Life Cycle Costing and Eco-E ﬃ ciency Assessment of Fuel Production by Coprocessing Biomass in Crude Oil Reﬁneries

: Biobased liquid fuels are becoming an attractive alternative to replace, totally or partially, fossil ones in the medium term, mainly in aviation and long-distance transportation. In this regard, coprocessing biomass-derived feedstocks in conventional oil reﬁneries might facilitate the transition from the current fossil-based transport to a biobased one. This article addresses the economic and environmental feasibility of such a coprocessing strategy. The biomass-based feedstocks considered include bio-oil and char from the fast pyrolysis of lignocellulosic biomass, which are coprocessed in ﬂuid catalytic cracking (FCC), hydrocracking, and / or cogasiﬁcation units. The assessment was based on the standardized concept of eco-e ﬃ ciency, which relates the environmental and economic performances of a system following a life-cycle approach. Data from a complete simulation of the reﬁnery process, from raw materials to products, were used to perform a life cycle costing and eco-e ﬃ ciency assessment of alternative conﬁgurations of the coprocessing strategy, which were benchmarked against the conventional fossil reﬁnery system. Among other relevant results, the eco-e ﬃ ciency related to the system’s carbon footprint was found to improve when considering coprocessing in the hydrocracking unit, while coprocessing in FCC generally worsens the eco-e ﬃ ciency score. Overall, it is concluded that coprocessing biomass-based feedstock in conventional crude oil reﬁneries could be an eco-e ﬃ cient energy solution, which requires a careful choice of the units where biofeedstock is fed.


Introduction
The increasing global energy demand and the progressive depletion, supply uncertainty, and environmental issues of fossil fuels have led to a growing interest in alternative and renewable energy sources [1]. Regardless of the expected upsurge in electromobility [2,3], the use of liquid fuels in transport will remain important in the medium term [4,5] since subsectors such as long-distance transportation and aviation cannot yet be effectively powered by electricity. In this sense, liquid biofuels would arise as the most straightforward alternative to fossil fuels, contributing to the global objectives of greenhouse gas (GHG) emission savings [6,7] without requiring a significant transformation of the existing infrastructure and vehicle fleets. However, the realization of a full biomass-to-fuel concept is still far off due to the huge demand of fuels, the relatively low maturity of the technologies involved, and their high capital and operating costs [8]. In the short-to-medium term, a realistic scenario could rely on the concept of coprocessing, especially for the production of drop-in fuels [9,10]. This concept mainly refers to the introduction of biomass-derived feedstock, in addition to conventional fossil

Economic Component
Life cycle costing (LCC) is a methodology for the analysis of the total cost of a system along its entire life cycle. Net present value (NPV) is among the most common life-cycle economic indicators. It represents the difference between the present value of cash inflows and the present value of cash outflows over the lifetime of the system. In order to calculate the NPV of each of the four case studies, the following steps were addressed: • Cost estimation for standard equipment through size dimensioning and well-established correlations.

•
Cost estimation for specific equipment through literature correlations and rescaling. • Estimation of direct, indirect, and other costs to calculate the total investment cost (TIC). These costs were estimated as a function of the cost of equipment. • Estimation of annual variable costs.

•
Evaluation of annual cash flows over lifetime and NPV calculation. Equations for cost estimation from the literature usually involve different currencies and years. In this regard, all monetary values were converted into €2019. Spain was assumed as the reference location for the estimation of other costs, for example, feedstock, electricity, services, and land. The industrial price index (IPRI) and USD/€ exchange rates from the Spanish National Statistics Institute [58] were used to express data in €2019. As done in the LCA study of coprocessing schemes in conventional refineries [44], four case studies were investigated to explore the feasibility of different combinations of biomass feedstock coprocessing in terms of eco-efficiency:

•
Case 1: This is the base case, where the refinery only processes petroleum crude (100 Mbbl/day). Angolan CLOV (Cravo-Lirio-Orquidea-Violeta oilfields) was considered, which is an intermediate-to-heavy sweet crude that may represent the future of refining according to the trend towards deep conversion from heavy crudes [44]. • Case 2: The refinery coprocesses crude oil (100 Mbbl/day) and HDO-oil in the FCC unit, and char in the cogasification section. HDO-oil accounts for 20 wt% of the riser feed (value reported as the maximum for cofeeding [52,53]). HDO-oil and char are produced in a dedicated pyrolysis plant from poplar biomass, and the amount of char corresponds to that coproduced along with the bio-oil in the pyrolysis plant [54]. • Case 3: The refinery coprocesses crude oil (100 Mbbl/day) and HDO-oil in the HC unit, and char in the cogasification section. As in Case 2, the amount of HDO-oil corresponds to 20 wt% of the hydrocracker feed and the amount of char is that coproduced with the bio-oil.
• Case 4: It represents a combination of Cases 2 and 3, increasing the amount of HDO-oil coprocessed in the refinery. Crude oil (100 Mbbl/day) is fed into the refinery together with HDO-oil in the FCC and HC units and char in the cogasification section. The amount of HDO-oil corresponds to 20 wt% of the riser feed plus 20 wt% of the hydrocracker feed. The amount of char corresponds to that coproduced with the bio-oil in the pyrolysis section.
The validated models and process simulation of these coprocessing cases were directly retrieved from previous works [17,43,44], where further details can be found, and used to obtain key data to perform the eco-efficiency assessment. In fact, the environmental component of the eco-efficiency assessment was directly based on the LCA results from [44], whereas the economic component was specifically addressed in this article along with the joint economic-environmental interpretation in terms of eco-efficiency. For the life-cycle evaluations, a cradle-to-gate approach was followed, covering from crude oil extraction and biomass cultivation to fuel production at the refinery. Most of the inventory data were obtained from process simulation, while additional inventory data were taken from Iribarren et al. [55] for HDO-oil and char as well as from well-established databases [56]. According to the original LCA study [44], the environmental component of the study includes six life-cycle indicators evaluated with the CML method (Institute of Environmental Sciences of Leiden University [57]): abiotic depletion of elements (ADPe), abiotic depletion of fossil fuels (ADPf), global warming (GWP), ozone layer depletion (ODP), acidification (AP), and eutrophication (EP). ADPe is related to the extraction of mineral resources and expressed in kg Sb eq, while ADPf is associated with the extraction of fossil fuels and expressed in energy units (e.g., kJ). ODP refers to stratospheric ozone depletion and is expressed in kg CFC-11 eq. AP, which is expressed in kg SO 2 eq, is related to the emission of acidifying substances to the air, while EP, which is expressed in kg PO 4 3− eq, refers to nutrification because of emissions of nutrients to air, water, and soil. GWP, expressed in kg CO 2 eq, is associated with greenhouse gas emissions to the air over a 100-year time horizon. In this respect, it should be noted that CO 2 uptake during biomass growth was quantified at the biomass plantation stage, thus avoiding the need for a distinction between the biogenic and non-biogenic origin of subsequent emissions [44]. Finally, the economic and eco-efficiency components of the study are detailed in Sections 2.2 and 2.3, respectively.

Economic Component
Life cycle costing (LCC) is a methodology for the analysis of the total cost of a system along its entire life cycle. Net present value (NPV) is among the most common life-cycle economic indicators. It represents the difference between the present value of cash inflows and the present value of cash outflows over the lifetime of the system. In order to calculate the NPV of each of the four case studies, the following steps were addressed:

•
Cost estimation for standard equipment through size dimensioning and well-established correlations.

•
Cost estimation for specific equipment through literature correlations and rescaling.

•
Estimation of direct, indirect, and other costs to calculate the total investment cost (TIC). These costs were estimated as a function of the cost of equipment.

•
Estimation of annual variable costs.

•
Evaluation of annual cash flows over lifetime and NPV calculation.
Equations for cost estimation from the literature usually involve different currencies and years. In this regard, all monetary values were converted into € 2019 . Spain was assumed as the reference location for the estimation of other costs, for example, feedstock, electricity, services, and land. The industrial price index (IPRI) and USD/€ exchange rates from the Spanish National Statistics Institute [58] were used to express data in € 2019 . Cost estimation for standard equipment was mainly based on the principal dimensioning and design parameters from the simulation. On the other hand, some estimations were made by rescaling from data reported for similar equipment, assuming a Williams scaling exponent of 0.7. Table 1 summarizes the cost estimation method used for general and specific equipment. Table 1. Cost estimation method for general and specific equipment.

Equipment Cost Estimation Method Comments
Vessels (flash separators, storage tanks, distillation columns, and some reactors)

HDS (hydrodesulfurization)
Correlated from [59] Included: catalyst initial load, product fractionation, complete preheating, reaction, hydrogen circulation facilities, heat exchangers  TIC involves the sum of the design, construction, and installation costs of the system. It is composed of ISBL (inside battery limits), OSBL (outside battery limits), contingencies, and EPC (engineering, procurement, and construction) costs [65], which were calculated as a function of the total purchased equipment cost (TPEC) as shown in Table 2. ISBL investment represents the purchasing and installation costs of all the equipment of the process. It includes materials, catalysts, engineering, construction, and supervision costs. On the other hand, OSBL investment represents costs associated with general services, interconnections, and commissioning. Moreover, contingencies represent likely variations in the investment estimation, while EPC costs are those estimated for crude distillation unit (CDU), vacuum distillation unit (VDU), FCC, HC, coking, hydrodesulfurization (HDS), pyrolysis and Claus units as final installed ones according to Table 1. Finally, some installed units involve the duty to pay royalties, and thus paid-up royalties were also considered as a cost contributing to TIC [59]. Table 2. Method for the total investment cost (TIC) calculation. TPEC: total purchased equipment cost; ISBL: inside battery limits; OSBL: outside battery limits; EPC: engineering, procurement, and construction.

Estimation of Annual Variable Costs
The operation of the refinery involves costs related to the consumption of feedstock, general services, pyrolysis plant operation, and others. In this sense, the main annual variable costs of the system are those detailed in Table 3, which include: • Materials: crude oil, natural gas, process water, monoethanolamine (aq.), oxygen, air, and catalyst replacement. It should be noted that the biomass consumed in the pyrolysis plant was not included in this group but within the pyrolysis costs. • General services: also known as utilities, including cooling water, heating steams, and electricity. • Pyrolysis costs: biomass consumption, electricity, waste disposal, catalysts, and cooling water according to Peters [54].

•
Other costs: staff, depreciation, insurance, and running royalties. Staff was assumed to be 300 people in the refinery, and 15 people in the pyrolysis plant (assuming a 5% increment in the original staff), with a mean gross salary of 40,000 €/year. Linear depreciation over 15 years was considered (6.67% of TIC each year). Insurance was considered to be 1% of TIC. Running royalties were considered for FCC, HC, and HDS according to [59].

Net Present Value Calculation
The net present value (NPV) is the difference between the present value of cash inflows and the present value of outflows over a period of time. This economic indicator represents the profitability and economic potential of an investment, taking into account inflation and discount rates, annual variable costs, and inflows from selling products. It was calculated using Equation (1): where C t is the net cash flow in the year t, r is the discount rate, and T stands for the total number of years assumed for the project investment. Selling prices (without taxes) of products were assumed to be 450 €/t for propane and butane; 0.39, 0.30, and 0.40 €/l for gasoline, kerosene, and diesel, respectively; and 550 €/t for hydrogen [43]. Other general assumptions in the LCC study were 8000 annual operating hours, 3 years of construction, and 30 years of operation, 10% discount rate, and 1% linear inflation.

Eco-Efficiency Framework
The eco-efficiency indicator (or eco-efficiency score) was calculated according to Equation (2), using the selected life-cycle economic indicator (NPV) in the numerator, monetizing the system's functional value, and a life-cycle environmental indicator (ADPe, ADPf, GWP, ODP, AP, or EP) in the denominator. This definition of the system's eco-efficiency means that the most favorable scores should involve a high NPV and a low impact (under the specific environmental indicator considered). This definition of eco-efficiency is in line with the standardized concept [46] as well as with other related works [45,50,68].
where EE i,j represents the eco-efficiency indicator for the case study i (i.e., 1, 2, 3, or 4) and the life-cycle environmental indicator j (ADPe, ADPf, GWP, ODP, AP, or EP for the whole lifetime of the refinery). Furthermore, the benchmarking of each case study against the base case (i.e., case study 1) was performed through the ratio of the corresponding eco-efficiency scores. This ratio, known as factor-X according to [46], quantifies the relative level of eco-efficiency improvement or decline with respect to the conventional refinery (Equation (3)): where FX i,j represents the factor-X of the case study i for the environmental indicator j.

Cost of Standard and Specific Equipment and Total Investment Cost
The costs of standard and specific equipment were estimated following the methodology detailed in Section 2.2.1. Figure 2 shows the breakdown of costs by relevant section of the refinery. When compared to the base case (case study 1, i.e., conventional refinery without biofeedstock coprocessing), the introduction of HDO-oil in the refinery (case studies 2-4) increases the cost of HC (cases 3 and 4) and FCC (cases 2 and 4) and adds the cost of the pyrolysis plant. The contribution of these three sections means approximately half of the equipment costs in all the coprocessing cases. The rest of equipment remains similar, only showing slight changes due to capacity increments.

Eco-Efficiency Framework
The eco-efficiency indicator (or eco-efficiency score) was calculated according to Equation 2, using the selected life-cycle economic indicator (NPV) in the numerator, monetizing the system's functional value, and a life-cycle environmental indicator (ADPe, ADPf, GWP, ODP, AP, or EP) in the denominator. This definition of the system's eco-efficiency means that the most favorable scores should involve a high NPV and a low impact (under the specific environmental indicator considered). This definition of eco-efficiency is in line with the standardized concept [46] as well as with other related works [45,50,68].
where EEi,j represents the eco-efficiency indicator for the case study i (i.e., 1, 2, 3, or 4) and the lifecycle environmental indicator j (ADPe, ADPf, GWP, ODP, AP, or EP for the whole lifetime of the refinery). Furthermore, the benchmarking of each case study against the base case (i.e., case study 1) was performed through the ratio of the corresponding eco-efficiency scores. This ratio, known as factor-X according to [46], quantifies the relative level of eco-efficiency improvement or decline with respect to the conventional refinery (Equation 3): where FXi,j represents the factor-X of the case study i for the environmental indicator j.

Cost of Standard and Specific Equipment and Total Investment Cost
The costs of standard and specific equipment were estimated following the methodology detailed in Section 2.2.1. Figure 2 shows the breakdown of costs by relevant section of the refinery. When compared to the base case (case study 1, i.e., conventional refinery without biofeedstock coprocessing), the introduction of HDO-oil in the refinery (case studies 2-4) increases the cost of HC (cases 3 and 4) and FCC (cases 2 and 4) and adds the cost of the pyrolysis plant. The contribution of these three sections means approximately half of the equipment costs in all the coprocessing cases. The rest of equipment remains similar, only showing slight changes due to capacity increments.   As a consequence of the increase in the cost of equipment, and according to the methodology detailed in Section 2.2.2, the implementation of coprocessing involves an increased TIC (Table 4). This increase with respect to the base case is +20%, +21%, and +35% for cases 2, 3, and 4, respectively. TIC also increases when expressed per installed capacity (MW and MWh annual ), mainly due to the erection of the pyrolysis plant. When compared to the base case (24.17 €/MWh annual ), coprocessing adds 3.21, 3.71, and 5.17 € to the TIC per annual MWh of products in cases 2, 3, and 4, respectively.

Annual Variable Costs and Inflows
Annual variable (operating) costs account for 1521, 1609, 1598, and 1675 MM€ for cases 1, 2, 3, and 4, respectively. Figure 3 shows the contribution of each variable cost per MWh of product. It should be noted that these costs refer to a normalized year, while inflation was considered for cash-flow calculation in the specific years. Furthermore, although catalyst replacement in some reactors (gasifier, tar reformer, water-gas shift (WGS)) occurs in different years, the value considered in the analysis was annualized and added to the rest of the annual costs for catalyst replacement. Nevertheless, the replacement costs were considered in the expected replacement years for NPV calculation (Section 3.1.3).
As shown in Figure 3, crude oil, the main feedstock of the refinery, was identified as the main contributor to variable costs, representing 79-87% (1331 MM€/year and 22.9-25.4 €/MWh) depending on the case study. It is distantly followed by depreciation (8-10%) and electricity (around 1.5%). Hence, the fluctuation in the price of crude oil has an important impact on the system's economic performance. Even though the absolute annual costs increase due to coprocessing, annual unit costs slightly decrease (Figure 3): Case 4 shows the lowest annual unit cost (28.77 €/MWh), followed by case 2 (28.89 €/MWh) and case 3 (29.06 €/MWh). The relatively low price of the biomass feedstock and, consequently, the low cost of the pyrolysis plant operation, in addition to the change in the fuel yields of the refinery, are behind this finding. Thus, the costs associated with the increase in amortization due to the increased capacity of the refinery and the operation of the pyrolysis plant are offset. Energies 2019, 12, x FOR PEER REVIEW 11 of 18 Regarding the inflows of the refinery, Table 5 presents the economic values attributed to the products. In the conventional refinery (case 1), diesel represents 47.3% of the monetary incomes, followed by gasoline (26.4%) and kerosene (23.9%), whereas the remaining products only represent 2.4%. When compared to the base case, the coprocessing scheme in case 2 (characterized by the use of HDO-oil in FCC) involves an increase in gasoline (+8%) and kerosene (+57%) revenues, which respectively represent 27.6% and 36.6% of the total incomes in case 2. The monetary inflow associated with hydrogen also increases (+39%) due to char cogasification. However, diesel revenues decrease (-27%) as a consequence of the changes in product distribution. Alternatively, the coprocessing scheme in case 3 (characterized by the use of HDO-oil in hydrocracking) was found to lead to an increase in the incomes related to both gasoline (+42%) and diesel (+8%) with respect to the base case, but at the expense of reducing kerosene revenues (−27%). In this case, hydrogen production does not fully meet the system's hydrogen demand, and therefore hydrogen does not constitute an inflow but a net operating cost. Finally, case 4, as a combination of cases 2 and 3, shows increased revenues for gasoline (+42%) and kerosene (+45%) at the expense of reduced revenues for diesel (−25%), with gasoline, kerosene, and diesel representing 33.8%, 31.3%, and 32.2% of the total incomes, respectively.

. Net Present Value
In order to estimate the NPV, the cash flows over the refinery lifetime were calculated in each case study considering costs, inflows, inflation, and discount rate. The resultant NPVs are 3512, 3134, 4258, and 3776 MM€ for cases 1, 2, 3, and 4, respectively. Figure 4 shows the NPV evolution over the refinery lifetime. The NPV was found to follow the same trend in all the case studies considered. As stated in Section 2.2.4, a lifetime of 33 years was considered, with 3 years for design and construction and 30 years for operation. The following TIC payment distribution was considered during the first three years: year 1 for costs related to EPCs, TPEC, materials, engineering, services, interconnections, Regarding the inflows of the refinery, Table 5 presents the economic values attributed to the products. In the conventional refinery (case 1), diesel represents 47.3% of the monetary incomes, followed by gasoline (26.4%) and kerosene (23.9%), whereas the remaining products only represent 2.4%. When compared to the base case, the coprocessing scheme in case 2 (characterized by the use of HDO-oil in FCC) involves an increase in gasoline (+8%) and kerosene (+57%) revenues, which respectively represent 27.6% and 36.6% of the total incomes in case 2. The monetary inflow associated with hydrogen also increases (+39%) due to char cogasification. However, diesel revenues decrease (−27%) as a consequence of the changes in product distribution. Alternatively, the coprocessing scheme in case 3 (characterized by the use of HDO-oil in hydrocracking) was found to lead to an increase in the incomes related to both gasoline (+42%) and diesel (+8%) with respect to the base case, but at the expense of reducing kerosene revenues (−27%). In this case, hydrogen production does not fully meet the system's hydrogen demand, and therefore hydrogen does not constitute an inflow but a net operating cost. Finally, case 4, as a combination of cases 2 and 3, shows increased revenues for gasoline (+42%) and kerosene (+45%) at the expense of reduced revenues for diesel (−25%), with gasoline, kerosene, and diesel representing 33.8%, 31.3%, and 32.2% of the total incomes, respectively.

Net Present Value
In order to estimate the NPV, the cash flows over the refinery lifetime were calculated in each case study considering costs, inflows, inflation, and discount rate. The resultant NPVs are 3512, 3134, 4258, and 3776 MM€ for cases 1, 2, 3, and 4, respectively. Figure 4 shows the NPV evolution over the refinery lifetime. The NPV was found to follow the same trend in all the case studies considered. As stated in Section 2.2.4, a lifetime of 33 years was considered, with 3 years for design and construction and 30 years for operation. The following TIC payment distribution was considered during the first Energies 2019, 12, 4664 11 of 17 three years: year 1 for costs related to EPCs, TPEC, materials, engineering, services, interconnections, paid-up royalties, and 1/3 of contingencies; year 2 for 1/2 of construction and 1/3 of contingencies; and year 3 for commissioning, 1/2 of construction, and 1/3 of contingencies. Hence, as shown in Figure 4, the first years are associated with negative values, and afterwards, once operative, the system starts to recover the investment.
paid-up royalties, and 1/3 of contingencies; year 2 for 1/2 of construction and 1/3 of contingencies; and year 3 for commissioning, 1/2 of construction, and 1/3 of contingencies. Hence, as shown in Figure 4, the first years are associated with negative values, and afterwards, once operative, the system starts to recover the investment.
Regarding the effect of coprocessing with respect to the base case, case 2 (use of HDO-oil in FCC) was found to lead to a decrease in the profit (−11%). On the other hand, case 3 (use of HDO-oil in hydrocracking) results in a 21% NPV increase. In this case, despite the costs related to the pyrolysis plant and other additional costs such as catalyst replacement, the enhanced amount and distribution of products leads to significantly high inflows. Finally, case 4 shows an intermediate behavior, with a 7% NPV increase in year 33.

LCC Summary
The analysis of TIC, variable costs, and NPV proved that coprocessing could be economically feasible. Nevertheless, coprocessing can be performed under different layouts and, therefore, different consequences compared to a conventional refinery. Coprocessing in FCC (case 2) involves an increase in the investment, mainly related to the FCC unit and the addition of the pyrolysis plant. Consequently, the operational costs associated with the pyrolysis plant, FCC catalyst replacement, and services grow. Nevertheless, the operating unit cost (per MWh of produced fuel) decreases since the production rate increases. Product revenues also increase due to the higher production (mainly gasoline and kerosene). However, the NPV of case 2 result is lower than that of the conventional refinery (case 1), implying less profit throughout the operation of the process.
Coprocessing in hydrocracking (case 3) also increases the investment cost because of the HC unit and the pyrolysis plant, as well as the operating costs due to hydrogen consumption, HC catalyst replacement, services, and the pyrolysis plant. On the other hand, the rise in gasoline and diesel production involves an increase in inflows. In fact, the NPV of case 3 result is higher than that of the conventional refinery, which means an enhancement of the profit on the investment.
Coprocessing in both FCC and HC (case 4) shows an intermediate behavior between cases 2 and 3. It involves a growth of the investment, closely linked to the pyrolysis plant and the FCC and HC units, as well as of the operating costs related to catalyst replacement, services, and hydrogen consumption. Due to the product distribution achieved, gasoline and kerosene inflows increase, while the diesel inflow decreases. The NPV of this case is higher than that of the base case, but lower than that of case 3. Regarding the effect of coprocessing with respect to the base case, case 2 (use of HDO-oil in FCC) was found to lead to a decrease in the profit (−11%). On the other hand, case 3 (use of HDO-oil in hydrocracking) results in a 21% NPV increase. In this case, despite the costs related to the pyrolysis plant and other additional costs such as catalyst replacement, the enhanced amount and distribution of products leads to significantly high inflows. Finally, case 4 shows an intermediate behavior, with a 7% NPV increase in year 33.

LCC Summary
The analysis of TIC, variable costs, and NPV proved that coprocessing could be economically feasible. Nevertheless, coprocessing can be performed under different layouts and, therefore, different consequences compared to a conventional refinery. Coprocessing in FCC (case 2) involves an increase in the investment, mainly related to the FCC unit and the addition of the pyrolysis plant. Consequently, the operational costs associated with the pyrolysis plant, FCC catalyst replacement, and services grow. Nevertheless, the operating unit cost (per MWh of produced fuel) decreases since the production rate increases. Product revenues also increase due to the higher production (mainly gasoline and kerosene). However, the NPV of case 2 result is lower than that of the conventional refinery (case 1), implying less profit throughout the operation of the process.
Coprocessing in hydrocracking (case 3) also increases the investment cost because of the HC unit and the pyrolysis plant, as well as the operating costs due to hydrogen consumption, HC catalyst replacement, services, and the pyrolysis plant. On the other hand, the rise in gasoline and diesel production involves an increase in inflows. In fact, the NPV of case 3 result is higher than that of the conventional refinery, which means an enhancement of the profit on the investment.
Coprocessing in both FCC and HC (case 4) shows an intermediate behavior between cases 2 and 3. It involves a growth of the investment, closely linked to the pyrolysis plant and the FCC and HC units, as well as of the operating costs related to catalyst replacement, services, and hydrogen consumption. Due to the product distribution achieved, gasoline and kerosene inflows increase, while the diesel inflow decreases. The NPV of this case is higher than that of the base case, but lower than that of case 3.
It is important to remark that changes in the crude oil selected and/or in the quality of the coprocessed HDO-oil and char, strongly dependent on biomass composition and pyrolysis conditions, could significantly affect relevant aspects such as product distribution, and thus economic and environmental results. However, regardless of specific implications, the conclusion on the potential feasibility of coprocessing is not altered, given the validity of the data used in the study.
Finally, it should be noted that no economic penalty or externality was assumed according to the origin of the fuels (fossil or biobased). If taxes were implemented by policy-makers, for example, on fossil greenhouse gas emissions, coprocessing could, to a certain extent, contribute to keeping the existing refineries profitable.

Eco-Efficiency Results
Based on the NPV results (Section 3.1.3) as well as on the LCA results retrieved from [44], the eco-efficiency scores of each case study were calculated for each environmental indicator according to Equation (2). The corresponding results are presented in Table 6. The higher the scores in each category, the better the eco-efficiency performance achieved. Except for the ADPe-related eco-efficiency, where case 1 involves the highest score, the most favorable eco-efficiency scores were found to be associated with case studies coprocessing biomass-based feedstock. In particular, four of the six highest eco-efficiency scores refer to case 3, while case 4 involves the most favorable result for the carbon footprint-related eco-efficiency. A straightforward identification of the most eco-efficient case study is not possible due to the dependence on the specific life-cycle environmental indicator considered. Given the common difficulty in understanding the dimensions and units of the eco-efficiency indicators, the factor-X calculation (Equation (3)) was used since it facilitates the report of eco-efficiency results and the benchmarking of the different case studies against the reference case (i.e., case 1) [46,50]. Factor-X values above 1 indicate an improvement in eco-efficiency with respect to the conventional refinery, whereas values below 1 point to a decline in eco-efficiency.
As shown in Figure 5, the coprocessing of HDO-oil in FCC (case 2) was found to involve a generalized decline in eco-efficiency when compared to the base case, which is closely linked to the reduced NPV. On the other hand, coprocessing in HC (case 3) was found to lead to an improvement in eco-efficiency for all the environmental categories considered, except for ADPe. For instance, coprocessing biomass-based feedstock in hydrocracking shows a 32% improvement in the carbon footprint-related eco-efficiency. The favorable (i.e., generally eco-efficient) behavior of case 3 is linked to the enhanced NPV, which keeps the favorable ADPf, GWP, and ODP results of case 3 while counterbalancing its environmental deterioration in terms of AP and EP (but not sufficiently to overcome the environmental decline in ADPe).

Conclusions
This article used the LCC methodology and the standardized eco-efficiency concept to discuss the feasibility of coprocessing biomass-based feedstock in conventional petroleum refineries. From the LCC results, the economic feasibility of coprocessing was proven. In particular, coprocessing in hydrocracking and cogasification units was found to significantly improve the economic performance of the refinery. In contrast, coprocessing in FCC and cogasification involves a reduction in the net present value of the refinery. In between, coprocessing in FCC, hydrocracking, and cogasification units involve a moderate increase in the net present value of the refinery, supporting the effect of coprocessing in hydrocracking over the effect of coprocessing in FCC.
The eco-efficiency assessment showed that coprocessing in hydrocracking and cogasification units generally improves the eco-efficiency of the refinery, for example, 32% improvement in the carbon footprint-related eco-efficiency score. However, opposite findings arose when coprocessing in FCC, while the eco-efficiency of coprocessing in FCC, hydrocracking, and cogasification units was found to be highly dependent on the specific life-cycle environmental indicator considered. Overall, it is concluded that coprocessing biomass-based feedstock in conventional crude oil refineries could be an eco-efficient energy solution, which requires a careful choice of the units where biofeedstock is fed.
Author Contributions: P.L.C. performed the economic assessment; P.L.C. and D.I. performed the environmental and eco-efficiency assessment; all authors conceived the study, analyzed the data, and contributed to writing the article.  Finally, since case 4 was defined as a combination of cases 2 and 3, it shows an eco-efficiency improvement for three environmental indicators (ADPf, GWP, and ODP), but an eco-efficiency decline for the remaining environmental indicators (ADPe, AP, and EP). In other words, the moderate NPV increase when coprocessing biobased feedstock in both FCC and HC does not compensate for the environmental penalty in several categories.

Conclusions
This article used the LCC methodology and the standardized eco-efficiency concept to discuss the feasibility of coprocessing biomass-based feedstock in conventional petroleum refineries. From the LCC results, the economic feasibility of coprocessing was proven. In particular, coprocessing in hydrocracking and cogasification units was found to significantly improve the economic performance of the refinery. In contrast, coprocessing in FCC and cogasification involves a reduction in the net present value of the refinery. In between, coprocessing in FCC, hydrocracking, and cogasification units involve a moderate increase in the net present value of the refinery, supporting the effect of coprocessing in hydrocracking over the effect of coprocessing in FCC.
The eco-efficiency assessment showed that coprocessing in hydrocracking and cogasification units generally improves the eco-efficiency of the refinery, for example, 32% improvement in the carbon footprint-related eco-efficiency score. However, opposite findings arose when coprocessing in FCC, while the eco-efficiency of coprocessing in FCC, hydrocracking, and cogasification units was found to be highly dependent on the specific life-cycle environmental indicator considered. Overall, it is concluded that coprocessing biomass-based feedstock in conventional crude oil refineries could be an eco-efficient energy solution, which requires a careful choice of the units where biofeedstock is fed.
Author Contributions: P.L.C. performed the economic assessment; P.L.C. and D.I. performed the environmental and eco-efficiency assessment; all authors conceived the study, analyzed the data, and contributed to writing the article.