Introduction
In the last few decades, the environmental impacts caused by human activities on the planet have severely intensified. Such impacts materialize as higher-than-normal average temperatures leading to critical climate alteration, damage of land and oceanic ecosystems, massive extinction of species, and drinking water shortage to name a few. In part, these impacts arise from the perturbation of the dynamic cycles of chemicals in the environment and the overshoot of the ecosystems’ natural capacity. For instance, the natural slow and fast carbon cycles can manage and recycle between 0.01 and 100 billion tons of carbon per year, respectively [1]. Humans currently consume about 9-billion-ton oil equivalent of coal and petroleum per year [2], thus seriously increasing the amount of carbon dioxide in the atmosphere. Clearly, this massive relocation of solid and liquid materials from the lithosphere to the atmosphere poses a major threat to the stability of the natural carbon cycles. Similarly, large-scale human activities (e.g. agriculture, industry, urbanization, energy usage) exert pressure on the natural cycles of soil nutrients (i.e. nitrogen, phosphorous, and sulfur) and water as well as on other eco-systemic flows. Furthermore, the integrity of entire ecosystems is being jeopardized by the environmental pollution caused by synthetic chemicals (e.g. halogenated molecules, pharmaceutical active compounds, polymers), nuclear materials, biologically active compounds (e.g. enzymes, hormones), and biological agents. In addition to the environmental impacts, and partially as their consequence, a variety of social issues are increasingly affecting communities around the world, such as poverty, inequality, unemployment, and reduced access to food and water. Clearly, all these issues are related to the fulfillment of basic human needs, which the United Nations recognizes as a goal to be achieved in the near future [3].
In general, the majority of impacts and issues mentioned earlier can be attributable to the development paradigm prevalent in the 19th and 20th centuries, which was decoupled from sustainability principles. Historically, human activities have been commonly assessed in light of the economic dimension whereas the environmental and social dimensions have been regarded as constraints, or merely as the monetary value of their benefits, or impacts. In this regard, sustainable development, or development that harmoniously integrates the economic, environmental, and social dimensions, is one of the major challenges of this century, and it should constitute a goal of paramount importance for the global industry. The achievement of this goal requires to rethink current engineering practices in light of these three dimensions, referred to as the triple bottom line (TBL), thereby leading to economic prosperity, environmental responsibility, and social development. In particular, the chemical industry, as one of the key players in the reduction of impacts derived from unconscious development, has been increasingly improving its efficiency regarding energy and material utilization as well as its environmental performance [4,5]. Thus, it is essential to include TBL considerations at every stage of chemical process design and engineering, from the very early conception stages to the end of life of production facilities, to maximize efficiency and increase sustainability [6]. In this respect, the following passages elaborate on the most current tools for the assessment of TBL dimensions and suitable metrics for decision making during chemical process and product design.
Sustainability assessment in chemical process design
Various methodologies have been proposed for assessing sustainability in designing chemical processes and products. In this regard, Table 1 presents a conceptual basis common to such methodologies in terms of the TBL dimensions, as well as a few instances of sustainability criteria and indicators that the methodologies deploy. The simplest assessment methodologies evaluate different indicators of each TBL dimension separately, and decision-making among process alternatives is performed by comparing each indicator via n-dimensional diagrams. This is the case of GREENSCOPE [7,8], the AIChE Sustainability Index [9], and IChemE Sustainable Development Progress Metrics [10]. Regardless of the dimensions involved, the incorporation of sustainability during process design is generally formulated as a multi-objective optimization problem. In solving this problem, a set of non-dominated process-design options are identified, beyond which it is not possible to reduce impacts in some dimensions without affecting others. Subsequently, decision makers select among the best options from the non-dominated set of solutions. Alternatively, other approaches aggregate the different dimensions into a single composite metric that combines a set of indicators from one or more dimensions via weighting factors, thus obtaining a single value describing the sustainable performance of each process alternative being assessed. In this case, identification of the desirable solution by optimizing the composite metric is generally straightforward. Typically, only the TBL dimensions are involved in the assessment; however, additional dimensions can be incorporated, such as technology, innovation, and political considerations [11,12].
Table 1. Conceptual basis for sustainability assessment in terms of TBL dimensions during chemical process design with some instances of criteria, indicators, and composite metrics
| Principles | Criteria | Indicators [17,18•,19••] | |
|---|---|---|---|
| Definition: Premises that define sustainability. | Definition:Measurable condition (qualitative or quantitative) that establishes the level of application of the principles. | Definition: A quantitative or qualitative parameter that can be assessed in light of a criterion. It is an objectively verifiable and unambiguous descriptor of the system. | |
| Economic Dimension | Chemical processes must be sustainable at both macroeconomic and microeconomic levels [13•]. | Level of influence of raw materials production, consumption, and prices (domestic and international) | Local annual production of raw materials per ton of product |
| Global consumption of raw materials per global consumption of product | |||
| Maximization of process profitability | Added value of a specific chemical route | ||
| Environmental Dimension | Chemical processes must ensure air, water, and soil quality [14]. | Fulfilling effluent specifications as defined by law | Biological and chemical oxygen demand of wastewater |
| Chemical processes should be designed to maximize mass, energy, space, and time efficiency [15]. | Minimization of the water consumed in the production process | Water used annually per ton of product | |
| Reduction of the use of energy | Energy consumed per ton of product | ||
| Chemical processes should promote the use of renewable resources [15]. | Incremental use of bio-based raw materials | Renewability of a specific chemical route | |
| Social Dimension | Chemical processes must be socially acceptable [13•] [16••]. | Contribution to local prosperity associated with the reduction of poverty | Weighted annual average of people in poverty |
| Chemical processes should use or generate substances of low or no toxicity to human health and the environment [15]. | Reduction of the toxicity of the substances involved in the chemical process | Human Toxicity Potential by Ingestion | |
Composite Metric: A qualitative or quantitative metric that characterizes a system and embeds two or three dimensions of sustainability, which is obtained by using the indicators of the dimensions being considered and suitable weighting factors. This aggregation permits to infer on the system’s relative sustainability. Instances of composite metrics are given below.
Pollution Balance (PB) [20]; Potential Environmental Impact (PEI) [21,22,23]; Sustainability Process Index (SPI) [24,25]; BASF Eco-efficiency [26]; Inherent Benign-ness Indicator (IBI) [27]; Socio-eco-efficiency analysis by the SEEBALANCE [28]; Sustainable Cumulative Index (SCI) [29•]; Sustainability Weighted Return on Investment Metric (SWROIM) [30•]; Safety and Sustainability Weighted Return of Investment Metric (SASWROIM) [31••]; Metric of Sustainability (MOS) [32••]; Green Net Value Added (GNVA) [33•]
The design and engineering of a process, be it chemical, physicochemical, or biochemical, involves stepwise stages of increasing complexity [34]. The process design starts from the identification of needs and the product that can satisfy them, for example, by using product-design methodologies. Then, the selection of a chemical route is fundamental to ensure a benign-by-design approach and a conscious incorporation of green chemistry principles [29•,35]. Subsequently, heuristic or superstructure-based process synthesis is deployed to obtain the irreducible architecture of the process capable of yielding the desired product. At the same time, incorporation of economic, health, safety, and environmental indicators can contribute to attain inherent sustainability [36]. Following this, process analysis, integration, and multi-criteria optimization (under TBL criteria) are carried out during the conceptual design stage [36]. Upon definition of the processing units and the corresponding mass and energy interconnections for the optimal operating conditions, basic and detail engineering define the specifications required for equipment procurement, commissioning, plant start-up and operation. After the plant enters operation, further optimization can be performed to enhance process performance with the possible involvement of retrofitting activities. Upon completion of the plant’s life cycle, shutdown and decommissioning activities take place, thus ending the process’ engineering.
Because of the complex nature of tasks involved in chemical process design and engineering, the incorporation of sustainability goals into the entire life cycle of the process requires the consideration of a multitude of interdisciplinary factors at various process stages with varied levels of detail. These factors must be considered in a systematic way by combining quantitative and qualitative methods for them to be effective as an objective decision-making tool during process design. In view of this, assessment of sustainability performance at the different stages of process design would require massive amounts of information. Traditionally, process design requires large amounts of data, such as the physicochemical properties of all the chemical species involved, and numerous mathematical models representing unit operations, utility costs, equipment cost, and so on, together with plant and site data, market size, and product specifications [36]. When environmental and social dimensions are included, the amount of information required for the design task increases dramatically. Thus, it is necessary to obtain data and models regarding environmental impacts, health and safety issues, land and natural resource use, resources availability, emission factors, regulating policies, social statistics, and so on [37,38].
The complete evaluation of the TBL dimensions during chemical process design can be performed via distinct frameworks [19••,39,40•,41••]. The simplest one, gate to gate, effects the assessment within the limits of the operation, equipment, unit, or plant; in other words, only an internal perspective of the system is considered. A further refinement, cradle to gate, expands the boundaries of the evaluation by including the origin of the raw materials and incorporating the impacts corresponding to their procurement. Another refinement, cradle to cradle, attempts to emulate nature with the incorporation of the concept of recycling, thereby trying to close the material loops. This framework is aligned with the modern development paradigm based on circular economy. Finally, a life cycle framework extends far beyond the previous approaches by considering an enlarged spatial boundary and accounting for broader TBL implications of the process during its entire life span. Figure 1summarizes the general framework for sustainability assessment during chemical process design as described in most comprehensive discourses on the topic [6,14,35,37,42, 43, 44, 45]. The same figure also classifies some sustainability indicators in terms of the sequential stages of process design. In this regard, Ruiz-Mercado et al. [17] comprehensively reviewed nearly 140 TBL indicators, which can be augmented and/or complemented with those described in more recent contributions. For instance, the ecological indicators deployed by Bautista et al. [13•], the social sustainability indicators presented by Hale et al. [16••], novel metrics and methods related to green chemistry discussed by Sheldon [19••], and some process safety indicators [46••,47•,48••]. Other instances of recent TBL indicators deployed in a variety of processes include composite metrics incorporating the level of environmental burden associated to purchase and consumer demand [18•]; expert weighting factors at early stages of process design [29•]; a green engineering based checklist tool [49•]; demand-response based metrics [50]; metrics developed in light of the food-energy-water (FEW) nexus [51•]; a penalty points green metric [52]; 3D Pareto plots for the TBL dimensions [53•]; metrics for transportation useful in life cycle frameworks [54•]; and technical performance metrics [55•]. As seen in Figure 1, the indicators that can be used in product design and early process-design stages are mostly based on the inherent properties of the chemical species involved, such as physicochemical, environmental, economic, safety, and occupational health properties. The most recent methods also attempt to assess process sustainability under uncertainty [56,57••]. In process synthesis as well as in subsequent design stages, the indicators are deployed based on mass and energy balances, detailed economics, emissions assessment, risk analysis, and so on. During process operation and retrofitting, indicators of economic and environmental nature can be refined with the information obtained from the process operation, thus improving the indicators’ quality. Moreover, the impact of the process on the local, or global, context can be captured by incorporating social indicators [16••,58,59].
Figure 1. Framework for sustainability assessment in designing chemical processes and products.Challenges and opportunities
A major challenge in performing sustainability assessment of chemical processes is the relationship between the availability and quality of information and the impact of the decisions that must be made based on such a relationship at each design stage. In this regard, Figure 2 shows a schematic representation of the evolution of the various factors to be considered in assessing process sustainability at each stage of process design. In the early design stages, including product and process design as well as conceptual engineering, the available information is scarce, its quality low, and high levels of uncertainty regarding the same are to be expected. Nevertheless, this information together with expert knowledge are the basis for critical decisions to be made at the early design stages, which will have an enormous impact on the process’ sustainability. Such decisions are related to product formulation, chemical-route selection, materials selection (raw materials, solvents, catalysts, etc.), separation operations, production capacity, and plant location, to name a few. At this juncture, indicators have meaning only for comparison when different design alternatives are being evaluated. Thus, uncertainty in their calculation should be considered to determine if the numerical differences observed among alternatives mean an actual difference in sustainable performance. Besides, the level of uncertainty in the data required for sustainability evaluation tends to worsen when the assessment is carried out in light of innovative frameworks (e.g. bio-based substances, novel synthetic chemicals, new chemical pathways, novel product or processes, and intensified processes). This emphasizes the importance of developing quantitative tools to incorporate the inherent uncertainty of data into the sustainability assessment [56,57••].