A new approach to estimate fugitive methane emissions from coal mining in China

Science of the Total Environment 543 (2016) 514–523

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

A new approach to estimate fugitive methane emissions from coal mining in China Yiwen Ju a,b,⁎, Yue Sun a,b, Zhanyou Sa c, Jienan Pan d, Jilin Wang e, Quanlin Hou a,b, Qingguang Li a,b, Zhifeng Yan a,b, Jie Liu c a

Key Laboratory of Computational Geodynamics of Chinese Academy Sciences, Beijing 100049, China College of Earth Science, University of Chinese Academy Sciences, Beijing 100049, China Department of Safety Engineering, Qingdao Technological University, Qingdao 266520, China d School of Resources and Environment, Henan Polytechnic University, Jiaozuo 454000, China e School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Propose a new method to estimate fugitive methane emissions from coal mining. • New method has accurate prediction for CMM emissions without activity data updating. • Mining influence coefficient involved in new method is determined in range 1.3–1.9.

a r t i c l e

i n f o

Article history: Received 26 July 2015 Received in revised form 4 November 2015 Accepted 4 November 2015 Available online 21 November 2015 Editor: D. Barcelo Keywords: Greenhouse gas Methodology Methane emission Coal mining China

a b s t r a c t Developing a more accurate greenhouse gas (GHG) emissions inventory draws too much attention. Because of its resource endowment and technical status, China has made coal-related GHG emissions a big part of its inventory. Lacking a stoichiometric carbon conversion coefficient and influenced by geological conditions and mining technologies, previous efforts to estimate fugitive methane emissions from coal mining in China has led to disagreeing results. This paper proposes a new calculation methodology to determine fugitive methane emissions from coal mining based on the domestic analysis of gas geology, gas emission features, and the merits and demerits of existing estimation methods. This new approach involves four main parameters: in-situ original gas content, gas remaining post-desorption, raw coal production, and mining influence coefficient. The case studies in Huaibei–Huainan Coalfield and Jincheng Coalfield show that the new method obtains the smallest error, +9.59% and 7.01% respectively compared with other methods, Tier 1 and Tier 2 (with two samples) in this study, which resulted in +140.34%, +138.90%, and −18.67%, in Huaibei–Huainan Coalfield, while +64.36%, +47.07%, and −14.91% in Jincheng Coalfield.

⁎ Corresponding author at: Key Laboratory of Computational Geodynamics of Chinese Academy Sciences, Beijing 100049, China. E-mail address: [email protected] (Y. Ju).

http://dx.doi.org/10.1016/j.scitotenv.2015.11.024 0048-9697/© 2015 Elsevier B.V. All rights reserved.

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Compared with the predominantly used methods, this new one possesses the characteristics of not only being a comparably more simple process and lower uncertainty than the “emission factor method” (IPCC recommended Tier 1 and Tier 2), but also having easier data accessibility, similar uncertainty, and additional post-mining emissions compared to the “absolute gas emission method” (IPCC recommended Tier 3). Therefore, methane emissions dissipated from most of the producing coal mines worldwide could be more accurately and more easily estimated. © 2015 Elsevier B.V. All rights reserved.

1. Introduction The tremendous progress of human socio-economy since the Industrial Revolution has simultaneously created various positive and negative effects on the earth's system, with a significant amount of pertaining to global climate change (Steffen et al., 2015). The most recent assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) has demonstrated that the global average temperature has risen by 0.85 °C from 1880 to 2012, and warming is predicted to continue to increase 0.3–0.7 °C in the period of 2016 to 2035 (IPCC, 2014). While the root cause of global warming has not yet been agreed upon (Lindzen, 2007; Wang, 2010), there is no doubt that reducing emissions of greenhouse gases could mitigate global warming to a certain extent (Montzka et al., 2011; IPCC, 2014). Methane (CH4), the second most important anthropogenic greenhouse gas after carbon dioxide (CO2), plays an important role in atmospheric chemistry and radiation balance, of which the global warming potential (GWP) is 28 over a time horizon of 100 years (Ghosh et al., 2015). Recent estimations have suggested that atmospheric CH4 emissions have contributed to approximately 20% of global warming since the Industrial Revolution (Nisbet et al., 2014; Yvon-Durocher et al., 2014). Atmospheric CH4 concentration increased from 700 ppb during pre-industrial times (Etheridge et al., 1998) to 1813.9 ppb in 2013 according to measurements by the U.S. National Oceanic and Atmospheric Administration. This findings also shows that it is increasing at a higher rate compared to the growth rate of atmospheric CO2 concentration over the same period of time (Dlugokencky et al., 2011). The main sources of methane emissions in order of contribution are agriculture, energy activities, and waste disposal (Yusuf et al., 2012; Kirschke et al., 2013). Global methane emissions from energy activities in 2010 and 2015 are presented in Fig. 1, which shows that methane emissions in energy activities account for 38.27% and 37.7% of the total methane emissions, respectively. Furthermore, methane emissions from coal mining is roughly 600 MtCO2e, making it responsible for 8–10% of anthropogenic-related CH4 (Su et al., 2011), and these emissions are predicted to rise by 15% by 2020 (Li et al., 2015b).

China is one of the few countries among the major world economies that uses coal as its primary energy source; more specifically, it produced 3.68 billion tons of coal in 2013, which represents 45.5% of total coal production throughout the world for that year (IEA, 2014) and accounts for 71.64% and 67.5% of China's total primary energy production and consumption, respectively, in 2013 (BP, 2014; NBSPRC, 2014). In 2007, CH4 emissions corresponding to coal mining made up nearly 7% of the total GHG emissions in China (Chen and Zhang, 2010), which makes China the world's largest emitter of CMM (coal mine methane) (IEA, 2009). The Chinese government has taken various measures to speed up its national energy restructuring; however, since 90% of China's fossil energy reserves is coal reserves, the leading position of coal in the energy mix of China will continue to persist over the long term. Consequently, the coal-related greenhouse gas emissions that occupy a large portion of Chinese corporate GHG inventory have been attracting more attention recently. In accordance with the principle of “common but differentiated responsibilities”, the Kyoto Protocol has only appointed certain explicit quantified emission limitations and reduction commitments to developed countries, but there are no strict restrictions on developing countries, including China. However, as a large and responsible power, China has developed a series of policy processes and technical innovations to reduce GHG emissions and aims to further reduce CO2 intensity by 40–45% from the 2005 baseline by 2020 (NDRC, 2014). To this end, China first needs to obtain better data to produce national GHG emission inventories (Wang, 2014). Unfortunately, there appears to be a discrepancy among the CMM emissions calculated by the investigators who use different estimation methods, data sources, investigated areas, and calculation precision. With Chinese methane emissions from coal mining in 2005 as an example, since that year is both the base year of China's pledge to cut CO2 emissions and the latest official National GHG Inventory year of China (NDRC, 2012), the values vary considerably among different studies, with the highest one being about five times higher than that of the lowest value found (Table 1), causing an adverse impact on policy formulation and technology promotion regarding CMM exploitation and utilization. In this work, based on considering rationality and the limitations of conventional computing methods, special research efforts have been made to analyze the characteristics and main controlling factors of coal-bed methane adsorption-desorption and establish regressive statistics using different data in typical coal mine areas. On this basis, a new approach that is better suited to the present conditions of China is proposed. The results of the new method are compared with those

Table 1 Estimates of the CMM emissions in China (base year: 2005).

Fig. 1. Global methane emissions from energy activities, categorized by source, in 2010 and 2015 (inlet: methane emission by sectors) (EPA, 2012).

Methane emissions/108 m3

CO2-equivalent emissions/Mt

References

90.51 140 152.6 170.71 192.86 198.01 250.59 200–500

136.31 210.83 229.82 257.09 271.45 278.21 377.39 301.20–753.01

Yang (2009) Li and Hu (2008) Wang et al. (2013) EPA (2012) NDRC (2012) Yue et al. (2012) Zhang et al. (2014a) IPCC (2006)

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Fig. 2. Schematic of methane emissions from coal mining.

of conventional methods in this case study in order to facilitate the carbon abatement process while developing coal resources and actions among international climate change talks with more accurate carbon emission data. 2. Coal mine methane (CMM) emission and utilization in China 2.1. The pathway of CMM emissions in China Coal-bed methane is trapped in coal matrix surfaces under steady pressure due to the coal reservoir's naturally low permeability. When the existing stress equilibrium in the rock mass is disturbed by mining activities, an inner coal seam appears at the pressure gradient between the in-situ gas pressures and the mine atmosphere, resulting in “free gas” release into the underground workings (Lunarzewski, 1998). Then, through various ventilation and gas drainage systems or coal lumps, the methane is extracted as discharge into the atmosphere, except for the portion being utilized, as shown in Fig. 2. CMM release often occurs at three locations: the excavation roadway, the working faces, and the goafs; both the excavation roadway and working faces can be subdivided into two sources: wall and coal lumps, while the goafs have three: residual raw coal, adjacent coal seams, and surrounding strata. According to the law of conservation of mass, the methane emissions from underground coal mining should satisfy Formula 1: Q emission ¼ Q effusion þ Q control −Q utilization ¼ Q effusion þ Q discharge

ð1Þ

where Q emission refers to the total methane emissions into the atmosphere Q effusion refers to the quantity of ground coal lumps effused by desorption Q control refers to the collection quantity through a ventilation and drainage system Q utilization refers to the utilized portion of the collection quantity Q discharge refers to the unutilized portion of the collection quantity. 2.2. The extraction and utilization of CMM in China In spite of the security threat of coal mines with regard to coal exploitation, CMM is a clean energy, and industrial chemicals, which have been developed in China since the 1950s, have been incorporated into China's capital construction investment plan for energy conservation.

In general, CMM is emitted in three streams (Su et al., 2005): (1) CMM drained pro-mining (CH4 content 60–95%), (2) coalmine ventilation air (CH4 content 0.1–1%), and (3) CMM drained from goafs (CH4 content 30–95%). According to “The Coal Mine Safety Rules” (SAWS, 2011), CMM with a methane content less than 30% should not be utilized and is required to be released into the atmosphere. In China, CMM with a methane content less than 30% accounts for about 60–70% of total CMM emissions so the effective utilization of dilute CMM is the crux of CMM emission reduction (Su and Agnew, 2006; Karakurt et al., 2011). Table 2 lists the CMM recovery and utilization in China from 2001 to 2014, which explains that although the utilization amount increases every year, from 540 million to 8.5 billion cubic meters, the ratio is below 50%, far from the 83% of that in the U.S.; therefore, China has huge potential for CMM utilization and mitigation. 3. A new approach to estimate CMM emissions in China 3.1. Conventional methodology for estimating CMM emissions 3.1.1. Emission factor method (IPCC Tier 1 and Tier 2) For countries with underground mining and where mine-specific measurement data are unavailable, IPCC recommends using Formula 2 below based on the emission factor: CH4 emissions ¼ Raw coal production  CH4 Emission Factor  Units conversion factor

ð2Þ

Table 2 2001–2014 CMM recovery and utilization in China. Year

Recovery/×108°m3

Utilization/×108°m3

Ratio/%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 (prediction)

10 12 15 19.3 21.3 26.1 47 58 71.89 88 115 125 156 180

5.4 6.2 6.2 9.1 6.45 9.1 14.5 18 17.7 36 53 52 66 85

54.0 51.7 41.3 47.2 30.3 34.9 30.9 31.0 24.6 40.9 46.1 41.6 42.3 47.2

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Table 3 Emission factors and uncertainty for Tier 1and Tier 2 approaches. Tier 1

Emission factors (m3/t)

Mining

Post-mining

Uncertainty (IPCC, 2001)

Higha Averagea Lowa High Average Low Mining Post-mining

Tier 2

underground

surface

underground

25 18 10 4.0 2.5 0.9 Factor of 2 greater or smaller Factor of 3 greater or smaller

2.0 1.2 0.3 0.2 0.1 0 Factor of 3 higher or lower Factor of 3 higher or lower

Country- or basin-specific emission factors

surface

10%–30% of in-situ gas content

±50–75% ±50%

0 0.1 (preferred) 0.2 Factor of 2 higher or lower ±50%

a Underground: high, mining depths of N400 m; low, mining depths of b200 m; average, intermediate depths. Surface: high, overburden depths of N50 m; low, overburden depths of b25 m; average, intermediate depths.

where units are: CH4 emissions — Gg/year; Raw coal production — t/year; CH4 Emission Factor — m3/tonne; Units conversion factor — 0.67 × 10−6Gg·m−3.

The

density

of

methane,

Raw coal production activity data is provided by enterprises or statistical divisions. The emission factor, which consists of mining and post-mining, is the average global range of emission factors and country- or basin-specific emission factors, i.e. Tier 1 and Tier 2. Tier 1 is employed when no (or very limited) local data are available, excluding raw coal production, while Tier 2 is employed when no mine-bymine data are available, but country- or basin-specific data are. The specific values of emission factors and uncertainties are shown in Table 3. Although the calculation process of the emission factor method is simple, and a low volume of data is required, the one significant shortage is calculation error, which causes low accuracy in the emission inventories. 3.1.2. Absolute CMM emissions method (IPCC Tier 3) For countries with underground mining, and where mine-specific measurement data are available, IPCC recommends using the Tier 3 based on ventilation air measurements and degasification system measurements, i.e. the absolute CMM emissions method, which follows Formula 3 below (Mutmansky and Wang, 2000): XZ

C ðt Þ  Q ðt Þ dt

ð3Þ

where: refers to methane concentration at time t; refers to air quantity at time t; refers to varied time from the beginning of the year to the end; ∫ refers to the true methane emissions in any return airway; ∑ refers to the true methane emissions in all return airways of one coal mine. For variations in the rate of mining and drainage of gas and the components of gas, the uncertainty of Tier 3 comes from measurement

C(t) Q (t) t

Table 4 Estimates of uncertainty for underground coal mining for the Tier 3 approach (IPCC, 2001). Source

Details

Uncertainty

Drainage gas

Spot measurements of CH4 for drainage gas Degasification flows Continuous or daily measurements Spot measurements every two weeks Spot measurements every three months

±2% ±5% ±5% ±10% ±30%

Ventilation gas

frequency and measurement accuracy. The uncertainty estimates for underground mines are shown in Table 4. The absolute CMM emissions method may reflect actual emissions on a mine-by-mine basis and thus produces a more accurate estimate than using the emission factor method, but the data required by this method can be difficult to obtain due to its high data volume. Furthermore, Tier 3 cannot estimate CMM post-mining emissions. 3.1.3. Current situation of CMM emission inventory compilation in China Tier 2 of the emission factors method is universally employed to estimate CMM emissions by researchers in China, but different country- or region-specific emission factors are adopted (CCCCSG, 2000; Zheng et al., 2005; Wang et al., 2013). Lists with certain generally accepted emission factors issued by a competent authority are shown in Tables 5 and 6. It should be noted that the emission factors list above is summarized on the basis of the relative gas gushing quantity confirmed by identifying the gaseous mine classification (Zheng, 2002; Zheng et al., 2005), but the confirmed one is a maximum in a set of measurements over a period of time on account of ensuring safe working conditions in underground coal mines (SAWS, 2006). As a consequence, the authors hold that the CMM emissions calculated using the emission factors method overestimate the actual CMM emission levels in China. Nearly 95% of China's total coal production comes from underground mining (Cheng et al., 2011). Under these conditions, the absolute CMM emissions method is much more reliable because it avoids CMM emission spatial and temporal heterogeneity caused by variability in geologic formations and mining practices (Irving and Tailakov, 1999), but this method has the disadvantage of nationwide time series data and potential repeat measurements being very cost- and labor-intensive, as well as the highest stage of emission monitoring, i.e. continuous monitoring. In summary, neither the emission factor method nor the absolute CMM emissions method is appropriate for accurately estimating CMM emissions throughout the country. 3.2. Establishment of a new method for estimating CMM emissions 3.2.1. Influence factors of CMM emissions (1) In-situ virgin gas content.

In-situ virgin gas content is the primary factor impacting CMM emissions (Boyer and Bai, 1998). A coal seam is both the source and reservoir Table 5 Emission factors from the “China Climate Change Country Study” (base year: 1990). Stage

Mining Post-mining

Underground mining (m3/t) High gassy mine

Low gassy mine

21.83 3.02

4.53 1.13

Surface mining (m3/t)

2.5 0.1

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Table 6 Emission factors from NDRCC (base year: 1994 or 2000). Region

North Northeast Northwest Southwest CSa East a

1994 (m3/t)

2000 (m3/t)

Underground

Surface

Post-mining

Underground

Surface

Post-mining

4.18 11.75 6.00 19.02 7.19 5.46

1.59

High gassy mine = 3

6.97 14.40 5.97 21.68 7.83 6.22

1.65

High gassy mine = 3

Low gassy mine & Surface mine = 0.5

Low gassy mine & Surface mine = 0.5

Central South.

of CMM, so any CMM release, regardless of where or when it occurs, is closely related to this factor. Coal seams in China are naturally different bases on the coal-forming period, organic matter abundance, coalification degree, etc. Because the coal-bearing stratums experience a multi-stage structural evolution, there is obvious otherness in distribution on space of virgin gas content (Tang and Lin, 2000; Yao et al., 2009; Moore, 2012; Zhang et al., 2014b; Chen et al., 2015). In general, the coal sedimentary basins of China are located within four large geographic regions: Northeast, North, South, and Northwest, which are divided by the warp and weft of the orogenic belt that lies under the Chinese tectonic framework (Xu et al., 2008; Cao et al., 2013); these four regions are shown in Fig. 3. According to the theory of geologic tectonic level control, Zhang et al. divided CMM occurrence and distribution into 29 areas, including 16 high and outburst gas areas and 13 low gas areas within the four regions; the 29 areas are further divided into 88 sub-areas (Zhang, 2009; Zhang and Wu, 2013). Table 7 displays the virgin gas content of some main mine areas in China. A crisscross network of these areas and sub-areas with a widely varying in-situ virgin gas content makes it hard to obtain a country- or region-specific emission factor. (2) Residual gas content of coal lumps.

Residual gas content is defined as the remaining gas content of certain coal samples attaining adsorption–desorption equilibrium at one bar of pressure (Gao, 2014).

One quality of the coal reservoirs in China is the development of tectonically deformed coal, which has many property differences from primary structure coal, e.g. pore configuration and macromolecular structure (Ju et al., 2004; Cao et al., 2008). Tectonic deformation also has an obvious effect on CMM adsorption capacity at low temperatures, due to not only the varying deformation degrees and deformation properties of tectonic coal, but also the variations in nanoscale pore size and pore volume of such adsorption (Ju et al., 2009; Pan et al., 2012). As a general rule, the nanoscale pore volume, internal specific surface area, and methane adsorption capacity of tectonically deformed coal have a positive relationship with deformational degree at the same temperature and pressure (Qu et al., 2010). Residual gas content in some tectonic coal samples accounts for 20–90% of in-situ virgin gas content, of which contains residual gas, desorbed gas, and lost gas, as shown in the graphs in Fig. 4. Consequently, residual gas content as a deduction according to the conservation of mass is employed to act as an important parameter to achieve accurate CMM emission inventories. (3) CMM emissions from adjacent coal seam areas and surrounding rock.

The surrounding rock of an active coal seam and adjacent inactive coal seams within the zone disturbed by mining also release gas into the working space through the channels of the rock mass caused by unloading relaxation. Creedy's research suggests that this zone may expand to 160 m up and 40 m below the active coal seam (Kirchgessner et al., 2000). Unfortunately, the CMM emissions that come from adjacent coal seam areas and surrounding rock cannot be distinguished to

Fig. 3. Location map of coal sedimentary basins in China (EPA, 1996).

Y. Ju et al. / Science of the Total Environment 543 (2016) 514–523 Table 7 Estimated gas content of main mine areas in China. Geographic regions

Coal reserves (105 Mt)

North

18.78

Gas content AVG (m3 tonne−1) 8.425

South

3.349

19.89

Northeast

2.564

14.53

Northwest

30

4.5

Gas content of main mine areas (m3 tonne−1) Jining Yanzhou Yangquan Lu'an Jincheng Huainan Pingdingshan Hebi Songzao Liupanshui Yinggangling Tiefa Shenyang Hunchun Shuangyashan Hegang Chenghe Jingyuan Qinghai A'kesu

0.004–1.85 0.27–1.1 0.49–16.8 3.74–20.69 7.11–38.7 0.04–44.81 0.145–9.776 8–20 8.42–21.99 10.865–17.45 4.75–29.76 1.86–3.77 5–15.76 1.67–6.20 0.85–10 5–14 0.02–0.67 0.02–1.51 0.001–0.082 2.46–10.79

obtain accurate measurements and thus usually have to be calculated by experimental formulas. Saghafi found the actual emissions to be four times the in-situ gas content after investigating Australian CMM emissions (Saghafi et al., 1997), and Kissell found the coefficient to be close to 7 in the United States (Kissell et al., 1973), while Noack found a coefficient of 10 for that in Germany (Noack, 1998). Excess emissions should come from the surrounding rock and adjacent inactive coal seams. Different coefficients are found in various regions because of unique mining operations and geological conditions (Karacan et al., 2011).

519

Q coalem refers to the relative CMM emissions from active coal seams, m3/tonne Q strataem refers to the relative CMM emissions from the adjacent strata, m3/tonne γ refers to the strata emission coefficient. Incorporating the amount of utilization and the annual production of raw coal, the total relative CMM emissions can be described by the difference between in-situ virgin gas content and residual gas content, and Formula 4 can be transformed into Formula 5: Mne ¼ ½η  ðQ ori −Q res Þ  P  ρ−M u −0:98M f

ð5Þ

where Mne η Q ori Q res P ρ Mu Mf 0.98

refers to the net CMM emission, Gg/year refers to 1 + γ, the mining influence coefficient refers to the in-situ virgin gas content, m3/tonne refers to the residual gas content, m3/tonne refers to the raw coal annual production, tonne/year refers to the density of CH4, 0.67 × 10− 6Gg·m− 3 (20 °C, 1 atm) refers to the annual amount of CMM utilization refers to the annual amount of CMM simply combustion with no useful energy (flared) represents the combustion efficiency of natural gas that is flared (API, 2004).

3.2.3. Evaluation of the parameters in Formula 5 In Formula 5, the main parameters contain the in-situ virgin gas content, the residual gas content, the mining influence coefficient, raw coal annual production, and the annual CMM utilization amount; the evaluation of these parameters are as follows: (1) In-situ virgin gas content.

3.2.2. Development of a new calculating formula From Section 3.2.1 and Formula 1, the active coal seam CMM emissions and the strata (the surrounding rock and adjacent inactive coal seams) CMM emissions compose the total CMM emissions in underground mining, and the strata CMM emissions are in a certain proportion to the active coal seam CMM emissions. In order to perform easy measurements, relative emissions on the basis of CMM emissions per unit mass are applied in Formula 4: Q emission ¼ Q coalem þ Q strataem ¼ ð1 þ γÞQ coalem

ð4Þ

where Q emission refers to the total relative CMM emissions in underground mining, m3/tonne

This parameter depends on a number of factors, the most important of which are coalification degree and coal seam depth. The virgin gas content increases as coal rank rises. Furthermore, there is generally a positive correlation between gas content and seam depth, but considering that the Quaternary sedimentary layers almost did not affect preservation of coal-bed gas, “effective depth”, i.e. overlying strata thickness and subtracting Quaternary layers' thickness to predict the gas content of a certain seam depth should be adopted when no direct measurement is available. This parameter can be evaluated by alternative standard methods, GBT19559-2008 (exploration) or GBT23250-2009 (underground). The data obtained adopting GBT23250-2009 (underground) are limited to whether the mines have drained gas pro-mining so it varies

Fig. 4. Relationship between residual gas content and in-situ virgin gas content (a. Baode mine area; b. Dengfeng mine area).

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Fig. 5. Relationship between relative gas emissions and in-situ gas content.

widely, generally less than the actual one. Meanwhile, the data obtained adopting the GBT19559-2008 (exploration) is not liable to be affected by external conditions and thus can best reflect the virgin gas content and its components of target coal seams. The determination of final adopted value in computational formula reference “gas-geological map method”(Zhang and Zhang, 2005), to be specific, it is dividing the whole explored area of a single coalmine into multiple separate units in the map of mining gas-geology employing geological boundaries e.g. fault, thin-out, denudation etc., within the relevant unit averaging the several in-situ gas content along with panel shift. (2) Residual gas content.

This parameter mainly depends on deformation degree, coalification degree, and coal particle size. These factors work by affecting CMM transportation in the pore-fracture system in coal (Li et al., 2012; Nie et al., 2015).

This parameter can be evaluated by spot measurement, i.e. taking a fresh coal sample to the ground, standing 150 min and determining the gas content adopting GBT23250-2009. The final adopted value in computational formula is the average of the testing values of multiple cognate samples. (3) The mining influence coefficient.

This parameter mainly depends on wall-rock lithology and mining operations. Fig. 5 shows the result that we linearly fit into the relative gas emissions and in-situ gas content derived from seven representative coal mines with various wall-rock lithology and mining operations. The mining influence coefficient shows a variation from 1.3 to 2.0 with the high determination coefficient close to 1. Compared with that of the United States and Europe, the lower ratios in relative gas emissions and in-situ gas content in China are probably because the result of the lower stratum permeability inducing gas that possesses poor fluidity.

Table 8 CMM emissions in typical coal mines in Huainan–Huaibei Coalfield (in 2010). Coalmines

In-situ gas content/m3 t−1

Residual gas content/m3 t−1

Mining influence coefficient

Production/Mt

CMM emissions/Mm3

Panyi Paner Xinzhuangzi Panbei Zhangbei Haizi Linhuan Qinan Luling Yangzhuang Shitai Total

8.4 8 14 7.4 6.9 8.7 5.6 8.59 12.2 5.06 9.6

0.55 0.56 0.44 0.04 0.29 0.17 0.76 0.62 0.77 0.16 0.29

1.5 1.5 1.5 1.3 1.4 1.5 1.5 1.5 1.5 1.5 1.5

4.63 3.6 3.37 1.7 13.7 1.38 2.4 2.88 2.24 2 1.22 39.12

54.48 40.21 68.48 16.27 126.76 17.68 17.39 34.38 38.42 14.71 17.04 445.82

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Table 9 Comparison between the different methods in Huainan–Huaibei Coalfield. Methods

Tier 1

Tier 2 (Table 5)

Tier 2 (Table 6)

Tier 3

New method

Factor Term Value Result/Mm3 Error

Global average emission factors Depth N 400 29 3812.05 +178.8%

Country-specific emission factors High gassy mine 24.85 3266.53 +138.90%

Region-specific emission factors East 8.46 1112.07 −18.67%

Relative gas emissions Measurement

Measurement

1367.3 0

1498.36 +9.59%

Consulting the Chinese safety industry standard for the “predicting method of mine gas emission rate” (AQ 1018-2006), for single coal seam mining, the mining influence coefficient may vary from 1.3 to 1.6, wherein 1.3 shall be chosen when the direct roof and floor of the active coal seam is shale, while 1.6 corresponds to carbonaceous or sandstone; for multiple coal seam mining or slicing mining, the recommended mining influence coefficient is between 1.6 and 2.0. (4) Raw coal annual production.

Annual CMM utilization amount and annual CMM flare amount. This parameter can be evaluated by field investigation and consulting the “China coal industry yearbook”. (5) Annual CMM utilization amount and annual CMM flare amount.

This parameter can be evaluated by accepting the statistical data of mine operators by installing gas meter in the gathering pipeline and end users. 4. Results and discussion 4.1. Case study in Huainan–Huaibei Coalfield and Jincheng Coalfield The Huainan–Huaibei Coalfield, located in northern Anhui Province in China, contains abundant coal resources and is a potential area for coalbed methane (Li et al., 2015a; Wang et al., 2015). Table 8 displays the main parameters and calculation results of CMM emissions in Huainan–Huaibei Coalfield in 2010. In 2010, the raw coal production of all of Huainan–Huaibei Coalfield is 131.45 Mt; for similar geological conditions and mining operations, the total CMM emissions in Huainan–Huaibei Coalfield derived from that of typical coalmines is 1498.36 Mm3. Compared with other methods, the new method established in the present work has the smallest error +9.59%, and the result of the new method has added CMM post-mining, which is excluded in Tier 3, so the real error would be smaller, as shown in Table 9. The Jincheng coalfield, located in southeastern Shanxi Province, is largest anthracite coal production base in China, enjoying the most prospective future for CMM recovery and utilization. Table 10 displays the main parameters and calculation results of CMM emissions in Jincheng Coalfield in 2010. In 2010, the raw coal production of all of Jincheng Coalfield is 46.95 Mt; for similar geological conditions and mining operations, the total CMM emissions in Jincheng Coalfield derived from that of typical coalmines is 867.49 Mm3.

Compared with other methods, the new method established in the present work has the smallest error +7.01%, and the result of the new method has added CMM post-mining, which is excluded in Tier 3, so the real error would be smaller, as shown in Table 11. 4.2. Discussion (1) Using the CMM emissions calculated by the Tier 3 method as the target for benchmarking, the result obtained from the new method has the smallest error in comparison with the results obtained from the Tier 1 and Tier 2 methods. (2) The new method proposed in this paper assumes that the CMM emission is the difference between in-situ gas content (including active coal seams and surrounding rock and adjacent inactive coal seams) and the residual gas content on the basis of the conservation of mass in order to adjust the deletion of CMM emissions post-mining omitted by the Tier 3 method. (3) To reduce the work involved in measurements, it is feasible to approximately express unknown local-data using known localdata, as long as inter-individual geological conditions, mining operations, and coal properties are similar, for the selection of parameters involved in the new method, which seriously considers various factors, such as depth, coal rank, coal deformation, formation lithology, and mining operations. In particular, if sufficient in-situ gas content data are available, an in-situ gas content contour map can be created based on the coal floor contours, the result of which can partly predict CMM emissions along with working field shift when recent data are lacking.

5. Conclusions Fugitive methane fugitive emissions in underground coal mining are an important component of GHG emission inventory with an increasing consideration within scientific and technical literature. Several tools and methods are being developed for estimating them This paper proposes a new method to estimate CMM emissions based on analyzing the features of gas-geology distribution, coal properties, mining operations, and CMM emission processes in China. The active data are composed of easy-to-access parameters i.e. in-situ gas content, residual gas content, raw coal production and alternative mining influence coefficient variation within the range of 1.3 to 2.0 through regression analysis of typical coalmines' data. Not only overcoming the shortage of overestimation by the emission factors methods(Tier 1 and Tier 2), but also surmount the deficiencies of heavy workload, weak timeliness, and CMM

Table 10 CMM emissions in typical coal mines Jincheng Coalfield (in 2010). Coalmines

In-situ gas content/m3 t−1

Residual gas content/m3 t−1

Mining influence coefficient

Production/Mt

CMM emissions/Mm3

Chengzhuang Sihe Zhaozhuang Total

13.47 19.18 13.94

3.05 5.19 3.23

1.5 1.5 1.5

8.62 15.7 6.15 30.47

134.73 329.46 98.80 562.99

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Table 11 Comparison between the different methods in Jincheng Coalfield. Methods

Tier 1

Tier 2 (Table 5)

Tier 2 (Table 6)

Tier 3

New method

Factor Term Value Result/Mm3 Error

Global average emission factors Depth N 400 29 1651.55 +64.36%

Country-specific emission factors High gassy mine 24.85 1415.21 +47.07%

Region-specific emission factors North 9.97 567.79 −14.91%

Relative gas emissions Measurement

Measurement

771.62 0.00%

867.49 +7.01%

emissions post-mining absence by the relative CMM emissions method (Tier 3). It is verified in these case studies that the new method has the smallest error of + 9.59% and − 7.01% in Huaibei–Huainan Coalfield and Jincheng Coalfield respectively compaing with other methods. Compiling the CMM emission inventory using the new method can better reflect the reality of CMM emissions in China.

Acknowledgments This work was supported by the “Climate Change: Carbon Budget and Related Issues” Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05030100), the National Major Research Program for Science and Technology of China (2011ZX05060-005), and the National Natural Science Foundation of China (41372213, 41530315, 41030422). We appreciate the valuable comments and advice from the reviewers and the editor.

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