Recent Developments in Synthesis, Properties, Applications and Recycling of Bio-Based Elastomers.

In 2021, global plastics production was 390.7 Mt; in 2022, it was 400.3 Mt, showing an increase of 2.4%, and this rising tendency will increase yearly. Of this data, less than 2% correspond to bio-based plastics. Currently, polymers, including elastomers, are non-recyclable and come from non-renewable sources. Additionally, most elastomers are thermosets, making them complex to recycle and reuse. It takes hundreds to thousands of years to decompose or biodegrade, contributing to plastic waste accumulation, nano and microplastic formation, and environmental pollution. Due to this, the synthesis of elastomers from natural and renewable resources has attracted the attention of researchers and industries. In this review paper, new methods and strategies are proposed for the preparation of bio-based elastomers. The main goals are the advances and improvements in the synthesis, properties, and applications of bio-based elastomers from natural and industrial rubbers, polyurethanes, polyesters, and polyethers, and an approach to their circular economy and sustainability. Olefin metathesis is proposed as a novel and sustainable method for the synthesis of bio-based elastomers, which allows for the depolymerization or degradation of rubbers with the use of essential oils, terpenes, fatty acids, and fatty alcohols from natural resources such as chain transfer agents (CTA) or donors of the terminal groups in the main chain, which allow for control of the molecular weights and functional groups, obtaining new compounds, oligomers, and bio-based elastomers with an added value for the application of new polymers and materials. This tendency contributes to the development of bio-based elastomers that can reduce carbon emissions, avoid cross-contamination from fossil fuels, and obtain a greener material with biodegradable and/or compostable behavior.

Wastewater treatment, energy consumption, and greenhouse gas emissions: An operational approach to comparing Barcelona and Mexico City.

This study delves into the critical nexus between wastewater treatment, energy consumption, and greenhouse gas emissions. Wastewater treatment is a linchpin of sustainable development, yet its energy-intensive processes contribute significantly to greenhouse gas emissions. The research focuses on wastewater treatment plants (WWTPs) in Mexico City (CDMX) and the Metropolitan Area of Barcelona (AMB), exploring the disparities between a developed country and a developing country. The study examines how factors such as water treatment technologies and electricity sources influence carbon emissions. The AMB exhibits superior performance by treating all wastewater, cogenerating energy from the biomass contained in the wastewater and generating 10% fewer emissions, in stark contrast to CDMX, which does not capture the CH4 produced during water treatment, on top of only treating the water of 14% of the city's agglomeration. It underscores the critical implications of WWTP efficiency on climate change and progress toward UN Sustainable Development Goals. Given the limited attention to the Global South, this research serves as a vital contribution to the discourse on sustainability and development.

Eco-efficiency evaluation in wastewater treatment plants considering greenhouse gas emissions through the data envelopment analysis-tolerance model.

The eco-efficiency evaluation in wastewater treatment plants (WWTPs) is used to know and improve the environmental and economic efficiency of these processes, systems, products, and services. The eco-efficiency evaluations in WWTP contemplate the inputs to be minimized, the desirable results to be maximized, and the undesired results to be minimized. Data envelopment analysis (DEA) is a widely used method to evaluate the eco-efficiency of WWTPs; integrating several approaches in a single index, traditional DEA models do not take into account the uncertainty in the data. This study evaluates the eco-efficiency of a sample of Catalan WWTPs, considering the uncertainty of the data (DEA tolerance model), and it is for the first time that together with CO2, other greenhouse gas (GHG) such as CH4 and N2O are considered as part of the process outputs. GHG emissions were quantified using methods reported in the literature. Seven hundred twenty-nine eco-efficiency scores were estimated for each WWTP instead of a single score like conventional DEA models, analyzing optimistic and pessimistic scenarios. The WWTPs were classified according to the estimated eco-efficiency scores, accounting for the uncertainty in each of the scenarios, and demonstrating the changes in the performance of the WWTPs in the different scenarios. Only two WWTPs were eco-efficient in all the scenarios evaluated. This approach provides essential information to improve efficiency and innovation in the wastewater sector.

Analysis of empirical methods for the quantification of N2O emissions in wastewater treatment plants: Comparison of emission results obtained from the IPCC Tier 1 methodology and the methodologies that integrate operational data.

Wastewater is a source of N2O emission that is generated, both directly from advanced treatment plants and indirectly from the discharge of wastewater into the natural environment, due to its remaining nitrogen content. There are a variety of methods based on different parameters used to calculate N2O emission in wastewater treatment plants. The methodology proposed by the IPCC is used as an international reference for national inventories. In this work, we use five international methodologies to calculate the N2O emission of the WWTPs in two areas with high population density: The Metropolitan Area of Barcelona (MAB) and Mexico City (MXC). The MAB has 100% population served and has advanced treatment plants (five WWTP) and traditional wastewater treatment plants (two WWTP), the MXC served 14% of its population and had advanced treatment plants (six WWTP) and traditional plants (nineteen WWTP) in 2016. The results obtained show that the IPCC and Das methodologies underestimate the emission of N2O by considering the per capita consumption of proteins as a constant nitrogen value and also by the suggested emission factors. The methodologies that use the operational data of each plant provide emission results closer to those found in the literature. The value of TN should be the parameter to be considered for a correct estimate of the N2O emission in the WWTPs. The emission factors currently used are very low, with a low level of confidence of up to 1.3%. The range currently used should be increased and have a minimum range of 0.03 kg N2O-N/kg N. The emission factors reported in the literature are very variable and with very high levels of uncertainty, and therefore underestimate the emission of N2O in WWTPs. More research should be done to obtain higher and more reliable emission factors than those currently used.