Process design within planetary boundaries: Application to CO2 based methanol production

Urea production: An absolute environmental sustainability assessment

The demand for urea, as the most popular global nitrogen fertilizer, is on the rise and as such, its performance in an environmentally sustainable perspective relative to planetary boundaries is high on the agenda. The increasing interest in nitrogen fertilizers is to improve agricultural methods for a better production rate, but can it become environmentally sustainable? Which is due to the significant contribution of fertilizers in the anthropogenic impacts of industrial activities on nature, should be considered. Here, a system analysis based on real data using life cycle assessment linked to the planetary boundaries framework (PB-LCIA) was conducted to study the performance of total urea consumption in Iran, 1.8E+6 metric tons per year. In LCA, midpoint and endpoint methods (ReCiPe 2016) and for AESA, a PB-LCIA methodology was utilized. Results showed that global warming potential, freshwater eutrophication, and marine eutrophication contribute 1.37E+09 kg CO2 eq, 1.63E+04 kg P eq, and 1.28E+04 kg N eq, respectively, while the GHG emissions of combustion, electricity, and natural gas sweetening have the most contribution to global warming by 35, 24 & 15 %, respectively. Regarding absolute sustainability, global warming, ocean acidification, and biochemical N exceed this activity's assigned share of safe operating space (SoSOS). However, choosing different sharing principles can influence to what extent this activity exceeds or stays within the assigned SoSOS; accordingly, the Nitrogen Biogeochemical flows depend on the sharing principle. Ultimately, the total Iranian urea consumption as fertilizer is not absolutely sustainable. The promising point is that producing sustainable electricity and feedstocks could lead to more sustainable urea fertilizers.

The Relevance of Life Cycle Assessment Tools in the Development of Emerging Decarbonization Technologies

The development of emerging decarbonization technologies requires advanced tools for decision-making that incorporate the environmental perspective from the early design. Today, Life Cycle Assessment (LCA) is the preferred tool to promote sustainability in the technology development, identifying environmental challenges and opportunities and defining the final implementation pathways. So far, most environmental studies related to decarbonization emerging solutions are still limited to midpoint metrics, mainly the carbon footprint, with global sustainability implications being relatively unexplored. In this sense, the Planetary Boundaries (PBs) have been recently proposed to identify the distance to the ideal reference state. Hence, PB-LCA methodology can be currently applied to transform the resource use and emissions to changes in the values of PB control variables. This study shows a complete picture of the LCA's role in developing emerging technologies. For this purpose, a case study based on the electrochemical conversion of CO2 to formic acid is used to show the possibilities of LCA approaches highlighting the potential pitfalls when going beyond greenhouse gas emission reduction and obtaining the absolute sustainability level in terms of four PBs.

Social life cycle assessment of green methanol and benchmarking against conventional fossil methanol

Green methanol could play a major role in decarbonising both the chemical and energy sectors. While techno-economic and environmental studies on green methanol following a life-cycle perspective are available, its social implications from a supply-chain standpoint remain largely unexplored. In order to fill this gap, this work presents the first social life cycle assessment of green methanol produced with CO₂ directly captured from the air and hydrogen from wind power electrolysis. When compared to conventional methanol from natural gas, the results suggest an unfavourable performance of green methanol under negative social indicators (forced labour, women in the sectoral labour force, health expenditure, social responsibility promotion, and fair salary) due to the increased supply-chain complexity of the green system. In contrast, green methanol would outperform its conventional counterpart in terms of sectoral contribution to economic development, a positive social indicator which would benefit from the increase in working hours. Besides future consideration of a higher number of positive indicators and potential improvements in country- and sector-specific risk levels towards high-quality social and working conditions, an enhanced social life-cycle performance of green methanol requires technical improvements to reduce the high demand for energy inputs and equipment across its supply chain. Acknowledging decarbonisation as the actual driver of green methanol deployment, future social studies are suggested to focus on the comparison of renewable alternatives for its production and the effect of social regulations.

Design and Operation of Multipurpose Production Facilities Using Solar Energy Sources for Heat Integration Sustainable Strategies

Industrial production facilities have been facing the requirement to optimise resource efficiency, while considering sustainable goals. This paper addresses the introduction of renewable energies in production by exploring the combined design and scheduling of a multipurpose batch facility, with innovative consideration of direct/indirect heat integration using a solar energy source for thermal energy storage. A mixed-integer linear programming model is formulated to support decisions on scheduling and design selection of storage and processing units, heat exchange components, collector systems, and energy storage units. The results show the minimisation of utilities consumption, with an increase in the operational profit using combined heat integration strategies for the production schedule. A set of illustrative case-study examples highlight the advantages of the solar-based heat storage integration, assessing optimal decision support in the strategic and operational management of these facilities.

A Survey on Sustainable Surrogate-Based Optimisation

Surrogate-based optimisation (SBO) algorithms are a powerful technique that combine machine learning and optimisation to solve expensive optimisation problems. This type of problem appears when dealing with computationally expensive simulators or algorithms. By approximating the expensive part of the optimisation problem with a surrogate, the number of expensive function evaluations can be reduced. This paper defines sustainable SBO, which consists of three aspects: applying SBO to a sustainable application, reducing the number of expensive function evaluations, and considering the computational effort of the machine learning and optimisation parts of SBO. The paper reviews sustainable applications that have successfully applied SBO over the past years, and analyses the used framework, type of surrogate used, sustainable SBO aspects, and open questions. This leads to recommendations for researchers working on sustainability-related applications who want to apply SBO, as well as recommendations for SBO researchers. It is argued that transparency of the computation resources used in the SBO framework, as well as developing SBO techniques that can deal with a large number of variables and objectives, can lead to more sustainable SBO.

Methanol Production in the Brayton Cycle

This article presents the concept of renewable methanol production in the gas turbine cycle. As part of the work, an analysis was performed, including the impact of changing the parameters in the methanol reactor on the obtained values of power, yield and efficiency of the reactor, and chemical conversion. The aim of this research was to investigate the possibility of integrating the system for the production of renewable methanol and additional production of electricity in the system. The efficiency of the chemical conversion process and the efficiency of the methanol reactor increases with increasing pressure and decreasing temperature. The highest efficiency values, respectively η = 0.4388 and ηR = 0.3649, are obtained for parameters in the reactor equal to 160 °C and 14 MPa. The amount of heat exchanged in all exchangers reached the highest value for 14 MPa and 160 °C and amounted to Q˙ = 2.28 kW. Additionally, it has been calculated that if an additional exchanger is used before the expander (heating the medium to 560 °C), the expander’s power will cover the compressor’s electricity demand.