Computer simulation of energy use, greenhouse gas emissions, and costs for alternative methods of processing fluid milk.

Computer simulation is a useful tool for benchmarking electrical and fuel energy consumption and water use in a fluid milk plant. In this study, a computer simulation model of the fluid milk process based on high temperature, short time (HTST) pasteurization was extended to include models for processes for shelf-stable milk and extended shelf-life milk that may help prevent the loss or waste of milk that leads to increases in the greenhouse gas (GHG) emissions for fluid milk. The models were for UHT processing, crossflow microfiltration (MF) without HTST pasteurization, crossflow MF followed by HTST pasteurization (MF/HTST), crossflow MF/HTST with partial homogenization, and pulsed electric field (PEF) processing, and were incorporated into the existing model for the fluid milk process. Simulation trials were conducted assuming a production rate for the plants of 113.6 million liters of milk per year to produce only whole milk (3.25%) and 40% cream. Results showed that GHG emissions in the form of process-related CO2 emissions, defined as CO2 equivalents (e)/kg of raw milk processed (RMP), and specific energy consumptions (SEC) for electricity and natural gas use for the HTST process alone were 37.6g of CO2e/kg of RMP, 0.14 MJ/kg of RMP, and 0.13 MJ/kg of RMP, respectively. Emissions of CO2 and SEC for electricity and natural gas use were highest for the PEF process, with values of 99.1g of CO2e/kg of RMP, 0.44 MJ/kg of RMP, and 0.10 MJ/kg of RMP, respectively, and lowest for the UHT process at 31.4 g of CO2e/kg of RMP, 0.10 MJ/kg of RMP, and 0.17 MJ/kg of RMP. Estimated unit production costs associated with the various processes were lowest for the HTST process and MF/HTST with partial homogenization at $0.507/L and highest for the UHT process at $0.60/L. The increase in shelf life associated with the UHT and MF processes may eliminate some of the supply chain product and consumer losses and waste of milk and compensate for the small increases in GHG emissions or total SEC noted for these processes compared with HTST pasteurization alone. The water use calculated for the HTST and PEF processes were both 0.245 kg of water/kg of RMP. The highest water use was associated with the MF/HTST process, which required 0.333 kg of water/kg of RMP, with the additional water required for membrane cleaning. The simulation model is a benchmarking framework for current plant operations and a tool for evaluating the costs of process upgrades and new technologies that improve energy efficiency and water savings.

Computer simulation of energy use, greenhouse gas emissions, and process economics of the fluid milk process.

Energy-savings measures have been implemented in fluid milk plants to lower energy costs and the energy-related carbon dioxide (CO2) emissions. Although these measures have resulted in reductions in steam, electricity, compressed air, and refrigeration use of up to 30%, a benchmarking framework is necessary to examine the implementation of process-specific measures that would lower energy use, costs, and CO2 emissions even further. In this study, using information provided by the dairy industry and equipment vendors, a customizable model of the fluid milk process was developed for use in process design software to benchmark the electrical and fuel energy consumption and CO2 emissions of current processes. It may also be used to test the feasibility of new processing concepts to lower energy and CO2 emissions with calculation of new capital and operating costs. The accuracy of the model in predicting total energy usage of the entire fluid milk process and the pasteurization step was validated using available literature and industry energy data. Computer simulation of small (40.0 million L/yr), medium (113.6 million L/yr), and large (227.1 million L/yr) processing plants predicted the carbon footprint of milk, defined as grams of CO2 equivalents (CO2e) per kilogram of packaged milk, to within 5% of the value of 96 g of CO 2e/kg of packaged milk obtained in an industry-conducted life cycle assessment and also showed, in agreement with the same study, that plant size had no effect on the carbon footprint of milk but that larger plants were more cost effective in producing milk. Analysis of the pasteurization step showed that increasing the percentage regeneration of the pasteurizer from 90 to 96% would lower its thermal energy use by almost 60% and that implementation of partial homogenization would lower electrical energy use and CO2e emissions of homogenization by 82 and 5.4%, respectively. It was also demonstrated that implementation of steps to lower non-process-related electrical energy in the plant would be more effective in lowering energy use and CO2e emissions than fuel-related energy reductions. The model also predicts process-related water usage, but this portion of the model was not validated due to a lack of data. The simulator model can serve as a benchmarking framework for current plant operations and a tool to test cost-effective process upgrades or evaluate new technologies that improve the energy efficiency and lower the carbon footprint of milk processing plants.

Fermentation and costs of fuel ethanol from corn with Quick-Germ process.

The Quick-Germ process developed at the University of Illinois at Urbana-Champaign is a way to obtain corn oil, but with lower capital costs than the traditional wet-milling process. Quick-Germ has the potential to increase the coproduct credits and profitability of the existing dry-grind fuel ethanol process, but the fermentability of the corn remaining after oil recovery has not been tested. Therefore, a series of pilot scale (50 L) fermentations was carefully controlled and monitored with unique methods for standard inoculation and automatic sampling. It was found that the concentration of suspended solids was significantly reduced in the Quick-Germ fermentations. When compared at the same concentration of fermentable sugars, the fermentation rate and yield were not statistically different from controls. When Quick-Germ was integrated into a state-of-the-art dry-grind fuel ethanol process, computer simulation and cost models indicated savings of approx $0.01/L of ethanol ($0.04/gal) with the Quick-Germ process. Additional savings associated with the lower suspended solids could not be quantified and were not included. However, the savings are sensitive to the price of corn oil.

A cost analysis of encapsulated spray-dried milk fat.

Anhydrous butter oil or cream was encapsulated in all-purpose flour, modified cornstarch, or sucrose and then spray-dried. We estimated the processing cost for a plant designed to produce 57,000 kg/d (125,000 lbs/ d) of encapsulated milk fat powder. Powder with a 50% milk fat content could be produced for about $0.23/kg plus the cost of the butter oil or cream, the encapsulant selected, and the other ingredients. Spray-drying of milk fat improved ease of handling and reduced storage costs.

Dry-grind process for fuel ethanol by continuous fermentation and stripping.

Conversion of a high-solids saccharified corn mash to ethanol by continuous fermentation and stripping was successfully demonstrated in a pilot plant consuming 25 kg of corn per day. A mathematical model based on previous pilot plant results accurately predicts the specific growth rate obtained from these latest results. This model was incorporated into a simulation of a complete dry-grind corn-to-ethanol plant, and the cost of ethanol production was compared with that of a conventional process. The results indicate a savings of $0.03 per gallon of ethanol produced by the stripping process. The savings with stripping result from the capacity to ferment a more concentrated corn mash so there is less water to remove downstream.