Assessment of Soil Degradation and Hazards of Some Heavy Metals, Using Remote Sensing and GIS Techniques in the Northern Part of the Nile Delta, Egypt

Soil degradation and pollution is one of the main problems threatening the sustainable development of agriculture. This study used remote sensing and geographic information system (GIS) techniques to assess the risks of soil degradation and the risks of heavy metals in some soils north of the Nile Delta. The study area suffers from salinity, alkalinity, and water logging, so a spatial degradation model was used. Relying on landsat ETM+ images and the digital elevation model (DEM), it was possible to produce a geomorphological map, and it showed that the studied area consists of two landscapes, i.e., flood plain and lacustrine plain. The results indicated that salinization, alkalization, compaction, and water logging were the main types of soil degradation in the studied area. The spatial land degradation model showed that 16.61% of soils were affected by low degrees of degradation, 74.03% were affected by moderate degrees, and 9.36% were affected by high degrees of degradation. The studied area was affected by chemical degradation risks between low and high at 90.62% and 9.37%, respectively, while the physical degradation risks varied between low, moderate, high, and very high with percentages of 9.37%, 41.53%, 40.14%, and 8.93%, respectively. The environmental risks of heavy metals were assessed in the studied area using pollution indices including, the enrichment factor (EF), the pollution load index (PLI), and the potential ecological risk index (PER)

Green Synthesis of Nanoparticles by Mushrooms: A Crucial Dimension for Sustainable Soil Management

Soil is the main component in the agroecosystem besides water, microbial communities, and cultivated plants. Several problems face soil, including soil pollution, erosion, salinization, and degradation on a global level. Many approaches have been applied to overcome these issues, such as phyto-, bio-, and nanoremediation through different soil management tools. Mushrooms can play a vital role in the soil through bio-nanoremediation, especially under the biological synthesis of nanoparticles, which could be used in the bioremediation process. This review focuses on the green synthesis of nanoparticles using mushrooms and the potential of bio-nanoremediation for polluted soils. The distinguished roles of mushrooms of soil improvement are considered a crucial dimension for sustainable soil management, which may include controlling soil erosion, improving soil aggregates, increasing soil organic matter content, enhancing the bioavailability of soil nutrients, and resorting to damaged and/or polluted soils. The field of bio-nanoremediation using mushrooms still requires further investigation, particularly regarding the sustainable management of soils

Nano-Restoration for Sustaining Soil Fertility: A Pictorial and Diagrammatic Review Article

Soil is a real treasure that humans cannot live without. Therefore, it is very important to sustain and conserve soils to guarantee food, fiber, fuel, and other human necessities. Healthy or high-quality soils that include adequate fertility, diverse ecosystems, and good physical properties are important to allow soil to produce healthy food in support of human health. When a soil suffers from degradation, the soil’s productivity decreases. Soil restoration refers to the reversal of degradational processes. This study is a pictorial review on the nano-restoration of soil to return its fertility. Restoring soil fertility for zero hunger and restoration of degraded soils are also discussed. Sustainable production of nanoparticles using plants and microbes is part of the process of soil nano-restoration. The nexus of nanoparticle–plant–microbe (NPM) is a crucial issue for soil fertility. This nexus itself has several internal interactions or relationships, which control the bioavailability of nutrients, agrochemicals, or pollutants for cultivated plants. The NPM nexus is also controlled by many factors that are related to soil fertility and its restoration. This is the first photographic review on nano-restoration to return and sustain soil fertility. However, several additional open questions need to be answered and will be discussed in this work

Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling

The proper assessment of trace element concentrations in the north Nile Delta of Egypt is needed in order to reduce the high levels of toxic elements in contaminated soils. The objectives of this study were to assess the risks of contamination for four trace elements (nickel (Ni), cobalt (Co), chromium (Cr), and boron (B)) in three different layers of the soil using the geoaccumulation index (I-geo) and pollution load index (PLI) supported by GIS, as well as to evaluate the performance of partial least-square regression (PLSR) and multiple linear regression (MLR) in estimating the PLI based on data for the four trace elements in the three different soil layers. The results show a widespread contamination of I-geo Ni, Co, Cr, and B in the three different layers of the soil. The I-geo values varied from 0 to 4.74 for Ni, 0 to 6.56 for Co, 0 to 4.11 for Cr, and 0 to 4.57 for B. According to I-geo classification, the status of Ni, Cr, and B ranged from uncontaminated/moderately contaminated to strongly/extremely contaminated. Co ranged from uncontaminated/moderately contaminated to extremely contaminated. There were no significant differences in the values of I-geo for Ni, Co, Cr, and B in the three different layers of the soil. According to the PLI classification, the majority of the samples were very highly polluted. For example, 4.76% and 95.24% of the samples were unpolluted and very highly polluted, respectively, in the surface layer of the soil profiles. Additionally, 14.29% and 85.71% of the samples were unpolluted and very highly polluted, respectively, in the subsurface layer of the soil profiles. Both calibration (Cal.) and validation (Val.) models of the PLSR and MLR showed the highest performance in predicting the PLI based on data for the four studied trace elements, as an alternative method. The validation (Val.) models performed the best in predicting the PLI, with R2 = 0.89–0.93 in the surface layer, 0.91–0.96 in the subsurface layer, 0.89–0.94 in the lowest layers, and 0.92–0.94 across the three different layers. In conclusion, the integration of the I-geo, PLI, GIS technique, and multivariate models is a valuable and applicable approach for the assessment of the risk of contamination for trace elements, and the PLSR and MLR models could be used through applying chemometric techniques to evaluate the PLI in different layers of the soil