DOI: 10.3303/CET2291066 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Paper Received: 16 February 2022; Revised: 7 April 2022; Accepted: 18 May 2022 
Please cite this article as: Tacchini E., Tugnoli A., Cozzani V., 2022, Key Performance Indicators for Implementing Sustainability and 
Environmental Protection in Early Process Design Activities, Chemical Engineering Transactions, 91, 391-396  DOI:10.3303/CET2291066 
  

 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 91, 2022 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Valerio Cozzani, Bruno Fabiano, Genserik Reniers 

Copyright © 2022, AIDIC Servizi S.r.l. 

ISBN 978-88-95608-89-1; ISSN 2283-9216 

Key Performance Indicators for Implementing Sustainability 

and Environmental Protection in Early Process Design 

Activities 

Eugenio Tacchini, Alessandro Tugnoli*, Valerio Cozzani 

LISES – Dipartimento di Ingegneria Civile, Chimica, Ambientale e dei Materiali, Alma Mater Studiorum – Università di 

Bologna, via Terracini n.28, 40131 Bologna, Italy. 

a.tugnoli@unibo.it 

The adoption of a sustainability perspective in chemical industry shall start from the early phases of process 

design (e.g. conceptual design, technology selection, process development) where the key drivers in the 

environmental, economical, and hazard fingerprint of a process are defined. These phases also allow the 

opportunities for the lower cost of design change. A sound support of design activities requires quantitative 

tools, allowing for the assessment of the sustainability profile of a process, the identification of possible 

improvements and supporting informed tradeoffs. 

Though several tools for process development were proposed in last decades, application is still limited in the 

current practice because of issues on data requirement, indicator definition and customization to specific 

application needs (e.g. PFD definition in design of polypropylene production plants). 

This study focuses on the application to the early process design of environmental and exergy Key Performance 

Indicators (KPIs) to support sustainability-oriented design activities. It was tailored on the specific industrial 

application of polypropylene production plants. The choice of a specific sector allowed customization of the 

method, promoting ease of application and allowing the assessment of multiple scenarios (e.g. sensitivity on 

material and energy supply strategies, comparison of different technologies). Results obtained draw up 

sustainable guidelines to improve design activities within the scope in a lifecycle perspective. 

1. Introduction 

In the last decades, society has been asking to the chemical and process industry a growing commitment toward 

the development of sustainable and safer production processes. Sustainability and green engineering have 

become, beside conventional economic and technical aspects, a key driver in the development of new 

production processes.  

Early process design (e.g. conceptual design, technology selection, process development) is a key phase in the 

adoption of the sustainability perspective, as higher degrees of freedom for change are possible at low marginal 

costs (Sugiyama et al., 2008). Though conceptual guidelines like Green Chemistry principles or Green 

Engineering principles provide a direction for the actions, a sound support of design activities requires 

quantitative tools. These allow for the assessment of the sustainability profile of a process, the identification of 

possible improvements and the evaluation of the effectiveness of alternative design choices (Dal Pozzo et al., 

2017). Moreover, they can support informed tradeoffs in case of conflicting issues. 

The development quantitative tools for the sustainability analysis of process schemes received significant 

attention in the last two decades. Metrics based on material and energy flow analysis (Brinkmann et al., 2010), 

exergy balances (Ren and Toniolo, 2021), midpoint environmental indicators (Brunet et al., 2012), endpoint 

environmental indicators (Goedkoop and Spriensma, 2001), ecological indexes (Tugnoli et al., 2008), and 

combinations of indicators (Huijbregts et al., 2017) were proposed. These metrics were adopted for application 

in the assessment of several kind of chemical and petrochemical processes and technologies. However, the 

use of these tools for process development is still limited in the current practice. Critical points concern the large 

amount of data required in relations to the timeframe and the limited information available in early design phases, 

391



the identification of a specific but yet complete set of indicators for the assessment, and the absence of tools 

specifically tailored to the required application needs (e.g. specific phase of the design lifecycle and industrial 

sector). 

Considering, for example, the case of polypropylene production (a sector currently producing worldwide 130 

Mt/y of polypropylene with a growth forecast of 192 Mt/y for 2030 (Fernández, 2021)), a literature review reveals 

that no approach specifically designed for environmental impacts of alternative technologies during early design 

phases is proposed. Applicable current literature on process analysis focuses mainly on technical and efficiency 

issues (Touloupides et al., 2010) or studied quality control mechanism (Ohshima and Tanigaki, 2000). Life Cycle 

Assessment (LCA) studies on polypropylene, like the one published periodically by PlasticsEurope 

(PlasticsEurope, 2016), lack of the detail needed to discriminate the effect of process design choices, and focus 

mainly on factors as nature of raw materials and polymer waste recycling. Moreover, the metrics used in these 

LCA studied are not directly suitable for application as design support tools in polymerization process 

development. In facts, LCA metrics are suited to the analysis of the whole environmental performance of the 

lifecycle system, which is only one of the aspects of concern in process design: they are not, alone, able to 

analyse the way energy and material are used within the specific process sections and the margins of 

improvement still available, given the physical (e.g. thermodynamics) constraints, which would require different 

metrics (e.g. exergy analysis).  

In this context, the presented methodology is developed in a lifecycle perspective supporting technology design 

activities of chemical processes. The methodology is aimed at the quantification of environmental and exergy 

Key Performance Indicators (KPIs) of a well-defined system. In this perspective, different scopes for emissions 

along the lifecycle of the reference can be adopted. Reference system includes a primary process (e.g. 

polymerization plant) and all the required activities for energy and material supply and waste treatment. 

Appropriate level of detail is allowed in the definition of required input data for each contribution considered. In 

facts, inputs/outputs more closely related to the primary process design activities were assessed with greater 

level of detail than environmental pressures originated by lifecycle processes out of the control. Databases of 

generic average data for these lifecycle processes were developed to support the final user. Exergy analysis is 

implemented alongside the use of environmental indicators, with the aim to pinpoint the sources of stronger 

inefficiencies in the use of energy and the opportunities of improvement. The development of a process flow 

diagram for a polypropylene production plant was used for demonstration of the proposed methodology, proving 

the applicability and the typical outcomes. 

2. Methodology 

2.1 General overview of the method  

The developed methodology is specifically aimed at the quantification of environmental impacts and energy 

efficiency indicators to be used for supporting Front End Engineering Design (FEED) activities of chemical 

industries, with particular attention to polyolefin polymerization processes. In particular the method supports the 

evaluation of the sustainability profile of a process scheme, the identification of critical points of improvement, 

the screening design of alternatives and the prediction of the operative impacts. The approach implements the 

concept of Life Cycle Thinking at different levels to compute indicators as a function of chemical processes input 

and output. 

The process object of the design is assumed as Primary process of the assessment. Auxiliary technologies 

(Background processes) are required for raw material and energy supply: these are generally out of the scope 

of design, but must be included in the analysis as they affect the overall environmental performance of the 

system (i.e. Lifecyle perspective). 

A certain level of detail (compatible with the information available in the FEED design phase) is required to 

characterize energy and material consumption of the Primary process. Background processes are instead out 

of the control of designer, and generic datasets that measure the average technologies performances can be 

used. Figure 1 briefly illustrates the method scope and boundaries. Background datasets can characterize 

specific site-location technology or average performances. In this perspective, a reference unit (e.g. production 

potentiality) is required to be defined as comparative basis for the characterization of environmental and 

exergetic performances of the system. Several environmental problematics are analyzed (e.g. emissions of toxic 

substances, green house gas emissions, depletion of not renewable resources) (Tugnoli et al., 2011). Site 

specific information about Background processes allow to generate specific case-study applications of a single 

Primary process. Decision regarding site-location and technologies involved in the reference scenario allow to 

monitor the overall lifecycle perspective of the system. Moreover, the application of exergy balance to the 

reference scheme allows to evaluate the energy management inside the system. Results obtained can highlight 

strength and weaknesses of process decisions and draw up guidelines to drive design activities. In this direction, 

comparative assessment can be carried out and generate informed trade-offs in case of conflicting issues. In 

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this perspective, the analysis is intended to be a support tool for early design activities (e.g. conceptual design 

of Primary process, process comparison). 

 

 

Figure 1: Conceptual definition of scope and boundaries in the application of the proposed method 

2.2 Calculation of environmental indicators 

The basic set of environmental indicators to be used in the method is proposed in Table 1. These derive from 

midpoint indicators typically adopted in LCA studies. The basic set of environmental indicators can be adapted 

in accordance with the specific goal of the considered application. Air, water and solid can be selected as target 

for environmental analysis. Reference substances are adopted to characterize environmental results in 

accordance with LCA technique (ISO, 2006) . Literature average datasets are used to simulate background 

processes. Characterization factors (𝐶𝐹𝑖) from the CML-2002 method (Huijbregts, 1999)  are introduced to 

convert specific emissions into their reference substance as shown in Eq(1). 

𝐼𝑗 = ∑
𝑚𝑖
𝑃

𝑛,𝑠𝑢𝑠𝑏𝑎𝑛𝑐𝑒𝑠

𝑖=1

∙ 𝐶𝐹𝑖 (1) 

Where mi is the mass flow rate of the i-th substance exchanged with the environment by the studied system, P 

is the reference potentiality of the system and CF is the characterization factor for substance i. 

Table 1: List of environmental indicators. 

Indicator ID [𝐼𝑗 ] Indicator name Example of substances 

(*reference)  

 Unit of measure  

ADI,e Abiotic Depletion Indicator (elements) Sb*, Al, Pb, Ti, Na  [kgSb,eq/ref. unit.]  

ADI,f Abiotic Depletion Indicator (fossil fuels) Fossil fuel*, natural gas, 

coal, oil crude 

 [MJ/ref. unit.]  

GWI Global Warming Indicator CO2*, CH4    [kg CO2,eq/ref. unit.]  

AI Acidification Indicator SOx, (SO2)*, NOx, NH3, HF  [kg SO2,eq/ref. unit.]  

EI Eutrophication Indicator 𝑃𝑂4
3− *, NOx, NH3  [kg 𝑃𝑂4

3−,eq/ref. unit.]  

POCI Photochemical Ozone Creation 

Indicator 

C2H4 *, VOCs, NOx   [kgEthylene,eq/ref. 

unit.] 

 

HTI Human Toxicity Indicator 1,4 – Dichlorobenzene*, 

Benzene, Acrylonitrile, 

Arsenic 

 [kg 1,4 – 

Dichlorobenzene,eq/

ref. unit.] 

 

Star (*) marks the reference substance used in definition of CF. 

 

The mass flows in Eq(1) shall be calculated taking into account all the emissions over the “environmental 

boundary” of Figure 1. Given the additive nature of the indicators, the calculation with reference to the emissions 

from specific processes within the boundary allows to monitor the entire polymer production chain from 

environmental standpoint. In this direction, the effect of utilization of different sources for material and energy 

supply can be quantified. Furthermore, comparative assessment can promote and drive design decisions 

through the quantification of specific set of indicators. This versatility allows to evaluate the effect of specific 

background processes (e.g spanning from non-renewable to renewable technologies for electricity and steam 

generation). 

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2.3 Calculation of exergy indicators 

Exergy analysis is based on the simultaneous application of the First and the Second Thermodynamic Laws. It 

is able to assess the way energy is used in operations, overcoming the limitation of energy balances based only 

on the First Thermodynamic Law, that do not provide information about the degradation of energy or material 

sources during a process use. Exergy of a system (e.g. process stream) is assumed equal to zero at 

environmental equilibrium of pressure and temperature (dead state, e.g. Polymeric outlet stream). 

Exergy value of material input and output is calculated by Eq(2). Exergy destruction indicator is derived by the 

application of exergy balance Eq(3) to the reference system. This approach allows to characterize the exergy 

lost due to the irreversibility of chemical and physical transformations inside the system.  

𝐸𝑋𝐼𝑁/𝑂𝑈𝑇 = ∑ �̇�𝑖,𝐼𝑁 /𝑂𝑈𝑇 [�̂�𝑖 − �̂�𝑖,0 − 𝑇0(�̂�𝑖 − �̂�𝑖,0)]

𝑁𝑐𝑜𝑚𝑝

𝑖=1

 (2) 

𝐸𝑥, 𝑑 =

∑ (𝐸𝑋𝐼𝑁𝑖
𝑂𝑈𝑇𝑖

⁄
 + �̇�) 𝑆𝑡𝑟𝑒𝑎𝑚𝑠𝑖  

𝑃
 

(3) 

Where H is the specific enthalpy of a material stream, T is the temperature of the material stream, s is the 

specific entropy of the material stream, m is the mass flowrate of the material stream and W is the energy 

flowrate of an electric stream. 

Exergy balance is typically applied to a single process boundary aimed at the determination of an index of 

irreversibility due to chemical and physical operations within the framework. Furthermore, the application of 

exergy balance to single unit allows to determinate the specific energy efficiency index of the involved 

operations. In this context, the quantification of single unit exergy destruction terms allows to monitor the 

efficiency of each single operation inside the boundary pinpointing potential for improvement. In a lifecycle 

perceptive the minimization of exergy destruction term is an index of the sustainability of the process.  The 

definition of exergy destruction term in a comparative assessment is a key driver for decision making supporting 

design activities (e.g. technology selection, improvement study).  

3. Case-study  

3.1 Set up of the case 

The method is demonstrated by the application to the design of a polypropylene production plant. Plant 

potentiality is assumed to be 400 kt/y of polymeric pellet.  

Polypropylene (PP) is a thermoplastic polymer involved in a wide number of applications in packaging, textiles, 

stationery, containers, and components in the manufactory industry. New plants are continuously built to full fill 

the ever-increasing plastic demand. Despite the fossil origin of the feedstocks currently used in production of 

PP, outlooks of the future of the market agree on the expectation that production will increase and new plants 

will be built in the future. 

The Primary process, in this case study, is represented by the polymerization technology which convert 

propylene to polypropylene. Main Background processes are:  

• Monomer production technologies (Crude oil extraction, Naphtha reforming and Steam Cracker) 

• Electricity generation process 

• Steam production process 

 

Use and disposal of the polymer are out of the scope of current analysis as they do not depend on the design 

choices of concern. Reference process scheme to be analyzed is derived by Polypropylene EcoProfile 

(PlasticsEurope, 2016). Primary process is based on available information on raw material and energy average 

consumption of Spheripol technology (Axens, 2005) and extruders (Abeykoon et al., 2014). 

In this case, 1 kg of polypropylene (PP) with its pellet shape is adopted as reference unit. Indicators are 

expressed per kg of PP. 

The goal of the study is the identification of critical points inside the polymer production chain. In this framework, 

two nested boundaries are introduced. The first boundary (Environmental boundary) includes all the principal 

process operations (polymerization, monomer production, electricity generation and steam production). This 

boundary allows to obtain the environmental impact indicators associated to the production of 1 kg of PP. The 

sensitivity of environmental results regarding raw material and energetic polymerization input can be performed 

considering different technologies for material and energy supply. In this context, three scenarios are considered 

in order to measure the effect of different utilization of electricity sources (renewable and non-renewable). A 

second boundary (Polymerization boundary) is introduced tailored to the polymerization process. This boundary 

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allows to carry out exergy balance and define exergy destruction term associated to polymerization activities. 

Performances of background processes are obtained by literature datasets (European Commision, 2022). A 

schematic representation of reference layout is given in Figure 2. 

 

 

Figure 2: Reference adopted scheme for the application of the presented method 

3.2 Results and discussion 

For sake of brevity only two indicators will be presented in the following: one environmental indicator (GWI) and 

the Exergy destruction indicator (Ex,d). Global Warming Indicator (GWI) was selected as representative of the 

environmental performance of the system as strongly related to the energy and material efficiency of the 

process. 

The principal results obtained are reported in Table 2. Eq(1) introduced in section 2.2 allows to estimate the 

carbon footprint of the Environmental boundary. Different scenarios are analyzed for plant location, considering 

Italy (Scenario 1) and US (Scenario 2); this affects mainly the supply of electricity and steam to the studied 

system. In addiction, the effect of the use of exclusively renewable resource for electricity supply is evaluated 

(Scenario 3). Eq(3) of section 2.3 applied to the Polymerization boundary allows to obtain the exergy destruction 

indicator.  

Table 2: Global Warming Indicator (GWI) and Exergy destruction indicators (Ex,d) of the reference 

polypropylene production chain 

Indicators Scenario 1 Scenario 2 Scenario 3 

GWI [kgCO2/kgPP] 1,520 1,556 1,437 

Ex,d [kJ/kgPP] 1218,3 1218,3 1218,3 

 

Results are representative of an average situation, therefore specific plant data and information about process 

configurations can slightly modify the indicators. The effect of site-location dependence on polymer chain is 

appreciated by the comparison between Scenario 1 and 2. The GWI increases of about 2,6% due to the use of 

a US electricity grid mix and steam production technology. Regarding Scenario 3, a more sustainable results is 

achieved for the utilization of renewable resource. The GWI indicator is reduced of about 5,5%. Considering an 

average polymerization plant with a capability of 400 ktPP/y the reduction of GWI moving from Scenario 1 to 

Scenario 3 can be quantified in the reduction of approximately 33,4 ktCO2/y. Furthermore, considering single 

processes within the environmental boundary, monomer production activities are responsible of approximately 

90% of the indicator. In this direction, other environmental benefits can be achieved for the utilization of 

renewable resources for monomer supply.  

The analysis of the Exergy destruction indicator shows that results are not affected by site-location and 

technologies for supply of raw material and energy. In addiction, Ex,d allows to recognize the principal source 

of energy consumption inside a reference system. In particular, reference adopted extruder is responsible of 

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about 52% of the Ex,d. This result shows that more than half of the exergy destructed by polymerization activities 

is located in the final extrusion section.  

4. Conclusions 

This work presents a sustainability-oriented design support methodology applied to a polypropylene production. 

Key Performance Indicators (KPI) are used to measure the environmental impact profile and the energy use 

efficiency. In the presented case study, Global Warming Indicator (GWI) and Exergy destruction indicator (Ex,d) 

are calculated to characterize polymerization strategies and auxiliary processes. Results obtained can support 

design activities pinpointing inefficient operations and potential for improvements. Regarding GWI, the principal 

source of greenhouse gasses is the monomer production, suggesting that maximisation of process yield is a 

priority from this point of view. Environmental benefits can be obtained by the utilization of renewable resources 

(e.g. electricity generation process). Regarding exergy results, extrusion area is the principal source of exergy 

destruction term due to the high quantity of electricity consumed. In this perspective, it can be reduced by 

improving the design of this section (e.g. using waste heat or green energy). 

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