The use of different energy sources and the worry of running out of some of them in the modern world have made factors such as environmental pollution and even energy sustainability vital. Vital resources for humanity include water, environment, food, and energy. As a result, building strong trust in these resources is crucial because of their interconnected nature. Sustainability in security of energy, water and food, generally decreases costs and improves durability. This study introduces and describes the components of a system named “Desktop Energetic Dark Greenhouse” in the context of the quadruple nexus of water, environment, food, and energy in urban life. This solution can concurrently serve to strengthen the sustainable security of water, environment, food, and energy. For home productivity, a small-scale version of this project was completed. The costs and revenues for this system have been determined after conducting an economic study from the viewpoints of the investor and the average household. The findings indicate that the capital return period is around five years from the investor’s perspective. The capital return on investment for this system is less than 4 years from the standpoint of the households. According to the estimates, this system annually supplies about 20 kg of vegetables or herbs, which means about one third of the annual needs of a family.

In most studies on hydroclimatic variability and trend, the notion of change point detection analysis of time series data has not been considered. Understanding the system is crucial for managing water resources sustainably in the future since it denotes a change in the status quo. If this happened, it is difficult to distinguish the time series data’s rising or falling tendencies in various areas when we look at the trend analysis alone. This study’s primary goal was to describe, quantify, and confirm the homogeneity and change point detection of hydroclimatic variables, including mean annual, seasonal, and monthly rainfall, air temperature, and streamflow. The method was employed using the four-homogeneity test, i.e., Pettitt’s test, Buishand’s test, standard normal homogeneity test, and von Neumann ratio test at 5% significance level. In order to choose the homogenous stations, the test outputs were divided into three categories: “useful”, “doubtful”, and “suspect”. The results showed that most of the stations for annual rainfall and air temperature were homogenous. It is found that 68.8% and 56.2% of the air temperature and rainfall stations respectively, were classified as useful. Whereas, the streamflow stations were classified 100% as useful. Overall, the change point detection analyses timings were found at monthly, seasonal, and annual time scales. In the rainfall time series, no annual change points were detected. In the air temperature time series except at Edagahamus station, all stations experienced an increasing change point while the streamflow time series experienced a decreasing change point except at Agulai and Genfel hydro stations. While alterations in streamflow time series without a noticeable change in rainfall time series recommend the change is caused by variables besides rainfall. Most probably the observed abrupt alterations in streamflow could result from alterations in catchment characteristics like the subbasin’s land use and cover. These research findings offered important details on the homogeneity and change point detection of the research area’s air temperature, rainfall, and streamflow necessary for the planers, decision-makers, hydrologists, and engineers for a better water allocation strategy, impact assessment and trend analyses.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

Climate and vegetation are variables of the physical space that have a dynamic and interdependent relationship. Flora modifies climatic elements and gives rise to a microclimate whose characterization is a function of regional climatic conditions and vegetation structure. The objective of this work was to compare the climatic variations (inside and outside) of the Caldén Forest in the Parque Luro Provincial Reserve. Temperature, relative humidity, wind speed, wind direction and precipitation data from two meteorological stations for 2012 were analyzed and statistically compared. The influence of the forest on climatic parameters was demonstrated and it was found that the greatest variations were in wind speed, daily temperature and precipitation.

Alfalfa is considered the most used forage crop in the world, its main use is for cattle feeding, due to its high nutritional value, specifically in protein and digestible fiber. Currently, the trend in agriculture is to reduce the application of chemicals and among them are fertilizers that pollute soil and water, so the adoption of new technologies and other not so new is becoming a good habit among farmers. Nanotechnology in the plant system allows the development of new fertilizers to improve agricultural productivity and the release of mineral nutrients in nanoforms, which has a wide variety of benefits, including the timing and direct release of nutrients, as well as synchronizing or specifying the environmental response. Biofertilizers are important components of integrated nutrient management and play a key role in soil productivity and sustainability. While protecting the environment, they are a cost-effective, environmentally friendly and renewable source of plant nutrients to supplement chemical fertilizers in the sustainable agricultural system. Nanotechnology and biofertilization allow in a practical way the reduction in the application of chemicals, contributing to the sustainability of agriculture, so this work aims to review the relevant results on biofertilization, the use of nanotechnology and the evaluation of the nutritional composition of alfalfa when grown with the application of biofertilizers.

One of the biggest environmental problems that has affected the planet is global warming, due to high concentrations of carbon (CO₂), which has led to crops such as coffee being affected by climate change caused by greenhouse gases (GHG), especially by the increase in the incidence of pests and diseases. However, carbon sequestration contributes to the mitigation of GHG emissions. The objective of this work was to evaluate the carbon stored in above and below ground biomass in four six-year-old castle coffee production systems. In a trial established under a Randomized Complete Block Design (RCBD) with the treatments Coffee at free exposure (T1), Coffee-Lemon (T2), Coffee-Guamo (T3) and Coffee-Carbonero (T4), at three altitudes: below 1,550 masl, between 1,550 and 2,000 masl and above 2,000 masl. Data were collected corresponding to the stem diameters of coffee seedlings and shade trees with which allometric equations were applied to obtain the carbon variables in the aerial biomass and root and the carbon variables in leaf litter and soil obtained from their dry matter. Highly significant differences were obtained in the four treatments evaluated, with T4 being the one that obtained the highest carbon concentration both in soil biomass with 100.14 t ha^-1 and in aerial biomass with 190.42 t ha^-1.