Scholarly article on topic 'Optimization of CO2 separation technologies for Chinese refineries based on a fuzzy comprehensive evaluation model'

Optimization of CO2 separation technologies for Chinese refineries based on a fuzzy comprehensive evaluation model Academic research paper on "Chemical engineering"

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Academic research paper on topic "Optimization of CO2 separation technologies for Chinese refineries based on a fuzzy comprehensive evaluation model"

Pet. Sci. (2015) 12:197-206 DOI 10.1007/s12182-014-0001-x


Optimization of CO2 separation technologies for Chinese refineries based on a fuzzy comprehensive evaluation model

Qian-Qian Song • Qing-Zhe Jiang • Zhao-Zheng Song

Received: 29 June 2014/Published online: 22 January 2015

© The Author(s) 2015. This article is published with open access at

Abstract This study aims at determining the optimal CO2 separation technology for Chinese refineries, based on current available technologies, by the method of comprehensive evaluation. Firstly, according to the characteristics of flue gas from Chinese refineries, three feasible CO2 separation technologies are selected. These are pressure swing adsorption (PSA), chemical absorption (CA), and membrane absorption (MA). Secondly, an economic assessment of these three techniques is carried out in accordance with cash flow analysis. The results show that these three techniques all have economic feasibility and the PSA technique is the best. Finally, to further optimize the three techniques, a two-level fuzzy comprehensive evaluation model is established, including economic, technological, and environmental factors. Considering all the factors, PSA is optimal for Chinese refineries, followed by CA and MA. Therefore, to reduce Chinese refineries carbon emission, it is suggested that CO2 should be captured from off-gases using PSA.

Keywords Chinese refineries • CO2 emission • Separation technique • Economic evaluation • AHP-entropy method • Fuzzy comprehensive evaluation model

Q.-Q. Song • Q.-Z. Jiang (&) • Z.-Z. Song (&)

State Key Laboratory of Heavy Oil Processing, China University

of Petroleum, Beijing 102249, China


Z.-Z. Song

e-mail: Edited by Xiu-Qin Zhu

1 Introduction

It is well accepted that carbon dioxide (CO2), which is considered as the leading source of greenhouse gas (GHG) emissions, results in the climate change. Direct emissions of CO2 from industry account for approximately 20 % of global CO2 emissions (IEA 2010). Globally, the petroleum refining industry is one of the largest contributors to anthropogenic CO2 emissions (IEA 2009; de Mello et al. 2009; Kuramochi et al. 2012). CO2 emissions from refineries account for about 4 % of the global CO2 emissions, close to 1 billion metric tons of CO2 per year (Van Straelen et al. 2010).

China has surpassed U.S. as the world's largest emitter of CO2. In 2012, China contributed 26.1 % of total world CO2 emissions, equal to 8,254 million metric tons (Mt) (EIA 2013). On the other hand, the overall goal of the Chinese government is to reduce the CO2 emissions per unit of GDP by 40-45 % by 2020 from 2005 levels. Nevertheless, with the ever-increasing enlargement of refining scale, the rising demand for high-quality products and the restricted supply of light and sweet crudes, CO2 emissions of Chinese refineries have increased significantly. In 2012, Chinese crude oil refining reached 468 Mt. Consequently, it was estimated that CO2 emissions would be around 133 Mt according to the CO2 emission factor of 0.284 t/t crude oil (Ma et al. 2011). In this paper, a proper mitigation strategy for the Chinese oil refining sector is badly needed to enable China to appropriately implement its climate change policy with consideration of its socioeconomic features.

At present, CO2 emissions of oil refineries can be reduced in three ways. The first option requires energy conservation. The second option requires energy consumption switching to non-fossil fuels such as hydrogen,

nuclear, biomass, and solar energy. The third option involves CO2 capture and storage (CCS). However, the nature of oil refining implies that even if a refinery is highly energy efficient, it will consume considerable amounts of energy, and therefore produce considerable amounts of CO2. The first two measures could reduce the current CO2 emissions by 9-20 Mt/year, yet a 13-80 % reduction of CO2 emissions could be achieved by implementing carbon capture (Johansson et al. 2012). Thus, to meet mid- to long-term CO2 reduction, cost-effective CO2 separation technologies are the key issue for oil refineries.

Most of the reported studies have focused on technical and economic performance of CO2 capture technology for power generation, and only a very few studies are about CO2 capture for the petroleum refining industry (IEA-GHG 2000; Van Straelen et al. 2010; de Mello et al. 2009; Ku-ramochi et al. 2012; Ho et al. 2011). Specifically, no studies have been reported on Chinese refineries.

The objective of this study is to optimize CO2 separation technologies for Chinese refineries. Section 2 of this paper reviews CO2 separation technologies and initially selects available technologies for Chinese refineries. Section 3 introduces the method of economic evaluation and fuzzy comprehensive evaluation. Section 4 presents the results. Section 5 gives the conclusions. The general frame of this study is shown in Fig. 1.

2 Preliminary selections of CO2 separation technologies

Currently, the technologies for separating CO2 from a flue gas include absorption, adsorption, use of membranes, cryogenics, and chemical-looping combustion (CLC) (Figueroa et al. 2008; Yang et al. 2008; Olajire 2010; Mondal et al. 2012). Choosing a suitable technology

depends on the characteristics of the flue gas stream and its separation requirements.

CO2 may be emitted from a variety of sources at a refinery, even over 20 sources of emissions for a complex refinery. The main CO2 emission sources include furnaces, boilers, catalyst regeneration, and hydrogen manufacturing. Figure 2 shows the CO2 emissions of a typical Chinese refinery with 12 Mt/year of crude processing capacity (Jiang et al. 2013). The CO2 concentration of flue gases changes in a wide range. For example, it is 10-20 vol% for catalyst regeneration in fluid catalytic cracking (FCC) (de Mello et al. 2009), and 50-55 vol% for hydrogen manufacturing units (Reddy and Vyas 2009). Table 1 shows the composition of some CO2 emission sources for the typical Chinese refineries. Table 2 provides a summary of the pros and cons of CO2 separation techniques. Based on the characteristics of the flue gases, three available CO2 separation technologies are initially selected for Chinese refineries, as follows:

2.1 Pressure swing adsorption (PSA)

The PSA for CO2 separation is based on the preferential or selective adsorption of CO2 on a solid adsorbent at a relatively high pressure by contacting hot gas with solid adsorbent in a packed column. The adsorbed component (CO2) is then des-orbed from the solid by lowering the gas-phase partial pressures inside the column so that the adsorbent can be re-used. From the point of view of technology, PSA can capture CO2 of almost all concentrations from flue gases. But some studies have proved that at the present commercial development state, PSA is not a suitable technology for bulk capture of CO2 from postcombustion power plant flue gas (Reiner et al. 1994; Liu et al. 2012). However, due to relatively low energy consumption and easy operation, PSA is a promising technology

CO2 separation technologies for Chinese refineries

Off-gases of hydrogen manufacturing unit

Low concentration flue gases

Fig. 1 The general frame diagram of this study 1 Springer

Power (14% imported), 8%

H2 production,

Flares, 3%

Incineration and

effluent processes, 1%

Fig. 2 CO2 emissions of a Chinese refinery (Jiang et al. 2013)

Table 1 Compositions of some CO2 emission sources for the typical Chinese refineries

Compositions, vol%

FCC Hydrogen


CO2 16.6 50

N2 82 -

O2 0.8 -

H2 - 30

CO 0.6 -

SOx, ppmv 20 -

Other combustible gas (e.g., methane, light - 20 alkanes & alkenes)

for capturing CO2 of high concentration (20-80 vol%) (Ho et al. 2008; Martunus et al. 2012). In oil refineries, most hydrogen manufacturing units use a PSA to recover H2 from the syngas. PSA can only recover 75-90 % of the overall H2 in the syngas. PSA off-gas containing CO2, unrecovered H2, and combustible gas is usually burned as fuel gas (shown in Table 1). The direct combustion of off-gases would lead to not only energy waste, but also the emission of large quantities of CO2. Therefore, to maximize overall production and profitability, oil refineries should recover the CO2 and remaining valuable H2 in PSA off gas. Reddy and Vyas (2009) have investigated the recovery of CO2 and H2 from PSA off gas using the CO2LDSep plant. Beijing Yanshan Petrochemical Company (China) has constructed a PSA unit recovering hydrogen manufacturing off-gases, with which 0.2 Mt food-grade CO2,64.8 Mm3 combustible gases and 36 Mm3 H2 can be produced annually. In the study, some relevant data of the PSA is determined based on this industrial application.

2.2 Chemical absorption (CA)

The chemical absorption process, using amine solutions, is a commercialized technology and has been used in natural gas

industry for 60 years. It is regarded as a mature process. The most commonly used solvent is monoethanolamine (MEA). Many studies have been reported about CO2 capture from an existing coal-fired power plant using chemical absorption method based on MEA (Singh et al. 2003; Alie et al. 2005; Aroonwilas and Veawab 2007; Rubin et al. 2007; Abu-Zahra et al. 2007). They all have indicated that CO2 capture using MEA is the only feasible option in the short term for flue gases with low concentration CO2. Therefore, in this study, random packed columns and ordinary carbon steel are used to act as the absorber and stripper with anticorrosive flu-ororubbers and stainless steel internals. Furthermore, 20 wt% MEA is selected to absorb CO2, and the CO2 loadings of lean and rich solution are, respectively, set to 0.20 mol-CO2/mol-MEA and 0.45 mol-CO2/mol-MEA (Alie et al. 2005). An absorption temperature of 40 °C is used and the average pressure is around 0.01 MPa. The regeneration temperature is 110 °C and pressure is 0.025 MPa. Therefore, based on these operating conditions, the size of absorber and stripper needed can be determined using the model provided by Abu-Zahra et al. (2007).

2.3 Membrane absorption (MA)

MA, that is using a membrane in conjunction with chemical absorption, is considered as a suitable alternative to chemical absorption by many researchers, due to its unique advantages including large interfacial area, good device-modularity, good operational flexibility, and high mass transfer coefficient (Rangwala 1996; Falk-Pedersen and Dannstrom 1997; Feron and Jansen 2002; deMontigny et al. 2005; Yeon et al. 2005; Yan et al. 2007, 2008, 2011). In addition, membrane CO2 absorption technology can also solve the operating problems, successfully including entrainment, flooding, and foaming. It means that solvent losses can be reduced substantially, thereby reducing the absorbent makeup cost. However, the barriers in coal-fired power plants are membrane wetting and plugging which degrade CO2 separation performance. In order to maintain constant CO2 removal efficiency, membrane modules need to be replaced again and again, and hence the cost of captured CO2 will be increased (Mavroudi et al. 2003; Wang et al. 2005; Yan et al. 2008, 2011). Because there are no particles in the flue gas of refineries, membrane plugging will not occur. So, in the assessment of MA in this study, only the membrane wetting problem is considered. With higher specific surface area than packings, hydrophobic hollow fiber membrane contactor is used as the permeable barrier between gas and liquid phase, and the CO2 can be captured by solvents (e.g., MEA) (Li and Chen 2005). Therefore, hydrophobic polypropylene membranes are selected owing to their relatively low price and commercial availability, with an assumption that the working life of the membranes is 5 years. In addition, the only difference between MA technique and CA technique is the

Table 2 Pros and cons of CO2 separation technologies

Separation technologies

Applicable situations

Chemical absorption (CA) Lower or medium CO2 pressure

Membrane absorption (MA) Lower CO2 pressure

Pressure swing adsorption Higher CO2 pressure (PSA)

Physical absorption


Membrane technology

Higher CO2 and total pressure

High CO2 pressure (concentration,

*60 vol%) Higher CO2 pressure

Chemical-looping combustion (CLC)

Under research

High selectivity Wide application Reproducible solvent Quick reaction velocity Large contact area

No problems of bubbling, flooding and

entrainment Better permeability and selectivity Low energy consumption Good modularity Easy process Low energy consumption No pollution and corrosion High adaptability and product purity

Low energy consumption and

corrosiveness Easy regeneration and lower dosage of adsorbent

Higher separation efficiency and purity Simple device No pollution

Low energy consumption High separation efficiency No NOx

Low energy consumption Low operation cost

Large loss of absorbent

High energy consumption of regeneration

Strong corrosiveness

Porous membrane easily wetted

or blocked Under research

Low recovery Big investment Large floor area

Low selectivity and separation

efficiency Higher pressure

High cost and energy

consumption High selectivity but not high

permeability Not high CO2 purity Not resistant to high temperature Not easily cleaned No large commercial application

type of absorber. Others are designed as same as CA technique. Because of the constant liquid-gas contact area, the total membrane contact area can be easily scaled-up linearly based on some successful projects or even the experimental results. According to literature (Yeon et al. 2005; Yan et al. 2007, 2008, 2011), the total membrane contact area could be calculated.

3 Methods

3.1 Method for economic evaluation

Many studies on economic evaluation of CO2 capture from industrial sources have been reported (Abu-Zahra et al. 2007; de Mello et al. 2009; Yan et al. 2011; Meerman et al. 2012). For Chinese refineries, the economic assessments are subject to two generally accepted guidelines: the Economic Assessment Method and Parameters for Capital Construction Projects (NDRC and MOC 2006), the

Economic Assessment Method and Parameters for Oil Construction Projects (MOHURD 2010). Although the economic indicators are not the same due to geographic differences, the methodology is similar.

In the study, the economic assessment using cash flow analysis are made up of the following six key economic categories: capital cost, operating and maintenance (O & M) cost, internal rate of return (IRR), net present value (NPV), dynamic payback period (DPP), and after-tax net profit (ANP). The cost model developed in the present study is based on the China-specific guidelines, and the methods for calculating the costs of each category and the data are drawn from the two guidelines (Table 3).

3.2 Method for fuzzy comprehensive evaluation

The evaluation of the optimal CO2 separation technology for Chinese refineries is influenced by a number of factors, such as economic benefits, environmental policy, technological level, and social impact. However, because of the

Table 3 Cost estimation of CO2 separation technologies

C1-C9 are the parameters extracted from the China-specific Guidelines stated above. C\ is the equipment procurement cost (104 Yuan); C2 is the installation cost (104 Yuan); C3 is the construction cost (104 Yuan); C4 is the miscellaneous fixed asset cost in the proportion of engineering cost, 0.12; C5 is the budgetary reserves ratio, 0.1; C6 is the construction period (years); C7 is the owner's capital-capital cost ratio; C8 is the loan interest rate; and C9 is the income tax rate

1 Capital cost Formulas

1.1 Engineering C1 ? C2 ? C3

1.2 Miscellaneous 1.1 x C4

1.3 Budgetary reserves (1.1 ? 1.2) x C5

1.4 Annual interest (1.1 ? 1.2 ? 1.3)/C6 x (1 - C7)/C6 x C8

1.5 Liquidity

Capital cost 1.1 ? 1.2 ? 1.3 ? 1.4 x C6 ? 1.5

2 Operating and maintenance (O & M) cost Formulas

2.1 Materials

2.2 Fuels & power

2.3 Wage & Welfare

2.4 Depreciation Straight-line depreciation

2.5 Maintenance

2.6 Miscellaneous

2.7 Administration

2.8 Financial Straight-line amortization

2.9 Sales

Annual O & M cost P2.i (where 2.i is 2.1-2.9)

3 Annual cash flow Formulas

3.1 Income

3.2 Cash inflow 3.1

3.3 Construction investment (1.1 + 1.2 + 1.3)/C6

3.4 Operating cost 2.1 + 2.2 + 2.3 + 2.5 + 2.6 + 2.9

3.5 Tax and extra charges

3.6 Income tax When (3.1 - 3.7 - 3.6) > 0, (3.1 - 3.7 - 3.6) x C9

3.7 Cash outflow 3.3 + 3.4 + 3.5 + 3.6

3.8 Net cash flow 3.2 - 3.7

complexity and uncertainty involved in evaluation, a decision maker must consider these factors in a comprehensive evaluation to avoid one-sidedness. Fuzzy comprehensive evaluation is the process of evaluating an objective utilizing fuzzy set theory. When evaluating an objective, multiple related factors must be considered comprehensively in order to give an appropriate, non-contradicting, and logically consistent judgment (Jorge et al. 2000; Chen et al. 2002; Liang et al. 2006).

In this study, a two-level fuzzy comprehensive evaluation is used as follows.

• Assuming that the objective being evaluated contains n factors, i.e., the factor set is U = {U1, U2, U3,..., Un}

• First-level fuzzy evaluation is carried out for each factor Uk(k = 1,2,..., n) Ak = (akl, ak2,..., akp) is the

fuzzy weight vector of each sub-factor in Uk, where ak[

is the relative importance of factor l, and akl = 1.

The fuzzy appraisal matrix of all p sub-factors:

rk11 Tk12 . rk1m

Rk = rk21 rk22 . rk2m

Jkp1 rkp2 . rkpm

where rkij is referred to the fuzzy membership degree of appraisal of factor i. In the study, based on the type of factor i, rkij is defined as (Xie et al. 2012): For benefit factors:


xtJ minxij

For cost factors:

maxx;; — x;j

where xij is the eigenvalue of factor i, max xij and min Xj is, respectively, the maximum, the minimum. The first-level appraisal result, Bk, can be obtained:

Bk = (bk1, bk2,..., bkm) = Ak x Rk (4)

xtj — minxij

maxxtj — minxtj

Second-level fuzzy evaluation is implemented for U According to the aforementioned results, the comprehensive appraisal result, B, is calculated as:

Table 4 Assumptions for economic evaluation with PSA, MA and CA techniques

B =(b1, ¿2,..., bm)= A x R

b11 ¿12

1, Ü2, .. ., On)

¿21 ¿22 bn1 bn2

The priority of evaluated objects can be obtained, and the optimal separation technology for Chinese refineries can finally be determined based on different scenarios.

4 Results

4.1 Economic evaluation

Three CO2 separation technologies without considering CO2 compression and transportation can recover 0.1 Mt/ year liquid CO2. Faced with the restricted downstream demand, CO2 is usually consumed nearby. Hence, it is assumed for the boundary of the economic evaluation model that around oil refineries there are enough market demands and CO2 can be completely sold as a commodity. Additionally, Chinese government has established 7 CO2 pilot emission trading markets in Beijing, Shanghai, Tianjin, Shenzhen etc., and will establish a China national CO2 emission trading market in the 13th Five-Year Plan. Therefore, some mandatory measures, such as CO2 emissions taxation, must be taken in the near future in China for refineries as large emission sources. Considering the carbon emissions taxation, CO2 capture can obtain additional economic benefit. Due to many uncertainties in the pilot carbon market, the CO2 price may fluctuate greatly, for example, the lowest CO2 price is 28 Yuan/t and the highest CO2 price can reach 140 Yuan/t in Shenzhen carbon market. So, in the economic evaluation in this work, a CO2 price of 140 Yuan/t is used. However, it is worth noting that with the PSA technique, 18 Mm3/year of H2 can be recovered simultaneously, and can be sold at a price of 2.0 Yuan/m3. The common basis for the three techniques is shown in Table 4.

The cost of major equipment for the PSA technique is estimated in terms of investment per unit capacity. Based on the PSA unit of Beijing Yanshan Petrochemical Company (China), the major equipment investment for the PSA technique is estimated to be 243.6 Yuan/t, accounting for

Items Value

CO2 capture efficiency, % 90

CO2 purity, % >99

Project working life, years 15

Construction period, years 1

Plant operating time, h/year 8000

Discount rate, % 12

CO2 sale price, Yuan/t 260

CO2 transaction price, Yuan/t 140

Owner's capital/capital cost 0.3

Loan interest rate, % 6.55

Income tax rate, % 25

Table 5 Economic evaluation results for the three techniques


Capital cost, 104 Yuan 3453.3 3613.9 3671.3

O & M cost, 104 Yuan/year 3407.1 3397.0 3348.3

IRR, % 17.55 17.75 86.05

approximately 72 % of total construction investment. For the CA and MA techniques, the cost of the absorber and stripper is firstly calculated from the above designs of CA and MA. Then, other costs are estimated in terms of certain proportions. The economic evaluation results for the three CO2 separation techniques are shown in Table 5.

Table 5 shows that the capital cost of the PSA technique is the highest, but its other economic indicators are optimal. The reason is that it can simultaneously recover CO2 and by-product H2. The capital cost of the MA technique is higher than that of CA. That is because the membrane price is high (about 13 Yuan/m2), and the membrane needs to be replaced about every 5 years. However, the O & M cost of CA is higher than that of MA, because of lower CO2 loading capacity, higher solvent losses, and regeneration heat consumption, meaning that using membrane gas absorption process can save the O & M cost in capture of CO2.

4.2 Fuzzy comprehensive evaluation

4.2.1 Establishment of the factor set

A factor set consists of various factors affecting the evaluation objective. The evaluation objective of this study is to optimize CO2 separation technologies. Combining experts' knowledge and experience with the actual production condition of Chinese refineries, the factor set

Table 6 Factors for CO2 separation technologies

Table 7 Results of the weight vector by AHP

Items Types Attributes C Ci C2 C3 W

0.4000 0.2000 0.4000

Economy (C1)

IRR (A) Benefit Quantitative Ii 0.4149 0 0 0.1660

NPV (/2) Benefit Quantitative I2 0.2592 0 0 0.1037

DPP (/3) Cost Quantitative I3 0.0501 0 0 0.0200

Capital cost (/4) Cost Quantitative I4 0.0848 0 0 0.0339

O&M cost (/5) Cost Quantitative I5 0.1609 0 0 0.0644

ANP (/6) Benefit Quantitative I6 0.0300 0 0 0.0120

Technology (C2) I7 0 0.0732 0 0.0146

Technological complexity (/7) Cost Qualitative Is 0 0.4269 0 0.0854

Technological maturity (/8) Benefit Qualitative I9 0 0.1824 0 0.0365

CO2 purity (/9) Benefit Quantitative I10 0 0.0413 0 0.0083

Floor space (/10) Cost Qualitative Iii 0 0.2762 0 0.0552

Energy consumption (/11) Cost Qualitative I12 0 0 0.5000 0.2000

Environment (C3) 113 0 0 0.5000 0.2000

CO2 capture efficiency (/12) Benefit Quantitative

Secondary pollution (/13) Cost Qualitative

C is the optimization of CO2 separation technologies for Chinese refineries; Wi is the weight of the factor set

involving economic, technological, and environmental factors has been established (Table 6).

4.2.2 Determination of the weight vector

There are dozens of methods to determine a weight, including Delphi (Ma et al. 2003), AHP (Saaty and Shang 2011; Jiang et al. 2012) and entropy (Lai et al. 2012; Khan and Bhuiyan 2014) methods. Each method has its background, significance, merits, shortcomings, and specific areas of application. Combination of different methods can offset the shortcomings of each, integrate their various advantages, and result in an advanced evaluation method (Refat et al. 2011). In this study, the weight of factors is determined by a combination of subjective (AHP) and objective (entropy) methods, that is, the AHP-entropy method takes into account the data and the subjective preferences of decision-makers to achieve a synthesis of subjective and objective and to make the results more realistic and reliable. Determination of the weight vector by AHP method AHP, originally developed by Saaty (1977, 1990, 1994), is a mathematical method for analyzing complex decision problems with multiple criteria and through combination of quantitative analysis with qualitative ones. In this paper, the model is based on the combination of qualitative opinions from experts and references and quantitative analysis from aforementioned economic evaluation, and the results are listed in Table 7.

Table 8 Results of the weight vector by entropy method

Items Ei di Wi


I1 IRR 0.0181 0.9819 0.1212

I2 NPV 0.0337 0.9663 0.1192

I5 ANP 0.0022 0.9978 0.1231

I8 Technological maturity 0.5119 0.4881 0.0602

I9 CO2 purity 0.6219 0.3781 0.0467

I12 CO2 capture efficiency 0.6072 0.3928 0.0485

I3 DPP 0.0960 0.9040 0.1116

I4 Capital cost 0.4659 0.5341 0.0659

I6 O & M cost 0.3793 0.6207 0.0766

I7 Technological complexity 0.5119 0.4881 0.0602

I10 Floor space 0.4555 0.5445 0.0672

In Energy consumption 0.5794 0.4206 0.0519

I13 Secondary pollution 0.6126 0.3874 0.0478

Ei is the entropy; di is the diversity; Wt is the entropy weight Determination of the weight vector by entropy method Entropy, first proposed by Shannon, is a concept originating from information theory (Chen et al. 2012). It can calculate the amount of information in the message, which consists of a countable length of character combination. By computing the total probabilities of all the characters in the message, the information entropy of the message is obtained. Generally, the smaller the entropy of a certain factor is acquired, the more weight the factor is given, and vice versa. Table 8 presents the results of the weight vector by the entropy method.

Table 9 Results of the weight vector by AHP-entropy method

Items AHP Entropy AHP-entropy

Economy (C1)

h 0.4149 0.1962 0.4392

h 0.2592 0.1931 0.2700

h 0.0501 0.1806 0.0488

h 0.0848 0.1067 0.0488

h 0.1609 0.1994 0.1731

h 0.0300 0.1240 0.0201

Technology (C2)

/7 0.0732 0.2105 0.0791

h 0.4269 0.2105 0.4614

¡9 0.1824 0.1630 0.1526

/10 0.0413 0.2348 0.0498

111 0.2762 0.1813 0.2571

Environment (C3)

/12 0.5000 0.5035 0.5035

/13 0.5000 0.4965 0.4965 Determination of the weight vector by AHP-entropy method The combined weights are determined by Eq. (6), and the results are shown in Table 9.

(X x <)

• For the economic factors, B\ = [0.0489 0.0203 0.9512]. The order of the economic benefit of the three techniques is PSA>CA>MA.

• For the technological factors, B2 = [0.8217 0.3069 0.3076]. The order of the technological level is CA>PSA>MA.

• For the environmental factors, B3 = [0.5035 0.6480 0.4965 ]. The order of the environmental benefit is MA>CA>PSA.

(2) Results of two-level fuzzy comprehensive evaluation The B1, B2, and B3 constitute the fuzzy appraisal matrix of second-level factor, that is,

" 0.0489 0.0203 0.9512" Rc = 0.8217 0.3069 0.3076 0.5035 0.6480 0.4965 The economic, technological, and environmental factors all belong to benefit attribute, and based on the AHP-entropy method, the weigh vector is A = [0.3247 0.3664 0.3089]. The overall fuzzy comprehensive evaluation is

B = A x RC =[0.3942 0.3220 0.6349]. The order of the three separation technologies is PSA>CA>MA.

4.2.3 Determination of the fuzzy appraisal matrix

5 Conclusions and implications

Based on Eqs. (1), (2), and (3), the fuzzy appraisal matrix for the economic, technological, and environmental factors

1.0000" 1 . 0000 7 1 . 0000 77 0.0000 ' 1.0000 1 . 0000 0.3333" 0.33337 0.7538 , 0.25007 0.0000 0.0000' 1 . 0000

4.2.4 Results and analysis

(1) Results of first-level fuzzy comprehensive evaluation According to Eq. (4), the following results of the single-level fuzzy evaluation are obtained:

Chinese refineries should prefer PSA, due to its unique advantage of recovering both CO2 and H2. With the increasing amounts of heavy and high-sulfur crude oils to be processed, demand for H2 in Chinese refineries is rising. The recovery of hydrogen from manufacturing off-gases with PSA can not only reduce total emissions from refineries, but also expand their production and profitability. On the other hand, MA, if the obstacle of the membrane wetting is overcome, will be the most promising alternative to chemical absorption to capture CO2 from oil refinery flue gas in the future. In addition, the methodology presented might be beneficial to decision-making for CO2 capture projects in oil refineries in other countries. The result is important for evaluating the deployment of CCS in Chinese refining sector.

Utilization of technological options for separation and/ or capture of CO2 from flue gases will make Chinese refining industry realize their target of emission reduction in the future. However, without mandatory cuts, incentives, and a major technological break-through, the high costs impose restrictions on the implementation of carbon capture at Chinese refineries. There are a lot of uncertainties about which technologies could lead to real improvements and which have no real prospects for reducing the cost of

is obtained as follows:

"0.0000 0.0029

0.0000 0.0061

0.0000 0.0224

1.0000 0.2633

0.0003 0.0000

0.0000 0.1718

1 . 0000 0.0000

1 . 0000 0.0000

1 . 0000 0.0000

0.0000 1 . 0000

0.5000 1 . 0000

1 . 0000 0.6296

0.0000 0.6667

capture. On the other hand, the use of the captured CO2 as a secondary product appears to be attractive. The utilization includes producing chemical substances through the application of organic chemistry, biofuels, etc., or injecting pure captured CO2 underground for enhanced oil recovery (EOR), enhanced gas recovery (EGR), and enhanced coal-bed methane (ECBM), although this is not mentioned in the paper.

Acknowledgments The authors gratefully acknowledge the general support from the China University of Petroleum Foundation, and the Research Institute of Safety and Environment Technology, China National Petroleum Corporation.

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.


Abu-Zahra MRM, Niederer JPM, Feron PHM, et al. CO2 capture from power plants: part II. A parametric study of the economical performance based on mono-ethanolamine. Int J Greenh Gas Control. 2007;1(2):135-47.

Alie C, Backham L, Croiset E, et al. Simulation of CO2 capture using MEA scrubbing: a flowsheet decomposition method. Energy Convers Manag. 2005;46(3):475-87.

Aroonwilas A, Veawab A. Integration of CO2 capture unit using single- and blended-amines into supercritical coal-fired power plants: implications for emission and energy management. Int J Greenh Gas Control. 2007;1(2):143-50.

Chen JH, Sheng DR, Li W, et al. A model of multi-objective comprehensive evaluation for power plant projects. Proc CSEE. 2002;22(12):152-5 (in Chinese).

Chen XL, Wang RM, Cao YF, et al. A novel evaluation method based on entropy for image segmentation. Procedia Eng. 2012;29:3959-65.

de Mello LF, Pimenta RDM, Moure GT, et al. A technical and economical evaluation of CO2 capture from FCC units. Energy Procedia. 2009;1(1):117-24.

deMontigny D, Tontiwachwuthikul P, Chakma A. Comparing the absorption performance of packed columns and membrane contactors. Ind Eng Chem Res. 2005;44(15):5726-32.

Falk-Pedersen O, Dannström H. Separation of carbon dioxide from offshore gas turbine exhaust. Energy Convers Manag. 1997;38(S):81-9.

Feron PHM, Jansen AE. CO2 separation with polyolefin membrane contactors and dedicated absorption liquids: performances and prospects. Sep Purif Technol. 2002;27(3):231-42.

Figueroa JD, Fout T, Plasynski S, et al. Advances in CO2 capture technology-The U.S. Department of Energy's Carbon Sequestration Program. Int J Greenh Gas Control. 2008;2(1):9-20.

Ho MT, Allinson GW, Wiley DE. Comparison of MEA capture cost for low CO2 emissions sources in Australia. Int J Greenh Gas Control. 2011;5(1):49-60.

Ho MT, Allinson GW, Wiley DE. Reducing the cost of CO2 capture from flue gases using pressure swing adsorption. Ind Eng Chem Res. 2008;47(14):4883-90.

IEA Greenhouse Gas R&D Programme (IEA GHG). CO2 abatement in oil refineries: fired heaters. Report no. IEA/CON/99/61. Cheltenham: U.K. 2000.

IEA. Energy technology transitions for industry—strategies for the next industrial revolution. Paris. 2009.

International Energy Agency (IEA). Energy Technology Perspective. Paris. 2010.

Jiang QZ, Ma JK, Chen GS, et al. Estimation and analysis of carbon dioxide emissions in refineries. Mod Chem Ind. 2013;33(4):1-6 (in Chinese).

Jiang QZ, Xu YM, Xin WJ, et al. SWOT-AHP hybrid model for vehicle lubricants from CNPCLC, China. Pet Sci. 2012;9(4):558-64.

Johansson D, Rootzeen J, Berntsson T, et al. Assessment of strategies for CO2 abatement in the European petroleum refining industry. Energy. 2012;42(1):375-86.

Jorge H, Antunes CH, Martins AG. A multiple objective decision support model for the selection of remote load control strategies. IEEE Trans Power Syst. 2000;15(2):865-72.

Khan JF, Bhuiyan SM. Weighted entropy for segmentation evaluation. Opt Laser Technol. 2014;57:236-42.

Kuramochi T, Ramirez A, Turkenburg W, et al. Comparative assessment of CO2 capture technologies for carbon-intensive industrial processes. Prog Energy Combust Sci. 2012;38(1):87-112.

Lai WK, Khan IM, Poh GS. Weighted entropy-based measure for image segmentation. Procedia Eng. 2012;41:1261-7.

Li JL, Chen BH. Review of CO2 absorption using chemical solvents in hollow fiber membrane contactors. Sep Purif Technol. 2005;41(2):109-22.

Liang ZH, Yang K, Sun YW, et al. Decision support for choice optimal power generation projects: fuzzy comprehensive evaluation model based on the electricity market. Energy Policy. 2006;34(17):3359-64.

Liu Z, Wang L, Kong XM, et al. Onsite CO2 capture from flue gas by an adsorption process in a coal-fired power plant. Ind Eng Chem Res. 2012;51(21):7355-63.

Ma JK, Jiang QZ, Song ZZ, et al. Construction of refinery carbon industry chain in low carbon economy perspective. Mod Chem Ind. 2011;31(6):1-6 (in Chinese).

Ma YT, Wang ZG, Yang Z, et al. Fuzzy comprehensive method for gas turbine evaluation. Proc CSEE. 2003;23(9):218-20 (in Chinese).

Martunus, Helwani Z, Wiheeb AD, et al. In situ carbon dioxide capture and fixation from a hot flue gas. Int J Greenh Gas Control. 2012;6:179-88.

Mavroudi M, Kaldis SP, Sakellaropoulos GP. Reduction of CO2 emission by a membrane contacting process. Fuel. 2003;82(15-17):2153-9.

Meerman JC, Hamborg ES, van Keulen T, et al. Techno-economic assessment of CO2 capture at steam methane reforming facilities using commercially available technology. Int J Greenh Gas Control. 2012;9:160-71.

Ministry of Housing and Urban-Rural Development (MOHURD). The economic assessment method and parameters for oil construction projects. 1st ed. Beijing: China Planning Press; 2010 (in Chinese).

Mondal MK, Balsora HK, Varshney P. Progress and trends in CO2 capture/separation technologies: a review. Energy. 2012;46(1): 431-41.

National Development and Reform Commission (NDRC) and Ministry of Construction (MOC). The economic assessment method and parameters for capital construction projects. 3rd ed. Beijing: China Planning Press; 2006 (in Chinese).

Olajire AA. CO2 capture and separation technologies for end-of-pipe applications-a review. Energy. 2010;35(6):2610-28.

Rangwala HA. Absorption of carbon dioxide into aqueous solutions using hollow fiber membrane contactors. J Membr Sci. 1996;112(2):229-40.

Reddy S, Vyas S. Recovery of carbon dioxide and hydrogen from PSA tail gas. Energy Procedia. 2009;1(1):149-54.

Refat AG, Muhammad H, Shesha J. Transformer insulation risk assessment under smart grid environment due to enhanced aging effects. Electrical Insulation Conference. Annapolis MD. 5-8 June 2011; 276-279.

Reiner P, Audus H, Smith AR. Carbon dioxide capture from fossil fuel power plants, Report SR2, IEA Greenhouse Gas R&D Programme. Cheltenham. 1994.

Rubin ES, Yeh S, Antes M, et al. Use of experience curves to estimate the future cost of power plants with CO2 capture. Int J Greenh Gas Control. 2007;1(2):188-97.

Saaty TL, Shang JS. An innovative orders-of-magnitude approach to AHP-based multi-criteria decision making: Prioritizing divergent intangible humane acts. Eur J Oper Res. 2011;214(3):703-15.

Saaty TL. A scaling method for priorities in hierarchical structures. J Math Psychol. 1977;15(3):234-81.

Saaty TL. Highlights and critical points in the theory and application of the analytic hierarchy process. Eur J Oper Res. 1994;74(3):426-47.

Saaty TL. How to make a decision: the analytic hierarchy process. Eur J Oper Res. 1990;48(1):9-26.

Singh D, Croiset E, Douglas PL, et al. Techno-economic study of CO2 capture from an existing coal fired power plant: MEA scrubbing vs. O2/CO2 recycle combustion. Energy Convers Manag. 2003;44(19): 3073-91.

U.S. Energy Information Administration (EIA). International Energy Outlook 2013. Washington D.C. 2013.

Van Straelen J, Geuzebroek F, Goodchild N, et al. CO2 capture for refineries: a practical approach. Int J Greenh Gas Control. 2010;4(2):316-20.

Wang R, Zhang HY, Feron PHM, et al. Influence of membrane wetting on CO2 capture in microporous hollow fiber membrane contactors. Sep Purif Technol. 2005;46(1-2):33-40.

Xie CS, Dong DP, Hua SP, et al. Safety evaluation of smart grid based on AHP-entropy method. Syst Eng Procedia. 2012;4:203-9.

Yan SP, Fang MX, Wang Z, et al. Economic analysis of CO2 separation from coal-fired flue gas by chemical absorption and membrane absorption technologies in China. Energy Procedia. 2011;4:1878-85.

Yan SP, Fang MX, Zhang WF, et al. Comparative analysis of CO2 separation from flue gas by membrane gas absorption technology and chemical absorption technology in China. Energy Convers Manag. 2008;49(11):3188-97.

Yan SP, Fang MX, Zhang WF, et al. Experimental study on the separation of CO2 from flue gas using hollow fiber membrane contactors without wetting. Fuel Process Technol. 2007;88(5):501-11.

Yang HQ, Xu ZH, Fan MH, et al. Progress in carbon dioxide separation and capture: a review. J Environ Sci. 2008;20(1):14-27.

Yeon SH, Lee KS, Sea B, et al. Application of pilot-scale membrane contactor hybrid system for removal of carbon dioxide from flue gas. J Membr Sci. 2005;257(1-2):156-60.