Regardless of how China is perceived in the west, in the medium term, the world’s most ambitious energy efficiency goals can be found in that country. In only five years, from 2010 to 2015, it’s seven biggest industrial regions have to meet energy efficiency targets of 16-19% and emission reductions of 17-21%.
However, in order to achieve carbon emission targets, you first need a reliable baseline for reference. Read in this article how big the carbon gaps are between different statistical assessments, and not only in China, and why inherently inaccurate baseline figures don’t automatically deem greenhouse gas reduction efforts to failure.
China’s Giant Emission Gap
Liu Shuang and Xu Nan wrote a comprehensive article for China Dialogue (Data gaps hobble carbon trading) that reviewed the challenges and difficulties absolute emission caps present in China. As the article shows, one of the biggest challenges is what is known as the emission gap: different data sources with different methodologies produce different emission figures. Simply put, the problem when you aim to reduce emissions is that you don’t really know which baseline figure to use:
“’Top-down calculations and bottom-up calculations don’t match up, nor do the figures from industry associations and those from emission inventories.’ This is inevitable when statistics are collected over different scopes, and through different channels.
Data from businesses is not itemised, and – as energy audits are still uncommon – data verification is extremely hard.
Most provinces and cities have energy-saving supervision centres, which oversee the reporting of energy use statistics by high-consuming companies. In Guangdong, energy use is reported quarterly, for example, while in Shanghai it happens monthly.”
It is certainly a desirable goal to put precise figures at the base of environmental regulation. However, it is not only regulation efforts that benefit from consistent data gathering methods. As the authors continued:
In the long term, this data base won’t only be useful for carbon trading – improvements made here can feed into other information-gathering efforts, such as greenhouse-gas emission inventories and energy audits. But at the moment, without solid company-level emissions data, there is no basis on which to allocate emission quotas.
Baseline Figures for Kyoto Protocol Were Only Estimates
Now if you assume that the countries at the other end of the Eurasian Plate perform better, because the European emission trading scheme has been running for a while now, you’re wrong. And you’re right, at the same time. How can that be? Well, despite the much more consistent data gathering methods that evolved over the past 20 years in Europe and the US, western countries face the same problem as China: Back in the 1990s, baseline figures, especially those of the Kyoto protocol, were mere estimates, rather than accurate measurements. As it now turns out, the national carbon emission baselines for the 1990s were underestimated by a stunning 7%. So, according to a Sydney Morning Herald article, said Roger Francey when he was interviewed about the Atmospheric verification of anthropogenic CO2 emission trends paper he and fellow researchers published in “Nature Climate Change” three weeks ago (Feb 2013).
In the same way that Chinese emission figures on the national level drastically differed from the figures aggregated for the individual provincial level, the sum of official Kyoto protocol baseline figures for the countries of the northern hemisphere differed from the actual measurements in the atmosphere. For more information on the former, see the original paper The gigatonne gap in China’s carbon dioxide inventories (Nature Climate Change 2, 672–675 (2012)) or Brad Plumer’s brief and accurate summary of it at Wonkblog. He reviewed the two possible causes behind China’s emission gap as follows:
The researchers, Dabo Guan, Zhu Liu, Yong Geng, Sören Lindner and Klaus Hubacek, come up with two possible explanations for the gap. The first is that the data is simply messy, due to the fact that many smaller Chinese firms are burning coal without the national government knowing about it. That might be due to shoddy record keeping. Or it might be due to black-market activity — small inefficient coal mines and coal-washing mills that were shuttered by the government and then quietly reopened elsewhere.
Alternatively, there’s the possibility that government officials are massaging the data. Local politicians, for instance, are promoted based on their economic performance. So they have an incentive to overstate growth — and then revise the emissions data so that it matches. (The researchers note that the “carbon gap” between national and local data lines up pretty well with a similar “GDP gap” in the statistics.) But that’s not all. Satellites have also turned up evidence that the national government in Beijing may be understating some coal activity — possibly in order to claim success on its environmental laws.
More Atmospheric Methods Needed to Verify National Data
Personally, I guess the truth lies somewhere between the two extremes. What’s more interesting, however, is the implication to be drawn from the inadequate statistics. In a short Power Point presentation (PDF), Sören Lindner, one of the authors who discovered the Chinese emission gap, came up with one pretty obvious implication. He argued that “Remote sensing data may be suitable to monitor and verify CO2 emission data ” – the same conclusion that the authors of the Francey et al. paper drew; it may seem hardly intelligible at first sight, but the paper’s official abstract contains striking news:
Growth and inter-hemispheric concentration difference during the onset and recovery of the Global Financial Crisis support a previous speculation that the reported 2000–2008 emissions surge is an artefact, most simply explained by a cumulative underestimation (~ 9 Pg C) of 1994–2007 emissions; in this case, post-2000 emissions would track mid-range of Intergovernmental Panel on Climate Change emission scenarios. (…) We suggest atmospheric methods to help resolve this ambiguity.
Quite apparently, the above abstract contains a monster of a phrase, and, to a not-so-uncertain extent, a pretty concentrated one. So let me try to find simple words for the actual content it refers to, which is (of course) concentration. Carbon dioxide concentration, to be precise. John Ross explained it quite well in The Australian, so I allow myself to weave some of the facts he mentioned in his newspaper article into my summary. The first part of the above quotation’s first phrase basically says that during the financial crisis, there were different concentrations of carbon dioxide in the northern and the southern hemispheres, and, despite the crisis, total greenhouse gas emissions rose globally. From the way they rose, it can be concluded that there was no exceptional surge of emissions from 2000-2008. This is in contrast to the Kyoto protocol figures, which are based on accumulated national emissions data called national GHG inventories. In contrast to the latter, the concentrations the scientific team around Roger Francey found were based on atmospheric carbon dioxide measurements made at two observatories, one in Tasmania, Australia, and the other on Hawaii. Both observatories operate far away from global centers of industry, so the concentrations they measure closely reflect the global background concentration of carbon dioxide. Back to the paper’s abstract: phrase one, part two, states that the difference between reported and measured carbon concentrations most probably results from an inaccurate estimate of the carbon emissions during the years 1994-2007, a time when today’s more precise carbon assessment methods were still to be established. Actually, the figures reached at the observatories were 7% higher than the estimates used in the Kyoto framework national inventories! With the corrected, that is, actually measured, concentration, there was no drastic increase in emissions. Rather, the IPCC’s “midrange” scenario gained support. It predicted a constant but relatively linear rise of emissions.
Atmospheric Methods: Surface Observatories and Satellites
As I said, to resolve the issue of diverging concentration assessments, the researchers call for more “atmospheric methods”, as in more carbon dioxide measurements. Currently, roughly 90 stations around the world measure CO2 concentrations on the earth’s surface, and a few laser-equipped satellites do the same thing while spinning around the earth. Monitoring from space is fast and global, but less accurate than the stations on the surface. The latter, however, are influenced by local meteorology and their neighboring point-source emissions. To measure the background concentration, not the local one, you can either measure the CO2 in remote places like Tasmania or Hawaii, where the next industrial area is at least 3000 km away, or you can take the average figure of all of the world’s surface stations. This, however, only touches upon the global carbon dioxide concentration. When it comes to a carbon-dioxide assessment for individual countries, the most common way involves a more indirect approach. Instead of measuring the concentration in the air, you use carbon inventories that basically add up the use of all sorts of fossil fuels within the national borders. What’s more, they analyze the changes in land use that affect carbon sequestration within the national territory. This means that the calculation of generated carbon emissions seems pretty theoretical and prone to error, especially after hearing about the above mentioned findings. Without a doubt, the 7% underestimation back in the 1990s is shocking. But, you can also draw a positive conclusion from the new data: after 20 years of ongoing development, national greenhouse gas inventories have finally reached a satisfying level of accuracy, especially in the green-transition and statistics friendly European context of the 2010 decade.
- Atmospheric Measurement Techniques – An Interactive Open Access Journal of the European Geosciences Union, www.atmos-meas-tech.net
- How we measure background CO2 levels on Mauna Loa [Hawaii]
- Khan, Amir; Schaefer, David; Tao, Lei; Miller, David J.; Sun, Kang; Zondlo, Mark A.; Harrison, William A.; Roscoe, Bryan; Lary, David J. 2012. “Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles.” Remote Sens. 4, no. 5: 1355-1368.
- Balmer, Paul, Bösch, Hartmut, Kerr, Andy. “Measuring carbon from space”. Planet Earth Online Feature, 7 April 2011. Natural Environment Research Council, Swindon
- United Nations Framework Convention on Climate Change: Greenhouse Gas Inventory Data
Article image based on data obtained from NASA’s AIRS satellite, CC BY 2.0. AIRS stands for Atmospheric Infrared Sounder. The image shows the average CO2-concentration in June 2003, ranging from 360 ppm (blue) to 385 ppm (red).
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