[ANN] Announcing DICEModel.jl - DICE 2023 Integrated Assessment Model port to Julia

Package Announcements
1

DICEModel.jl provides a practical, full open-source (using all open-source tools) implementation of the latest version of the Nordhaus’s DICE (Dynamic Integrated Climate-Economy model) model, keeping the model readable, compact and as close as possible to the original (GAMS) code.

This package provides two functions:

  • run_dice_scenario(scenario_name) [browse code - documentation ] : runs one of the “official” 10 scenarios;

  • run_dice(;optimizer,bounds,kwargs...) [browse code - documentation] : run DICE with custom solver engine (and eventually options), custom variable constraints (bounds) or custom parameters (see Parameters).

In both cases the output (results) is a named tuple. Use keys(results) to find the available information (or just look at the source code) and results.VARIABLEX to obtain the values.

A summary of the main results is available on this page.

Example


using Pkg

Pkg.activate(@__DIR__)

Pkg.add(["DICEModel","Plots"]) # run only once, then comment out

using DICEModel, Plots

# CB Optimal scenario...

res_cbopt = run_dice_scenario("cbopt")

# Base scenario...

res_base = run_dice_scenario("base")

# Paris "extended" scenario...

tidx = 1:81

# upper limit to emissions mitigation rate

miuup = @. min( 0.05 + 0.04*(tidx-1) - 0.01*max(0,tidx-5) ,1.00)

res_parisext = run_dice(miuup = miuup) # or simply: run_dice_scenario("parisext")

# Max 2 °C scenario...

res_t2c = run_dice(bounds = Dict("TATM"=>("<=",2.0))) # or simply: run_dice_scenario("t2c")

# Plots

times = res_cbopt.times

# CO2 emissions plot...

plot(times[1:11],res_cbopt.ECO2[1:11],ylim=(0,70), title="CO₂ emissions",ylabel="GtCO₂/yr",label="C/B optimal", color=:blue4, markershape=:circle, markercolor=:white)

plot!(times[1:11],res_base.ECO2[1:11], label="Base", colour=:goldenrod3, markershape=:circle, markercolor=:goldenrod3)

plot!(times[1:11],res_parisext.ECO2[1:11], label="Paris ext", colour=:red, linestyle=:dash)

plot!(times[1:11],res_t2c.ECO2[1:11], label="T < 2 °C", colour=:green, markershape=:cross, markercolor=:green)

# Carbon price plot...

plot(times[1:9],res_cbopt.CPRICE[1:9],ylim=(0,300), title="Carbon price",ylabel="2019\$ / t tCO₂",label="C/B optimal", color=:blue4, markershape=:circle, markercolor=:white)

plot!(times[1:9],res_base.CPRICE[1:9], label="Base", colour=:goldenrod3, markershape=:circle, markercolor=:goldenrod3)

plot!(times[1:9],res_parisext.CPRICE[1:9], label="Paris ext", colour=:red, linestyle=:dash)

plot!(times[1:9],res_t2c.CPRICE[1:9], label="T < 2 °C", colour=:green, markershape=:cross, markercolor=:green)

CO%E2%82%82_emissions.png600×400 27.5 KB
Carbon_price.png600×400 27.1 KB

Other packages or implementations of the DICE model

Other packages, in both Julia and other languages, already implement the DICE model, but often don’t have the same level of readability and compactness as the original GAMS code:

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