(586d) Identifying Process Modifications Via Life Cycle Thinking - Insight from Life Cycle Assessment Versus Thermodynamic Methods

The goal of the current work is to develop a general methodology for identifying and quantifying opportunities for improvement both at the process and life cycle scales. Use of this methodology should result in a renewed emphasis upon using life cycle thinking to drive innovation in the design stages, instead of only evaluating after the fact.

Life cycle assessments (LCA) in the literature often focus on the emissions, impacts, and gross energy use of products or processes. This can lead to a general negativity toward new products and ideas. While it is important to evaluate impacts in all phases of the life cycle, it is possible to lose sight of the real goal of life cycle assessment. That goal should be one of improvement. Evaluating impacts and energy use should spur development toward more efficient design, not stifle it by merely pointing out flaws. The vast majority of published life cycle analyses overlook this idea of improvement, emphasizing the results without looking deeper into what could or should be done.

Traditional life cycle methodologies form the basis for improvement analysis, however from an engineering standpoint LCA has shortcomings. For instance, issues relating to the second law of thermodynamics are overlooked. For this reason, more thermodynamically rigorous methods have been considered. Combined first and second law methods involve calculating lost work or exergy loss. Exergy is defined as the maximum amount of useful work that can be obtained when a material stream is brought to equilibrium with the surroundings. This definition ultimately refers to gradients in not only temperature or pressure, but also concentration or chemical potential. Exergy gives a clearer view of the quality of resources than a first law energy analysis.

Potential for improvement is calculated in this study in terms of both gross losses and efficiencies. It is important to look at both values together to get the whole picture, because while a given unit may have a high efficiency, it could also represent the largest loss in the overall process. Alternatively, it may not be worth committing the resources to improve a unit with a low efficiency if it does not represent a large loss.

One case study considered in this study is a new process for producing titanium dioxide (TiO2) nanoparticles. This process was developed by Altair Nanotechnologies and is described in the literature. Eight major units and about thirty major flows were identified in the process. The primary feedstock for the process is ilmenite ore (FeTiO3), which is plentiful in many parts of the world. The ore is first digested with an excess of hydrochloric acid. The next three steps in the process are separation steps to remove the iron, chlorine, and remaining acid from the product stream. The three separation steps are crystallization/filtration, solvent extraction, and ion exchange. The acid and chloride ions are recycled back to the digestion unit through a pyrohydrolysis reaction and distillation step. Meanwhile, the titanium rich stream is reacted in the spray hydrolysis unit to produce hollow titanium dioxide particles. These particles are milled and finished to make the final product, anatase phase nanoparticles approximately 40 nm in diameter.

A life cycle assessment as well as full energy and exergy analyses were performed on this process to identify the areas with the highest potential for improvement. An exergy model was derived for the nanoparticle product using a general free energy model for nanocrystals available in the literature.

The impacts of the process were categorized and normalized by total world emissions. It was found that the spray hydrolysis step, which produces the titanium dioxide, represented the greatest environmental impacts due to the large amount of carbon dioxide released. The LCA and the energy analysis revealed that the largest first law energy losses were in the swing distillation step. The first law energy analysis also showed the crystallization/filtration step to have a very low efficiency, but not a very large energy loss.

The exergy analysis included second law losses related to entropy generation and the inequality of heat and work. Due to these differences, distillation was not identified as a top priority because most energy supplied to the distillation was in the form of heat. This result is to be expected because according to Carnot's heat engine, heat cannot be converted completely to useful work. It is also worth noting that the exergetic efficiency of the crystallization/filtration unit is around 82%, which shows that the low first law efficiency was the result of the low temperature of streams leaving the unit.

To summarize the case study, all three methods give us similar results in that they all direct us to improve spray hydrolysis. However, the energy analysis identifies distillation as the top priority, while exergy analysis disagrees, mostly due to the lower energy quality of high-pressure steam. Life cycle analysis shows spray hydrolysis to have the largest impact on global warming potential, but the suggested improvements would be much different from the thermodynamic methods. End of pipe solutions could be used to reduce carbon dioxide emissions or the use of different heat sources could be evaluated. In addition life cycle analysis encourages the careful isolation of all streams carrying hydrochloric acid. This would never be revealed by a thermodynamic method.

In conclusion, exergy analysis appears to yield all the information of a first law energy analysis along with information about quality of resources. However, depending on the initial goals of the evaluation, any one of these methods might be optimal. If you want a quick look at the energy flows and efficiencies, energy analysis might be enough. If you have more time and want a deeper thermodynamic understanding, you should use exergy analysis. And finally if your goals are to reduce the environmental impacts of your process, life cycle analysis is the best choice. It is expected that further case studies will reveal a general model for choosing an evaluation method for improvement analysis.

References

[1] Processing Titaniferous Ore to Titanium Dioxide Pigment (US patent 6,375,923; issued April 23, 2002).

[2] Processing Aqueous Titanium Chloride Solutions to Ultrafine Titanium Dioxide (US Patent 6,440,383; issued August 2, 2002).

[3] Processing Aqueous Titanium Solutions to Titanium Dioxide Pigment. (US Patent 6,548,039; issued April 15, 2003).

[5] D. Verhulst, B. Sabacky, T. Spitler and W. Duyvesteyn, ?The Altair TiO2 Pigment Process and its Extension to the Field of Nanomaterials?, CIM Bulletin, 95, 89-94 (2002).

[6] D. Verhulst, B. Sabacky, T. Spitler and J. Prochazka. ?New Developments in the Altair TiO2 Hydrochloride Pigment Process?, Hydrometallurgy 2003, Fifth International Conference in Honor of Professor Ian Ritchie, C.A. Young et al., Eds., TMS, Vancouver, B.C, 565-575 (2003).

[7] D. Verhulst, B. Sabacky, R. Marganski, B. Wang and D. Ellsworth. ?Optimization of the Critical Steps of the Altair Hydrochloride Pigment Process?, Sohn Symposium on Advanced Processing of Metals and Materials, F. Kongoli, Ed., TMS, San Diego, August 2006.

[8] D. Verhulst, B.J. Sabacky, J. Lang and D.K. Ellsworth. "Iron Control in the Altair Hydrochloride Pigment Process". Third International Symposium on Iron Control in Hydrometallurgy", The Metallurgical Society of CIM, Montreal, Oct. 2006.

[9] A. S. Barnard and P. Zapol, ?A model for the phase stability of arbitrary nanoparticles as a function of size and shape?, J. Chem. Phys., 121, 4276-4283 (2004).

[10] A. S. Barnard and L. A. Curtiss, ?Prediction of TiO2 nanoparticle phase and shape transitions controlled by surface chemistry?, Nano Letters 5, 1261-1266 (2005).