index.Rmd

---
title: "WITCH and EU Climate Policies"
subtitle: "Fit for 55, 2040 target, ..."
author: "Johannes Emmerling"
date: "EIEE Modelling Meeting, `r Sys.Date()`"
output: 
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    seal: true
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---

#Deployment: 
#renderthis::to_pdf("index.html") #for PDF
#usethis::use_github_pages(branch = "main") #to github (push the last changes to update!)

```{r setup, include=FALSE}
options(htmltools.dir.version = FALSE)
```

```{r xaringan-themer, include=FALSE, warning=FALSE}
library(xaringanthemer)
style_mono_accent(
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library(xaringanExtra)
use_logo(
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```{r load, include=FALSE, warning=FALSE}
require(tidyverse)
require(plotly)


load("data/temp.Rdata")
load("data/alpha.Rdata")


```


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# WITCH and EU Climate Policies

## Fit for 55, 2040 target, ...

### Johannes Emmerling

### `r Sys.Date()`

-->

# An overview of European Climate Targets for 2030

<img src="data/fitfor55.png" width="50%" style="display: block; margin-left: auto; margin-right: auto; width: 50%;">
     
---


# An overview of European Climate Targets for 2030

.pull-left[
1. Emission Target 2030: -40%(1990)<sup>*</sup>

1. Energy Efficiency Directive: -32.5% (Ref)

1. Renewables Target in FEN: 32% (Total)

1. Renewables Target in Electricity: % (Total)

1. Renewables Share in Transportation: 9%

1. Heating and Cooling by REN:

]

--

.pull-right[
1. Emission Target 2030: -40%(1990)<sup>*</sup>

1. Energy Efficiency Target: -36%(FEN) / -39%(PES) (Ref)

1. Renewables Target in FEN: 40% / 45% (REPowerEU)

1. Renewables Target in Electricity: 65% / 69% (REPowerEU)

1. Renewables Share in Transportation: 29%

1. Heating and Cooling by REN:

]

.footnote[[*] Always indicating the reference where applicable]

---

# Scenarios

Master scenarios
- MASTER bau
- MASTER NDC
- MASTER LTS

ECEMF scenarios
- ECEMF NPi
- ECEMF NetZero
- ECEMF ctax

All WITCH17
- Regional definition: "europe" = EU27 + Uk + Norway + Switzerland + Balkans
- witch34 working for ctax but still WIP for caps and pledges


---

# Emissions Target

- GHG climate neutrality target for Europe

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_emi_eu)  %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---

# Energy Efficiency Directive (EED)

- Demand for Total Final/Primary Energy

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_en_eu) %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---

# Renewable Energy Directive (RED)

- Share of Renewables in FEN and Electricity

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_ren_eu) %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---

# Sectoral Renewable Shares (RED)

- Heating/Cooling not represented. Transportation REN share reasonable

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_ren_dem_eu) %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---



# How fast to reach net zero?

- So far, pledges implemented as **linear** trends $(\alpha=1)$.

$$emicap_{y}=(E_{2030}-E_{NZY})\left(1-\frac{y-2030}{NZY-2030}\right)^{\alpha}$$
--


```{r out.width='80%', fig.height=5, include = T, echo = F, warning=F, fig.align='center'}
emicap <- function(y,alpha) (1-((y-2030)/20))^alpha
df_emicap <- expand.grid(y = seq(2030, 2050), alpha=c(0.1,0.5,1,1.25,1.5,2,3)) %>% mutate(emicap=emicap(y,alpha))
ggplotly(ggplot(df_emicap) + geom_line(aes(y,emicap, color=alpha, group=alpha))) %>% config(displayModeBar = F)


```


---

# How fast to reach net zero?

- Using `pol_lts.gms` in WITCH master (uses emi_cap then converts to tax, additional constraints)

--

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_alpha_emicap, tooltip = c("color", "y")) %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---

# How fast to reach net zero?

- Which speed is optimal?
--

```{r out.width='100%', fig.height=7, include = T, echo = F, warning=F}
plotly::ggplotly(p = p_alpha_welfare, tooltip = c("x", "y")) %>% layout(legend = list(orientation = 'h', x = 0.3, y = -0.1)) %>% config(displayModeBar = F)

```

---

# Conclusions

- Overall Current Policies, NDC, and Pledges work fairly well
- Final Energy reporting some fixes required
  - hydrogen
  - NEL
  - Transportation 
 
- Sectoral reporting a starting point but endogenous modelling next step
 
- Net Zero transition we could say something about it
- slighly convex shape $(\alpha=1.25)$ seems reasonable

---