This approaches what you want, however there must be some sort of conservation metric or other sort of scaling necessary to get the plot to appear as you want it to appear. I must leave that to you, since I do not understand how the various emissions values are related. (I left the ‘TotalEmissions’ vector that I created in the code, in the event you want to use it.)
T1 = readtable('CCC_data_emissions.xlsx');
T2 = T1; % Duplicate & Save Original
TF1 = ismember(T2.years, T2.years_1); % Matching Years
T2.emissions_1(TF1) = T1.emissions_1(~isnan(T1.emissions_1)); % Matching Values
T2.emissions_2(TF1) = T1.emissions_2(~isnan(T1.emissions_2)); % Matching Values
TotalEmissions = T2.emissions+T2.emissions_1+T2.emissions_2;
figure
area(T1.years, [T2.emissions-T2.emissions_1-T2.emissions_2, T2.emissions_1, T2.emissions_2])
legend('Emissions','Emissions_1','Emissions_2', 'Location','NE')
.
