A couple of days ago I posted an update to my 2023 article on the trend in carbon emissions in China after the pandemic. That blogpost compares emissions for the whole of 2023 to those for the whole of 2019. But what happened in 2024? So far we have nine months of data, which we can compare to the first nine months of 2023.
According to Carbon Monitor, emissions have fallen by 0.6% in 2024 compared to 2023. Emissions from power generation rose by 1.6% with smaller increases in transport (0.7%) and residential (0.8%) emissions offset by a 4% fall in industrial emissions. Does this mean that Chinese emissions are peaking?
Electricity output increased by 6.3% between 2023 and 2024 so far. The increase was supplied by roughly equal increases in thermal power, hydropower, and the new renewables. The increase in hydropower is weather-related and otherwise there would have been a more significant increase in thermal power.
Coal production is only up 0.7% on last year. In the first few months of the year, coal production was lower than in the previous year but by October it was running at 6% above the level of last year.
In conclusion, the fall in emissions so far this year is probably partly due to the increase in hydroelectric output and the slow economy early in the year. This probably doesn't yet constitute a sustainable peak in emissions.
Last year, I published an article in The Conversation followed by a paper in Environmental Challengeswith Khalid Ahmed on the trend in carbon emissions in China after the pandemic. We concluded that emissions continued to rise strongly after the pandemic. Most of the increase was in the electric power sector. A peak in emissions wasn't yet in sight. Has anything changed in the past year?
In the published paper, we compared emissions in the first eight months of 2019 - the last year before the pandemic - with the first eight months of 2023 - the first year after the pandemic. Now we can compare data for 2019 as a whole with 2023 as whole:
The differences between 2019 and 2023 for the power sector and total emissions are a little less dramatic than those in the published paper. Emissions in the power sector increased by 18% (21% using just the first 8 months) and total emissions increased by 8% from 2019 to 2023 (10% in the published paper). The data is from Carbon Monitor. Both of these differences are extremely statistically significant. Transport emissions fell by 1% (p = 0.01). The change in residential and industry emissions between the two years are not statistically significant. The published results showed a small but statistically significant increase in industrial emissions and no statistically significant change in transport or residential emissions.
We also presented the contributions of fossil fuels, nuclear, and renewable energy to electricity generation. Here is the graph updated for all twelve months of 2019 and 2023:
The shares of solar and wind increased from 1.6 and 5.0% in 2019 to 3.2% and 9.0% in 2023 but thermal electricity generation increased by 91 TWh p.a. compared to an increased of 51 TWh from the new renewables. Nuclear and hydropower increased by a total of 6 TWh. So, though output of electricity from new renewables increased a lot, thermal power still dominated the increase in electricity generation. The share of thermal power in total generation only fell from 72.2% to 70.1%. Finally, I've updated the coal production data to the end of 2023 (exponential trend fitted):
Coal production for 2023 was 26% higher than coal production in 2019 or a compound annual growth rate of 6%.
None of these results are much different than those in our published paper. But what about 2024? That will be the subject of my next post.
Monday, July 10, 2023
China is pumping out carbon emissions as if COVID never happened. That’s bad news for the climate crisis
Carbon emissions from China are growing faster now than before COVID-19 struck, data show, dashing hopes the pandemic may have put the world’s most polluting nation on a new emissions trajectory.
We compared emissions in China over the first four months of 2019 – before the pandemic – and 2023. Emissions rose 10% between the two periods, despite the pandemic and China’s faltering economic recovery. Power generation and industry are driving the increase.
Under the Paris Agreement, China has pledged to ensure carbon emissions peak by 2030 and reach net zero emissions by 2060. Our analysis suggests China may struggle to reach these ambitious goals.
Many believed the economic recovery from COVID would steer global development towards a less carbon-intensive footing. But China’s new path seems to be less sustainable than before. That’s bad news for global efforts to tackle climate change.
China has pledged to ensure carbon emissions peak by 2030 – but it’s heading in the opposite direction.Olivia Zhang/AP
An alarming trend in emissions
The COVID pandemic curbed greenhouse gas emissions in 2020, largely due to a drop in passenger travel. This led to hopes of a “green” economic recovery in which government stimulus spending would be invested into climate-friendly projects, to ensure a longer-term slowing of growth in emissions.
Some researchers examined the trends in China’s emissions up to 2019 and predicted the nation’s emissions would peak by 2026. Others have said the peak will occur even earlier, in 2025.
But unfortunately, it seems those predictions were too optimistic.
We examined data from Carbon Monitor, which provides science-based estimates of daily CO₂ emissions across the world. We compared emissions data from January to April 2019 (which represents typical pre-pandemic conditions in China) with the corresponding months in 2023. This period followed the removal of most COVID-related restrictions in China – such as testing requirements and quarantine rules – which essentially restored the country’s economy to business-as-usual.
We found average daily carbon emissions increased substantially between the two periods. In the first four months of 2019, China’s transport, industry, energy and residential sectors together emitted an average 28.2 million tonnes of CO₂ a day. In the first four months of 2023, daily emissions from those sectors were an average 30.9 million tonnes.
Emissions from the residential and transport sectors didn’t change much. This is mildly good news – it’s better than emissions going up. But these are the two smallest sectors, together accounting for only 18% of China’s emissions.
Rather, the increase was driven by emissions from China’s industrial and energy sectors. Average daily emissions from industry rose between 2019 and 2023 by 1.1 million tonnes or 11%. From energy, which includes electricity generation, they rose by 1.75 million tonnes or 14%.
Energy production from solar and wind in China did increase substantially between the two periods. But the growth was outweighed by electricity generated from fossil fuels.
Separate data show the growth of coal production in China has accelerated. In the two years prior to the pandemic, coal production variously fell or only grew slightly. But coal production grew during the pandemic, and this has continued. In the year to April 2023, coal production increased by about 5%.
While coal’s share of energy consumption fell substantially from 2007 to 2019, it has changed little since then. That’s mainly because energy use is growing fastest in the electricity sector, which remains dominated by coal.
The global picture
Emissions in many developed countries have fallen in recent years due to government policies, slow economic growth, and the shift from coal to natural gas.
Developing nations increasingly dominate global emissions. China might be expected to be a leader on the clean energy shift among developing countries – in part because it produces much less oil than it consumes. That means its energy supply is not secure, giving it an incentive to find alternative sources of power.
There’s another reason why China should be a trailblazer on emissions reduction. China is the world’s biggest emitter – so a percentage reduction in emissions there leads to far fewer tonnes of CO₂ in the atmosphere than if a smaller country reduced emissions by the same percentage. And, partly because China’s population and economy are so big, it stands to benefit more than any country in the world from a more stable global climate.
But as we’ve outlined, China’s trajectory is by no means world-leading. What’s more, moves by China on the international stage suggest it’s becoming less cooperative in climate negotiations than in recent years. We saw this at the COP27 global climate conference in Egypt late last year, when China did not join a pledge to curb methane emissions and refused to provide financial support to developing nations vulnerable to climate change.
The potential for cooperation on climate policy is being reduced further by ongoing tensions between China and the United States. All this serves to cast doubt on China following through on its Paris pledges – and certainly, on any chance its emissions will peak in the next two years.
Alejandro Puerto is a 20 year old who lives in
Cuba. He has written: "Western Cycles: United Kingdom" a book that
covers the economic and political history of the UK from 1945
onwards. He maintains a website of the same name that showcases his writing. You can also follow him on Twitter. He asked me whether I would I would do an interview for his blog. Here it is:
When did you became interested in the energy and the environment on economics?
I was interested in the environment from an early age and so I studied geography, biology (and chemistry) in the last 2 years of high school in England (1981-3) and then went on to study geography at university (in Israel). I had to pick another field and initially chose business as something practical but quickly switched to economics. I then realised that economics could explain a lot of geography and environmental trends. It was only when I went to do my PhD starting in 1990 that the faculty at Boston University at the Center for Energy and Environmental Studies which was linked to the Geography Department there were really focused on the role of energy in the economy and environmental trends that I became interested in understanding the role of energy. So I got a PhD in geography officially but had quite a lot of economics training and over time drifted closer to economics, so now I am even director of the economics program at the Crawford School of Public Policy at ANU.
I think that my generation is more informed on climate change because of the work of people like you. Do you think the same? Describe us some of your research.
Well, I think it has just become a much bigger and obvious issue as the global temperature has increased. The awareness of what is happening has been driven by people in the natural sciences. I have done some research applying time series models used in macroeconomics to modelling the climate system and though our first paper was published in Nature in 1997 and we have been cited on that in IPCC reports it has largely been on the fringes of climate science. My view of that research is that it takes an entirely different approach to modelling the system than most climate scientists use (mostly they use big simulation models called GCMs) and finds similar results which strengthens their conclusions. Most of my research has been on the role of energy in economic growth and the effect of economic growth on emissions and concentrations of pollutants. The effect of energy on growth is much more complicated than many people think – it seems that energy is more important as growth driver in the past in the developed world – adding energy when you have little has more effect than when you already have a lot. On pollution I’ve argued that the idea of the environmental Kuznets curve – that as countries get richer eventually growth will actually be good for the environment and reduce pollution is either outright wrong or too simplified. Instead in fast growing countries like China, growth overwhelms efforts to reduce pollution, while in slower growing developed economies clean up can happen faster than growth.
The Paris Summit filled your expectations as an environmental economist?
It was probably better than expected give the lack of success in getting agreement before then. Countries pledges are too little to reach the goal of limiting warming to 2C and we will probably have to remove carbon from the atmosphere in a big way later in this Century. The real question is whether countries will actually fulfil their voluntary pledges. OTOH low-carbon technology is developing fast and that is a positive that is making achieving the goals looking more possible.
How dangerous would be the environmental policy of the United States under the Trump administration on climate change?
It will delay action, unclear how much effect it will really have. Encouraging the development of new technology is important and having the largest and leading economy not focused on that is a negative. The US can’t actually leave till late 2020 and Trump has left the door open to submitting a weaker INDC in the interim and claiming victory. The US will still be involved in UNFCCC talks etc.
What do you think about the emissions of developing countries as they become industrious?
Developing country emissions are now larger than developed country emissions. But there is a big difference between China which now has higher per capita emissions than the European Union and say India which has still very low per capita emissions. China needs to take action and has made a moderately strong pledge. We should expect much less from India say. India is, though, strongly encouraging renewables development. Hopefully, technology is advancing fast enough that the poorest countries will end up going down a lower carbon path anyway as fossil fuel technologies gradually phase out.
Since 2006 China has become the greatest global polluter and emissions still growing continuously. China has no plans for decrease these emissions until 2030. What do you think about the attitude of this country?
They say they will peak emissions by 2030. In terms of reduction in emissions intensity per dollar of GDP their goal is quite strong. In the last 3 years Chinese CO2 emissions have been constant. Some argue they are already peaking now. I am a bit more skeptical. We need to see a few more years. There are several reasons why China is pursuing a fairly strong climate policy including energy security, encouraging innovation and reducing local air pollution as well as realising that they can benefit a lot from reducing their own emissions because they are such a large part of the problem.
In the long term, which kind of renewable energy would be the first to think about? Solar? Wind?
Solar – it has a greater potential total resource and looks like eventually prices will be below wind. Wind of course is strong in places without much sunshine like the Atlantic Ocean off NW Europe. I’m concerned though about the environmental impact of lots of wind power. In the long-run I’m still hoping for fusion to work out :)
Tell us about one of your favorite posts published by you on Stochastic Trend.
I’ve done less blogging recently as I now use Twitter for short things. Most of the posts are excerpts from papers or discussions of new papers. The most popular blogpost this year with visitors is:
Where I discuss our working paper on the role of coal in the Industrial Revolution. The research and writing of this paper took a very long time and I was really happy to be able to announce to the world that it was ready.
Do you drive an electric car?
No, I don’t have a driving licence. My wife drives and we have a car but it is a large petrol-engined car that is not very efficient. We don’t drive it much though. We’ve driven less than 30,000 km since buying it in 2007.
Have you ever visited Cuba? Are you interested? There are a lot of 1950s cars, but there are places with tropical nature.
No, I haven’t been to Cuba. The only place I’ve been in Latin America is Tijuana, Mexico. I’m not travelling that much recently as we now have a 1 1/2 year old child. But Cuba probably wouldn’t be high on my agenda. I travel mostly to either visit family or go to academic conferences and work with other researchers. The only time I flew somewhere outside the country I was living in just to go on vacation was when I flew from Ethiopia to Kenya. I was at an IPCC meeting in Ethiopia.
The first paper, coauthored with Zsuzsanna Csereklyei, is the first to emerge from our ARC funded DP16 project. Our goal was to look at the factors associated with the adoption of more or less energy efficient electricity generating technologies using a detailed US dataset. For example, combined cycle gas turbines are more energy efficient than regular gas turbines and supercritical coal boilers are more efficient than subcritical. Things are complicated by the different roles that these technologies play in the electricity system. Because regular gas turbines are less energy efficient but have lower capital costs they are mainly used to provide peaking power, while combined cycle turbines contribute more to baseload. So comparing combined cycle gas to subcritical coal makes more sense as a test of how various factors affect the choice of energy efficiency than comparing the two types of gas turbine technologies.
Additionally, some US regions underwent electricity market reform where either just wholesale or both wholesale and retail markets were liberalized, while other regions have retained integrated regulated utilities, which are typically guaranteed a rate of return on capital. Unless regulators press utilities to adopt energy efficient technologies there is much less incentive under rate of return than under wholesale markets to do so.
The graph shows that following widespread market reform at the end of the 20th Century there was big boom in investment in the two main natural gas technologies. More recently renewables have played an increasing role and there was a revival of investment in coal up to 2012. These trends are also partly driven by the lagged (because investment takes time) effects of fuel prices:
We find that electricity market deregulation resulted in significant immediate investment in various natural gas technologies, and a reduction in coal investments. However, market deregulation impacted less negatively on high efficiency coal technologies. In states that adopted wholesale electricity markets, high natural gas prices resulted in more investment in coal and renewable technologies.
There is also evidence that market liberalization encouraged investments into more efficient technologies. High efficiency coal technologies were less negatively affected by market
liberalization than less efficient coal technologies. Market liberalization also resulted in increased investment into high efficiency combined cycle gas. In summary the effect of liberalization is most negative for the least efficient coal technology and most positive for the most efficient natural gas technology.
The second paper is based on a survey of households in rural China and assesses the potential for energy conservation and carbon emissions mitigation when energy saving technologies are not fully implemented. In reality, appliances do not always survive for their designed lifetime and households often continue to use other older technologies alongside the new ones. The effect is to raise the cost of reducing energy use and emissions by a given amount. The paper computes marginal abatement cost curves under full and partial implementation of the new technologies.
The graph shows the marginal abatement cost curve for rural households in Hebei Province, scaled up from the survey and our analysis. Full-Scenario is the curve with full implementation of new technologies and OII-Scenario is with actual partial implementation. This analysis does not take into account any potential rebound effect of energy efficiency improvements.
The first author, Weishi Zhang, is a PhD student at the Chinese University of Hong Kong. She contacted me last year about possibly visiting ANU, and I supported her application for a scholarship to fund the visit (which unfortunately she didn't get), because I thought her research was some of the more interesting research on Chinese energy use and pollution that I had seen. I helped write the paper (and responses to referees in our revise and resubmit).
I don't like looking at my published papers because I hate finding mistakes. Today I saw that there is a missing coefficient in Table 2 of my recent paper with Donglan Zha "Economic growth and particulate pollution concentrations in China". In the column for Equation (2) for PM 2.5 the coefficient for the interaction between growth and the level of GDP per capita is missing. The table should look like this:
I checked my correspondence with the journal production team. They made lots of mistakes in rendering the tables and I went through more than one round of trying to get them to fix them. But the version I eventually OK-ed had this missing coefficient. At least the working paper version has the correct table.
A new working paper coauthored with Donglan Zha, who is visiting the Crawford School, which will be published in a special issue of Environmental Economics and Policy Studies. Our paper tries to explain recent changes in PM 2.5 and PM 10 particulate pollution in 50 Chinese cities using new measures of ambient air quality that the Chinese government has published only since the beginning of 2013. These data are not comparable to earlier official statistics and we believe are more reliable. We use our recently developed model that relates the rate of change of pollution to the growth of the economy and other factors as well as also estimating the traditional environmental Kuznets curve (EKC) model.
Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications have focused on pollution emissions. Yet, it would seem more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. This is the first application of our new model to such concentration data.
The data show that there isn't much correlation between the growth rate of GDP between 2013 and 2014 and the growth rate of PM 2.5 pollution over the same period:
What is obvious is that pollution fell sharply from 2013 to 2014, as almost all the data points have negative pollution growth. We have to be really cautious in interpreting a two year sample. Subsequent events suggest that this trend did not continue in 2015.
In fact, the simple linear relationship between these variables is negative, though statistically insignificant. The traditional EKC model and its growth rate equivalent both have a U shape curve - the effect of growth is negative at lower income per capita levels and positive at high ones. But the (imprecisely estimated, so not statistically significant) turning point fro PM 2.5 is way out of sample at more than RMB 400k.* So, growth has a negative effect on pollution in the relevant range. When we add the initial levels of income per capita and pollution concentrations to the growth rates regression equation the turning point is in-sample and statistically significant. The initial level of pollution has a negative and highly statistically significant effect. So, there is "beta convergence" - cities with initially high pollution concentrations, reduced their level of pollution faster than cleaner cities did.
So what does all this mean? These results are very different than those we found for emissions of CO2, total GHGs, and sulfur dioxide. In all those cases, we found that growth had a positive and quite large effect on emissions. In some cases, the effect was close to 1:1. Of course, we should be cautious about interpreting this small Chinese data set. But our soon to be released research on global PM 2.5 concentrations, will again show that the effect of growth is smaller for these data than it is for the key pollution emissions data. This confirms early research that suggested that pollution concentrations turn down before emissions do, though it doesn't seem to support the traditional EKC interpretation of the data.
A new working paper coauthored with Chunbo Ma on estimating long-run elasticities. This is one of the major parts of our ARC DP12 project, the "Present" part of the title: "Energy Transitions: Past, Present, and Future". We just resubmitted the paper to a journal and I thought that was a good time to post a working paper with the benefit of some referee comments.
We review the econometric research that discusses how best to get long-run elasticity estimates from panel data. One suggestion is to use the between estimator, which is equivalent to an OLS regression on the average values over time for each country, firm etc. in the panel.
Alternatively, Chirinko et al. (2011) argued in favor of estimating long-run elasticities of substitution using a long-run difference estimator, which is very similar to the "growth rates estimator" we have used recently.
We apply both these estimators to a Chinese dataset we have put together from both public and non-public data sources. We have data for 30 Chinese provinces over 11 years from 2000 to 2010. We estimate models for choice of fuels - interfuel substitution - and for the choice between capital, labor, and energy - interfactor substitution.
A big issue with the between estimator, which has made it relatively unpopular, is that it is particularly vulnerable to omitted variables bias. The big omitted variable in most production analysis is the state of technology. There is a lot of variation across provinces in productivity and prices and it seems that the two are correlated:
The first graph shows the price index for aggregate coal input that we constructed. Generally, coal is more expensive in Eastern China. The second graph shows an index of provincial total factor productivity, relative to Shanghai, which is the most productive province. Coastal provinces are the most productive - their distance to the technological frontier is low. To address this potential omitted variables bias, we add province level
inefficiency and national technological change terms to the cost
function equation. Chirinko et al. (2011) instead used instrumental variables estimation, but we found that their proposed instruments in many cases have very low or negative correlations with the targeted variables. We do use instrumental variables estimation, but this is due to the endogeneity inherent in our constructed coal and energy prices indices. We use Pindyck's (1979) approach to this. We also impose concavity on the cost function, if necessary.
The results show that demand for coal and electricity in China is very inelastic, while demand for diesel and gasoline is elastic. With the exception of gasoline and diesel, there are limited substitution possibilities among the fuels. Substitution possibilities are greater between energy and labor than between energy and capital. These results seem very intuitive to us. However, they are quite different to some previous studies for China, in particular the estimates in the paper by Hengyun Ma et al. (2008) Their estimates of the elasticities of substitution are negatively correlated with ours. Their study uses similar but older data, though we have improved the calculation of some variables. They use fixed effects estimation and don't impose concavity. These might be some of the reasons why our results differ. We also provide traditional fixed effects estimates with concavity imposed. These estimates are mostly close to zero. This suggests that the between and difference estimators are picking up longer-run behavior.
Which of these two estimators should we use in future? We can't give a definitive answer to that question but the difference estimator does seem to have some advantages. In particular, it allows cross-equation restrictions on the bias of technical change, which should result in better estimates of those parameters. So, that would be my first preference, though I am kind of reluctant to ignore the between variation in the data.
Donglan Zha is visiting Crawford School for the next year. She is an associate professor at Nanjing University of Aeronautics & Astronautics and works on energy economics including research on substitution possibilities and the rebound effect. Her office is in Constable's Cottage across the road from the main Crawford Building. Her ANU e-mail address is donglan.zha@anu.edu.au. Please welcome Donglan to the Crawford School, I'm sure she will be happy to meet with you.
A few days ago China and the US jointly announced emissions targets for 2030. China proposes that their carbon emissions will peak by not later than 2030. How ambitious is this goal? In our 2010 paper in Energy Policy, Frank Jotzo and I asked how ambitious China's 2020 target to reduce emission intensity by 40-45% between 2005 and 2020 was. We concluded that it represented significant effort beyond expected intensity reductions under business as usual.
In a recent paper Xiliang Zhang and coauthors project Chinese emissions under three scenarios. Under a no policy scenario, emissions rise to 16.5 billion tonnes (Gt) in 2030 and continue to rise throughout the century. Under their "continued effort" scenario where current policy initiatives are continued, emissions rise to 11.8 Gt in 2030 and peak in 2045. Finally, under their accelerated effort scenario, emissions rise to 10.2 Gt in 2030 where they peak. So, on this basis, China's proposal does constitute a new accelerated effort.
Another way of looking at these scenarios is in terms of the rate of reduction in emissions intensity in 2030. The rates are -1.9%, -3.4%, and -4.1% respectively. China's 2020 emissions intensity target represents a 3.6% annual rate of reduction in emissions intensity from 2005 to 2020. So, by this metric the new target represents an increase in effort over the current policies.
Some slides from my upcoming introductory lecture for my Energy Economics course:
This slide uses CDIAC data on the top twenty countries by emission of carbon dioxide globally in 2010. Carbon dioxide emissions here include only those from fossil fuel combustion and cement production. I also have summed up the emissions from the European Union and added it as if it was a single country (as the EU negotiates as a bloc) in addition to including all its member countries in the ranking. The three big emitters stand out clearly from all the rest. Emissions are measured by mass of carbon. To get carbon dioxide multiply by 3.66.
Of course, coal use is a big driver of CO2. This chart shows how China consumers so much more coal than any other country and after the US and India, the rest look pretty inconsequential.
On the whole, coal is consumed where it is produced with two important exceptions - Indonesia and Australia - the two biggest coal exporters. China produces the overwhelming majority of the coal it uses despite large imports. The majority of Australian exports are coal for iron smelting, so-called "metalurgical coal".
Chapter 5 was one of the main chapters of the Working Group III 5th Assessment Report at the centre of the controversy this week on so-called censorship of the Summary for Policy Makers (SPM). The SPM is an executive summary of the report for the IPCC member governments. Those member governments get to dictate what points from the underlying report get included in this summary and how they are "spun". However, there is also a Technical Summary that is written entirely by the researchers responsible for the main report. The material from Chapter 5 that was in the draft SPM but eliminated in the plenary meeting in Berlin referred to emissions from specific groups of countries. This blogpost provides a quick overview of the deleted figures, some of which are still in the Technical Summary.
The first graph breaks down emissions by broad global regions:
The developed countries are represented by the members of the OECD as it stood in 1990 (since then Mexico, Korea, Czech Republic etc. have joined). Eastern Europe and the former Soviet Union are designated "Economies in Transition" and the developing world is broken down into Asia (importantly including China and India), Latin America, and the Middle East and Africa. The left-hand panel shows emissions year by year since the Industrial Revolution and also breaks them down into energy and industrial and land use related emissions. The former continue to increase but the latter appear to have peaked. Since the 1970s, the majority of growth in energy and industrial emissions has come from developing countries and particularly Asia. In an attempt to better represent the historical responsibilities of each group of countries the right-hand panel shows the cumulative historical emissions of greenhouse gases by region.* China and particularly India have campaigned to get historical contributions to global warming better-acknowledged. But the results of our analysis show that less than half of the cumulative emissions now come from the developed countries as a whole (more when only energy and industrial emissions are considered). This, presumably, isn't the message that developing country delegates wanted to see.
The next controversial figure breaks down total and per capita greenhouse gas emissions by country income groups:
The leftmost panel shows total emissions which increased everywhere due to population growth. But they particularly increased in upper middle income countries (which includes China). The total emissions from this group are now almost equal to that from the high income countries. On a per capita basis, emissions were flat in the developed world and declining in the poorest countries (as emissions from land use declined). They rose in the middle income countries. The figure does, however, also show that in all developing country groups per capita emissions remain much below those in the developed countries.
The final deleted figure deals with emissions embodied in trade:
Looking at the emissions generated in producing imports and exports, the developed countries and economies in transition ("Annex B") import more "embodied" emissions than they export. The opposite is true of the developing countries ("Non Annex B"). Emissions that include the net emissions embodied in trade are termed "consumption emissions" in contrast to the "production emissions" that are the total emissions emitted within a country and are the usual way of calculating emissions.** These numbers are derived using input-output modelling. The results are often used to argue that developed countries have reduced their emissions by offshoring production to developing countries, which is a controversial question. But properly answering this question is more complicated than this. They are also used to claim that developed countries are responsible for their consumption emissions rather than their production emissions. But both importers and exporters gain from this trade. Because of these controversies I can understand the decision to drop the discussion and figure from the SPM.
* These do not directly correspond to the amounts of gases in the atmosphere. A large fraction of annual carbon dioxide emissions are absorbed by the ocean, vegetation etc. and methane only survives for an average of 11 years in the atmosphere before being oxidised to carbon dioxide and water. So, I am not very enthusiastic about treating cumulative emissions of carbon dioxide equivalent greenhouse gases as an indicator of historical responsibility.
** Economists would usually use the term "production emissions" to refer to emissions from production activities and "consumption emissions" to refer to emissions by consumers. This initially caused some communication problems among researchers from different disciplines in our chapter team.
If downloading papers from Springer = working then this paper by Wang et al has fascinating evidence on when researchers are working around the world. They got several days data on downloads of academic articles from Springer by location and time of day and composed download curves across the day for both weekdays and the weekend. Most of the cultural stereotypes hold up - late lunch in Spain and almost no lunch break in the US and UK. Australians tend to have a more defined workday than other English speakers. Americans, Chinese, and British work particularly hard at the weekend compared to other countries.
An in press paper by Nam et al. in Global Environmental Change uses a CGE model to estimate the co-benefits in terms of reduced CO2 emissions from the tougher new policies on SO2 and NOx emissions in the current Chinese 5 year plan. They find very large co-benefits with a reduction in CO2 emissions of 1.4 billion tonnes by 2015 alone. In later (post-plan) years these come to a large extent from switching to non-fossil energy. But in the short-run a large part of the reductions come from reducing energy use very significantly as shown in this figure from the paper:
The figure shows the reduction in energy use relative to business as usual in exajoules under an SO2 and NOx policy alone with no climate policy. For context, current Chinese energy use is in the rough ballpark of 100 exajoules a year. So the figure shows that by 2020 the reduction in energy use due
to the policy relative to BAU is around this current level of Chinese
energy use. This is simply huge. The policy also induces a complete shift away from using coal to generate electricity after 2040. The reason that the RHS figure above shows reduced coal use flattening out after 2035, is because China would already be using hardly any coal under this scenario.
Looking at historical analogs, when the US introduced tightened caps on SO2 emissions in the early 1990s there was some fuel switching in the long run to natural gas and other electric generation sources, but the main choice that electricity generators made was to switch to lower sulfur coal, to install scrubbers, and to use coal washing etc. I have less detailed knowledge of the reaction in Europe to similar policies but it involved these things in different proportions (more scrubbers and natural gas from what I understand). Presumably electricity use did fall a bit due to higher costs but not on a huge scale.
This model does not seem to have a low sulfur coal option though it does have a scrubber style abatement technology. Switching to natural gas can save some energy as it is a more
efficient fuel for electricity generation and switching to renewables
can save a lot of energy depending on how renewables are accounted for.
But these things mostly happen after 2020 in this paper. So most of the reduced emissions are from reducing energy use on a large scale. Nothing like this happened in the US or Europe (or elsewhere) in reaction to such policies.
My thinking is that the large energy use reductions relative to BAU must be due to high elasticities of substitution between energy and other inputs (the model uses nested CES functions) or other model features that are not immediately apparent to me. The costs of the policy seem to be quite small in the first ten years, so the reduced energy use does not have a big economic impact in the short-run.
I've just linked a Crawford School blog from the Development Policy Centre to my bloglist. Also from the Crawford School, though they don't describe it as a blog, is the East Asia Forum. P.S. As Paul noted in the comments, there is also the Global Water Forum, which is an initiative of of the UNESCO Chair in Water Economics and Transboundary Water Governance at the Crawford School. There are probably more that I don't know about yet. These kinds of blogs and forums are something I am enthusiastic about us using more to complement formal publications and events as well as traditional mentions in the media.
Based on reading of government documents and the writings of Chinese academics, Olivia Boyd's ANU masters thesis documents the role of three ideas in driving China's current energy and climate policies:
1. The idea of new energy security that stresses domestic, rather than international, sources of energy insecurity. 2. Green development and growing concern over the environmental and resource constraints on economic growth. 3. Low-carbon leadership, which posits a vision of China’s international political and economic influence based on climate leadership and low-carbon markets.
This is roughly what I have argued are China's motivations - for example in my CRWF 8000 lectures on energy and the environment that I gave in October - but I find a lot of resistance to accepting that China is serious about these issues and I based my view largely on conjecture rather than a close reading of the literature. This thesis stands on much more solid foundations.
I saw this paper on academia.edu, which I am finding more and more useful as people are posting interesting papers on it that I otherwise wouldn't see.
I was featured along with Frank Jotzo and others in this blogpost on DotEarth by Andy Revkin. I'm still confused about why people want Australia to go beyond its obligations under the UNFCCC. And it's not as if China isn't doing its part too, though very soon China will need to start reducing emissions rather than just emissions intensity. Wait to be surprised on that count I think.