Integration of Process Modelling and Life Cycle Inventory. Case Study: i-Pentane Purification Process from Naphtha. L. Kulay^^\ L. Jimenez^^\ F. Castells^^\ R.
European Symposium on Computer Aided Process Engineering - 13 A. Kraslawski and I. Turunen (Editors) © 2003 Elsevier Science B.V. All rights reserved.
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Integration of Process Modelling and Life Cycle Inventory. Case Study: i-Pentane Purification Process from Naphtha L. Kulay^^\ L. Jimenez^^\ F. Castells^^\ R. Banares-Alcantara^^^ and G. A. Silva^*^ (1) Chem. Eng. Dept., University of Sao Paulo, Av. Prof. Luciano Gualberto tr.3 380, 05508-900 Sao Paulo, Brazil. E-mail: {luiz.kulay, gil.silva}@poli.usp.br (2) Chem. Eng. Dept., University Rovira i Virgili, Av. Paisos Catalans 26,43007 Tarragona, Spain. E-mail: {Ijimenez, fcastell, rbanares}@etseq.urv.es
Abstract A framework for the assessment of the environmental damage generated by a process chain and based on a life cycle approach is proposed. To implement it, a methodology based on the integration of process modelling and environmental damage assessment that considers all the processes of the life cycle was developed. This integration is achieved through an eco-matrix formed by eco-vectors containing the most relevant environmental loads. To verify the methodology, a case study on the deisopentaniser plant of REPSOL-YPF (Tarragona, Spain) has been carried out. The environmental profile of the alternative scenarios is improved when co-generation and heat recovery are considered.
1. Introduction Modern society demands a constant improvement on the quality of life. One of the actions of the administration is to guarantee a better environment. In this context, chemical process industries suffer an increasing pressure to operate cleaner processes. To achieve this goal, environmental aspects and the impact of emissions have to be considered in the design of any project using one of the procedures already developed [ISO, 1997]. Life Cycle Assessment (LCA) is the most common tool for the evaluation of the environmental impact of any industrial activity. The LCA is chain-oriented procedure that considers all aspects related to a product during its life cycle: from the extraction of the different raw materials to its final disposal as a waste, including its manufacture and use. According to ISO 14040 [ISO, 1997], LCA consists of four steps: goal and scope definition, inventory analysis, impact assessment and interpretation. The LCA identifies and quantifies the consumption of material and energy resources and the releases to air, water and soil based upon the Life Cycle Inventory (LCI). The procedure as it is applied to chemical processes has been previously described by Aelion et al. (1997). The results from the LCI are computed in terms of environmental impacts, which allow the establishment of the environmental profile of the process. For environmental assessment the application of potential impacts is restricted to the estimation of global impacts. For example, the amount of CO2 released is used as an indicator of climate change due to its global warming potential. One kilogram of CO2 generated by an industrial process in any of the different stages of a product life cycle
186 contributes equally to the climate change. However, this is not the case for sitedependant impacts, such as the potential impact of acidification measured as H"^ release. Unfortunately, the LCA does not accommodate for site-specific information of different process emissions. To include it, weighting factors across the system boundaries have to be selected, a task which is beyond the objective of this work [Sonneman et al., 2000]. For this reason, a methodology that includes environmental aspects in the analysis of processes has been developed. Applying the LCA perspective to different scenarios for electricity generation and steam production provides key information to decision makers at a managerial and/or political level.
2. Methodology This section describes a proposed methodology to evaluate the environmental impact of a chemical industrial process chain in the most accurate way possible. It includes a procedure to compute the LCI based on the concept of eco-vectors [Sonneman et al., 2000]. Each process stream (feed, product, intermediate or waste) has an associated ecovector whose elements are expressed as Environmental Loads (EL, e.g. SO2, NOx) per functional unit (ton of main product). All input eco-vectors, corresponding to material or energy streams, have to be distributed among the output streams of the process (or subsystem). In this sense, a balance of each EL of the eco-vector can be stated similarly to the mass-balance (inputi = outputi + generation,). This is the reason why all output streams are labelled as products or emissions. The eco-vector has negative elements for the pollutants contained in streams that are emissions and/or waste. Figure 1 illustrates these ideas for an example of a chain of three processes that produces a unique product. The proposed procedure associates inventory data with specific environmental impacts and helps to understand the effect of those impacts in human health, natural resources and the ecosystem.
3. Problem Statement The methodology has been applied to the debutaniser and depentaniser columns of a naphtha mixture processed in the REPSOL-YPF refinery (Tarragona, Spain). The process PFD is shown in Figure 2. The first column is fed with a naphtha stream rich in C4 (= 28.3 tonh"^). This unit is a debutaniser and removes n-butane and lighter components (= 0.50 tonh"*). Perfect separation is not achieved since capital investment must be balanced against operating costs to arrive at an acceptable economic payout. As a result, it is more convenient to think of the debutaniser as having a cut point between n-butane and i-pentane, which is removed as top product from the second column (= 16.3 tonh'^). The intermediate naphtha input stream (C5 rich-naphtha = 71.5 tonh'^) comes from another plant in the same refinery. Production under design conditions is 83.0 ton•h'^ Proper understanding of recovery in both columns can improve refinery economics, due to the downstream effects of light components. The plant has four heat exchangers, and two of them (HX-1 and HX-3) recover process heat. Both condensers are air cooled, and thus plant utilities are electricity and steam. The production of these two utilities consumes additional natural resources and generates additional releases to the environment, and thus they were included.
4. Results The LCI was computed using process simulation as a support tool. This approach is appropriate for both, the design of new processes and the optimisation of existing ones. The use of process simulators to obtain the LCI guarantees a robust approach that
187 allows LCA to exploit their advantages in terms of availability of information, and reduces the uncertainty associated with data in the early phases of design. However, we can expect that on a long-term perspective, relative and uncertain values are valid when comparing among alternatives. The models for the naphtha plant, the electricity generation, the steam production and the heat recovery system were developed using Hysys.Plant®, and were validated using plant data. To build accurate models for all alternatives is not practical, and thus the models were reused for the different alternatives considered. The key simulation results were transferred to a spreadsheet (Microsoft® Excel), through macros programmed in Visual Basic™. Despite the fact that emissions were produced at different locations (e.g. those related to its extraction, transport and refining), the eco-vector has a unique value for each stream, i.e. it does not considers site-dependant impacts. The eco-vectors associated to all the inputs and outputs of the process are computed per ton of product (i-pentane). The aspects included in the eco-vector were divided into two categories: > Generated waste: in air (CO2, SO2, NO^, and VOC; estimated as fugitive emissions), wastewater (chemical oxygen demand, COD) and solids wastes (particulate matter and solids).
Raw material
Process I
(^^A + \
J RM
Process 3
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+
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NO,
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)1
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Figure 1. Life cycle inventory analysis according to the eco-vector principle. Econd D6-C4
HX_1
I
Econd De-iC5
De-C4
Figure 2. Simplified PFD of the REPSOL-YPF plant. >
Consumption of natural resources: depletion of fossil fuels (fuel-oil, gas-oil, carbon, natural gas and oil), consumption of electricity and water. The plant consumes medium-pressure steam, while electricity generation and steam
188 production may use high or low pressure steam. The eco-vectors that correspond to these streams are also considered. The environmental loads of the process inputs were retrieved from the ETH Report [Frischknecht et al., 1996] and the TEAM™ database [TEAM, 1998]. The use of different scenarios allows the comparison among alternatives. The scenarios were chosen based on the source of steam and the generation of electricity (Table 1). Three of them focus on the environmental impacts of the original process (scenarios VI, VII and VIII) where changes related to the production of steam were compared. All other cases compare alternatives for a possible future implementation, e.g. those considering co-generation to produce electricity. For each one of the scenarios the eco-vector was divided into the three different processes: steam production, electricity generation and naphtha plant. As an example, the eco-vectors of scenario III are shown in Table 2. The results indicate that: • To reduce the CO2 and the BOD we have to focus on the production of steam. For scenarios VI, VII and VIII the electricity generation has also a certain impact (^ 3 to 29%). • To decrease the SO2 changes should be made in the production of steam and/or in the generation of electricity (Figure 3). The scenarios that include cogeneration radically minimise this value. • NOx, VOC and solid wastes are produced completely by the generation of electricity. • H2O consumption is mainly due to steam production. As expected, heat integration allows the reduction of this amount by 91%. Results (Figure 4a) show that scenarios VII, VIII and, to some extent, scenario V concentrate most of the consumption of fossil fuels, while the best alternatives in terms of water consumption are scenarios III and IV. As expected, heat recovery has a great impact on the results of scenarios III, IV, VI and, to a lesser extent, scenario VIII. If cases III and VIII are compared, the impact of co-generation on ELs is easily detected. Concerning the consumption of natural resources, the best alternative is scenario III (cogeneration, downgrading of steam and heat recovery). In terms of atmospheric releases (Figure 4b), the best options are scenarios III and IV. On the contrary, the most significant impacts were observed in scenarios VII and VIII. Nevertheless, the releases of NOx, SO2 (scenario V) and VOC's (scenario VIII) must be highlighted. Table 1. Main characteristics of the scenarios considered.
I II III IV V VI VII VIII
Electricity generation Co-generation Co-generation Co-generation Co-generation Expansion of steam in a turbine Spanish energy grid Spanish energy grid Spanish energy grid
Steam production Generation of steam Expansion of steam Generation + heat recovery Expansion + heat recovery Fuel oil & fuel gas burning Fuel oil & fuel gas burning + heat recovery Fuel oil & fuel gas burning Generation + heat recovery
189 Table 2. Eco-vectors for scenario 111.
Natural gas/kg Water/kg Electricity/kW High pressure steam/kg Medium pressure steamykg Electricity/kW High pressure steam/kg Medium pressure steam/kg COz/kg SOa/kg NO,/kg VOC/kg Particulate matter/mg DQO/mg
• Steam production
Steam Electricity production generation Inputs 0. 1.410"' 0. 1.5-10' 0. 0. 1.8-10-' 0. 0. 0. Outputs 3.410"" 0. 1.810"' 0. 0. 1.810"' Atmospheric emissions ^ 3.7-10"' 0. 0. 0. 0. 0. 0. 0. 1.5-10" 1.510" 0. Liquid efluents 3.9-10"' 0.
Plant operation
Total /ton i-Cs
0. 1.510"' 3.4-10"^ 0. 1.810"'
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0. 0. 0.
3.4-10"'' 1.8-10"' 1.810"'
0. 0. 0. 0. 0.
3.7-10" 0. 0. 0. 1.510 1.510"
0.
3.910"'
I Electricity generation
Figure 3. Comparison of the SO2 generation, (a) Scenario VI; (b) Scenario VII; (c) Scenario VIII. With respect to wastewater generation, there are a few scenarios with low impact (III, IV, VI and VIII) while the rest exhibit very similar values. If all aspects are analysed simultaneously, the best alternatives are scenarios III and IV, while the worst one is scenario VII. It is noteworthy to say that all environmental loads considered in the ecovector have to be balanced to reach a compromise, as their impacts in the ecosystem and human health differ widely. Also, note that some of the impacts are local (e.g. steam production), while others are distributed in different regions (e.g. extraction, external electricity generation) even though the LCA approach does not allow to differentiate among them.
190
I
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IV
V
VI
B Natural gas
H Fuel oil
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a Water
D Electricity
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in
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V
VI
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Figures 4a and 4b. Percentage of the impact on different Environmental Loads for each scenario, (a) Raw materials consumed; (b) Emissions.
5. Conclusions Significant progress in the integration of environmental aspects with technical and economic criteria has been achieved to date, although limitations still exist due to the uncertainty of the available data. The proposed methodology shows that the use of process simulators to obtain the LCI guarantees a robust approach. Furthermore, the methodology provides valuable information to compare alternatives for future implementation by assessing and preventing environmental impacts. This study will be extended with the application of models to predict the damage on human health, natural resources and the ecosystem. For the case study two different types of environmental profile can be identified (scenarios I-IV and scenarios V-VIII). The use of co-generation to produce electricity decreases the total damage, as its relative impact is lower than the one resulting from the use of the Spanish electricity grid.
6. References Aelion, V., Castells, F. and Veroutis, A., 1995, Life cycle inventory analysis of chemical processes. Environ. Prog., 14 (3), 193-195. Frischknecht, R., Bollens., U., Bosshart, S. and Ciot, M., 1996, ETH report, Zurich, Switzerland. ISO 14040, 1997, Environmental management. Life cycle assessment. Principles and framework, ISO, Geneve, Switzerland. Sonnemann, G.W., Schuhmacher, M. and Castells, F., 2000, Framework for environmental assessment of an industrial process chain, J. Haz. Mat., 77, 9 1 106. TEAM®, 1998, Ecobilan Group, Paris, France.
7. Acknowledgements One of the authors (L. Kulay) wishes to thank CAPES (Ministry of Education of Brazil) for the financial support. We also acknowledge the cooperation of REPSOL-YPF, and Hyprotech (now part of Aspentech) for the use of an academic license of Hysys.Plant®.
