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Climate change and population growth are driving the increasing demand for alternative water sources in agriculture. Nutrient-rich treated municipal wastewater emerges as a potential alternative for agriculture production. Therefore, a pot experiment using zeolite as the growing substrate to simulate hydroponic conditions was conducted to assess the impacts of fully treated municipal wastewater and partially treated wastewater that undergone only mechanical treatment step on basil (Ocimum basilicum cv. Edwina) production, aiming to explore the potential of nutrient recovery from these wastewater sources. Tap water and optimal liquid fertilizer were utilized as negative and positive controls, respectively. Results showed that primarily treated wastewater significantly enhanced basil production compared to the tap water, although the large relative increase was partly attributable to the extremely low biomass under tap-water irrigation. However, with consistently greater production and nutrient concentrations produced by the positive control, nutrient supplementation was still required in the wastewater treatments to achieve greater production and nutrient levels comparable to those with complete mineral nutrient solution. Analysis of selected heavy metals indicated no evidence of excessive accumulation in basil shoots under the conditions of this study, although comprehensive food safety assessment would require evaluation of additional contaminants, including microbiological hazards and emerging pollutants. The findings provide insights into the potential of treated municipal wastewater reuse for nutrient recovery in controlled agricultural systems.

Collaboration between academia and industry has been demonstrated to be vital for students’ career skill development and employability. These partnerships can bridge the gap between theoretical and practical applications by promoting internships, networking events, and collaborative research projects. Employers in any laboratory environment, including water and wastewater utility laboratories, value experience in both soft skills, such as communication and teamwork, as well as technical skills with basic and advanced analytical chemistry instrumentation. Collaborative partnerships can lead to unique research opportunities, help guide academic curricula and standards to better match industry needs, and expose students to real-world experiences. Academic institutions also benefit from access to industry resources that would otherwise limit teaching and research opportunities. Ultimately, these types of collaborations can contribute to preparing students for various job markets while generating academic growth and industrial interest. This article will discuss how the City of Wichita Falls Cypress Environmental Laboratory has worked to bridge this gap by collaborating with three universities to help prepare students for entering the workforce.

With carbon dioxide (CO2) levels continuing to rise in the coming decades and threatening agro-ecosystems worldwide, it is crucial to understand the impact of elevated CO2 on global food production and security. Elevated CO2 levels have been found to reduce micronutrients such as Zinc (Zn) and Iron (Fe) in staple crops, potentially exacerbating the already existing global micronutrient deficiency issue. However, as vegetables serve as another key source of micronutrients, it remains uncertain to what extent this negative effect on micronutrient levels also applies to them. To address this, we investigated the effects of elevated CO2 on Zn and Fe in vegetables using a meta-analysis. As expected, we found a significant increase (27%, 95% CI: 14-41%) in vegetable biomass production under elevated CO2 levels. Elevated CO2 (i) significantly reduced overall Zn concentration in vegetables by 8.9% (95% CI: 4-14%), while this effect was pronounced only in fruit vegetables (11%), but not in leafy and stem vegetables; (ii) consistently exhibited minimal effects on Fe concentration in vegetables. In the context of climate change with rising CO2 levels, these findings suggest that elevated CO2 could potentially exacerbate Zn deficiencies through vegetable consumption, albeit with enhanced vegetable yields. Furthermore, as the global population increasingly adopts vegetarian diets in the future, these results underscore the need for mitigation strategies to address potential future micronutrient deficiencies.

.Abstract Aquatic ecosystems in mountainous regions are crucial for fulfilling natural and anthropogenic water demands around the world. This study integrates Escherichia coli (E.  coli) enumeration, microbial source tracking (MST), and environmental DNA (eDNA) analysis to identify sources of fecal contamination in oligotrophic mountain waters. Conducted in an area with intense tourism and traditional reindeer herding, this research addresses the urgent need to identify fecal pollution sources to safeguard the water quality of these vital ecosystems. Our study reveals that E. coli levels vary significantly across different locations and times, suggesting varied sources of contamination from humans, wildlife, and livestock animals. MST techniques, alongside eDNA analysis, provided insights into the complex patterns of fecal pollution, allowing for the distinction between human and animal contributions to water contamination. Our findings highlight the importance of combining various analytical methods to track fecal pollution sources effectively, and to develop targeted strategies for water quality management.

As demand for food continues to rise, innovative methods are needed to sustainably and efficiently meet thegrowing pressure on agriculture. Indoor farming and controlled environment agriculture have emerged aspromising approaches to address this challenge. However, optimizing fertilizer usage, ensuring homogeneousproduction, and reducing agro-waste remain substantial challenges in these production systems. One potentialsolution is the use of optical sensing technology, which can provide real-time data to help growers makeinformed decisions and enhance their operations. optical sensing can be used to analyze plant tissues, evaluatecrop quality and yield, measure nutrients, and assess plant responses to stress. This paper presents a systematicliterature review of the current state of using spectral-optical sensors and hyperspectral imaging for indoorfarming, following the PRISMA 2020 guidelines. The study surveyed existing studies from 2017 to 2023 toidentify gaps in knowledge, provide researchers and farmers with current trends, and offer recommendations andinspirations for possible new research directions. The results of this review will contribute to the development ofsustainable and efficient methods of food production.

Accurate and rapid determination of moisture content is essential in crop production and decision-making for irrigation. Near-infrared (NIR) spectroscopy has been shown to be a promising method for determining moisture content in various agricultural products, including herbs and vegetables. This study tested the hypothesis that NIR spectroscopy is effective in accurately measuring the moisture content of Genovese basil (Ocimum basilicum L.), with the objective of developing a respective calibration model. Spectral data were obtained from a total of 120 basil leaf samples over a period of six days. These included freshly harvested and detached leaves, as well as those left in ambient air for 1–6 days. Five spectra were taken from each leaf using a handheld NIR spectrophotometer, which covers the first and second overtones of the NIR spectral region: 950–1650 nm. After the spectral acquisition, the leaves were weighed for fresh mass and then put in an oven for 72 h at 80 °C to determine the dry weight and calculate the reference moisture content. The calibration model was developed using multivariate analysis in MATLAB, including preprocessing and regression modeling. The data obtained from 75% of the samples were used for model training and 25% for validation. The final model demonstrates strong performance metrics. The root mean square error of calibration (RMSEC) is 2.9908, the root mean square error of cross-validation (RMSECV) is 3.2368, and the root mean square error of prediction (RMSEP) reaches 2.4675. The coefficients of determination for calibration (R2C) and cross-validation (R2CV) are consistent, with values of 0.829 and 0.80, respectively. The model’s predictive ability is indicated by a coefficient of determination for prediction (R2P) of 0.86. The range error ratio (RER) stands at 11.045—highlighting its predictive performance. Our investigation, using handheld NIR spectrophotometry, confirms NIR’s usefulness in basil moisture determination. The rapid determination offers valuable insights for irrigation and crop management.

The atmospheric carbon dioxide (CO2) concentration has been progressively increasing since the onset of the Industrial Revolution and has already reached at around 420 μmol mol⁻¹ nowadays. It is well recognized that elevated CO2 concentration stimulates the yield for C3 crops, but it also simultaneously changes the essential nutrients. However, compared with the main crops, far less attention has been devoted to the effects of elevated CO2 concentration on vegetable growth and quality. Vegetables are highly recommended in daily diets due to their diverse range of beneficial compounds, such as vitamins, antioxidants, minerals, and dietary fiber.  In controlled greenhouse vegetable cultivation, elevated CO2 has been widely adopted as an agricultural practice for enhancing plant growth. Thus, understanding both vegetable growth and nutrient status is crucial to assess the potential impacts of elevated CO2 on future food security in both natural and controlled environments. However, much more attention has been paid to biomass enhancement, and elevated CO2 effects on nutrient quality are less recognized. Among the nutrients, Zinc (Zn) and Iron (Fe) are essential elements in humans. Previous studies have demonstrated a decreasing trend of Zn and Fe in main crops such as wheat and rice with increased CO2, while less is known about whether this alleviation effect on Zn and Fe can apply to vegetables. Therefore, a meta-analysis was conducted in this study to evaluate the influence of elevated CO2 concentration in the atmosphere on vegetable Fe and Zn status, and quantify the potential impact of future climate on nutrition security.

Modern civilization is defined by the unsustainable consumption of most of the Earth’s natural resources and the contribution with different kinds of hazards to the air, water and soil. More than two centuries since the industrial revolution have caused the accu-mulation of different contaminants in different forms in most of the environmental compartments, therefore, there is an urgent need to shift this trend to sustainable solu-tions where protecting our environment needs to be in the core of new strategies. Waste management is one of the major areas where development towards sustainable devel-opment has a potential by implementing new strategies to protect the environment and also providing societies with secondary resources for the continuation of living on this Earth. In this chapter, an integrated waste management system based on the European hierarchy is introduced as an input towards reducing the impact of losing virgin mate-rials as wastes. In addition, international and European regulations and policies are also presented as a crucial tool to save the environment.

This article summarizes and performs a systematic analysis using experimental results from recent research on ammonium recovery from aqueous sources using biochar. Numerous studies have focused on using different materials to produce biochar adsorbents, and many have attempted to draw conclusions about the physical or chemical characteristics that dominate the adsorption to infer the mechanism. However, to date, there has not been statistical analysis performed on a large set of adsorption data and physical/chemical characteristics of chars to be able to draw conclusions about ammonium adsorption mechanisms. From this analysis, it was found that consistency in experimental methods and characteristic measurement reporting is lacking, and therefore it is difficult to perform metadata analysis and draw conclusions about ammonium adsorption on biochar. Among the important factors influencing ammonia recovery proposed in literature, the meta-analysis only strongly supports the effect of BET surface area and NH4+ concentration, with weaker support for the importance of cation exchange capacity and pyrolysis temperature. This suggests that standard procedures for biochar production, experiments and analysis of physical and chemical characteristics are needed to usefully compare results across different studies. Examples of the present difficulty in identifying trends across studies are shown by comparing clusters in the data identified by the analysis. The ability to make such comparisons would provide clearer direction in how best to further improve the adsorption capacity of biochars.

Fault detection is an important part of process supervision, especially in processes where there are strict requirements on the process outputs like in wastewater treatment. Statistical control charts such as Shewhart charts, cumulative sum (CUSUM) charts, and exponentially weighted moving average (EWMA) charts are common univariate fault detection methods. These methods have different strengths and weaknesses that are dependent on the characteristics of the fault. To account for this the methods in their base forms were tested with drift and bias sensor faults of different sizes to determine the overall performance of each method. Additionally, the faults were detected using two different sensors in the system to see how the presence of active process control influenced fault detectability. The EWMA method performed best for both fault types, specifically the drift faults, with a low false alarm rate and good detection time in comparison to the other methods. It was shown that decreasing the detection time can effectively reduce excess energy consumption caused by sensor faults. Additionally, it was shown that monitoring a manipulated variable has advantages over monitoring a controlled variable as setpoint tracking hides faults on controlled variables; lower missed detection rates are observed using manipulated variables.