendgroup = "set", name = 'Settlements', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(158,202,225)')) %>%
add_trace(y = ~pre1997$`HWP and Indirect N20 Emissions`, legendgroup = "oth", name = 'HWP and Indirect N2O Emissions', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(198,219,239)')) %>%
add_trace(y = ~pre1997$`Land Use Change`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Forestland`, legendgroup = "forest", name = 'Forestland', mode = 'lines',
visible = T, showlegend = TRUE, line = list(color = 'rgb(8,69,148)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Cropland`, legendgroup = "crop", name = 'Cropland', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(33,113,181)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Grassland`, legendgroup = "grass", name = 'Grassland', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(66,146,198)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Wetlands`, legendgroup = "wet", name = 'Wetlands', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(107,174,214)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Settlements`, legendgroup = "set", name = 'Settlements', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(158,202,225)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`HWP and Indirect N20 Emissions`, legendgroup = "oth", name = 'HWP and Indirect N2O Emissions', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(198,219,239)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Land Use Change`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
autorange = TRUE,
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Public**
```{r Pub}
plot_ly(pre1997, x = ~Year, y = ~`Public`, legendgroup = "pub", name = 'Public', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Public Total`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Public`, legendgroup = "pub", name = 'Public', mode = 'lines',
visible = T, showlegend = TRUE, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Public Total`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Residential**
```{r Res}
plot_ly(pre1997, x = ~Year, y = ~`Residential-combustion`, legendgroup = "rescomb", name = 'Residential-combustion', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Residential Other`, legendgroup = "resoth", name = 'Residential Other', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Residential Total`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Residential-combustion`, legendgroup = "rescomb", name = 'Residential-combustion', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Residential Other`, legendgroup = "resoth", name = 'Residential Other', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Residential Total`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Transport**
```{r transport}
plot_ly(pre1997, x = ~Year, y = ~`Domestic Aviation`, legendgroup = "aviation", name = 'Domestic Aviation', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>% add_trace(y = ~pre1997$`Road Transport`, legendgroup = "road", name = 'Road Transport', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Railways and Shipping`, legendgroup = "rail", name = 'Railways and Shipping', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(107,174,214)')) %>%
add_trace(y = ~pre1997$`Transport Other`, legendgroup = "oth", name = 'Transport Other', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(158,202,225)')) %>%
add_trace(y = ~pre1997$`Transport`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Domestic Aviation`, legendgroup = "aviation", name = 'Domestic Aviation', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Road Transport`, legendgroup = "road", name = 'Road Transport', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Railways and Shipping`, legendgroup = "rail", name = 'Railways and Shipping', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(107,174,214)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Transport Other`, legendgroup = "oth", name = 'Transport Other', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(158,202,225)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Transport`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
### **Waste Management**
```{r waste}
plot_ly(pre1997, x = ~Year, y = ~`Landfill Sites`, legendgroup = "lf", name = 'Landfill Sites', type = 'scatter', mode = 'markers', visible = T, showlegend = F, markers = list(color = 'rgb(8,81,156)')) %>%
add_trace(y = ~pre1997$`Waste Water Treatment`, legendgroup = "wwt", name = 'Wastewater Treatment', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(49,130,189)')) %>%
add_trace(y = ~pre1997$`Other Waste`, legendgroup = "oth", name = 'Other Waste', mode = 'markers', visible = T, showlegend = F, marker = list(color = 'rgb(107,174,214)')) %>%
add_trace(y = ~pre1997$`Waste Management`, legendgroup = "total", name = 'Total', visible = 'legendonly', showlegend = F, marker = list(color = 'rgb(0,0,0)')) %>%
add_trace (x = ~post1997$Year, y = ~post1997$`Landfill Sites`, legendgroup = "lf", name = 'Landfill Sites', mode = 'lines',
visible = T, showlegend = T, line = list(color = 'rgb(8,81,156)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Waste Water Treatment`, legendgroup = "wwt", name = 'Wastewater Treatment', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(49,130,189)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Other Waste`, legendgroup = "oth", name = 'Other Waste', mode = 'lines', visible = T, showlegend = T, line = list(color = 'rgb(107,174,214)')) %>%
add_trace(x = ~post1997$Year, y = ~post1997$`Waste Management`, legendgroup = "total", name = 'Total', mode = 'lines', visible = 'legendonly', showlegend = T, line = list(color = 'rgb(0,0,0)')) %>%
layout(title = "",
paper_bgcolor = 'rgb(255,255,255)', plot_bgcolor = 'rgb(255,255,255)', hovermode = "compare",
xaxis = list(title = "",
gridcolor = 'rgb(255,255,255)',
showgrid = FALSE,
range = c(1988, max(post1997$Year)),
ticktext = ticklabs,
tickvals = tickval,
showline = TRUE,
dtick = 1,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
zeroline = FALSE),
yaxis = list(title = "Kiltotonnes CO2e",
titlefont = list(size = 11),
gridcolor = 'rgb(229,229,299)',
rangemode = "tozero",
showgrid = TRUE,
showline = TRUE,
showticklabels = TRUE,
tickcolor = 'rgb(127,127,127)',
ticks = 'outside',
tickformat = ",",
zeroline = FALSE))
```
Reader Information & Contact Details {data-icon="fa-chart-line"}
===========================================================
**Reader Information**
*These statistics are based on the NI bulletin of the greenhouse gas inventory. The greenhouse gas inventory data are produced annually by Ricardo Energy and Environment, on behalf of the Department for Business, Energy & Industrial Strategy, the Scottish Government, the Welsh Assembly Government and the Northern Ireland Department of Agriculture, Environment and Rural Affairs. Each year the greenhouse gas inventory is extended and updated. The entire historical data series, from base year to 2021, is revised to incorporate methodological improvements and new data. This takes into account revisions to the datasets used in its compilation. *
*Emissions are reported for seven greenhouse gases: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Depending on their molecular weights, radiative properties and residence times in the atmosphere, each greenhouse gas has a different capacity to cause global warming. The base year is 1990 for carbon dioxide, methane and nitrous oxide, and 1995 for the fluorinated gases. The fluorinated gases are hydrofluorocarbons, perfluorocarbons, sulphur hexafluoride and nitrogen trifluoride. Emissions are reported according to the National Communication sectors in accordance with international reporting guidelines from the United Nations Framework Convention on Climate Change (UNFCCC).*
*The greenhouse gas emission estimates are based on a wide range of data sources and sources of uncertainty include statistical differences, assumptions, proxy datasets and expert judgement. In addition, the natural variability in the processes that are being modelled introduce uncertainty. For example, carbon content of fuels and farming practices under different climatic conditions and soil types. The uncertainties presented are a close approximation of the 95% confidence interval. The width of the interval provides a measure of the accuracy of the estimates. Uncertainty estimates for Northern Ireland emissions are available for the base year, the latest year (2021) and for the percentage change between the two years. For the base year, uncertainty is ±8%, and for 2021 it is ±5%. For the percentage reduction between the base year and 2021, the uncertainty interval ranges from 16% to 33%. There remains greater uncertainty around emissions in Northern Ireland compared to other parts of the United Kingdom due to the relative importance of methane and nitrous oxide emissions in the agriculture sector. Emissions of this gas are more difficult to estimate than carbon dioxide, and the agriculture sector makes up a larger share of Northern Ireland’s emissions than in other parts of the UK.*
*The UK greenhouse gas inventory National Statistics user guide provides a simple guide to the origins and use of data in the compilation of the UK Greenhouse Gas Inventory. This guide can be accessed through the Department for Business, Energy & Industrial Strategy website https://www.gov.uk/government/publications/uk-greenhouse-gas-emissions-statistics-user-guidance.*
**Contact Details**
*DAERA Statistics & Analytical Services Branch is keen to hear your feedback.*
*Please e-mail comments to env.stats@daera-ni.gov.uk*
*Further information can be found on the DAERA Statistics website https://www.daera-ni.gov.uk/landing-pages/statistics*
Row {.tabset .tabset-fade}
-------------------------------------
```