AI-assisted systematic review on remediation of contaminated soils with PAHs and heavy metals.

This systematic review addresses soil contamination by crude oil, a pressing global environmental issue, by exploring effective treatment strategies for sites co-contaminated with heavy metals and polycyclic aromatic hydrocarbons (PAHs). Our study aims to answer pivotal research questions: (1) What are the interaction mechanisms between heavy metals and PAHs in contaminated soils, and how do these affect the efficacy of different remediation methods? (2) What are the challenges and limitations of combined remediation techniques for co-contaminated soils compared to single-treatment methods in terms of efficiency, stability, and specificity? (3) How do various factors influence the effectiveness of biological, chemical, and physical remediation methods, both individually and combined, in co-contaminated soils, and what role do specific agents play in the degradation, immobilization, or removal of heavy metals and PAHs under diverse environmental conditions? (4) Do AI-powered search tools offer a superior alternative to conventional search methodologies for executing an exhaustive systematic review? Utilizing big-data analytics and AI tools such as Litmaps.co, ResearchRabbit, and MAXQDA, this study conducts a thorough analysis of remediation techniques for soils co-contaminated with heavy metals and PAHs. It emphasizes the significance of cation-π interactions and soil composition in dictating the solubility and behavior of these pollutants. The study pays particular attention to the interplay between heavy metals and PAH solubility, as well as the impact of soil properties like clay type and organic matter on heavy metal adsorption, which results in nonlinear sorption patterns. The research identifies a growing trend towards employing combined remediation techniques, especially biological strategies like biostimulation-bioaugmentation, noting their effectiveness in laboratory settings, albeit with potentially higher costs in field applications. Plants such as Medicago sativa L. and Solanum nigrum L. are highlighted for their effectiveness in phytoremediation, working synergistically with beneficial microbes to decompose contaminants. Furthermore, the study illustrates that the incorporation of biochar and surfactants, along with chelating agents like EDTA, can significantly enhance treatment efficiency. However, the research acknowledges that varying environmental conditions necessitate site-specific adaptations in remediation strategies. Life Cycle Assessment (LCA) findings indicate that while high-energy methods like Steam Enhanced Extraction and Thermal Resistivity - ERH are effective, they also entail substantial environmental and financial costs. Conversely, Natural Attenuation, despite being a low-impact and cost-effective option, may require prolonged monitoring. The study advocates for an integrative approach to soil remediation, one that harmoniously balances environmental sustainability, cost-effectiveness, and the specific requirements of contaminated sites. It underscores the necessity of a holistic strategy that combines various remediation methods, tailored to meet both regulatory compliance and the long-term sustainability of decontamination efforts.

Investigating the applicability of UAVs in characterizing desert shrub biomass and developing biological indicators for the selection of suitable revegetation sites.

This study focused on evaluating factors influencing the growth of perennial shrubs by integrating field-based experiments and spatial analysis using unmanned aerial vehicles (UAVs) to identify ecological indicators that can help detect potential locations for restoration and revegetation of native plants. The experiment was implemented in the Al-Abduli protected area in Kuwait, which is mainly dominated by a Rhanterium epapposum community (desert shrub). Aerial imagery of the study site was acquired using UAVs during the growing season to estimate the desert shrub biomass and carbon stock. Then, soil samples were collected based on vegetation density to determine the impact of the soil's physical and chemical properties on vegetation biomass, growth, and distribution. It was found that shrub biomass was significantly correlated with crown area and shrub volume. We also observed that annual plants support the growth of perennial shrubs, as the mean shrub height and crown area (CA) are significantly higher, with averages of 0.7 m and 3 cm, respectively, in the presence of high annual plant density. However, shrubs in plots with low annual density had an average shrub height of 0.5 m and CA of 1.4 cm. Annual plants also enhance the soil by providing approximately 50% higher soil moisture, phosphorous (P), organic matter (OM), and carbon dioxide (CO2) sequestration. In addition, annual plants are mainly supported by loamy soils in the deeper soil layers. We concluded that locations covered with annual plants represent suitable soils and that this can be considered a biological indicator for convenient locations for restoration and revegetation of native perennial shrubs. Remote sensing technologies could be utilized for initial assessments to detect sites that may support annual plant growth over a large scale for classification as potential restoration and revegetation areas.