Green walls and green dams are increasingly being considered as part of many national and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria), from 1972 to 2019, by using Landsat imagery, Land Change Modeler, and OpenLand package. The future evolution of pine plantations, for the year 2029, was also forecasted, based on an anthropogenic scenario (i.e., anthropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but, after that, pine plantations deteriorated significantly, due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land change modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation continues at the same rate, the green dam in the Moudjbara region will disappear during the next few decades. Being aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy, by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation. We strongly recommend moving away from the singular tree planting focus, to diversifying desertification control methods.

An increasing amount of CO₂ emissions from the household sector of Iran led us to analyze the inequality and understand the possible driving force behind the CO₂ emissions. The study of inequality provides information to policy-makers to point policies in the right direction. By considering the differences in the socio-economic factors of provinces, the study aims to analyze the inequality in CO₂ emissions and different kinds of energy consumption, including oil, gas and electricity, for the household sector of Iran’s provinces between 2000 and 2017. For this aim, the Theil index and Kaya factor, as a simple and common method, were considered to evaluate the inequality in both CO₂ emissions and energy consumption, and determine the driving factor behind CO₂ emissions. According to the results, inequality in oil and natural gas consumption were increasing, electricity was almost constant; however, CO₂ emissions experienced a decreasing trend for the study period. The Theil index changed from 0.4 to 0.65 for oil, from 0.18 to 0.22 for natural gas, from 0.17 to 0.15 for electricity, and from 0.2 to 0.14 for CO₂ emissions between 2001 and 2017. In addition, the results of the inequality study indicated that most of the inequalities belong to within-group inequalities in energy consumption and CO₂ emissions. The results of the Kaya factor indicate that the second factor, energy efficiency, with a 0.21 value was the main driving factor of inequalities in CO₂ emissions; however, the first factor, energy consumption, can be a potential factor for inequality in the following years, as it increased from 0.00 to 0.11 between 2001 and 2017. It seems that by removing the energy subsidy policy in 2010 and 2013, low-standard and energy-wasting old vehicles were the most effective factors of energy inefficiency in the household sector, which need more accurate policy-making.

The discharge of nutrients and organic pollutants is increasing at an alarming rate, driven by the rapid development of human activities. This growing pollution is contributing to significant environmental issues, including eutrophication, making the treatment of wastewater essential before its release into the environment. Prior to being released into water bodies, treated wastewater must undergo rigorous laboratory analysis. For this reason, analysis using standard methods was carried out at the Laboratory Waterworks in Debrecen on multiple samples taken from various wastewater treatment plants in Hungary. The primary objective of this research was to assess the quality of effluents from (14) wastewater treatment plants and investigate their efficiency by measuring various physicochemical and microbiological parameters as indicators. The microbiological indicator monitored was the heterotrophic count (HPC) by estimating its total number. The results revealed that substantial removal efficiencies were demonstrated by parameters including total nitrogen (TN), chemical oxygen demand (COD), and biochemical oxygen demand (BOD₅), with reductions averaging 91%, 92%, and 87%, respectively. However, the reduction in nitrogenous compounds (nitrite NO₂⁻ and nitrate NO₃⁻) was limited, indicating areas for process improvement. Recommendations for enhancing treatment efficiency are proposed to optimize the overall performance of the wastewater treatment plants.

Drought has emerged as a major challenge to global food and water security, and is particularly pronounced for Algeria, which frequently grapples with water shortages. This paper sought to monitor and assess the temporal and spatial distribution of drought severity across northern Algeria (excluding the Sahara) during the growing season from 2011 to 2022, while exploring the relationship between the normalized difference vegetation index (NDVI) anomaly and climate variables (rainfall and temperature). Temporal NDVI data from the Terra moderate resolution imaging spectroradiometer (MODIS) satellite covering the period 2000–2022 and climate data from the European Reanalysis 5th Generation (ERA5) datasets collected during the period 1990–2022 were used. The results showed that a considerable portion of northern Algeria has suffered from droughts of varying degrees of severity during the study period. The years 2022, 2021, 2016, and 2018 were the hardest hit, with 76%, 71%, 66%, and 60% of the area, respectively, experiencing drought conditions. While the relationship between the NDVI anomaly and the climatic factors showed variability across the different years, the steady decrease in vegetation health indicated by the NDVI anomaly corroborates the observed increase in drought intensity during the study period. We conclude that the MODIS-NDVI product offers a cost-efficient approach to monitor drought in data-scarce regions like Algeria, presenting a viable alternative to conventional climate-based drought indices, while serving as an initial step towards formulating drought mitigation plans.

The climate and environment of metropolitan areas have been negatively impacted by swift urbanization and industrialization. Surface Urban Heat Islands (SUHIs) are among the most critical environmental phenomena. This research focused on the spatiotemporal analysis of land use/land cover (LULC) changes in relation to surface urban heat islands and their interconnections from 1992 to 2022. Land Surface Temperature (LST), LULC, and LULC indices, such as the Normalized Difference Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI), were generated using Landsat data. Urban hot spots (UHSs) were identified, and the Urban Thermal Field Variance Index (UTFVI) was then used to evaluate the spatiotemporal variation in thermal comfort. The results indicated LST values between a low of 14.24 and a maximum of 46.30. Urban areas and exposed surfaces, such as open or bare soil, exhibit the highest surface radiant temperatures. Conversely, regions characterized by vegetation and water bodies have the lowest. Additionally, this study explored the correlation between LULC, LULC indices, LST, and SUHIs. LST and NDBI show a positive relationship because of urbanization and industrialization (R² = 0.57 for the year 1992, R² = 0.38 for the year 2010, and R² = 0.35 for the year 2022), while LST shows an inverse relationship with NDVI and NDMI. Urban development should account for thermal sensitivity in densely populated regions. This study introduced an innovative spatiotemporal framework for monitoring long-term changes in urban surface environments. Furthermore, this research can assist planners in creating urban green spaces in cities of developing nations to minimize the adverse impacts of urban heat islands and improve thermal comfort.

Increasing pollution of aquatic ecosystems due to anthropogenic activities underscores the urgent need for effective water quality monitoring. This study evaluates the use of fish scales from chub (Squalius cephalus) and nase (Chondrostoma nasus) as non-invasive bioindicators of trace and macroelement pollution in the Maros/Mureș River. We conducted qualitative and quantitative elemental analyses using X-ray fluorescence (XRF) and inductively coupled plasma optical emission spectrometry (ICP-OES). Scanning electron microscopy (SEM) revealed distinct scale structures among the species studied. Concentrations of Ca, K, Mg, Na, P, S, Al, Ba, Cu, Cr, Fe, Mn, Sr, and Zn were measured by ICP-OES. Our findings indicate significant variability in elemental accumulation in fish scales, supporting their potential use as bioindicators of environmental pollution, with variability depending on the ecological characteristics of the species. This methodology offers promising applications for modern interdisciplinary monitoring programs.