Vision-based techniques are frequently used to compute the dynamic deflections of bridges but they are rather computationally complicated and require demanding instrumentation. In this article, we show that it is possible to reconstruct the 2-D kinematics of flexible bridges using a simplified algorithm to analyze common video imagery. The only requirements are that the movement of the control points is clearly visible on the images and that next to each control point, there exist vertical and horizontal bridge elements defining the image scale. We applied this technique during controlled, forced excitations of a timber bridge that was stiff in the vertical but very flexible in the lateral axis because of cumulated damage. We used videos from low-cost cameras, in which the changes of the pixel coordinates of several control points during excitation events and their attenuation were clear. These videos were obtained during two annual structural health monitoring surveys using numerous sensors (Global Navigation Satellite Systems (GNSS), robotic total station (RTS), accelerometers), and hence the output of the video analysis was fully controlled. Because of various errors, the transformation of the video image coordinates into bridge coordinates yielded spurious deflections along the main axis of the bridge, which were used to control the uncertainty of our results. We found that the computed lateral deflections (i) were statistically significant, (ii) satisfied structural constraints, and (iii) were consistent with structural estimates derived from other sensors. Additionally, they provided accurate estimates of the natural frequency and the damping factor of the bridge. This approach can be applied in other cases of monitoring of flexible structures if the requirements for planar deformation, pixel resolution and scale definition are satisfied.

Eutrophication, a global threat that leads to degradation of freshwater and seawater aquatic ecosystems, is driven by excessive nutrient loading. This study explores the sustainable management of eutrophic water bodies with the application of natural and modified clay-based materials as a practical solution to mitigate eutrophication by removing ammonium and orthophosphate ions. Comparative analyses of six materials: natural zeolite, bentonite, and perlite, along with their modification with calcium and iron, were assessed after kinetic analysis of each material. Batch adsorption experiments were performed to evaluate the material’s performance in fresh and seawater. Fitting experimental data assessed adsorption kinetics to pseudo-second-order models. Furthermore, Langmuir isotherm models were employed to determine each material’s maximum adsorption capacity for ammonium and orthophosphate ion uptake. The results revealed that freshwater applications of modified zeolite or natural bentonite achieved better orthophosphate ion removal efficiency from seawater, whereas employing natural zeolite maximized the ammonium ion removal efficiency in freshwater bodies. Finally, orthophosphate and ammonium ion removal efficiency results for almost all materials were diminished in seawater. This research contributes valuable insights to the development of efficient and sustainable nutrient removal methodologies to remediate natural eutrophic water bodies and protect aquatic ecosystems.

Eutrophication of freshwater bodies is primarily caused by excessive nitrogen and phosphorus, resulting in significant environmental challenges, including harmful algal blooms and hypoxia. This review examines the potential for natural and modified zeolites to act as adsorbents and regulate nutrient concentrations in eutrophic freshwater ecosystems, excluding applications for wastewater or industrial water effluents. Natural zeolites are effective adsorbents of ammonium, whereas modified zeolites (with aluminum, iron, calcium, and many others) have been noted to have enhanced phosphate adsorption and a higher overall nutrient removal efficiency. The application of modified zeolites for controlling eutrophication in freshwater bodies has proven to have high efficiency in adsorbing nitrogen and phosphorus, resulting in reduced nutrient release from sediments and improved water quality in shallow lakes and reservoirs. This review describes the adsorption mechanisms and modification methods, with an appreciation for the multifunctional role of zeolites in nutrient immobilization and capping sediments. Finally, it presents the potential to use zeolite-based materials in eutrophic freshwater restoration through sustainable circular economy approaches. Zeolite materials present ample environmental applications for cost-effective and targeted mitigation approaches to freshwater eutrophication.

Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tracking changes over time, enabling the evaluation of water bodies’ trophic status. This research presents a novel and replicable methodology able to derive accurate phenological patterns using remote sensing data. The methodology proposed uses the two-decade MODIS-Aqua surface reflectance dataset, analyzing data from 30-point stations and calculating chlorophyll-a concentrations from NASA’s Ocean Color algorithm. Then, a correction process is implemented through a robust, simple statistical analysis by applying LOESS smoothing to detect and remove outliers from the extensive dataset. Different scenarios are reviewed and compared with field data to calibrate the proposed methodology accurately. The results demonstrate the methodology’s capacity to produce consistent chlorophyll-a time series and to present phenological patterns that can effectively identify key indicators and trends, resulting in valuable insights into the coastal body’s trophic state. The case study of the Ambracian Gulf is characterized as hypertrophic since algal bloom during August reaches up to 5 mg/m³, while the replicate case study of Aitoliko shows algal bloom reaching up to 2.5 mg/m³. Finally, the proposed methodology successfully identifies the positive chlorophyll-a climate tendencies of the two selected Greek water bodies. This study highlights the value of integrating statistical methods with remote sensing data for accurate, long-term monitoring of water quality in aquatic ecosystems.

The present work, which has been carried out in the framework of EEA project BLUE-GREENWAY, is a contribution to the study of the evolution of hypoxia/anoxia in Aitoliko lagoon, Greece. The study area suffers from anoxia which is a very important environmental problem lately mainly due to anthropogenic activities. Unpublished data from two measurement campaigns (2013–2014, 2023) have been used, and a 3D ocean model (SINMOD) has been configured for the region, that couples hydrodynamics, biochemistry and ecology. The analysis of model results includes monthly, annual and interannual variability of fields of dissolved oxygen, temperature, salinity, density, currents and wind as well as Brunt-Väisala frequency and Richardson number. Main results concerning oxygen are: a) the lagoon shows anoxic behavior at 5–7 m depth with a seasonal dependence, b) the seasonal variability in the upper water column with deeper ventilation during winter when the surface stratification is weaker than that during summer, c) anoxic water is reaching the surface of the lagoon for a short period of time.