The eddy covariance (EC) technique is a precise and reliable method for quantifying net ecosystem exchange (NEE) of carbon dioxide (CO2) at the field scale. Despite the sustained increase in atmospheric CO2 levels, seasonality in NEE remains substantial, driven by the absorption and emission dynamics of terrestrial ecosystems. This study monitors seasonal variability in NEE using EC flux-tower data and Sentinel-2A multispectral satellite imagery. Flux tower data from six Prairie View A&M University sites and Sentinel-2A data were integrated to estimate gross primary production (GPP) using an empirically derived Light Use Efficiency (LUE) model. The R2 values ranged from 0.53 to 0.68 across the flux tower locations, with RMSE of 40.93 gC m 2 and MAE of 33.19 gC m⁻2 10 d⁻1, indicating the LUE model captured the seasonal dynamics of GPP with moderate skill between EC and Sentinel-2A satellite observations. Seasonally, the carbon sink increased markedly during spring and summer, corresponding to the hottest and wettest periods, and decreased post-harvest, such as fall and winter, reflecting the influence of agricultural practices. In addition, pastureland exhibits more stable and sustained carbon uptake, whereas croplands show greater variability driven by phenological cycles and management practices. This study underscores the potential of integrating satellite observations with EC data to scale up local flux tower measurements to broader ecosystem assessments. Such approaches provide valuable insights into the spatiotemporal dynamics of carbon fluxes, advancing our understanding of ecosystem responses to environmental and anthropogenic drivers.
Desalination’s high energy demand has increasingly limited the sustainable supply of fresh water in arid coastal areas, posing a major challenge within the water-energy nexus. This paper develops and validates a comprehensive techno-economic framework that decouples water security from fossil fuel price volatility. Specifically, this study evaluates the integration of intermittent wind energy and Public-Private Partnership (PPP) financial models, using the Dakhla region of Morocco as a baseline case. The assessment rigorously examines the mutual dependence of surplus grid electricity sales, public capital subsidies, and desalination load factors across four distinct techno-economic scenarios. The results demonstrate a profound financial synergy: the combination of wind energy export revenues and targeted public grants drastically reduces the Levelized Cost of Water (LCOW) from a fossil-dependent baseline of 8,38 MAD/m3 down to an optimal 2,71 MAD/m3. The findings reveal that utilizing the national electrical grid to monetize surplus wind energy is the most financially viable strategy to overcome the high costs of renewable desalination. Furthermore, closing the water affordability gap for agriculture cannot be achieved by technology alone; it requires a synergistic approach combining these dynamic energy-wheeling regulations with targeted public subsidies. By doing so, actively decoupling desalination from fossil fuels transforms a historically cost-prohibitive process into a sustainable, scalable driver for both agricultural expansion and regional decarbonisation. Ultimately, this research demonstrates that large-scale desalination achieves long-term economic sustainability only when engineered as a fully integrated renewable energy asset rather than an isolated water facility.
Water and energy are critical yet interconnected resources in agriculture, linking to land use, crop production, and greenhouse gas (GHG) emissions within the Water-Energy-Food (WEF) and Carbon nexus. This study develops a single-objective constrained nonlinear programming model to maximize total cropping profit by optimizing irrigation water and land allocation, while internalizing relevant environmental costs. The profit function integrates crop revenues minus variable costs, including water, energy, and a carbon price applied to GHG emissions. Crop yield is simulated using Stewart’s water production functions; energy use is linked to irrigation water via diesel pumping; and emissions are quantified for both irrigation and all other farm operations. Constraints include total water availability, maximum irrigation rates, and irrigated area limits. Applied to a case study of cotton-wheat rotation in Toowoomba region, Australia, using government data and expert interviews, the model demonstrates optimal allocations for different resources. Under current costs and a 38.92 GL water limit, the optimum allocation is 72% (7,768 ha) of irrigated area to wheat (2.02 ML/ha) and 28% (3,003 ha) to cotton (7.74 ML/ha). Gross margins are AUD 4,132/ha for cotton and AUD 1,584/ha for wheat. Total GHG emissions are 20.91 ktCO2e (wheat) and 9.77 ktCO2e (cotton), with intensities of 2.69 tCO2e/ha (wheat) and 3.25 tCO2e/ha (cotton). The model provides a transferable tool for quantifying trade-offs between profitability, resource efficiency, and environmental performance in irrigated cropping systems.
The installation of sand filters in cooling water systems is essential to maintain optimum performance and minimise maintenance downtime. Sand filters are commonly used in cooling towers to remove suspended solids, algae and other particles that can clog the system and reduce efficiency. The benefits of sand filters in cooling water systems include reducing fouling in the cooling water stream, where sand filters significantly reduce fouling of heat exchangers and other components in the cooling system, helping to reduce operating costs and downtime. The importance of cooling water treatment with sand filters is to improve water quality. Sand filters can remove total suspended solids (TSS), reduce conductivity, chemical oxygen demand (COD), biochemical oxygen demand (BOD) and turbidity. The purpose of this study was to investigate the performance of installing a sand filter in the cooling water return line to reduce the amount of effluent due to high levels of contaminants in the cooling water and also to reduce the use of fresh water. TSS dropped from 1200 mg/L to 350 mg/L, conductivity from 1700 µS/cm to 700 µS/cm, COD from 230 mg/L to 150 mg/L, BOD from 35 mg/L to 15.6 mg/L and turbidity from 5.6 NTU to 3.2 NTU after the sand filter was installed. After the sand filter was installed, the recirculation rate increased by approximately 16.5%, the blowdown rate decreased by approximately 24%, the evaporation rate decreased by approximately 20.5% and the water make-up decreased by approximately 14.2%.
Water pollution is one of the most serious environmental challenges the world faces nowadays. Adsorption has emerged as a promising method for addressing this issue. In this study, novel adsorbents were synthesized by combining zeolitic imidazolate framework-8 (ZIF-8) and zeolitic imidazolate framework-67 (ZIF-67) with layered triple hydroxide (LTH)/calcined layered triple hydroxide (cLTH) through various synthesis approaches. These adsorbents were thoroughly characterized using a range of techniques to determine their textural properties, crystallinity, and functional groups before being applied to treat wastewater samples contaminated with a variety of pollutants, including acid red 1 (AR1), methyl orange (MO), crystal violet (CV), methylene blue (MB), 2-nitrophenol (2NP), bisphenol A (BPA), lead (Pb(II)), and chromium (Cr(VI)). Rather than assuming that hybridization would generally enhance adsorption performance, this work adopts a systematic comparative screening approach to evaluate pristine ZIFs, LTH/cLTH, and their nanocomposites across a broad pollutant matrix, revealing selective, pollutant-dependent enhancement and establishing a performance map that identifies best-in-class adsorbent–pollutant pairings. For instance, the adsorption capacities of CV onto cLTH, ZIF-8, and cLTH@ZIF-8 nanocomposite were found to be 286.3, 406.8, and 1335.3 mg/g, respectively, demonstrating the superiority of the nanocomposite. Additionally, the LTH@ZIF-67 nanocomposite showed superior CV adsorption performance (1027.9 mg/g) relative to pristine LTH (318.0 mg/g) and ZIF-67 (892.3 mg/g). Zeta potential measurements and the textural properties of the synthesized materials suggest that the adsorption of the aforementioned pollutants onto the synthesized adsorbents (including the nanocomposites) is likely governed by multiple mechanisms. Overall, the findings reported herein reveal the potential of the novel adsorbents synthesized in this study in boosting water decontamination.
