Costs of Gasiﬁcation Technologies for Energy and Fuel Production: Overview, Analysis, and Numerical Estimation

: During recent years, gasiﬁcation technology has gained a high potential and attractiveness to convert biomass and other solid wastes into a valuable syngas for energy production or synthesis of new biofuels. The implementation of real gasiﬁcation facilities implies a good insight of all expenses that are involved, namely investments required in equipment during the project and construction phases (capital expenditures, CapEx) and costs linked to the operation of the plant, or periodic maintenance interventions (operational expenditures, OpEx) or costs related to operations required for an efﬁcient and sustainable performance of a gasiﬁcation plant (e


Introduction
There is a significant and growing need to develop clean and renewable energy sources to achieve carbon neutrality by 2050 [1]. Biomass gasification is the only method that uses completely renewable resources and offers a range of advantages in terms of its associated environmental impact and carbon neutral characteristics [2]. Thus, it is critical to increase the production capacity of renewable gases from gasification processes. Various innovative gasification technologies are being developed, which offer improved efficiency and cost-effectiveness. These technologies include plasma gasification [3], entrained flow gasification [4,5], dual fluidized bed gasification [6,7], and sorption enhanced gasification [8][9][10], while other recent developments have been a resurgence in research into oxidizing agents, using air, steam, oxygen, carbon dioxide, or a combination of them [11][12][13][14][15]. It is expected that the hydrogen of future gasification plants, thereby minimizing the risks of a new installation [45,46]. This is of utmost importance, as realistically, the gasification technology and producer gas cleaning technologies are still in a demonstration phase, presenting various technical and non-technical risks [47]. In addition, the operation and expertise gained in demonstration plants may provide fruitful knowledge regarding marketing strategies for the different products generated (e.g., energy, and liquid and gaseous fuels).
This document aimed to present an overview of several large-scale gasification plants, using different feedstocks and technologies, to establish relationships between their investment costs and outputs throughout the years, from an evolutionary perspective of technology implementation. The novelty relies on the compilation and analysis of CapEx associated with demonstration and commercial gasification plants producing different products (heat, electricity, and other liquid and gaseous fuels), and to establish the mathematical correlations that relate technology costs with the year of implementation and product output. These studies may have a relevant contribution in the activities of decision makers (e.g., government bodies, technology manufacturers, and project developers) that work with similar technologies.

Overview of Capital and Operational Expenditures Associated with the Different Stages of Gasification
Regarding CapEx values focused on the scale of gasification technologies, the literature reported that fixed and fluidized bed gasifiers may have total installed capital costs between 1965-5235 €/kW, while gasifiers with CHP systems may have costs between 5115-6010 €/kW [48].
For product gas cleaning modules, there are a variety of technologies developed with this purpose, however the most sold are cyclones, filters, electrostatic precipitators, and wet gas scrubbing. Cyclones can remove up to 90% of the larger size particles at a reasonable cost (0.5-1.5 k€ for a gas flow of 1000 m 3 /h). However, high temperature ceramic or sintered metal filters (1-2 k€ for gas flowrates of 1000 m 3 /h) must be incorporated, or even electrostatic precipitators to remove small-sized particles (22-110 k€ for gas flows of 1000 m 3 /h) [49,50]. Another commonly considered option is wet gas scrubbing, which can remove up to half of the tar present; when used in combination with a venturi scrubber, the device can remove up to 97% of tar (23-70 k€ for saturated gas flowrates of 17,000 m 3 /h) [51]. OLGA's tar removal process uses several scrubbers, and effectively recycles almost all the tar contained in gas to the gasifier. The investment may be between 150-1750 € (gas flowrate of 1 m 3 /h) [52].
More information on thermochemical process costing is available in the Supplementary Materials, which contains Tables S1-S4 compiling information on OpEx and CapEx estimates according to gasifier type, oxidizing agents, syngas cleaning technology, and syngas applications.

Survey of Information Regarding Real Gasification Plants Producing Energy or Renewable Fuels
A thorough collection of information about existing operational plants, including those that entered operation in the past and meanwhile ceased working was performed. These additional non-operational plants were integrated in the study as they allow to increase the sample size for several product categories, and to provide useful data insights about similar facilities that eventually will be projected and built in the next years. Information that was retrieved for each plant (whenever possible) included its owner company, location, year, raw materials and products, output capacity, technology readiness level (TRL), and CapEx. Several sources were considered for data collection such as institutional reports, databases, and scientific articles, and the temporal period considered for this survey was between 1996 and 2021. The specific cost of each plant was calculated considering the ratio of total CapEx and the output capacity (expressed in mass or energy flow units, as appropriate), and updated through to 2020 through the application of producer prices in industry indexes, as published by Eurostat [53]. In addition, units that were considered to express power and fuel flow as output results were uniformized and converted to kW and t/y, respectively, to provide consistent relationships and estimations.

Categorization of Gasification Plants According to the Final Product Type
A classification for the different gasification plants based on the final product type was proposed to differentiate the available production technologies, process complexities, and capital investments required for each solution. The list of gasification plants and their corresponding products collected from the survey performed in Section 3.1 allowed to propose the following classification: products obtained from energy generation (electricity, heat, and combined heat and power (CHP)), from renewable gases generation (SNG), and from liquid fuels generation (ethanol, methanol, gasoline, and FT fuels). Therefore, a total of three product classes and eight product subclasses were established to group the facilities retrieved during the analyzes and discussions about capital investments. All surveyed plants in Section 3.1 were thus grouped according to this classification, based on the final products obtained.

Correlation Equations and Their Graphical Representations to Elucidate Evolutionary Trends of Plant Costs over Time, and Economy of Scale
Lastly, this work entailed the creation of graphical representations between the relevant variables, in particular specific investment vs. year and product output. These representations provided a way to identify and exclude several outlier points that would negatively interfere in the analysis, and then to determine correlation equations using regression methods. These equations aimed to relate the variables involved, and to estimate the specific costs inside and outside the range of the sampling period (1996-2021), or the range of product output. Linear and exponential regressions were then used to define the relationships between the specific cost and year, as well as the specific cost and output, respectively. Such correlations can therefore be used to identify trend patterns and to analyze the evolutionary trend of CapEx with time and scale, concerning gasification plants. Figure 1 summarizes the complete methodology of analysis that was followed in the present work. As far as we know, the complete methodology proposed here presents an innovative approach to evaluate and predict capital investments in gasification technologies and was not identified in other works as of yet.

Analysis on the Evolutionary Trend of Gasification Plant Investments
Several small and large-scale gasification plants able to process biomass and solid wastes into energy, biomethane and other liquid biofuels were identified in fourteen dif

Analysis on the Evolutionary Trend of Gasification Plant Investments
Several small and large-scale gasification plants able to process biomass and solid wastes into energy, biomethane and other liquid biofuels were identified in fourteen different countries. Most of the plants are in the USA (seven units), UK (six units), France (five units), and Finland and Canada (four units for each one). These facilities use different conversion technology approaches, and Table 1 presents a list containing information regarding these units. A first look at the output and specific investment columns from Table 1 revealed the existence of several outlier values that were too high, and were therefore removed from the economic study. This adjustment was deemed to be necessary as such values may provide inaccurate results and inconsistent estimates in the next stages of the study. Gasification facilities defined as outliers were Mitsubishi Materials and Kawasaki Steel (located in Japan), GTI Gas Technology Institute (USA), Engie (France), PHG Energy (USA), EERC (USA), Karlsruhe Institute of Technology (Germany), and Total (France).
Most facilities with available economic information are in Northern America and Northern Europe and process a variety of feedstocks that include forestry and wood wastes, municipal solid wastes (MSW) and its derivatives, sewage sludge, polymeric wastes, and energy crops. The calculated specific costs were relatively high in plants producing liquid or gaseous fuels, which were directly related to the complexity of the production process (values between 1800-34,000 €/(t/y)). These plants started to come out particularly in the last six years, thus justifying the low technological maturity and the high investment costs that were associated with them. Inside the group of energy production plants, those that generate electricity alone were deemed to be more expensive compared to heat production or CHP alternatives (5200-13,000 €/(t/y)). This occurrence may be justified by the higher efficiency of energy extraction from input feedstocks. Concerning liquid fuel plants, these presented a larger flexibility in terms of the list of final products, which include ethanol, methanol, gasoline, and various Fischer-Tropsch (FT) fuels (e.g., diesel, gasoline, and naphtha). The FT reaction mechanism is the most implemented, however, in some cases, major investments are still required. Plant scales ranged from 140 kW-190 MW for those dedicated to energy production, and 250-92,000 t/y for gaseous or liquid fuel production. Table 2 gives a brief overview of both the variation and average specific costs of gasification facilities, as according to the final product. As evidenced by the presented data, electricity and SNG production plants have the highest costs in the general categories of energy and fuel production (8583 €/kWe and 16,004 €/(t/y), respectively). However, the dispersion of results for specific costs was significantly higher in the case of liquid biofuels, a fact that may be explained by the large spectrum of fuel products (ethanol, methanol, gasoline, and diverse FT fuels), and by the diversity of conversion technologies that were involved.
Given the number of plants found in each product category, mathematical correlations were established for those producing electricity and CHP, once these categories contained a significant number of points to generate robust correlations. Moreover, all liquid biofuel production plants (ethanol, methanol, and FT fuels) were combined, again to provide a relevant number of points to deduce correlations (the gasoline production unit was excluded from the analysis once this was considered an outlier as previously declared). Therefore, a total number of three categories (electricity, CHP, and liquid biofuel production) were considered for the determination of the individual mathematical correlations.
Graphical representations and linear regression equations for specific investment vs. year for electricity, CHP, and liquid fuel production units are shown in Figure 2 and Table 3, respectively. All specific investments presented a decreasing tendency over time for the three plant types. The linear correlation fitted better to data regarding the electricity production plants, with a coefficient of determination (R 2 ) of 0.67. The other two plant typologies exhibited values lower or equal to 0.29. This was explained by the higher dispersion of points associated with the heterogeneity of specific costs, and potentially also due to the higher diversity of conversion technologies found in both CHP and liquid fuel production  All specific investments presented a decreasing tendency over time for the three plant types. The linear correlation fitted better to data regarding the electricity production plants, with a coefficient of determination (R 2 ) of 0.67. The other two plant typologies exhibited values lower or equal to 0.29. This was explained by the higher dispersion of points associated with the heterogeneity of specific costs, and potentially also due to the higher diversity of conversion technologies found in both CHP and liquid fuel production facilities (i.e., different gasifier types combined with various energy production pathways, gas cleaning technologies, and fuel synthesis processes).
The linear correlation of the data for the liquid fuel production plants has a lower coefficient of determination (R 2 ) with a value of 0.29. This was expected, as these technologies presented global reaction yields below 50% and a wide variety of products that can be obtained. The literature reported gasifiers with capacities ranging from 4.8-393 MWth, using different types of biomass residues from wood, wood chips, forest residues/wood pellets/straws, and rice straws with associated FT processes; yields of synthetic fuels achieved between 16.5-53.5% [68][69][70][71]. In addition to the operating conditions and the nature of biomass wastes, the type of catalysts applied in the FT processes also have an im- The linear correlation of the data for the liquid fuel production plants has a lower coefficient of determination (R 2 ) with a value of 0.29. This was expected, as these technologies presented global reaction yields below 50% and a wide variety of products that can be obtained. The literature reported gasifiers with capacities ranging from 4.8-393 MW th , using different types of biomass residues from wood, wood chips, forest residues/wood pellets/straws, and rice straws with associated FT processes; yields of synthetic fuels achieved between 16.5-53.5% [68][69][70][71]. In addition to the operating conditions and the nature of biomass wastes, the type of catalysts applied in the FT processes also have an impact on the yields and the products distribution [26,[72][73][74].
Liquid biofuel facilities presented a higher decreasing trend in specific investments with time due to the higher slope of the regression line in absolute terms (933.29 k€/(t/y)). The reason for this occurrence was related to the weaker maturity and recent emergence of these technologies with a strong potential for implementation in a near future, contrary to what happens with electricity or CHP plants that are well established and more developed solutions. All correlations were valid between the years 2005-2016 (electricity plants), 1996-2018 (CHP plants), and 2002-2021 (liquid fuel plants), respectively, as all facilities were retrieved during these periods. Extrapolation beyond these ranges can be admissible, but with some margins of error in the calculated estimates.
Heat and SNG production facilities were not included in the regression study, since the number of points were not considered sufficient to obtain a more robust analysis for these cases (only four and two production units were identified in the survey, respectively). However, preliminary assumptions can be established for these two groups: the specific cost associated with heat production was the lowest among all plants (average of 859 k€/kW), while SNG synthesis is currently very expensive (average of 16,004 k€/(t/y)). Considering that SNG will be an attractive fuel source in Europe, and will complement biomethane production from anaerobic digestion plants, financial incentives and subsidies are required for further developments in SNG synthesis technology (presently with a TRL between 4-8), and to disseminate and decentralize the construction of similar plants in the future. Figure 3 illustrates the evolutionary trend of economies of scale (graphics of specific investment vs. output) associated with the different types of gasification facilities (electricity, CHP, and liquid biofuels). plants), 1996-2018 (CHP plants), and 2002-2021 (liquid fuel plants), respectively, as all facilities were retrieved during these periods. Extrapolation beyond these ranges can be admissible, but with some margins of error in the calculated estimates.
Heat and SNG production facilities were not included in the regression study, since the number of points were not considered sufficient to obtain a more robust analysis for these cases (only four and two production units were identified in the survey, respectively). However, preliminary assumptions can be established for these two groups: the specific cost associated with heat production was the lowest among all plants (average of 859 k€/kW), while SNG synthesis is currently very expensive (average of 16,004 k€/(t/y)). Considering that SNG will be an attractive fuel source in Europe, and will complement biomethane production from anaerobic digestion plants, financial incentives and subsidies are required for further developments in SNG synthesis technology (presently with a TRL between 4-8), and to disseminate and decentralize the construction of similar plants in the future. Figure 3 illustrates the evolutionary trend of economies of scale (graphics of specific investment vs. output) associated with the different types of gasification facilities (electricity, CHP, and liquid biofuels).  Higher specific investments were obtained for plants with lower product outputs, which was evidenced by the distribution of points, particularly for the CHP and liquid biofuel plants. Exponential correlations presented a better fit for these two latter cases, with coefficients of determination between 0.3-0.7. This demonstrates the decreasing effect of specific investment, with output as the main rule in the economy of scale observed in gasification plants. However, facilities based on electricity production exhibited randomly distributed points, which complicated the establishment of a precise exponential correlation (R 2 = 0.0002) and the definition of a trend that rules the economy of scale. Anyway, the deployment of electricity plants is presently a less sustainable option due to the lower efficiency for energy extraction (typically less than 40%) [75]. The economic attractiveness and competitiveness of these plants became low in recent years, as evidenced by the lack of information in the survey since 2016 (see Figure 2).
In the specific case of CHP plants, the two isolated points located on the right-hand side of the middle graphic in Figure 3 correspond to gasification plants located in Finland. In this country, there seems to be a trend to implement large-scale gasification to produce district heating and fuel gas for the pulp and paper industry [44]. Research and development (R&D) on gasification was initiated in the late 1970s, aiming to decrease the dependence of the Finnish economy on imported oil. Throughout the 1980s, continuous governmental support in R&D focused on syngas applications was conducted, including the construction of a gasification plant for heat production [76]. These R&D efforts have established Finland as a major player in gasification technologies and services, offering solutions to meet the needs of various power and process industry sectors. Finland has bet on the modification of existing boilers or industrial kilns to be integrated with new gasification plants, which may achieve several hundreds of megawatts in output size. Additionally, existing fuel systems can be left as operational in parallel or for backup, some of which admit fossil fuels. As a result, Finnish gasification plants presented lower specific investment high outputs for CHP.

Conclusions
To compete with fossil-based technologies, large-scale gasification installations still require significant technological development, supporting economic subsidies and incentives, and efficient operational strategies. The mathematical regression analysis performed in this paper showed that specific investments tend to decrease over the years, particularly for gasification plants dedicated to producing electricity, CHP, and liquid biofuels. The latter group presented the highest decreasing trend, mainly due to the lower technological maturity, the recent emergence and interest in the production of biofuels, and global policies pressing for the adoption of carbon-neutral solutions. Economies of scale were more prevalent for CHP and liquid biofuel plants, evidencing the decrease of specific investments with product output through a downward exponential pattern. SNG production plants showed specific costs that were almost comparable to those of liquid biofuels. However, the consumption of these fuels, as well as their economic interest, was expected to increase with further technological developments and optimization. On the other hand, gasification plants producing only electricity presented a lower attractiveness for deployment in recent years.
These results, along with the variability of gasification technologies (e.g., specific gasifier design) and producer gas cleaning systems employed in large-scale gasification plants show that the technology is not mature, and still has to find its niche in the market. This uncertainty is the main cause of the lack of confidence from investors, delaying this technology's commercial maturity as a cost-efficient and reliable operation has yet to be fully demonstrated in practice. Nevertheless, this study offers several perspectives to boost the stakeholders' confidence in large-scale gasification plants. Data on the costs and expenses are useful to highlight areas where technological innovation can improve and reduce costs, allowing better decision-making, cost optimization, and improved project planning. However, full access to information on previous gasification plants is required to optimize these technologies and help with the development and operation of future plants. Learning effects from past endeavors are critical to making more informed choices about which final products from gasification to invest in and whether they are economically viable. Indeed, as gasification technologies continue to evolve and mature, it will be increasingly important for the technology to find its role in the transition to a more sustainable energy system and focus on high-value final products and specific industrial applications.