Journal of Cleaner Production 220 (2019) 408e416
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Life cycle assessment of typical methanol production routes: The environmental impacts analysis and power optimization Zhuo Chen a, b, Qun Shen a, **, Nannan Sun a, Wei Wei a, c, d, * a
Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, 201210, PR China University of Chinese Academy of Sciences, Beijing, 100000, PR China c Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, PR China d ShanghaiTech University, 100 Haike Road, Shanghai, 201210, PR China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 6 November 2018 Received in revised form 8 February 2019 Accepted 9 February 2019 Available online 11 February 2019
China is the largest producer and consumer of methanol in the world. The methanol industry will continuously develop in the long future in China and the environmental impact of the industry is greatly concerned about. In this study, a “cradle to gate” life cycle assessment of CTM, CGTM and NTM is conducted based on the Gabi education 6.0 software. The results suggest that CTM has a much more severe integrated impact, 2.0e3.4 times of the other two routes. In CTM route, environmental burden from synthetic gas production stage contributes most, while the methanol production stage is the major contributor to the burden in both CGTM and NTM routes. Notably, for the three methanol routes, 73.33% e78.50% of integrated impact put damage on the ecosystem. In addition, electricity has been found as the most sensitive parameter. And after power optimization, the integrated impact with 100% electricity generated from clean energy, could be reduced by 82.2%, 66.5% and 83.5% in CTM, CGTM and NTM routes, respectively. The CTM exhibits the largest reduction potential. From estimation, if 100% speciﬁc electricity from hydropower/wind/nuclear is adopted in CTM, its environmental impact is nearly equivalent with that of CGTM route. Meanwhile, CTM route with 100% application of clean energy based electricity will be competitive to CGTM and NTM routes with coal-based electricity matched. Therefore, it could be effective by adjusting its technique structure and/or the intelligent use of clean energy based power to realize the objective of cleaner production and sustainable development for methanol industry, not only in China, but also in other countries in the world. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Methanol production Life cycle assessment Integrated impact Power optimization
1. Introduction As an important raw material for the petrochemical and energy industries, methanol could be widely applied in industries, ranging from chemicals (e.g., as a solvent or an intermediate for producing oleﬁns, formaldehyde, acetic acid and esters) to energy (e.g., as a fuel by itself, blended with gasoline, or for use in direct methanol fuel cells) (Su et al., 2013a,b). With ‘‘methanol economy” proposed by G.A. Olah et al. (2009), it was expected that methanol will become an even more important commodity in the coming years and lead to a new fuel era, in particular for China and USA (Olah et al., 2009; Riaz et al., 2013; Yang and Jackson, 2012). China, as
* Corresponding author. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, 201210, PR China. ** Corresponding author. E-mail addresses: [email protected]
(Q. Shen), [email protected]
(W. Wei). https://doi.org/10.1016/j.jclepro.2019.02.101 0959-6526/© 2019 Elsevier Ltd. All rights reserved.
the largest methanol production country in the world, its methanol capacity has increased to 73.30 Mt in 2016 (National Bureau of Statistics of China, 2017), accounting for >50% of the global total value (China Industrial Information Network, 2018). In the “Petrochemical and Chemical Industry Development Plan (2016e2020)”, China’s methanol demand was predicted to be 80 Mt in recent 2020 with a high annual growth rate of 8.8% (Wang, 2010). Boomed by the traditional and emerging downstream industries, it is believed that China’s methanol industry will continuously develop in the long future (Liu, Z. et al., 2015). Currently, there are numerous technical routes to produce methanol by taking fossil fuels (natural gas, coal, crude oil, biomass, etc) as feedstocks. In China, inﬂuenced by its resource endowment of “abundant coal, scarce oil and natural gas” (Su et al., 2013a), 58% methanol production is produced from CTM route, the rest is mainly from CGTM route (17%) and NTM route (14%) in 2017 (China Industrial Information Network, 2018). Methanol production is a
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high energy-intensive industry and the environmental pollution is typically existed (Obueh, 2006). For example, great amount of acid gases (NOx, SOx and CO2) and waste water are discharged (Gao et al., 2018; Hong, Q. et al., 2015). Besides, the gas leakage from various connecting valves in the production process is commonly existed (Liu et al., 2016; Pehnt and Henkel, 2009). Due to the increasing concerns on the environmental issues in China, it is of high importance to investigate the environmental sustainability of the methanol production industry. To the best of our knowledge, there were great studies about the environmental and economic evaluation associated with methanol production and most of them were focused on the coal based methanol production with technology upgrading by the technoeconomic analysis. For example, Gong et al. (2017) proposed a CO2 recycle process combined with COG to methanol by using dry reforming technology with/without H2 separation scheme, which showed an excellent performance in element and energy efﬁciency. CO2 emission reduction and signiﬁcant economic beneﬁts were compared with the traditional CTM plant. Qian et al. (2015) proposed an integrated process of COG and coal gasiﬁcation to produce methanol, in which a tri-reforming reaction was used to convert methane and CO2 to syngas. Their evaluation results showed that the carbon utilization and energy efﬁciency of the new process increased, whereas CO2 emission was declined in comparison to the conventional coal to methanol process. Liu et al. (2016) found that CTM combined with CO2 capture and ORC power generation could improve the energy efﬁciency. However, the techno-economic analysis is not comprehensive in terms of the environmental impacts. LCA as a standard method based on the ISO 14040/14044 series, it could quantify the potential environmental burdens of products, processes and services during their whole life cycle, including production, use and disposal or recycling (ISO, 2006a, b). With the advantages of tracking and assessing the impacts systematically without burden shift, the LCA method was widely used in various industry evaluations, such as in the food production (Astuti et al., 2018), building industry (Vigovskaya et al., 2018) and chemical industries (Artz et al., 2018). It should be noted that the roots traceable analyses of the environmental problems were also presented in methanol production process (Anna et al., 2017; Gao et al., 2018; Li, C. et al., 2018; Li, J. et al., 2018). For example, Gao et al. (2018) performed a LCA of coal based methanol-to-oleﬁns process. It was identiﬁed that the coal-to-methanol process consumed a vast amount of water and energy with signiﬁcant CO2/ SO2/NOx emissions. Furthermore, it was found that the effect of CCS implement was negative due to its signiﬁcant consumption of the water and energy. Sliwinska et al. (2017) presented a LCA of greenhouse gas emissions generated through methanol and electricity co-production system based on coal gasiﬁcation technology. The results of the assessment were highly dependent on the alternative technology selected. Li, C. et al. (2018) used LCA method to evaluate the environmental impacts of two dominant coal-based methanol technologies (coal gasiﬁcation technology and coal coking technology). The results indicated that less environment harm was caused by using the coal coking technology than by using the coal gasiﬁcation technology, especially in terms of acidiﬁcation, global warming, and photochemical oxidation. Li, J. et al. (2018) conducted the LCA of COG-based methanol production and compared with coal and natural gas-based methanol routes. Their results showed that COG-based methanol production demonstrated the favorable environmental and economic beneﬁts for coke enterprises by technical adjustment. Additionally, Yao et al. (2018) conducted a life cycle environmental assessment associated with coal, natural gas and gasoline-based methanol production, which focused on the impact categories of the primary energy use, greenhouse gas (GHG) emissions, water consumption, and air
emissions (SO2 and NOx). It is noteworthy that most of the previous works were focused on the environmental and economic evaluation of a new or improved process to produce methanol. Although there were several works related to the conventional production routes (CTM, NTM and CGTM), the understanding was not complete and deep enough. For example, the environmental assessment was not thorough, and only some general environmental impact categories were involved. Also, there are still open questions remaining, regarding to how to effectively reduce the environmental impact in a whole, and how much the mitigation potential is if the key factors are improved, which are rarely reported. CTM, NTM and CGTM as the industrial routes to produce methanol, a good understanding of the current technical status and the gap between them with qualitative and quantitative environmental assessment have more realistic signiﬁcance. Therefore, in this work, a “cradle-to-gate” life cycle assessment of three typical methanol production routes (CTM, CGTM and NTM) in China is conducted and their integrated environmental impacts are compared. Besides, the crucial processes and parameters are identiﬁed and discriminated. Furthermore, with the sensitivity analysis and optimization, the mitigation potential by adjusting sensitive factor is estimated. Finally, suggestions for the sustainable development of the methanol industry in China and even in the global application are given. It is expected that this work’s result would provide useful insights for decisionmakers.
2. Methodology According to ISO (ISO, 2006a, b), the LCA study is usually performed as four steps: (1) goal and scope deﬁnition (2) life cycle inventory (LCI) analysis (3) life cycle impact assessment (LCIA) and (4) interpretation.
2.1. Goal and scope deﬁnition The goal of this study is to compare the comprehensive environmental impacts of three typical methanol production routes (CTM, CGTM and NTM). The function unit is deﬁned as 1t methanol produced by the selected technical routes. The boundary of the LCA is deﬁned as “cradle-to-gate”, namely the scope is focused on “the raw material exploitation to the methanol production”. The application and waste treatment of methanol are not included in this work, as the stages after the gate are supposed to be identical in all involved routes. Also, the environmental impacts in the transportation stages for feedstock and intermediate products are not taken into account, due to the negligible inﬂuence reported by literature (Larson and Ren, 2003; Liu and Yuan, 2015). In addition, the environmental impacts during all the infrastructures, facilities construction are not considered in this work. The system boundaries of three methanol production routes (CTM, CGTM and NTM) are clearly shown in Figs. 1e3, respectively.
Fig. 1. Process ﬂow of CTM technical route.
Z. Chen et al. / Journal of Cleaner Production 220 (2019) 408e416
2.2. Life cycle inventory and data sources
Fig. 2. Process ﬂow of CGTM technical route.
Fig. 3. Process ﬂow of NGTM technical route.
2.1.1. Coal-to-methanol route Methanol production by CTM route in China generally contains three steps: coal processing, synthetic gas production through coal gasiﬁcation technology and methanol production. As shown in Fig. 1, after mining and washing, the obtained hard coal is put into a gasifer such as GE/Texaco to generate raw syngas. In this process, an additional air separation unit must be matched to supply pure oxygen. Before methanol production process, the H/C ratio of the raw syngas should be adjusted (~2.1e2.2) by water-shift-gas reaction and after cooling, the gas then enters into a puriﬁcation unit to remove the impurities, such as CO2, H2S, CO and other components, with byproducts like sulphur produced. Also, part of the unreacted gas will be recycled into the gasifer. At last, the clean syngas is synthesized into raw methanol in the presence of catalyst (usually Cu/ZnO/Al2O3) under speciﬁc reaction condition and rectiﬁed in a distillation unit to produce reﬁned methanol.
2.1.2. Coke oven gas-to-methanol route As shown in Fig. 2 the whole CGTM process can be roughly divided into three stages, i.e. coal processing, coke production and methanol production. After mining and washing process, the hard coal is fed in a process of pyrolysis at nearly 1100 C in the coke oven to obtain coke as well as a considerable byproduct of raw COG. Similar to CTM route, the cooled COG should be puriﬁed by removing the impurities, such as sulphur, ammonia, raw benzene etc. In order to satisfy the condition of methanol synthesis, the syngas is also delivered into a reforming reactor (Hong, J. et al., 2015; Liu and Yuan, 2015) to adjust an appropriate H/C ratio (~2.5). After that, the methanol is produced in the synthesis reactor. Finally, the reﬁned methanol is obtained after the distillation unit.
2.1.3. Natural gas-to-methanol route The NTM technical route includes two main stages, namely natural gas extraction and processing, and the whole methanol production (including the synthetic gas production by steam reforming). As shown in Fig. 3, the natural gas, after desulfurization for acid gases such as SO2, H2S and dehydration, is converted into syngas by the steam reforming process, where the H/C ratio is modulated at approximately 3.0. Then, the synthesis gas is compressed and enters into the synthesis reactor to produce methanol. The similar distillation unit is then performed as the other two routes.
For the investigated technological routes, all the input and output data in speciﬁc process, such as the consumption of raw materials, energy and direct emissions, are collected. The life cycle inventories are listed in Tables 1e3 in detail and all the data sources of each technical route are identiﬁed as follows: For the CTM route, the data of material and energy consumption in the coal mining and processing process were obtained from the Clean Production Standard for Coal Mining and Processing Industry (Taiyuan Research and Design Institute of Environment Sciences, 2008; An, 2017) in China. The methane leakage data in China’s coal exploitation process were obtained from the statistical bulletin (National Bureau of Statistics of China, 2008). The data for the gasiﬁcation process were developed according to an IGCC plant project, which represented the update technology of gasiﬁcation (NETL, 2010). Also the air separation process was included in the gasiﬁcation process based on the data of Shanghai Coking & Chemical Corporation (Sun, 2013). Data in terms of methanol synthesis and distillation were developed based on the simulation by Larson and Ren (2003), in which the indirect coal liquefaction technology was applied to produce the methanol, and the clean production method was corresponded. For the CGTM route, the data of material and energy ﬂow in the coal exploration and processing were similar to that in the CTM route (An, 2017; Taiyuan Research and Design Institute of Environment Sciences, 2008). As for the data in the coke production, they were established from a commercial project of coke enterprise located in Shaanxi Province with a capability of 1.2 Mt of coke and 100 thousand tons of methanol (Azapagic and Clift, 1999; €rklund et al., 2010; Li, C. et al., 2018). For the methanol proBjo duction stage, the average data were also collected based on the publication reported by Li, C. et al. (2018). It should be noted that in the coke production process, coke and COG are simultaneously produced. Therefore, the energy input and environmental burden €rklund et al., should be allocated (Azapagic and Clift, 1999; Bjo 2010). In this study, the energy allocation method was selected in Gabi and the coefﬁcient was 11.4%. For the NTM route, the data of natural gas extraction and processing were from National Bureau of Statistics of China (2017) and Norm of Energy Consumption per Unit of Methanol Product (GB29436.2-2015) (China nitrogen fertilizer industry association, 2015), as well as the typical projects operated in China as examples (Song et al., 2014; Yuan et al., 2006). The average localized data related to methane to methanol production process in China were
Table 1 LCI of CTM technical route. Inputs
Coal processing Electricity 53.67 Fresh water 0.69 Hard coal 1.533 Oil 1.53 Synthetic gas production HP-steam 1.77 Electricity 1108.38 Air 4348.2 Water 134.01 Hard coal 1.38 Ammonia 0.03 Methanol production Synthesis gas 1.23 Electricity 825 Water 14.2 NaOH (10%) 1
kwh t t kg
Hard coal Gangue Methane
1.38 153 7.64
t kg kg
t kwh kg t t t
Synthetic gas Slag MP-nitrogen CO2 Sulphur
1.23 0.15 1523.7 1.74 30
t t kg kg kg
t kwh t kg
Methanol Flue gas Efﬂuents
1 0.07 0.266
t t t
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Table 2 LCI of CGTM technical route. Inputs Coal processing Electricity Fresh water Oil Hard coal Coke production Hard coal Compressed air Electricity LP-steam Sulfuric acid (98%) Fresh water Sodium, hydroxide Oil
468 6.02 13.34 13.374
kwh t kg t
Hard coal Gangue Methane Hard coal
12.04 1334 66.62 12.04
t kg kg t
12.04 46.34 411.39 1345 90.9 6.74 0.027 3.9
t Nm3 kwh kg kg t kg kg
Coke COG Coal tar Ammonium sulfate Raw benzene Sulphur NOx SOx Coke tar Dust
9.09 1968.66 327 118 100 9.09 1.55 0.64 0.55 0.27
t Nm3 kg kg kg kg kg kg kg kg
Nm3 kwh t t t
Methanol LP-steam Exhausted gas Methanol
1 938.4 676.35 1
t kg m3 t
Methanol production COG 1968.66 Electricity 678.32 MP-steam 2.25 Desalinated water 1.14 Fresh water 6.19
Table 3 LCI of NTM technical route. Inputs
Natural gas processing Hard coal Oil Iron Natural gas Fuel natural gas
47.39 11.97 0.05 617 20.11
kg kg kg Nm3 kg
CO2 CH4 NOx SOx CO PM Natural gas
153 5.44 0.48 0.39 0.043 0.025 617
kg kg kg kg kg kg Nm3
617 576.4 142 3.6 11 0.2 0.15
Methanol production Natural gas Electricity Oxygen Desalinated water Fresh water Sodium Hydroxide Trisodium phosphate
Nm kwh Nm3 t t kg kg
collected from the literature (He, 2013; Yao et al., 2018), in which a methanol plant outputting of 80 Mt product from China Offshore Oil Bohai Corporation was taken as a case. The indirect emissions are calculated by selecting speciﬁc secondary energy resources on the basis of GaBi education 6.0 database. For the materials and energy ﬂow, China’s localized data were prioritized. If the data are not existed, global average data are used. 2.3. Life cycle impacts assessment (LCIA) methods 2.3.1. The mid-point impact assessment method In order to account for all parameters along the cause-effect chain between the inventory data and the particular impact category, the widely-used CML 2001eJan 2016 methodology (Thinkstep Gabi, 2018), which is developed in mid-point level and problem targeted, is induced to evaluate the environmental impacts. As shown in Fig. 4, herein, the mid-point impact categories include: (1) Abiotic Depletion (ADP); (2) Acidiﬁcation Potential (AP); (3) Freshwater Aquatic Ecotoxicity Potential (FAETP inf.); (4) Marine Aquatic Ecotoxicity Potential (MAETP inf.); (5) Terrestrial Ecotoxicity Potential (TETP inf.); (6) Human Toxicity potential (HTP inf.); (7) Eutrophication Potential (EP); (8) Global Warming
Fig. 4. The map of methodology. Note a: impact category periods are usually 20, 100 and 500 years, as well as inﬁnite time span. Only 100 years were listed since it was recommended by IPCC and was widely used in research (Qin et al., 2013). b: the value of weighting was from a survey from CML in 2012 in Gabi (Thinkstep Gabi, 2018). This study considers the ADP (fossil) only for the damage level of ADP, and the value of ADP (elements) was too small to be selected in our results.
Potential (GWP); (9) Ozone Layer Depletion Potential (ODP); (10) Photochem Ozone Creation Potential (POCP). For the calculation of speciﬁc impact category, all the ﬂows related to the cause-effect impact during the life cycle are characterized based on Eq. (1):
Where Wi is the quantity of a certain pollutant i, Xji is the characteristic factor of a certain pollutant i in a speciﬁc environmental impact j, Aj presents the result of j mid-point impact with speciﬁc functional units, which is used to ensure an equivalent level of function or service for the outcome results. This effect of characterization enables to check and compare the results of different mid-point impact categories.
2.3.2. The end-point impact category and integrated impact assessment method From the mid-point impact assessment, due to the inconsistency of unit, the environmental impact in different production routes could be compared only based on a speciﬁc environmental category. Therefore, a comprehensive and quantitative environmental impact level is necessary (Bueno et al., 2016). Learning from the end-point impact assessment (also called as damage-based evaluation method), the selected 10 mid-point impacts categories are classiﬁed according to their environmental damage objectives. Therefore, as shown in Figs. 4 and 10 mid-point impact categories are assorted into their corresponding end-point categories (Ismaeel, 2018), related to “Resource”, “Ecosystem”, “Human health” and the cross inﬂuence of “Eco & Human”. That is, the AP, FAETP inf., MAETP inf. and TETP inf. categories are classiﬁed into “Ecosystem” damage. As for the EP, GWP, ODP and POCP impact categories, their damage objective could be human health and ecosystem, thus assorted into “Eco & Human” subject, whereas for the “Resource” and “Human health” subjects, they only include the ADP and HTP inf. impact category, respectively. Before integration, normalization is made on the basis of the result of mid-point impact assessment. In combination with the weighting values, the total environmental impact level could be assessed according to
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m X i¼1
n X j¼1
Where Aj is the result of the speciﬁc j mid-point impact with speciﬁc functional units; Mj is the standardized baseline value for the speciﬁc j impact category, herein the total amounts of various environmental burden in the worldwide in 2000 are selected as the standardization values (Thinkstep Gabi, 2018); Ɵj is the weighting value of the speciﬁc j impact category; Zi is the classiﬁed i environmental impact and Z is the integrated environmental impact. Herein, the weighting values are directly derived from the coefﬁcients in Gabi software, according to Leiden University CML’s survey and calculation ([dataset] CML - Department of Industrial Ecology; Sleeswijk et al., 2008), which are listed in Fig. 4.
3. Results and discussion 3.1. LCIA results and impact analysis 3.1.1. The comparison based on mid-point impacts The life-cycle impact assessment results calculated based on CML method for the CTM, CGTM and NTM are shown in Table 4. For the CTM route, the environmental impacts in all selected impact categories are the greatest. As for the NTM route, its impacts are the slightest except the ODP indicator. The impact ratios of CTM/CGTM and CTM/NTM are generally ranged in 1.4e2.6 and 1.9e3.4, respectively. For the ODP indicator, the impact ratios of CTM/NTM and CTM/CGTM are 54.2 and 32.8, which is extremely high. The relative contribution of life cycle stage to the LCA results in the speciﬁc methanol route is illustrated in Fig. 5. In the case of CTM, it is apparently exhibited that in ADP category, the coal processing stage leads to the highest fossil resource consumption (64.8%), followed by syngas production stage (22.2%) and methanol production stage (13.0%). Whereas, in the categories of AP, EP, FAETP, MAETP, TETP, GWP, HTP and POCP categories, more than 50% of the environmental impacts are resulted from syngas production stage. Notably, for ODP category, it is even higher than 90%, which is due to the high consumption of electricity and steam. Possibly, the radioactive elements, such as Rn and Kr, are emitted from energy combustion in the electricity and steam generation. Also, the impact from methanol production stage cannot be overlooked, roughly ~35% contribution in these impact categories, followed by the coal mining and processing stage with a share of ~15%. In CGTM route, similar to the CTM route, the ADP category is also mainly from the coal extraction and process stage. For the other categories, the impact from methanol production stage makes the overwhelming contribution (>80%) due to the high electricity consumption. In addition, coke production stage, as an energy-
Fig. 5. Contribution of sub-stages to the LCIA of typical technical routes.
intensive process, the environmental impacts after allocated on COG production are also noteworthy. For the NTM route, the environmental impacts from natural gas extraction and process are relatively obvious. Besides its maximal contribution in the ADP category, its shares in the AP, EP, GWP and POCP categories are also signiﬁcant, which are due to the gas leakage, such as acid gases, H2O, CH4, hydrocarbon gas. The methanol production stage including the steam reforming process exhibits major impacts due to the high electricity consumption. 3.1.2. The comparison based on integrated environmental impact and end-point impact categories After characterization and normalization of the mid-point environmental impacts, the integrated impacts of three conventional methanol routes are calculated and shown in Fig. 6. The value of integrated impact in CTM is the largest, which is almost double of that in CGTM route, and 3.4 times to the value of NTM route. The integrated impact of CGTM route is the second large one, which is 1.7 times to the value of NTM route. Therefore, it is apparently exhibited that NTM is the cleanest route. Taking close insight into the contribution from different sub-stages, as shown in Fig. 6, in CTM route, 54% share is from syngas production stage, and >36% is from methanol production. While for the CGTM and NTM routes, the contribution to the integrated impact is mainly from methanol production stage, accounting for 81% and 87% respectively. Therefore, the syngas production process plays the most important role for the environmental-friendliness of the entire CTM technology.
Fig. 6. Integrated impact of typical technical routes.
Table 4 Result of 10 mid-point impacts and ratios between typical technical routes. Impact category
ADP AP EP FAETP MAETP TETP GWP HTP ODP POCP
MJ kg SO2-Equiv. kg Phosphate-Equiv. kg DCB-Equiv. kg DCB- Equiv. kg DCB-Equiv. kg CO2-Equiv. kg DCB-Equiv. kg R11-Equiv. kg Ethane-Equiv.
6.39Eþ04 9.16 0.827 19.6 3.88Eþ05 15.8 2.67Eþ03 669 1.09E-08 0.909
4.88Eþ04 4.33 0.32 9.74 1.84Eþ05 8.3 1.22Eþ03 352 2.03E-10 0.449
3.42Eþ04 3.21 0.263 5.81 1.05Eþ05 4.42 798 189 3.32E-10 0.268
1.3 2.1 2.6 2.0 2.1 1.9 2.2 1.9 53.7 2.0
1.9 2.9 3.1 3.4 3.7 3.6 3.3 3.5 32.8 3.4
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Fig. 7. Comparative results of 4 end-point impacts in typical technical routes and substages.
Regarding to the contribution from different end-point impact categories in Fig. 7, the situations of three routes are almost similar. 73.33%e78.50% damage is affecting the ecosystem, especially the ecotoxicity for the water and terrane. The impact directing to the resources and human health are 6.67%e12.12% and 10.04e10.95%, respectively. It is supposed that the health nuisance mainly results in the toxicosis of human body and leads to cancer or other severe diseases. For the resource damage, it is mainly caused by the fossil consumption. The rest 4.08%e4.51% damage is affecting both ecosystem and human health, according to the “Eco & Health” indicator. However, if focusing on the most important impact category “Ecosystem”, the absolute value ratios of CTM/CGTM and CTM/ NTM are 2.1 and 3.6 respectively, which is extremely higher than the other impacts, indicating that the damage to ecosystem in CTM route is much more severe than the other two routes. As shown in Fig. 7, the “Ecosystem” impact in CTM route is mainly from syngas and methanol production processes, and in CGTM and NTM routes, it is mainly from methanol production process.
Fig. 9. Sensitivity result of CGTM input parameters. * Electricity_c1 in term of the parameter in synthetic gas production, Electricity_c2 in coke production, Electricity_c3 in methanol production.
3.2. Sensitivity analysis Fig. 10. Sensitivity result of NTM input parameters.
Sensitivity analysis is conducted to reveal the key factors which inﬂuence the impact evaluation results. The input data of material and energy parameters are adjusted by ±10% to determine the inﬂuence degree. It should be noted that the parameters whose sensitivities are less than 2% are neglected, such as the electricity consumption in coal mining and processing in CTM route. If taking ADP, AP, HTP and GWP as the typical categories, the results are shown in Figs. 8e10. As the situation in CTM route in Fig. 8, it is clearly shown that electricity consumed in the syngas production process is the most sensitive parameter and the electricity used in methanol
Fig. 8. Sensitivity result of CTM input parameters. * Fresh water_1/Electricity_1 in term of the parameter in synthetic gas production, Fresh water_2/Electricity_2 in term of the parameter in methanol production.
production process is the second important one in the selected impact categories. Their total sensitive degree will be attained to ±8.20%, ±6.72% and ±6.72% in the AP, HTP and GWP impact categories, respectively. For the ADP category, the hard coal input is the most overwhelming factor, while electricity consumption is the second sensitive parameter. In the case of CGTM route in Fig. 9, also, the hard coal is the main sensitive parameter in the ADP impact category. For the other three categories (AP, HTP and GWP), the electricity consumption in the methanol production is the most sensitive parameters, whose sensitive degrees are ranged in ±6.92%, ±8.37% and ±4.70% in the AP, HTP and GWP impact categories, respectively. It is noteworthy that the inﬂuences of hard coal parameter in the AP and GWP categories are also considerable. For the NTM route in Fig. 10, similar to the situation in CTM and CGTM routes, the natural gas as a raw material is the most sensitive parameter in the ADP category, with a range of ±7.31% sensitive degree. In the AP, HTP and GWP impact categories, the electricity in methanol production process is also the most important sensitive factor with ±6.82%, ±9.69% and ±6.56% sensitive degree, respectively. Similarly, the inﬂuence of electricity on HTP is the largest. In addition, the parameter of natural gas consumption also plays an important role to inﬂuence the AP and GWP categories. Therefore, from sensitive analysis, electricity as an essential parameter in the three conventional methanol production routes, is the major sensitive factor to inﬂuence the result of environmental impacts.
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3.3. Mitigation potential of environmental impact by electricity optimization As shown in Fig. 11, the source structure of power generation is undergoing great change in China during 2012e2017 (China Electricity Council, 2018a,b; Huang and Li, 2015). Power share from coal-derived has declined from 74.46% to 63.00% in 2012e2017, with a stable decrease rate of 0.04%, indicating that coal combustion is still the dominant way for the power generation in short term. However, according to the “13th Five-Year Plan”, the share of coal-derived electricity will drop to 55% in 2020, and < 50% in 2050 as predicted by the China Electricity Council. On the other hand, the clean electricity (power from wind, hydro, nuclear and solar) is greatly encouraged, with the total share of 21.27%e29.09% in 2012e2017. Amongst, the electricity’s share from hydropower, wind, nuclear and solar power generation in 2017 is attained to 18.61%, 4.76%, 3.87% and 1.84%, respectively. It is believed that with the cost reduction, the share of clean energy based electricity will almost be equivalent, even higher than that of coal-based electricity in the long future. Herein, with the improvement of electricity generation, the mitigation potentials of the overall environmental impact in the three methanol production routes are evaluated and the results are shown in Fig. 12. If the 100% coal-derived electricity is replaced by mixed electricity (hard coal 74.23%, hydro 16.9%, wind 2.59%, heavy fuel oil 2.05%, natural gas 1.66%, coal gases 1.24%, and other fuels account for less than 1%) (Thinkstep Gabi, 2018), the integrated environmental impacts could be reduced by only 2.5%, 3.6% and 2.4% in CTM, CGTM and NTM routes, respectively. In the ideal situation, if the electricity is all from speciﬁc renewable energy, the mitigation potential will be much obvious. For example, there are 82.2%, 66.5% and 83.5% reduction rates with 100% wind power in CTM, CGTM and NTM routes, respectively. Similar results are observed if 100% hydropower or nuclear power is matched. In the case of electricity 100% generated from photovoltaics, the reduction potentials are 72.5%, 59.9%, 73.7% in CTM, CGTM and NTM routes, respectively, a little higher than that of other clean energy based power, but sill much lower than that of coal-derived power. The reason is that a large amount of silicon tetrachloride and other gases such as CO2, SO2 are exhausted during the production process of photovoltaic panel, which will have deep inﬂuence on the ecosystem as well as on the human health. From Fig. 12, it should also be noted that CTM route has the largest mitigation potential of environmental impact. The integrated environmental impacts of CTM and CGTM routes are close with each other, if 100% speciﬁc electricity from hydropower/wind/ nuclear is adopted. Furthermore, CTM route with 100% application of clean energy based electricity will be competitive with CGTM and NTM route with coal-based electricity matched. These results mean that by the replacement of electricity source, the CTM route can get out of trouble and compete with CTM and NTM routes. This is a very existing result. Because the electricity optimization in CTM
Fig. 11. Source structure of power generation in China.
Fig. 12. Integrated impact mitigation results after power optimization.
can make a huge contribution to environmental impact reduction in methanol industry, regarding to its absolute share of methanol production in China. The mitigation potential from four end-point impact categories by electricity optimization is further analyzed by the decomposition of the integrated impact, as shown in Fig. 13. Notably, if 100% speciﬁc clean energy based electricity is applied, “Ecosystem” as the major impact, its reduction is maximal, with 85%, 72% and 92% reduction rates in CTM, CGTM and NTM routes, respectively. “Human Health” as a signiﬁcant impact, its reduction is also prominent, with 93%, 73% and 97% reduction degrees in CTM, CGTM and NTM routes, respectively. However, as for the “Resource” impact category, its mitigation potential is relatively small, only 31%, 17% and 17% reduction rates in CTM, CGTM and NTM routes, respectively. For the “Eco-human” impact category, although its contribution is little, its reduction rates are also high (71%, 63% and 71% reduction rates in CTM, CGTM and NTM, respectively). 3.4. Discussion In consideration of the resource endowment, CTM as the major route of methanol production in China, will keep its dominance for a long time. However, its environmental impact is severer, mainly due to the syngas production process. Fortunately, the electricity optimization seems to be an effective way to mitigate its environmental impact. If the renewable/nuclear electricity is used, its environmental impact could be matched with that in NTM route. Actually, this ideal situation could be achieved in some areas of China, where abundant clean energy-based electricity is generated. Currently, the distribution of renewable power in China is highly depended on the local resources (National Energy Administration, 2018a,b; Zhang et al., 2018). Namely, the hydro power and nuclear are mainly distributed in the east and south of China, for wind and solar power mainly distributed in the north-western area. However, the utilization of renewable power in these areas is not enough. The abandon rates of wind power were 20% and 22% in Gansu and Xinjiang province, respectively (National Energy Administration, 2018a,b), and the utilization rate of hydro power potential was estimated to lower than 30% in 2015 (Shan et al., 2015). Therefore, it is supposed that in this area, the wasted
Fig. 13. End-point impact mitigation results after power optimization.
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renewable power could be considered to be used in the CTM industry. In addition, in order to reduce the pollutant emissions, more efﬁcient techniques for sewage treatment and waste disposal should be matched, such as the ﬂue gas treatment and circle usage in syngas production and the CCS, puriﬁcation of sewage and exhausted gas in methanol production. China as the largest coke production nation, the COG production as byproduct is also quite large. It is estimated that 1500 bcm COG is produced in 2014 and only 50% is recycled into the carbonization chamber as fuel. CGTM is one of the earliest way for COG utilization. As a result of the absence of gasiﬁcation process and only methane conversion process needed, its environmental impact is only half of that in CTM route. Therefore, the development of CGTM is not only in the range of circular economy, but also in the direction of energysaving and emission-mitigation. Compared to the other two routes, NTM is the cleanest way to produce methanol, whereas currently its development in China is seriously limited by the feedstock supply. Although the natural gas industry has experienced a fast development in the last decades, little natural gas is allowed to be applied in the methanol production. Only in some regions or provinces of rich natural gas supply but few other fossil energy, the NTM route is applied to meet local demand in a certain level. However, it is believed the NTM could also not be overlooked in China. In the future, beneﬁting from the success of shale gas development in U.S., the cheap methane could be imported from abroad. Meanwhile, in China, ambitious targets have been set that by 2020 its domestic shale gas production levels of 60e100 bcm per year will be reached (Ma and Xiao, 2017). Therefore, once the supply of raw materials is adequate, the NTM route will play a more and more important role and its mitigation potential will be considerable in the future. Furthermore, the implication of cleaner production in China’s methanol industry can also be applied to the global level. As reported by HeXun (2018), Northeast Asia has the largest methanol production capacity in the world (56%), and is followed by Middle East (13%) and South America (8%). Concerning the feedstock, the proportion of methanol production from the NTM route worldwide was around 58% in 2017 (HeXun, 2018), which was mainly contributed from Middle East, South America and North America. With the development of shale gas exploitation, the NTM route would keep the prominent role in the methanol production industry. In addition, its fossil fuel’s environmental burden could be effectively reduced by electricity optimization, especially in America, where the renewable power is well developed with 42% electricity generated from nuclear/hydropower/renewable energy (BP, 2018). In addition, in the region with the similar energy structure like China, renewable power should also be encouraged to permeate into the methanol industry. For example, in Europe, the traditional fossil resources are not very rich and 57% electricity (BP, 2018) is generated from nuclear/hydropower/renewable energy. Therefore, coal-based routes combined with nuclear/hydropower/ renewable energy could be considered in this area. All in all, it is suggested that all the methanol production routes could be integrated with renewable power to realize deep cleaner development if allowed. 4. Conclusions CTM, CGTM and NTM are the conventional technical routes to produce methanol in China, and their speciﬁc environmental impact at mid-point level and the overall impact classiﬁed by endpoint impacts are analyzed by LCA method. On the basis of sensitivity analysis, electricity is the most sensitive input parameter and the mitigation potential after power optimization is evaluated. The results show that CTM route exhibits the most server integrated
impact, 2.0e3.4 times as that of the other two routes, and NTM is the cleanest one. The synthetic gas production stage contributes most to environmental burden in CTM route, while the methanol production stage is the major contributor to the burden in both CGTM and NTM routes. For all the three routes, 73.33%e78.50% impact put damage on the ecosystem. Sensitive analysis indicates that electricity is the most important parameter to inﬂuence the environmental impact, especially the electricity consumed in syngas production stage in CTM route and in methanol production process in both CGTM and NTM routes. With the electricity optimization, we ﬁnd that the integrated impact with 100% electricity from nuclear/renewable power (such as wind or hydropower) could be reduced by 82.2%, 66.5% and 83.5% in CTM, CGTM and NTM routes, respectively. CTM is the most “dirty” route, but its environmental impact is nearly equivalent with that in CGTM route, if 100% speciﬁc electricity from hydropower/wind power/nuclear is adopted in both. Furthermore, CTM route with 100% application of clean energy based electricity will be competitive with CGTM and NTM routes adopting coal-based electricity. It is suggested that the largest electricity mitigation potential of CTM can be applied in the coal dominated region like China and Europe. Although the NTM is the cleanest route, considering the great mitigation potential, the power optimization can also be applied in particular regions, where the renewable power is also rich, like South America. Therefore, it is concluded that the methanol industry could realize its target of clean and sustainable development by adjusting its technique structure and/ or intelligent utilization of the renewable power. Notes It should be noted that uncertainties are unavoidable in this work, due to the parameter choice, model uncertainty and value choice. The data are from multi sources and some subjective determinations of value choices are thus existed, making deviations inevitable. Due to the differences in scope deﬁnition and the selected model, the results may be not completely consistent with the literature report. In addition, the normalization factors are limited by the veriﬁcation in Gabi. In order to verify the results, comparisons are made with many literature reports. Acknowledgments This paper is ﬁnancially supported by the (1) National Key Research and Development Program (No. 2016YFA0602603, No. 2016YFA0602602), (2) Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB10040200), (3) Chinese Academy of Sciences Youth Innovation Promotion Association Funding and (4) Shanghai Natural Science Foundation (No. 18ZR1444200). References An, L., 2017. Environmental Behaviors of the Whole Life Cycle of Coal and Their Effects on Land. China University of Mining and Technology. Dorota, B.K., Adam, S., 2017. Environmental life cycle assessment of Anna, S., methanol and electricity co-production system based on coal gasiﬁcation technology. Sci. Total Environ. 574, 1571e1579. Artz, J., Muller, T.E., Thenert, K., Kleinekorte, J., Meys, R., Sternberg, A., Bardow, A., Leitner, W., 2018. Sustainable conversion of carbon dioxide: an integrated review of catalysis and life cycle assessment. Chem. Rev. 118 (2), 434e504. Astuti, A.D., Astuti, R.S.D., Hadiyanto, H., 2018. Application of life cycle assessment (LCA) in sugar industries. E3S Web Conf. 31 (7), 04011. Azapagic, A., Clift, R., 1999. Allocation of environmental burdens in multiplefunction systems. J. Clean. Prod. 7 (2), 101e119. €rklund, A., Finnveden, G., Roth, L., 2010. Application of LCA in waste manageBjo ment. Solid Waste Technol. Manag. 1, 137e160. BP, 2018. BP Statistical Review of World Energy. https://www.bp.com/content/dam/
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List of the abbreviations CTM: coal-to-methanol CGTM: coke oven gas-to-methanol NTM: natural gas-to-methanol LCA: life cycle assessment LCI: life cycle inventory LCIA: life cycle impact assessment COG: coke oven gas Mt: million tons CCS: carbon dioxide capture and storage ADP: abiotic depletion AP: acidiﬁcation potential FAETP inf: freshwater aquatic ecotoxicity potential MAETP inf: marine aquatic ecotoxicity potential TETP inf: terrestrial ecotoxicity potential HTP inf: human toxicity potential EP: eutrophication potential GWP: global warming potential ODP: ozone layer depletion potential POCP: photochem ozone creation potential inf: inﬁmum bcm: billion cubic meter