This paper reviews the CO2 emissions data for China provided by various international organizations and databases (namely IEA, BP, EDGAR/PBL/JRC, CDIAC, EIA and CAIT) and compares them with China’s official data and estimation. The difference among these data is due to different scopes, methods and underlying data, and particularly the difference in fossil fuel consumption. Compared with data from other databases, IEA and CAIT data have the best comparability with China’s official data. The paper recommends that China enhance its coal statistics, raise the frequency of official data publication and improve the inventory completeness.


CO2 ; emissions data ; comparability

1. Introduction

Second National Communication (SNC) on Climate Change of the People’s Republic of China was submitted to the Secretariat of the United Nations Framework Convention on Climate Change (UNFCCC, hereinafter referred to as the Convention) in November 2012 [ NDRC , 2012 ] and was released to the international communities. The second part of the communication was about China’s GHG inventory in 2005. This was the third time China officially released its GHG data after the release of GHG data of 1994 in Initial National Communication on Climate Change of the People’s Republic of China (INC) in 2004 [ NCCC and NDRC , 2004 ] and data of 2004 in National Climate Change Programme (NCCP) in 2007 [ NDRC , 2007 ]. And this was also the first time China officially released the base year data after its 2020 CO2 mitigation target was announced in 2009 before the Copenhagen Conference, attracting wide attention from the international communities.

However, there are some differences between the data released by China and those by the internationally renowned research agencies or databases. These agencies are far surpassing China in terms of the frequency and timeliness of their data release, often resulting in the international community’s preconceived impression on China’s GHG emissions. This paper analyzes and compares the major international CO2 emissions data with China’s official data from the perspective of original data source, calculation scope and methodology . The purpose of the study is, on the one hand, to clarify the causes of differences through comparative analysis; and on the other hand, to identify the weaknesses in China’s energy statistics.

2. A comparison between CO2 emissions data officially released by China and data from other sources

2.1. China’s official CO2 emissions data and estimated data in 2006–2011

Table 1 lists China’s official CO2 emissions data. Both INC and SNC adopt TIER2 method provided by Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (hereinafter referred to as IPCC 1996) for inventory development, and the reference approach is also used for comparison [ NDRC, 2012  ;  NCCC (National Co-ordination Committee for Climate) and NDRC (National Development and Reform Commission), 2004 ]. The main sources of CO2 emissions covered by SNC are fossil fuel combustion, industrial processes (the production of cement, steel, lime, and calcium carbide and utilization of limestone and dolomite) as well as the combustion of a very small amount of non-botanic waste. CO2 emissions from fossil fuel combustion do not cover international bunker (listed separately) or non-energy use [ NDRC, 2012 ]. Other energy activities may also produce significant CO2 emissions, such as coal mining, venting and flaring in oil and gas system, but they are not estimated in SNC.

Table 1. Summary of China’s official CO2 emissions data
Emission category INC (1994) NCCP (2004) SNC (2005)
Energy-related CO2 emissions (Mt) 2,795 5,404
CO2 emissions from industrial processes (Mt) 278 (including 160 Mt from cement production) 5,070 569 (including 410 Mt from cement production)
Total GHG emissions (Mt CO2 -eq, 4,058 6,100 7,467
excluding LULUCF) Share of CO2 in overall GHG emissions (%) 75.7 83.1 80.0

Note: The data of 2004 were rough estimates, less comparable with those of 1994 and 2005; the scope adopted to calculate the inventory data of 2005 was slightly wider than that of 1994, but it has limited impacts

The paper estimates CO2 emissions from energy combustion in China in 2006–2011 based on the implied emission factors of primary fossil fuels in 2005, namely, CO2 emissions per unit of coal, oil and gas (t CO2 (TJ)−1 ). Meanwhile, according to CO2 emission factor of clinker production and proportion of clinker in cement, CO2 emissions from China’s cement production in 2006–2011 are also estimated , as shown in Figure 1 .

Trends of China’s CO2 emissions from fossil fuel combustion and cement ...

Figure 1.

Trends of China’s CO2 emissions from fossil fuel combustion and cement production in 2006–2011

It should be noted that the above estimations are all based on China’s official energy consumption and industrial production statistic data. China has gradually established its energy statistics system since the early 1980s, and a relatively complete system of statistical indicators and statistical agencies has been set up on both national and local levels to meet the needs in that time. Nevertheless, China’s energy statistics still has certain limitations, such as a shortage of high quality data, unsound energy statistical scopes and statistical indicators, and weak energy statistics foundations, etc. [ Di , 2011 ]. The marketization of energy industries has further weakened the original energy statistic system [ Li et al. , 2010 ]. Therefore, there are certain deviations in the official energy data released by China. Using these data as the basis of comparison with other data, by no means, denies the potential uncertainties in the data. Nevertheless, the comparison with other data will help further identify the shortcomings of China’s energy statistics and propose concrete recommendations for improvement.

2.2. Comparison of the data published by international research agencies and databases with the data released by China and estimated in this paper

The research agencies and databases regularly publishing national CO2 emissions include the Secretariat of the Convention , International Energy Agency (IEA), British Petroleum (BP), Emission Database for Global Atmospheric Research (EDGAR) jointly developed by Netherlands Environmental Assessment Agency (PBL) and the European Commission’s Joint Research Centre (JRC), Oak Ridge National Laboratory Carbon Dioxide Information Analysis Center (CDIAC), U.S. Energy Information Administration (EIA), and the Climate Analysis Indicators Tool (CAIT) of U.S. World Resources Institute (WRI).

Figure 2 shows the emissions data of China in 2005–2011 published by these research agencies and their comparison with the data released by China and estimated by this study. Upon examining the trends of these series in 2005–2011, it can be seen that: 1) as for CO2 emissions from energy combustion, the estimate data have basically formed the pattern of BP>EDGAR>EIA>IEA≈CAIT>CDIAC, and some agencies’ data are less than or closer to the data released by China, but the rest are much higher, especially the data after 2008 (Fig. 2 a & Fig. 1 ); 2) as for CO2 emissions from cement production process, the data in 2005–2006 from EDGAR are close to those of SNC and the estimate of this paper and then demonstrates significant deviation, and CDIAC estimate is far higher than that of this paper (Fig. 2 b & Fig. 1 ).

Estimation of China’s CO2 emissions from fossil fuel combustion (a), and cement ...

Figure 2.

Estimation of China’s CO2 emissions from fossil fuel combustion (a), and cement manufacture (b) in 2005–2011 by various agencies

3. Scope, methodology and sources of underling data of CO2 estimation in selected international research agencies

3.1. IEA data

IEA data have a relatively broad coverage (131 countries) and time series are quite complete (OECD countries: 1960–2010; other countries: 1971–2010). The limitation lies in its lack of timeliness, and the data generally lag by one year and a half (for example, the data in 2010 was released in mid-2012).

IEA uses both the reference approach in IPCC1996 and the TIER1 method in sectorial approach for fossil fuel CO2 estimation [ IEA , 2010 ]. The scope of the sectorial approach matches that of fuel combustion specified in IPCC1996, that is, excluding non-energy use emissions, international bunkers emissions, CO2 fugitive emissions from energy production process, and flaring emissions. Therefore, the energy combustion CO2 emissions data of IEA show good comparability with that in China’s SNC in terms of estimation scope and method.

The activity data are from IEA energy statistics, and emission factors adopt the default emission factors in IPCC1996 [ IEA , 2010 ]. According to the cooperation agreement between China and IEA, the National Bureau of Statistics of China (NBSC) provides China’s energy production and consumption data annually to IEA, which will reprocess the data according to its own information and format available. Thus, the China’s energy data in IEA publications are generally consistent with China’s official data.

However, there are significant differences between the CO2 emissions from fossil fuels in 2005 estimated by IEA and the data in China’s communications, and between IEA’s data of 2006–2007 and the estimates of this paper. This research has carried out a special study on this issue. Table 2 lists the data on China’s fossil fuel production and consumption in 2005 released by NBSC and IEA. It can be seen that the data from IEA are smaller than those of NBSC, especially in coal consumption. The reason lies in that in 2009–2010, NBSC adjusted China’s energy data in 1996 and onwards according to the second economic census [ ESD (Energy Statistics Division) and NBSC (National Bureau of Statistics, China), 2009  ;  Tu, 2011 ], and the coal data witnessed the most significant adjustment. The adjusted data in 2005 for coal consumption showed an increase of 150 Mt, equivalent to about 300 Mt of additional CO2 emissions. Similarly, China also adjusted its coal data in 2006 and 2007, but there was no corresponding update in IEA data, so its results were significantly lower.

Table 2. The comparison of fossil fuel data from NBSC and IEA for year 2005 (unit: Mtce)
Consumption Coal Crude oil Natural gas
Production 1,678 1,636 259 259 66 59
Import 20 31 181 181 0 3
Export 52 79 12 12 4 4
Change in stock –25 –25 1 1 0 0
Input for transformation –1,091 –1,032 –415 –422 –8 –18
Loss 0 0 2 0 1 1
End use 568 539 12 5 53 40
Balance difference 38 8 0 2 1 0
Total 1,659 1,571 430 428 62 59

Note: NBSC data are from China Energy Statistical Yearbook 2009; IEA data are from IEA energy balance sheet

3.2. BP data

The 2012 World Energy Review published by BP in June 2012 included the energy-related CO2 emissions data of 72 countries and regions, and covered the time span of 1965–2011 [ BP , 2012 ]. Due to its best timeliness, BP data have been cited considerably.

The scope and method of BP’s CO2 estimation is the simplest, most straightforward and transparent. The emissions data are obtained by multiplying coal, oil and natural gas consumption with their average emission factors, not excluding international bunkers emissions or any potential carbon sequestration. It can be concluded that what BP estimates is the maximum potential CO2 emissions from fossil energy use in various countries, bearing no comparability with the data from other sources and in particular that from national inventories.

BP energy statistics have their own system, and their official release time are earlier than IEA. This study compares BP energy statistics and NBSC energy statistics (Fig. 3 ). The observed difference shows that BP data generally overestimate China’s oil and coal consumption while underestimate natural gas consumption. The difference in oil data is relatively small, not exceeding 2% (but there is an increasing trend in recent years). The difference in coal consumption did not exceed 2.5% in 2002–2008, but from 2009 (2009 included), the difference in coal consumption data between these two systems soared and reached 10.4% in 2011, almost 350 Mt raw coal (NBSC announced China’s coal consumption was 2,380 Mtce in 2011, while BP data showed 2,627 Mtce). This is the major reason for BP’s much higher estimates of China’s energy-related CO2 emissions, and also the reason why the CO2 estimates of other databases based on BP energy data are higher.

The statistic difference of BP and NBSC on China’s fossil fuel consumption

Figure 3.

The statistic difference of BP and NBSC on China’s fossil fuel consumption

3.3. EDGAR and PBL/JRC

3.3.1. Scope and methodology

EDGAR and PBL/JRC have currently published the CO2 emissions data in 1970–2011, covering over 214 countries and regions [ PBL and JRC, 2012  ;  JRC, 2011 ]. The time series is inferior to that of IEA, but with better timeliness. Another difference between IEA and EDGAR is that the scope of the latter is much broader: it not only contains energy-related CO2 emissions, but also includes CO2 emissions from some industrial processes as well as CO2 emissions from nonenergy uses, and even emissions from some fuel spontaneous combustion [ PBL and JRC , 2012 ]. Energy-related CO2 emissions cover not only CO2 emissions from fossil fuel combustion, but also CO2 emissions from gas flaring, which is not included in either INC or SNC of China; industrial processes cover cement production, lime production/utilization and sodium carbonate (soda) production/utilization processes, in which cement production is the major source. It can be seen that there are many differences between EDGAR’s calculation scope and that of China.

EDGAR uses TIER 1 in 2006 IPCC Guidelines for National Greenhouse Gas Inventories (hereafter referred to as IPCC 2006) to estimate CO2 emissions, but its emission source classification still sticks to what is required in IPCC1996 to ensure the comparability with other data sources [ PBL and JRC , 2012 ].

3.3.2. Underlying data sources

With regard to the latest data in 1970–2011 released by PBL/JRC in June 2012, the basic data of different emission categories came from various sources. The energy consumption data before 2008 (2008 included) were mainly from IEA, and the energy consumption data in 2009–2011 came from BP; gas flaring data were from the analysis of satellite monitoring data provided by National Oceanic and Atmospheric Administration (NOAA) and the Global Gas Flaring Reduction Partnership (GGFR) organized by World Bank; cement production data mainly came from the data released by U.S. Geological Survey (USGS), and the data on China came from NBSC. Meanwhile, PBL/JRC also utilizes the clinker ratio data in the report released by World Business Council for Sustainable Development (WBCSD); the basic data on nonenergy uses were mainly from USGS and the World Steel Association (WSA).

3.3.3. Comparison and analysis

In general EDGAR emissions data have a broader coverage and a relatively poor comparability with China and IEA data. Here we will make a rough comparison between IEA emissions series and EDGAR’s energy-related emissions data (Fig. 4 ). It can be seen, the gap between the two remained relatively stable at 200–400 Mt before 2008, but since 2008, the gap began to jump to 700 Mt and reached 900 Mt in 2010. As the energy data in 2009–2011 in current EDGAR database were from BP, it seems to be inevitable that the gap between the calculated CO2 emissions and IEA’s data is widening .

The difference between estimation of IEA and PBL/JRC on China’s CO2 emissions ...

Figure 4.

The difference between estimation of IEA and PBL/JRC on China’s CO2 emissions from energy activities

This paper also carries out a simple analysis on CO2 emissions from China’s cement production released by EDGAR. It is found that EDGAR’s CO2 emission factor per unit of produced cement remained unchanged in 2005–2011 (0.39 t CO2 per ton cement). In fact, the proportion of clinker to cement in China has been decreasing in recent years. It decreased from 70% in 2005 to 61% in 2011 [ MIIT , 2012 ], and correspondingly the intensity of emissions from producing 1 t cement also decreased significantly. Given 0.54 t of CO2 emissions for 1 t clinker (data in 2005), CO2 emissions from China’s cement production were around 700 Mt in 2011, while EDGAR’s estimates were 17% higher.

Trends in Global CO2 Emissions published by PBL/JRC has a specific chapter dedicated to presenting the uncertainty in China’s estimation [ PBL , 2012 ]. It recognizes that the 2008 value is the highest in the available emissions data concerning China, and the uncertainty may be about 10%, but this uncertainty is asymmetrical, with higher possibility of overestimate. At the same time, it considers that there is great uncertainty in NBSC coal consumption data, and the deviation may not be fully adjusted by NBSC’s selfrevision in 2005 and 2009. It also finds the support from relevant materials [ Guan et al. , 2012 ] and BP’s estimate/correction on China’s coal production.

3.4. CDIAC data

By January 2013, CDIAC had collected, estimated and officially published the CO2 emissions data in 1751–2009 of 224 countries/regions [ CDIAC , 2013a ]; in the pursuit of timeliness, CDIAC also informally released in January 2013 the selected countries’ CO2 emissions data in 2010–2011 [ CDIAC , 2013b ]. CDIAC’s data include both energy-related and industrial process CO2 emissions. The former includes not only energy combustion but also natural gas flaring and non-energy use emissions, while the latter refers especially to CO2 emissions from cement production. In hence, CDIAC’s data scope shares some similarities with that for EDGAR. However, the two have differences in dealing with international bunkers: CDIAC includes international bunkers emissions of a country into its total emissions, while EDGAR removes it from the country’s total emissions and includes it into global total bunkers emissions. Due to inclusion of gas flaring and international bunker emissions, CDIAC energy-related CO2 emissions data are relatively less comparable with the official data of China.

CDIAC’s estimates are based on the methods of Marland and Rotty [ CDIAC, 2013a ; Qu et al ., 2008  ;  Marland and Rotty, 1984 ], similar to the reference approach in IPCC 1996. That is, it uses the apparent consumption of varieties of energies to calculate corresponding CO2 emissions.

The underlying data in 1950–2008 in CDIAC database are primarily from the United Nations Statistical Office (UNSO), with appropriate reference to the official statistical publications of each country, of which UNSO data largely reflect the results of the questionnaire distributed by IEA [ Andres et al. , 2012 ]. Cement production data are mainly from the data released by the USGS, and the flaring data come basically from the United Nations and are supplemented by the U.S. EIA data. The estimation in 2009–2010 uses BP energy data.

In theory, CDIAC’s and EDGAR’s energy-related emissions data, owing to similar calculation scopes and underlying data sources, should be relatively close. But the reality is that CDIAC data are closer to IEA data instead of EDGAR data(Fig. 2 a).

Although CDIAC shares similar basic data with EDGAR, its estimation on China’s cement production is far higher (Fig. 2 b). The previous analysis indicates that EDGAR estimates are relatively high, so CDIAC data prove even much higher.

3.5. EIA data

By 2012, EIA had collected, estimated and officially published the CO2 emissions data in 1980–2010 for 217 countries/regions [ EIA , 2012 ]. These data cover only energy-related emissions, including not only energy combustion but also natural gas flaring as well as some non-energy use emissions, and the emissions from international bunkers are included in national total emissions [ Andres et al. ,2012 ]. As a result, the scope of EIA’s CO2 emissions data is quite comparable with that of CDIAC’s energy-related CO2 emissions data. However, the comparability between EIA’s CO2 emissions data and China’s official data is also relatively poor due to the differences in dealing with gas flaring and international bunkers emissions. Similar to CDIAC, EIA also uses the apparent consumption method to calculate CO2 emissions from fossil fuel combustion. But EIA has its own energy statistics channels [ EIA , 2013 ], and it also uses the internal carbon content and oxidation rate data [ Andres et al. , 2012 ].

Despite the consistency in the method and scope adopted by EIA and CDIAC to estimate energy-related CO2 emissions, their results show great differences. As can be seen from Figure 2 a, the estimation of the two shows great differences except in 2006 and 2007 when the two were close, and EIA data in 2010 were nearly 100 Mt higher than CDIAC.

In order to explore the reason for EIA’s slightly higher CO2 emissions estimation, this paper analyzes China’s fossil energy consumption data in 2007–2010 released by EIA and makes a comparison with NBSC data (Fig. 5 ). The results show that EIA’s natural gas consumption data are slightly lower than the statistics of China, but its coal and oil consumption data are significantly larger than NBSC data, of which its coal consumption data in 2010 were about 437 Mtce higher and crude oil consumption data in 2009 were 80 Mtce higher than China’s statistics. Therefore, it is not difficult to understand the high EIA CO2 emissions data.

The difference between EIA and NBSC statistics on China’s fossil fuel ...

Figure 5.

The difference between EIA and NBSC statistics on China’s fossil fuel consumption

In addition, it is also found that the net calorific value of coal adopted by EIA (0.7994 kgce (kg coal)−1 ) is 11.9% higher than the value commonly used in China (0.7143 kgce (kg coal)−1 ). Therefore, from the perspective of physical quantity, EIA statistics on coal consumption in 2010 was about 230 Mt higher than NBSC statistics, but it grew up to more than 400 Mtce after equivalent conversion. The differences both in physical quantity and calorific value conversion factor lead to much higher EIA energy-related CO2 emissions data than IEA data and CDIAC data in recent years.

3.6. CAIT database of WRI

The emissions data in CAIT database, developed by WRI, were chosen from selected database instead of conducting original research. The CO2 emissions data provided by CAIT cover three sources of emissions: energy activities, industrial process (cement production) and land uses & land changes [ WRI , 2011 ]. Currently, the database covers the data of 1850–2008 for 185 countries.

CAIT’s energy-related CO2 emissions data are from a variety of databases. Based on the criteria of completeness (geographic and temporal completeness) and accuracy, CAIT has selected IEA, CDIAC and EIA as the sources of basic data, and the combination is shown in Table 3 . CAIT gives the highest priority to IEA data, followed by CDIAC, and finally EIA. Accordingly, China’s energy-related CO2 emissions data also follow this pattern. The data in 1971–2008 are from IEA, and the data in 1899–1970 are from CDIAC.

Table 3. Source of energy-related CO2 data used in CAIT
Database Used data
IEA Data of 25 OECD countries in 1960–2008; data of 106 developing countries in 1971–2008
CDIAC Data of 25 OECD countries in 1850–1959; data of 106 developing countries in 1850–1970; data of 53 countries in 1850–2008 (IEA does not provide the data of these 53 countries)
EIA The data of one country (Lesotho) in 1950–2008 (IEA and CDIAC do not provide the data of this country)

CAIT data on CO2 emissions from cement production are from CDIAC, covering the period of 1928–2008. Based on the above analysis, CDIAC data for CO2 emissions from cement production are noticeably higher, and they therefore affect the accuracy of the CAIT data.

3.7. Overall assessments of CO2 data from various databases

This paper compares the CO2 emissions data from selected databases from the perspective of methodology, scope, geographic/time coverage, underlying data source and comparability with China’s official data. The results are summarized in Table 4 .

Table 4. Overall assessments on various GHG databases
Name Number of countries covered Start time Calculation method Scope of estimation Comparability with China’s data
Energy combustion Flaring International bunkers Non-energy use Cement production process
IEAa 131 1960 (1971) IPCC1996 Sectoral approach Tierl/Reference approach Included Not included Not included Not included Not included Good
BPb 72 1965 Rough estimate Included Not included Not included Included Not included Not comparable
EDGARc 214 1970 IPCC2006 Tierl Included Included Included* Partially included Included Poor
CDIACd 224 1751 Reference approach Included Included Included** Included Included General
EIAe 217 1980 Reference approach Included Included Included** Included Not included Poor
CAITf 185 1850 No original calculation Included Depending on the country Depending on the country Depending on the country Included Good


  • . Not included in national total, but included in global total;
    • . included in national total.

a. It does not consider China’s energy data adjustment, so the data in 2005–2007 are slightly lower.

b. There are large differences in energy statistics in recent years, and coal consumption data are higher.

c. Recent energy data are from BP and are higher.

d. Energy-related emissions are relatively conservative, but emissions from cement production are higher.

e. Higher emissions caused by higher coal consumption and calorific values.

f. Energy-related emissions data are consistent with IEA, but cement emissions data are from CDIAC which are higher

Since IEA’s energy-related CO2 emissions calculation shares the same scope and similar methodology with China’s inventory, and its energy statistics is close to China’s official data, so IEA emissions data have good comparability with China’s data. The coverage of energy-related CO2 emissions in EDGAR and EIA database is slightly broader, and the estimation is a bit higher, particularly after 2008, so the comparability with China’s estimates was poor. The reason is that the underlying energy data are from either BP or a variety of sources where the coal consumption data are generally higher than China’s official statistics, and the coal calorific value data used by EIA are also much higher than the data commonly used in China. The methodology used by BP is rough and the gap on energy statistic between BP and NSB is very large, so BP’s emissions data generally have no comparability with China’s data. In terms of emissions from cement production, the data published by EDGAR and CDIAC are supposed to be higher, and the latter may be deviated as over 30%. As a comprehensive database without conducting original calculation, CAIT sticks to the principle of completeness and accuracy, and gives the top priority to IEA database, which also brings its data better comparability with China’s data (except for industrial process emissions). But it has similar limitations as IEA, data release is much lagging behind the real time. In order to use the latest data, the user often turns to EDGAR, BP and CDIAC that are more timely but less accurate.

4. Conclusions and recommendations

The above analysis indicates that the data from international research agencies and databases on China’s CO2 emissions vary from one another, and that a considerable part of the data show significant differences from the data China estimated based on TIER 2 of IPCC1996 sectorial approach, and the data gap is widening especially after 2008. Despite the rising emissions and proportion in the global total, CO2 emissions of China should be cited after careful comparison. The overall assessments on these databases and recommendations for China’s future inventory development are as follows:

IEA and CAIT data show relatively good comparability with China’s official data, so it can be used as the basis for comparison or as a reliable reference. If considering the timeliness, CDIAC data might be referred. It is also worth noting that CDIAC has much overestimated China’s cement production emissions, therefore affecting the accuracy of CAIT’s production process data.

The official CO2 emissions data of China should be released more frequently. At present, the frequency of China’s official data release is basically the same as that of the international financial support. In other words, the data are released within 4 to 5 years after receiving the funds, and data release is at least 6 or 7 years after the inventory year, so it is not timely [ Zhu and Wang , 2012 ], and the researchers have to cite more data from a variety of databases. It is suggested that China carry out self-funded estimate of the annual CO2 emissions data from fossil fuel combustion and cement production, thereby shorten data release cycle. In this case, it not only helps to monitor the progress of carbon intensity target during the Twelfth Five-Year Plan period (2011–2015), but also corrects the misleading data and provides a formal data source for researchers and other users in a timely manner.

And an objective assessment on China’s energy statistics system should be conducted to gradually improve the accuracy and credibility of relevant statistics. First of all, coal production and consumption statistics should be greatly enhanced. The higher underlying data on coal consumption cause that BP and BP-based databases (such as EDGAR and CDIAC) release higher emission data for China, and there are widespread doubts on China’s coal consumption statistics in international communities [ Tu, 2011  ;  Guan et al ., 2012 ]. Thus, it is suggested that China should improve domestic statistics while strengthening its energy statistics cooperation with international agencies. Secondly, we need to strengthen coal calorific value statistics and release official statistical data at appropriate time. On the one hand, we think that the coal calorific value factor EIA uses is too high, and on the other hand, we also have to admit that the coal calorific value of 20.94 MJ kg−1 (5,000 kcal kg−1 ) that has been used for many years in China will no longer reflect the actual situation. According to the results of thermal coal quality random inspection in 2005 by China National Coal Quality Supervision and Inspection Center [ NDRC , 2014 ], the gross calorific value of thermal coal in China was 22.71 MJ kg−1 (5,430 kcal kg−1 ) in that year. Given a 5% difference between gross and net calorific value, the net calorific value of coal was about 5,160 kcal kg−1 in 2005. From the perspective of coal consumers, demanding on high-quality coal is growing as large-scaled and standardized devices in energy-intensive industries are more and more popular. Therefore, the unchanged calorific value for many years cannot reflect the actual characteristic of coal used in China, which brings some deviations to inventory development.

CO2 fugitive emissions from energy activities should be included in future inventory development. Currently, CO2 fugitive emissions from coal mining and oil/gas system (particularly gas flaring) have not been included in inventory, resulting in limited completeness. It is suggested that the relevant emission sources should be included to improve completeness and international comparability.


This paper is supported by the project of research on key technologies for synthesis problems during climate change negotiations under 12FYP organized by Ministry of Science and Technology (No. 2012BAC20B02)


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. Since there are few research agencies estimating full-range GHG emissions and China’s autonomous target focuses on CO2 mitigation, this paper chooses CO2 as the object for comparison

. In most international researches, the calculation of production process emissions only covers cement production emissions generally, so this paper just makes a rough estimate of CO2 emissions from China’s cement production to facilitate the comparison with the data from other sources

. The Secretariat of the Convention only accepts the official submission of data, and this paper will not make detailed analysis

. EDGAR’s energy data in 2008 also come from IEA, but the difference in energy-related CO2 emissions between the two reached 740 Mt, far deviating from the relatively stable 300–400 Mt. The reason still remains to be explored

. Nature Climate Change published an article titled The Gigatonne Gap in China’s Carbon Dioxide Inventories in June 2012. In this paper, national and provincial energy production and consumption data released by NBSC were respectively used to calculate the CO2 emissions from China’s energy activities, and the results showed that the calculated results based on the latter were 1 Gt higher than that of the former

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