Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach

Process Design for Value-Added Products in a Biorefinery Platform from Agro and Forest Industrial Byproducts

Agroforestry wastes are industrial byproducts available locally such as eucalyptus sawdust (EUC) and sugarcane bagasse (SCB). These byproducts can be used as lignocellulosic raw materials to produce high-value products. This study is a techno-economic analysis of four potential scenarios to produce polyhydroxybutyrate (PHB) and levulinic acid (LA) from hemicellulosic sugars by a fermentative pathway in a biomass waste biorefinery. Mass and energy balances were developed, and technical and economic assessments were carried out to obtain gas, char, and tar from residual solids from autohydrolysis treatment. It was determined that microbial culture could be an attractive option for added-value product production. More than 1500 t/year of PHB and 2600 t/year of LA could be obtained by the proposed pathways. Microbial and enzymatic conversion of LA from sugars could significantly improve energy consumption on the conversion strategy. The products from solid residual valorization (char and tar) are the most important for economic performance. Finally, a variation in specific variables could mean substantial improvements in the final indicators of the processes, reaching a higher NPV than USD 17 million.

Stochastic Ex-Ante LCA under Multidimensional Uncertainty: Anticipating the Production of Undiscovered Microalgal Compounds in Europe

Due to their biodiversity, microalgae represent a promising source of high-value compounds that bioprospecting is aiming to reveal. Performing an ex-ante Life Cycle Assessment (LCA) to anticipate and potentially minimize the environmental burden associated with the European production of a bioprospected microalgal compound is subject to substantial and multi-factorial uncertainty as the compound remains undiscovered. Given that any microalgal strain could potentially host the compound of interest, the ex-ante LCA should consider this bioprospecting uncertainty together with the uncertainty on the technology and the production mix. Using a parameterized cultivation simulation and consequential LCA model and an extensive stochastic pseudo Monte Carlo approach, we define and propagate techno-operational, bioprospecting, and production mix uncertainties for a microalgal compound being currently bioprospected in Europe. We perform global sensitivity analysis using different sampling strategies to identify the main contributors to the total output variance. Overall, the uncertainty propagation allowed us to define and analyze the probabilistic scope for the potential environmental impacts in the emerging production of high-value microalgal compounds in Europe based on current knowledge. These findings can support policy-making as well as actors in the microalgal sector toward technological paths with lower environmental impact.

Algal biorefinery culminating multiple value-added products: recent advances, emerging trends, opportunities, and challenges

Algal biorefinery is rising as a prominent solution to economically fulfill the escalating global requirement for nutrition, feed, fuel, and medicines. In recent years, scientific productiveness associated with microalgae-based studies has elaborated in multiplied aspects, while translation to the commercial level continues to be missing. The present microalgal biorefinery has a challenge in long-term viability due to escalated market price of algal-mediated biofuels and bioproducts. Advancements are required in a few aspects like improvement in algae processing, energy investment, and cost analysis of microalgae biorefinery. Therefore, it is essential to recognize the modern work by understanding the knowledge gaps and hotspots driving business scale up. The microalgae biorefinery integrated with energy-based products, bioactive and green compounds, focusing on a circular bioeconomy, is urgently needed. A detailed investigation of techno-economic analysis (TEA) and life cycle assessment (LCA) is important to increase the market value of algal products. This review discusses the valorization of algal biomass for the value-added application that holds a sustainable approach and cost-competitive algal biorefinery. The current industries, policies, technology transfer trends, challenges, and future economic outlook are discussed. This study is an overview through scientometric investigation attempt to describe the research development contributing to this rising field.

Sustainability Assessment of Combined Animal Fodder and Fuel Production from Microalgal Biomass

We present a comparative environmental and social life cycle assessment (ELCA and SLCA) of algal fuel and fodder co-production (AF + fodder) versus algal fuel and energy co-production (AF + energy). Our ELCA results indicate that fodder co-production offers an advantage in the following categories: climate change (biogenic land use and land use change total), ecotoxicity, marine eutrophication, ionizing radiation, photochemical ozone creation, and land use. By contrast, the AF + energy system yields lower impacts in the other 11 out of 19 Environmental Footprint impact categories. Only AF + fodder offers greenhouse gas reduction compared to petroleum diesel (−25%). Our SLCA results indicate that AF + fodder yields lower impacts in the following categories: fair salaries, forced labor, gender wage gap, health expenditure, unemployment, and violation of employment laws and regulations. AF + energy performs favorably in the other three out of nine social indicators. We conclude that the choice of co-products has a strong influence on the sustainability of algal fuel production. Despite this, none of the compared systems are found to yield a consistent advantage in the environmental or social dimension. It is, therefore, not possible to recommend a co-production strategy without weighing environmental and social issues.

Electrocatalysis for Chemical and Fuel Production: Investigating Climate Change Mitigation Potential and Economic Feasibility

The manufacture of goods from oil, coal, or gas to everyday consumer products comprises in more or less all cases at least one catalytic step. Compared to conventional hydrothermal catalysis, electrocatalysis possesses the advantage of mild operational conditions and high selectivity, yet the potential energy savings and climate change mitigation have rarely been assessed. This study conducted a life cycle assessment (LCA) for the electrocatalytic oxidation of crude glycerol to produce lactic acid, one of the most common platform chemicals. The LCA results demonstrated a 31% reduction in global warming potential (GWP) compared to the benchmark (bio- and chemocatalytic) processes. Additionally, electrocatalysis yielded a synergetic potential to mitigate climate change depending on the scenario. For example, electrocatalysis combined with a low-carbon-intensity grid can reduce GWP by 57% if the process yields lactic acid and lignocellulosic biofuel as compared to a conventional fossil-based system with functionally equivalent products. This illustrates the potential of electrocatalysis as an important contributor to climate change mitigation across multiple industries. A technoeconomic analysis (TEA) for electrocatalytic lactic acid production indicated considerable challenges in economic feasibility due to the significant upfront capital cost. This challenge could be largely addressed by enabling dual redox processing to produce separate streams of renewable chemicals and biofuels simultaneously.

Coproducts of algae and yeast-derived single cell oils: A critical review of their role in improving biorefinery sustainability

Oleaginous microalgae and yeast are of increasing interest as a renewable resource for single cell oils (SCOs). These have applications in fuels, feed and food products. In order to become cost competitive with existing terrestrial oils, a biorefinery approach is often taken where several product streams are valorised alongside the SCO. Whilst many life cycle assessment (LCA) and Techno-economic (TEA) studies have employed this biorefinery approach to SCO production, a systematic analysis of their implications is missing. This review evaluates the economic and environmental impacts associated with the use of coproducts. Overall, protein production plays the greatest role in determining viability, with coproduct strategy crucial to considering in the early stages of research and development.

Aligning sustainability assessment with responsible research and innovation: Towards a framework for Constructive Sustainability Assessment

Emerging technologies are increasingly promoted on the promise of tackling the grand challenge of sustainability. A range of assessment and governance approaches seek to evaluate these claims, but these tend to be applied disparately and lack widespread operationalisation. They also face specific challenges, such as high levels of uncertainty, when it comes to emerging technologies. Building and reflecting on both theory and practice, this article develops a framework for Constructive Sustainability Assessment (CSA) that enables the application of sustainability assessments to emerging technologies as part of a broader deliberative approach. In order to achieve this, we discuss and critique current approaches to analytical sustainability assessment and review deliberative social science governance frameworks. We then develop the conceptual basis of CSA - blending life-cycle thinking with principles of responsible research and innovation. This results in four design principles - transdisciplinarity, opening-up, exploring uncertainty and anticipation - that can be followed when applying sustainability assessments to emerging technologies. Finally, we discuss the practical implementation of the framework through a three-step process to (a) formulate the sustainability assessment in collaboration with stakeholders, (b) evaluate potential sustainability implications using methods such as anticipatory life-cycle assessment and (c) interpret and explore the results as part of a deliberative process. Through this, CSA facilitates a much-needed transdisciplinary response to enable the governance of emerging technologies towards sustainability. The framework will be of interest to scientists, engineers, and policy-makers working with emerging technologies that have sustainability as an explicit or implicit motivator.

Techno-Economic Analysis of a Small-Scale Biomass-to-Energy BFB Gasification-Based System

In order to limit global warming to around 1.5–2.0 °C by the end of the 21st century, there is the need to drastically limit the emissions of CO2. This goal can be pursued by promoting the diffusion of advanced technologies for power generation from renewable energy sources. In this field, biomass can play a very important role since, differently from solar and wind, it can be considered a programmable source. This paper reports a techno-economic analysis on the possible commercial application of gasification technologies for small-scale (2 MWe) power generation from biomass. The analysis is based on the preliminary experimental performance of a 500 kWth pilot-scale air-blown bubbling fluidized-bed (BFB) gasification plant, recently installed at the Sotacarbo Research Centre (Italy) and commissioned in December 2017. The analysis confirms that air-blown BFB biomass gasification can be profitable for the applications with low-cost biomass, such as agricultural waste, with a net present value up to about 6 M€ as long as the biomass is provided for free; on the contrary, the technology is not competitive for high-quality biomass (wood chips, as those used for the preliminary experimental tests). In parallel, an analysis of the financial risk was carried out, in order to estimate the probability of a profitable investment if a variation of the key financial parameters occurs. In particular, the analysis shows a probability of 90% of a NPV at 15 years between 1.4 and 5.1 M€ and an IRR between 11.6% and 23.7%.

A Monte Carlo-based integrated model to optimize the cost and pollution reduction in wastewater treatment processes in a typical comprehensive industrial park in China

Wastewater generated from an industrial park is usually characterized by large volumes, variation in composition, and high pollutant concentrations, and is generally toxic and difficult to biodegrade. Wastewater treatment at an industrial park includes several stages, namely, pretreatment inside factories (F-WWTPs), centralized wastewater treatment (C-WWTP), and reclaimed wastewater treatment (R-WWTP), during which the treatment efficiencies are mutually restricted. Therefore, water pollution control in industrial parks is extremely challenging. In this study, models, including those for pollutant reduction and operating costs, were established considering the F-WWTPs, C-WWTP, and R-WWTP stages at an industrial park. A Monte Carlo model was used to simulate the treatment and solve the above-mentioned models. Consequently, the characteristic values, including the extent of pollutant reduction, concentration of pollutants in the effluent, and operation costs, were predicted under optimal operating conditions of the wastewater treatment system. The established model was verified and applied to industrial park A in the Tianjin Economic-Technological Development Area in China. Based on the comparison of the above-mentioned optimization values with the sampled values as well as the theoretical analysis, the status of the wastewater treatment system in the industrial park was quantitatively evaluated to diagnose pertinent issues. Additionally, optimization and reformation strategies were proposed. Therefore, the established model can achieve optimization of pollution reduction and operation costs for the entire industrial park, thus contributing to industrial wastewater pollution control and water quality improvement.

A Unified Modeling Framework to Advance Biofuel Production from Microalgae

Modeling efforts to understand the financial implications of microalgal biofuels often assume a static basis for microalgae biomass composition and cost, which has constrained cultivation and downstream conversion process design and limited in-depth understanding of their interdependencies. For this work, a dynamic biological cultivation model was integrated with thermo-chemical/biological unit process models for downstream biorefineries to increase modeling fidelity, to provide mechanistic links among unit operations, and to quantify minimum product selling prices of biofuels via techno-economic analysis. Variability in design, cultivation, and conversion parameters were characterized through Monte Carlo simulation, and sensitivity analyses were conducted to identify key cost and fuel yield drivers. Cultivating biomass to achieve the minimum biomass selling price or to achieve maximum lipid content were shown to lead to suboptimal fuel production costs. Depending on biomass composition, both hydrothermal liquefaction and a biochemical fractionation process (combined algal processing) were shown to have advantageous minimum product selling prices, which supports continued investment in multiple conversion pathways. Ultimately, this work demonstrates a clear need to leverage integrated modeling platforms to advance microalgae biofuel systems as a whole, and specific recommendations are made for the prioritization of research and development pathways to achieve economical biofuel production from microalgae.

A Non-Probabilistic Solution for Uncertainty and Sensitivity Analysis on Techno-Economic Assessments of Biodiesel Production with Interval Uncertainties

Techno-economic assessments (TEA) of biodiesel production may comply with various economic and technical uncertainties during the lifespan of the project, resulting in the variation of many parameters associated with biodiesel production, including price of biodiesel, feedstock price, and rate of interest. Engineers may only collect very limited information on these uncertain parameters such as their variation intervals with lower and upper bound. This paper proposes a novel non-probabilistic strategy for uncertainty analysis (UA) in the TEA of biodiesel production with interval parameters, and non-probabilistic reliability index (NPRI) is employed to measure the economically feasible extent of biodiesel production. A sensitivity analysis (SA) indicator is proposed to assess the sensitivity of NPRI with regard to an individual uncertain interval parameter. The optimization method is utilized to solve NPRI and SA. Results show that NPRI in the focused biodiesel production of interest is 0.1211, and price of biodiesel, price of feedstock, and cost of operating can considerably affect TEA of biodiesel production.