![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg9JL-M4Y9_US5Bq2gya3Q9QHZbzoA22FXqQAd755PLOhFJrkEtpFcO740RZGxpbYKHvEDIcug8F_KTbImmRnyfy5O04R402Zm9utnOGuRW9L3rzdLl5iXIHzUp-7oGHJ67oVQPx8YZshMy/s400/China+Carbon+Price.gif)
The chart plots the carbon price in US Dollars (market exchange rate) against Gt of Co2 abated for China using the results from seven of the EMF-22 models. This is not really a cost curve as it includes data for different time periods and model scenarios. I've been struggling to model this data over the last 10 days or so on and off. But this is actually the first time I've plotted the data like this. It's always helpful I think to look at your data.
Fitting a straight line to this chart would imply that carbon prices are an exponential function of abatement. This is not a bad fit but something a bit more non-linear would probably work better. Another way of representing the data is to plot the carbon price against the percentage reduction in emissions:
![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhl2Tv6E5vaO5xy5fqmPdemxEYGMMMr-2c7RwLC9Is0OqUsGVzlIqmbGBMqF7P7LNpnrTqwGTn2uJJPuo-eRUAq-1PFaeYP6Ccf8NikZAqtnFE8o3SVMLfhneAF_NsE-cCpkuSZK0KoXp4Y/s400/China+Carbon+Price.gif)
Again, this appears to be roughly linear but a nonlinear curve would fit better.
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