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Background: The dairy industry requires substantial energy resources at all stages of production and supply to meet consumer needs in terms of quantity, quality and food safety. The expected future climate change effects will cause serious uncertainty to the dairy industry. Adapting to these upcoming conditions is a challenge and one that is compounded by the continuous increase in food demand, as a result of global population growth. Predictably, under current conditions, this situation might lead to a significant increase in the energy requirements of the dairy industry. Therefore, there is a clear need to mitigate energy use through enhanced energy conservation, waste reduction and waste management. Scope and approach: This review paper presents and discusses alternative dairy operations and mitigation strategies that have the potential to lead the dairy industry towards net-zero carbon emissions. Further, the focus of this work turns to supply chain energy modelling (SCEM) as means to mitigate energy use, while relevant work in the literature is reviewed. Key findings and conclusions: Supply chain energy models can provide a complete overview of the energy demand and the energy mix of a dairy supply chain. Additionally, they can highlight the most energy consuming processes and allow the evaluation of alternative energy-saving operations that can lead towards the net-zero carbon target. Overall, the development or use of computational tools for simulating the energy demand in the industry has strong potential for improving sustainability across the dairy supply chain.

Treated and untreated wastewater is often used for agricultural irrigation and, despite the many benefits of this practice, it poses the risk of biologically active chemical pollutants (such as pharmaceuticals, like tramadol) entering the environment. The partitioning of tramadol between soil/water at environmentally relevant concentrations is important to understand its environmental toxicity. Kinetics and isotherm sorption studies based on the Organisation for Economic Cooperation and Development (OECD) 106 Guideline were undertaken, ensuring comparability to previous studies. Studies were undertaken in three soils of different characteristics using aqueous concentrations of tramadol from 500 ng L−1 (environmentally relevant) to 100 μg L−1 (comparable to previous studies). Two of the soils presented a significantly (p < 0.05) higher sorption at a lower initial tramadol concentration (5000 ng L−1), compared to 20,000 ng L−1. Hysteresis was observed in all studied soils, indicating the accumulation of tramadol. Higher sorption to soils correlated with higher clay content, with soil/water partitioning coefficients (Kd) of 5.5 ± 13.3, 2.5 ± 3.8 and 0.9 ± 3.0 L kg1 for soils with clay contents of 41.9%, 24.5% and 7.4%, respectively. Cation exchange was proposed as the main sorption mechanism for tramadol to soils when the pH was below tramadol's pKa values (9.41 and 13.08). A comparative kinetics study between tramadol in soil/calcium chloride buffer and soil/wastewater effluent demonstrated significantly higher (p < 0.05) tramadol sorption to soil from wastewater effluent. This has the environmental implication that clay soils will be able to retain tramadol from irrigation water, despite the organic content of the irrigation water. Therefore, our studies show that tramadol soil sorption is likely to be higher in agricultural environments reusing wastewater than that predicted from experiments using the OECD 106 Guideline calcium chloride buffer.

Selenium (Se) is an essential element with application in manufacturing from food to medical industries. Water contamination by Se is of concern due to anthropogenic activities. Recently, Se remediation has received increasing attention. Hence, different types of remediation techniques are listed in this work, and their potential for Se recovery is evaluated. Sorption, co-precipitation, coagulation and precipitation are effective for low-cost Se removal. In photocatalytic, zero-valent iron and electrochemical systems, the above mechanisms occur with reduction as an immobilization and detoxification process. In combination with magnetic separation, the above techniques are promising for Se recovery. Biological Se oxyanions reduction has been widely recognized as a cost-effective method for Se remediation, simultaneously generating biosynthetic Se nanoparticles (BioSeNPs). Increasing the extracellular production of BioSeNPs and controlling their morphology will benefit its recovery. However, the mechanism of the microbial production of BioSeNPs is not well understood. Se containing products from both microbial reduction and abiotic methods need to be refined to obtain pure Se. Eco-friendly and cost-effective Se refinery methods need to be developed. Overall, this review offers insight into the necessity of shifting attention from Se remediation to Se recovery.

Advances in industrial digital technologies have led to an increasing volume of data generated from industrial bioprocesses, which can be utilised within data-driven models (DDM). However, data volume and variability complications make developing models that captures the underlying biological nature of the bioprocesses challenging. In this study, a framework for developing data-driven models of bioprocesses is proposed and evaluated by modelling an industrial bioprocess, which treats industrial or agrifood wastewaters whilst simultaneously generating bioenergy. Six models were developed to predict the reduction in chemical oxygen demand from the wastewater by the bioprocess and statistically evaluated using both testing data (randomly partitioned data from the model development) and unseen data (new data not used during the model development). The statistical error metrics employed were the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The stacked neural network model was best able to model the bioprocess, having the highest accuracy on the testing data (R2: 0.98; RMSE: 1.29; MAE: 2.27; MAPE: 4.08) and the unseen data (R2: 0.82; RMSE: 2.57; MAE: 1.75; MAPE: 3.68). Data visualisation is used to observe (or confirm) whether new data points are within the model boundaries, helping to increase confidence in the model’s predictions on future data.

We developed a top-down strategy to characterise an antimicrobial, oxidising sanitiser, which has diverse proposed applications including surface-sanitisation of fresh foods, and with benefits for water resilience. The strategy involved finding quenchers of antimicrobial activity then antimicrobial mode of action, by identifying key chemical reaction partners starting from complex matrices, narrowing down reactivity to specific organic molecules within cells. The sanitiser electrolysed-water (EW) retained partial fungicidal activity against the food-spoilage fungus Aspergillus niger at high levels of added soils (30–750 mg mL-1), commonly associated with harvested produce. Soil with high organic load (approx. 98 mg g-1) gave stronger EW inactivation. Marked inactivation by a complex organics mix (YEPD medium) was linked to its protein-rich components. Addition of pure proteins or amino acids (≤1 mg mL-1) fully suppressed EW activity. Mechanism was interrogated further with the yeast model, corroborating marked suppression of EW action by the amino acid methionine. Pre-culture with methionine increased resistance to EW, sodium hypochlorite, or chlorine-free ozonated water. Overexpression of methionine sulfoxide reductases (which reduce oxidised methionine) protected against EW. Fluoroprobe-based analyses indicated that methionine and cysteine inactivate free chlorine species in EW. Intracellular methionine oxidation can disturb cellular FeS-clusters and we showed that EW treatment impairs FeS-enzyme activity. The study establishes the value of a top-down approach for multi-level characterisation of sanitiser efficacy and action. The results reveal proteins and amino acids as key quenchers of EW activity and, among the amino acids, the importance of methionine oxidation and FeS-cluster damage for antimicrobial mode-of-action.

Mathematical modelling can play a key role in understanding as well as quantifying uncertainties surrounding the presence and fate of emerging pollutants in wastewater treatment processes (WWTPs). This paper presents for the first time a simplified emerging pollutant pathway in the WWTP that incorporates two potential pathways to sequestration. It develops de-terministic and stochastic ordinary differential equations to gain insight into the fate and behaviour of a case study pharmaceutical, with particular focus on sorption to the solid phase, as well as the nature of the experimentally measured solid parent compound. Statistical estimation and inferential procedures are developed and via a proof-of-concept examination, the study explores the transformation pathways of the bioactive chemicals (BACs) in the bioreactor, which is the heart of the WWTP. With a focus on the case study pharmaceutical 17??ethinlyestradiol (EE2), the simulation results show good agreement with the EE2 data. In addition, the results suggest that the experimentally measured solid EE2-parent concentration is very similar to the model-based sequestered EE2-parent concentration.

Copper and zinc are routinely used in livestock antimicrobial footbaths in commercial farming. The footbath mix is a cost to farmers, and the disposal of spent footbath into slurry tanks leads to soil contamination, as well as the potential for antimicrobial metal resistance and co-selection. This study assesses the potential to mitigate a source of antimicrobial metal resistance in slurry tanks while recovering copper and zinc from spent cattle footbaths. This is the first study in literature to investigate the potential of recovering copper from cattle footbath solutions via any method. The sorbent, Ca2Al-EDTA Layered Double Hydroxides (LDH), were used to remove Cu2+ from a Cu2SO4·5H20 solution at different temperatures. The maximum Cu2+ uptake from the Cu2SO4·5H20 solution was 568 ± 88 mg g−1. Faster and higher equilibrium uptake was achieved by increasing the temperature of the solution. The sorbent was found to be effective in removing copper and zinc from a commercially available cattle footbath solution (filtered footbath solution Cu2+ uptake 283 ± 11.05 mg g−1, Zn2+ uptake 60 ± 0.05 mg g−1). Thus, this study demonstrates the opportunity for a completely novel and potentially economically beneficial method of mitigating antimicrobial resistance in agriculture and the environment, while also providing a new valuable copper and zinc waste stream for secondary metal production.

The isolation of antimicrobial resistant bacteria (ARB) from wildlife living adjacent to humans has led to the suggestion that such antimicrobial resistance (AMR) is anthropogenically driven by exposure to antimicrobials and ARB. However, ARB have also been detected in wildlife living in areas without interaction with humans. Here, we investigated patterns of resistance in Escherichia coli isolated from 408 wild bird and mammal faecal samples. AMR and multi-drug resistance (MDR) prevalence in wildlife samples differed significantly between a Sewage Treatment Plant (STP; wastes of antibiotic-treated humans) and a Farm site (antibiotic-treated livestock wastes) and Central site (no sources of wastes containing anthropogenic AMR or antimicrobials), but patterns of resistance also varied significantly over time and between mammals and birds. Over 30% of AMR isolates were resistant to colistin, a last-resort antibiotic, but resistance was not due to the mcr-1 gene. ESBL and AmpC activity were common in isolates from mammals. Wildlife were, therefore, harbouring resistance of clinical relevance. AMR E. coli, including MDR, were found in diverse wildlife species, and the patterns and prevalence of resistance were not consistently associated with site and therefore different exposure risks. We conclude that AMR in commensal bacteria of wildlife is not driven simply by anthropogenic factors, and, in practical terms, this may limit the utility of wildlife as sentinels of spatial variation in the transmission of environmental AMR.

The stability of enzymes is critical for their application in industrial processes, which generally require different conditions from the natural enzyme environment. Both rational and random protein engineering approaches have been used to increase stability, with the latter requiring extensive experimental effort for the screening of variants. Moreover, some general rules addressing the molecular origin of protein thermostability have been established. Herein, we demonstrate the use of molecular dynamics simulations to gain molecular level understanding of protein thermostability and to engineer stabilizing mutations. Carbonic anhydrase (CA) is an enzyme with a high potential for biotechnological carbon capture applications, provided it can be engineered to withstand the high temperature process environments, inevitable in most gas treatment units. In this study, we used molecular dynamics simulations at 343, 353, and 363 K to study the relationship between structure flexibility and thermostability in bacterial α-CAs and applied this knowledge to the design of mutants with increased stability. The most thermostable α-CA known, TaCA from Thermovibrio ammonificans, had the most rigid structure during molecular dynamics simulations, but also showed regions with high flexibility. The most flexible amino acids in these regions were identified from root mean square fluctuation (RMSF) studies, and stabilizing point mutations were predicted based on their capacity to improve the calculated free energy of unfolding. Disulfide bonds were also designed at sites with suitable geometries and selected based on their location at flexible sites, assessed by B-factor calculation. Molecular dynamics simulations allowed the identification of five mutants with lower RMSF of the overall structure at 400 K, compared to wild-type TaCA. Comparison of free-energy landscapes between wild-type TaCA and the most promising mutants, Pro165Cys–Gln170Cys and Asn140Gly, showed an increased conformational stability of the mutants at 400 K.