Dataset for techno-economic analysis of catalytic hydrothermolysis pathway for jet fuel production

This detail the economics of Catalytic Hydrothermolysis (CH), an approve pathway for sustainable aviation fuel (SAF) production. Techno-economic analysis was conducted with the assumption of CH processing facility that process 832 metric tonnes per day of feedstock into renewable fuels such as SAF, gasoline and diesel. Economic data includes estimation of renewable fuel production plant cost such as capital and operating cost; cost benefit analysis model to predict the SAF or jet fuel price; regression models to evaluate the cost for co-product such as diesel and petroleum in relation to SAF price. Estimated SAF, gasoline and diesel cost for the feedstock such as carinata oil, soybean oil, yellow grease and brown grease feedstock is included in the data.


Specifications
Economics Specific subject area Techno-economic analysis (TEA) of a sustainable aviation fuel production pathway .  Type of data  Text,  Tables,  Figures, Excel Spreadsheet How data were acquired Data was acquired from secondary data sources including (i) techno-economic analysis studies on renewable fuel productions (ii) publicly available report on cost for utilities such as electricity, water and natural gas (iii) US refiner petroleum product price (iv) public report on feedstock price such as vegetable oil (carinata and soybean oil); yellow grease and brown grease price (iv) Experimental study on CH process (v) Employment cost index for total compensation for private industry workers by occupational group and industry (vi) TEA Evaluation model form the previous studies (vii) Plant design and economics for chemical engineers Data format Raw Analysed Parameters for data collection The model considered is a TEA of CH in the cost year 2017. Data required were equipment cost for three different processing that includes preconditioning unit, conversion unit and hydrotreating and fractionation unit; price of vegetable oil such as carinata oil and soybean oil; price of waste greases such as yellow grease and brown grease; price for petroleum-based fuel such as gasoline, diesel, and jet fuel; cost for the chemicals/catalyst; CH fuel yields; Gasoline, diesel and jet fuel density; green field fuel processing plant ratio factor based on equipment cost; operating labour cost. Description of data collection Equipment cost were estimated using literature data from the process with similar process conditions [ 1 , 2 ]. Historic price data for petroleum-based fuels such as gasoline, diesel, and jet fuel [3] . Cost of an oil seed processing plant for estimating carinata oil cost was adopted from the camelina oil seed processing study [4] . Soybean oil and yellow grease price were from U.S. State Department of Agriculture [5] . Equipment process conditions, CH process flow, fuel yield and fuel cuts for economic analysis were used from the CH experimental study [6][7][8] . Gasoline, diesel and jet fuel density were adopted from the technical review report on biodiesel conversion technologies [9] . Green field fluid processing plant ratio factor for estimating the capital cost based on the delivered equipment cost from Plant design and economics for chemical engineers [2] . Chemical plant operating labour cost from [10] . Data source location Primary data sources (resources for the secondary data used in this analysis): Patent and Experimental article for Catalytic Hydrothermolysis [ 6 , 7 ] US Average Annual Industrial Electricity and Natural gas rate [ 11 , 12 ] USDA oil crop and yellow grease cost [5] Review studies on the biofuel conversion pathways [9] Chemical Plant design and economics [ 2 , 10 , 13 ] Techno-economic analysis studies on renewable fuel productions [ 1 , 4 , 8 , 10 , 14 ] US Refiner Petroleum Product Prices by Sales, Sales for Resale [3] Employment Cost Index Historical Listing -Volume III National Compensation Survey,

Value of the Data
• The dataset provides detailed economic data for a chemical plant to perform economic assessment of CH SAF production pathway. The data includes equipment cost for individual processing units. Model evaluation is automated based on the feedstock chosen. • This dataset may be used in future studies and academic review on techno-economic analysis of SAF pathways, e.g. to estimate the fuel price for the conversion of different oil feedstock to jet fuel, adopting cost for processing units, evaluating co-product price in relation to jet fuel price by using regression analysis. • Cost benefit analysis is implemented in this TEA worksheet. The model worksheet can be reused to evaluate TEA with the change of delivered equipment cost and respective operating cost for any of SAF conversion pathway. Pilot scale and commercial scale production capacity can be conFig.d and calculate the minimum selling price of SAF for the scaled capacity.

Data Description
Secondary data from other sources and the primary data or the plant cost estimates used to build a TEA model of CH SAF pathway for the cost year 2017 is presented in this dataset. This dataset supports the original research on accessing the economic viability of the CH SAF pathway for commercial scale production of 832 metric ton per day. Table 1 provides the assumed economic parameters for the n th plant economic analysis. Table 2 provides the information on the Input parameters used for the TEA model. This includes the price of utilities such as Electricity, Natural gas, and water. Feedstock price per MT for Soybean oil, carinata oil, yellow grease, and brown grease. Table includes all the configurable data for the model.
Operation cost estimated for the model is detailed in the Tables 3, 4, 6 and 7 , this includes cost estimation for the utilities, chemical and catalyst, fixed operation cost for the plant for oneyear period.
Equipment cost estimation for the three processing units such as preconditioning, CH conversion and post refining step includes hydrotreating and distillation unit costs. Tables 8, 9, 10 and 11 details the estimated equipment cost based on the model scale for carinata oil feedstock. Processing waste grease feedstock such as brown grease or yellow grease do not include preconditioning cost.    Capital investment was estimated on the greenfield fluid processing ration factor from Plant design and Economics for chemical engineer hand book [2] . Estimated capital cost is presented in the Table 12 .
Regression over historic fuel price [3] to evaluate the cost of co-products such as gasoline and diesel in relation to jet fuel price.
Annual production quantity and the estimated jet fuel price per litre and regressed fuel price for diesel and gasoline based on equation in Fig. 1 is shown in the Table 13 below.
Estimated gasoline, diesel cost in relation with SAF minimum selling price for four selected feedstock such as Carinata oil, Soybean oil, Yellow grease and Brown grease is shown in Fig. 2 .

Experimental Design, Materials and Methods
The economic feasibility of a biofuel pathway depends on the combination of capital and raw material costs, availability of raw materials as well as other operational costs. Ratio factors were used to determine outside battery limits (OSBL) costs from inside battery limits (ISBL) equipment costs. ISBL equipment is integral to a specific process while OSBL equipment support the core process and include processes like steam generation, waste water treatment and buildings [2] . Equipment scale was estimated and used to scale the cost using the exponential correlation [ 1 , 2 ]. This cost was unified to 2017 dollars using the Chemical Engineering Plant Cost Index [18] . The ratio factor for a greenfield liquid processing plant was applied to the equipment costs, to estimate the direct costs and the fixed capital investment. The total capital investment (TCI) is the sum of the fixed capital investment (FCI) and the working capital. Working capital, which is used to cover operating costs when the facility is not able to cover expenses, is assumed to be 20% of the annual operating costs. Land cost is assumed to be 1.5% of the TCI [25] .
In the analysis, the production plant for CH pathway is assumed to depreciate in 7 years, following double declining balance to straight line, and the plant life is 20 years. The project is assumed to be 30% equity financed and 70% loan with loan term for 10 years. For the present cost analysis, the fixed capital investment is spread over 3 years at a rate of 8%, 60% and 32% respectively. A cost benefit analysis was used to evaluate the economic feasibility of the CH process by predicting the minimum selling price (MSP) of SAF. MSP per unit volume of SAF is defined as the price that has a net present value (NPV) of zero and nominal financial discount rate of 12.2%. We assume an inflation rate of 2% following the average inflation from 1997 to 2017. The inclusion of inflation in the economic analysis, which combines the real discount rate of 10% with inflation to determine the nominal discount rate of 12.2%.