Modeling the future emissions of global carbon is big business (albeit on an academic scale). There are dozens of groups with their more or less black box models, which if fed scenarios for e.g. income, population and technological change, will produce trajectories of global, regional and sometimes national emissions of CO2 and other greenhouse gases. These trajectories matter as climate modelers use them to project future climate under higher atmospheric concentrations of CO2. I have written on simpler, and in the short run more accurate ways to project business as usual emissions. However, econometric methods do generally not lend themselves to these non-marginal changes 100 years out. (The black box models may not do much better, but that is beside the point).
While looking at these projections for the purpose of writing a review piece on China’s greenhouse gas emissions from the burning of fossil fuels, I tried to understand how the “efficiency” of the Chinese economy had changed over the past 40 years in energy and CO2 terms. To frame my thinking, I went back to the famed Kaya identity, which underlies much of the IPCC’s approach to modeling emissions scenarios. It decomposes emissions as follows:
CO2 = Population * (GDP/Population) * (Energy/GDP) * (CO2/Energy)
The general thinking is that higher population and higher per capita income lead to higher emissions (as there is no solid evidence of a Kuznets curve for CO2, where per capita emissions start dropping at higher incomes). What I like about The Kaya identity over Holdren and Ehrlich’s IPAT identitiy, is that it decomposes the T slightly further into the energy intensity of GDP and the carbon intensity of energy at the national level. While this is of course obvious to most people working on this problem, I think it is worth pointing out that in this framework lower CO2 emissions come from two sources:
- a less energy intensive economy
- less carbon intensive energy consumption
While per capita GDP and population statistics for China and the US are well documented and much talked about, I was less certain about what the trajectories for energy intensity of GDP and carbon intensity of energy consumption look like. I fired up Matlab, downloaded some statistics from the world development indicators and arrived at the following figure:
The left panel displays the trajectory of energy consumption divided by real GDP for the US (solid line) and China (dashed line). What we see for both countries is a relatively steady drop in the energy intensity (2% p.a for the US and 4% for the PRC). The right panel displays total CO2 emissions divided by energy consumption. For the US we note a 0.3% p.a. drop in carbon intensity. For China, we observe a 1.1% p.a. increase in the carbon intensity of energy.
Why do I care? The product of these two measures, the carbon intensity of the economy, has been proposed as a measure which could be the subject of potentially binding targets. There are two ways of driving down this measure. One could either push harder on energy intensity of the economy. This could be done via encouraging energy efficiency or waiting for structural change towards a more service based economy to kick in. Or one could push harder on the carbon intensity of the economy by encouraging the use of less carbon intensive energy sources (e.g. via a CARBON TAX). At the beginning of the last century, both countries relied almost exclusively on coal. Today, the share of coal in US emissions is somewhere near 35% , while 72% of emissions in China still stem from coal.
In China, there is an opportunity to push hard on the carbon intensity of the energy using sectors (e.g. steel, power generation). The massive recent government encouraged and often financed investments in the construction sector and upstream related industries (e.g. steel and cement) have led to an explosion in the carbon intensity of the energy used. This effect is so significant that in the five years leading up to 2009, the carbon intensity of the economy has essentially remained unchanged. I am hoping that once this somewhat artificial boom in construction slows we will see a reversal in the trend of the carbon intensity of the energy sector.