Phytoremediation is one of the non-energy consuming processes of remediating polluted water. However, the disposal of post-remediated plants poses a threat of the re-introduction of pollutants back into the ecosystem. Re-routing remediated pollutants for commercial application could be one way to reduce the re-introduction of pollutants in an ecosystem. Heavy metal pollution in water bodies is one issue, which can be mitigated to an extent with phytoremediation. In the current study, the effect of heavy metal phytoremediation on the phytochemical fingerprint and bioactivity of Pistia stratiotes L. was investigated. Pistia stratiotes L. was subjected to different concentrations of iron (Fe) and lead (Pb), in the range of 5-20 ppm. Different parameters such as heavy metal estimation (in plants and water post-treatment), thin layer chromatography (TLC), antioxidant activity, and antiurolithic activity were measured. Post remediation, heavy metal concentration was found to be comparatively higher in roots (16.515 ± 0.008 mg.g-1 and 5.25 ± 0.086 mg.g-1 when treated with 15 ppm iron and lead respectively). TLC revealed differences between the fingerprints of treated and untreated plants. Some bands increased in intensity as the concentration of heavy metal increased, while some bands which were present in untreated, were absent in treated plant samples. Antioxidant activity of treated plants shows lesser IC50 values, compared to untreated, in that, treated leaves show better activity (IC50 = 1.8 ± 0.5220 mg.mL-1 of leaf treated with 2 ppm iron as opposed to IC50 > 5 mg.mL-1 of untreated leaf extract). The treated plants revealed good antiurolithic activity compared to untreated, in that, the percentage inhibition showed by Iron treated leaves and roots was better (96.87% and 98.95% exhibited by iron-10 ppm treated leaves and roots respectively), while the untreated showed a maximum of only 68.75% inhibition. The results suggest that the bioactivity of the plant extracts increases post-remediation. Potential applications of these extracts can be explored such as nanoparticle synthesis, drug discovery, etc.

Waters polluted with Pb and Cd have a negative impact on the environment. Padina australis grows abundantly on the coast of Palang Subdistrict, Tuban, and the local community consumes it. Macroalgae as food must be free of metal contamination. This study aims to determine the impact of Pb and Cd bioaccumulation on P. australis. Sampling was conducted at two stations, including Station I, Panyuran Village, and Station II, Glodog Village. Analysis of Pb and Cd metal levels using Atomic Absorption Spectrophotometry (AAS). Analysis of protein content using the Kjeldahl method. The data obtained was analyzed with Principle Component Analysis (PCA). The results of the analysis of Pb and Cd levels in P. australis at station II, which are 0.200 ± 0.028 and 0.021 ± 0.004 mg.kg-1 higher than station I, which are 0.194 ± 0.015 and 0.010 ± 0.001 mg.kg-1. The protein content of P. australis at station I was 4.713 ± 0.508 mg.kg-1, and at station II was 5.900 ± 0.928 mg.kg-1. This shows that P. australis is still considered good for consumption even though it has been polluted and contains Pb and Cd metals. P. australis can tolerate and does not experience severe physiological damage so it has the potential as a heavy metal phytoremediator.

Anthropogenic environmental pollution is a major development challenge in Ugandan rivers and lakes, the key drivers being industrialization, agriculture, and urbanization. The aim of the study was to assess the potential of heavy metal and microplastic contamination in River Mpanga, Fort Portal, Uganda. Triplicate water and sediment samples were collected from three sampling sites, preserved, and analyzed at the Chemistry Department, Makerere University for heavy metals, while microplastics analysis was conducted at NaFIRRI, Jinja. Sediment heavy metal contamination was assessed from the geoaccumulation index, while microplastic characterization and quantification were determined from stereomicroscopy and morphological features. Arsenic was the most prevalent metal with a mean concentration of 13.2 ppm thus higher than permissible maximum limits of WHO. The mean concentrations (ppm) of copper, lead, and cadmium were 0.01, 0.01, and 0.001 respectively, and below the permissible maximum. Sediment samples revealed very strong arsenic contamination, strong contamination for copper, moderate to strong contamination for lead, and a potential lack of contamination for cadmium. The higher concentrations of the heavy metals in the sediments compared to water could be attributed to bioaccumulation, as evidenced by the high geoaccumulation values. Microplastics occurred throughout the river and included fragments, filaments, film, pellets, form, and fibers. The presence of heavy metals and microplastics was attributed to anthropogenic activities within the river vicinity, which discharged heavy metal-laden waste into River Mpanga. High arsenic concentrations and sediment accumulation of contaminants pose serious potential public health threats to the local communities.

This paper aimed to investigate the Spatial and Temporal Variation of the air quality index (AQI) in the Amman and Zarqa Metropolitan Areas during the period 2016-2022 following the method adopted by the Environmental Protection Agency of the United States of America (EPA). Air quality data for PM10, PM2.5, O3, NO2, SO2, and CO recorded at five monitoring stations were downloaded from the official website of the Jordanian Ministry of Environment. Calculated AQI values were generally between the Good class (AQI <50) and the Moderate class (AQI 50-100) at all stations, the AQI calculations for PM10 demonstrated a noticeable increase during autumnal months, likely due to natural dust. PM2.5 demonstrated seasonal variation, with higher values in winter months where residents burn fossil fuel for heating. Stabel air in winter due to the cooled land surface, and the weak natural air mix and ventilation contribute to the deterioration of air quality. Calculated individual AQI for SO2 and NO2 reveals that all extent of the study area falls in the Good AQI class. Similarly, CO and ozone-based AQI values fluctuate within the “Good” class, with occasional episodes of compromised air quality at specific stations.

This study aimed to analyze the microplastic contamination of fresh and pindang fish and its health impact on the coast of Muncar, Banyuwangi Regency, Indonesia. In this study, a total of 115 respondents participated, providing questionnaire data on their fish consumption habits and health problems. Subsequently, spearman’s correlation coefficient, a non-parametric statistical test, was used to analyze the questionnaire data. This study also included 100 samples of marine fish, consisting of 89 fresh fish and 11 pindang fish from various types of marine species. The content of microplastic polymers detected through FTIR (Fourier-Transform Infrared Spectroscopy) was around 3-5 microplastic polymers/fish samples, and the most dominant were Polyethylene, Polyester, Polycaprolactam (Nylon 6) and Polyamide. This study showed that 94 percent of fish samples contained microplastics and only 6 percent of samples did not contain microplastics. The intensity of pindang fish consumption was positively correlated with respondents’ health symptoms and problems. Subsequently, implementing effective waste management systems and educational programs in the coastal areas is crucial in reducing the pollution of seawater resulting from inadequate waste disposal practices.

Aquatic ecosystems that are subject to urbanization and environmental changes, such as the Kapaleeswarar and Chitrakulam tanks, depend on evaluating water quality. Their complicated data present challenges for conventional approaches. The usefulness of the Mamdani fuzzy inference system in determining the water quality in these tanks is investigated in this work. It creates a comprehensive assessment based on subject-matter expertise by handling ambiguous descriptors with linguistic variables and fuzzy sets. The system’s procedures for implementation are described in detail, with an emphasis on how well they can manage interrelated variables. The study shows how well the system measures the water quality in tanks and suggests ways to improve it. Tank evaluation that incorporates the Mamdani system encourages comprehensive resource management and cultural preservation.

Polyaromatic Hydrocarbons (PAHs) in the environment have been linked to severe health effects. This study aims to assess the atmospheric pollutant and analyze the variation in PAHs, focussed on benzo[a]pyrene [B(a)P]. Among all PAHs, B(a)P is regarded as a marker for human carcinogenicity. This study reflects the B(a)P concentration and its correlation with the particulate matter (PM10 and PM2.5) in rural, peri-urban, and urban areas of Panvel Municipal Corporation, Maharashtra, India. Samples were collected during the pre & post-monsoon season for two consecutive years (Yr. 2020 and Yr. 2021). B(a)P level was determined using high-performance liquid chromatography coupled with a diode array detector. It was observed that PM2.5 and PM10 show a strong positive correlation (r=0.8-0.9) with B(a)P. It is observed that B(a)P concentrations were high in pre-monsoon w.r.t. post-monsoon, and this concentration increased spatially as we moved from rural to urban areas. Pre-monsoon B(a)P concentration varies somewhat by 5% between rural to urban areas as compared to post-monsoon. High levels of vehicular emissions and industry were associated with the distribution of B(a)P in urban areas, whereas a combination of local emissions and metropolitan area diffusion was responsible for the presence of B(a)P in peri-urban and rural areas. Also, this study captures the variation of B(a)P levels during the period of COVID-19. In future studies, Artificial Intelligence (AI) can augment the determination of PAHs in soil by improving the accuracy and speed of analysis using predictive modeling based on different input parameters to determine outliers in soil PAH data, building sensor networks for real-time monitoring of PAH levels, leverage robotics for automated sample preparations, and rapid testing of samples to identify hotspots.

Mauritania is a fishing country. However, the Mauritanian coast is increasingly exposed to environmental issues mainly due to anthropogenic activities such as the mining, gas, oil, and fishing industries, as well as new agricultural practices that unreasonably use inputs. Environmental monitoring of the Mauritanian coast faces several challenges; thus, improving the fisheries sector begins with enhancing the state of marine ecosystems and implementing environmental monitoring adapted to climatic conditions and local needs. This study aims to evaluate the quality of the sediments of the “Baie du Repos” in the town of Nouadhibou, Mauritania, through the study of organic matter and the quantification of trace metallic elements in the Quaternary sediments of the Bay. Six samples deemed representative of this Bay were taken and transported to the laboratory. The physicochemical analysis of these samples shows that the superficial horizons of 30 cm depth have overall organic matter contents higher than the average threshold value proposed by the literature for 4 out of 6 of the points studied. The contents recorded for the different metallic trace elements indicate that point 1 is the most exposed to contamination, with the highest concentrations of cadmium, lead, copper, iron, and zinc. The ACP (Principal Component Analysis) showed that the metallic trace elements Pb, Cu, Fe, Cd, and Zn are closely related and evolve positively in the same direction. Additionally, it was found that the points studied are divided into three groups: Group 1 contains only point 1, which is the most exposed to contamination by these toxic elements (Pb, Cu, Zn, Fe, and Cd). Group 2 contains points 3, 5, and 6, which are moderately contaminated by metallic elements with a significant dominance of organic matter (OM). Finally, Group 3 is the least contaminated, with a very high content of organic matter (OM).

Mineral scales of calcite are common in the oil field and pose a serious integrity problem in the wellbore, flow lines, and equipment. It is also a challenge faced by industries such as refineries and power plants. Scale deposition is a complex process depending on various factors such as concentration of scaling species, temperature, pH, and flow rates. Deterministic models are used to predict the scale formation from the level of supersaturation of the scaling species in the water at the operating conditions. However, due to the complexity of the interaction of variables affecting the scaling and inhibition by chemicals, it is suitable to be represented by statistical models. This work focused on applying statistical analysis techniques such as response surface methodology to understand the effect of different operating parameters on the inhibition efficiency of maleic acid-acrylamide copolymer on CaCO3 scales. The copolymer was synthesized, and its inhibition efficiency on the calcite scale was tested using static jar tests at different pH, temperature, and inhibitor concentrations. The effect of the critical parameters on the inhibition efficiency was analyzed using the statistical technique of Response Surface Methodology (RSM). The design of experiments (DoE) was created using a Box–Behnken design with three levels for each factor. The linear and the quadratic effects of the factors were studied and the interaction effects were analyzed using analyses of variance (ANOVA) and RSM. A desirability function was used to optimize the performance for the combination of the variables. The analysis showed that the linear effect of the parameters had the highest impact on the inhibition efficiency. Significant interaction effects were also identified between the operating variables. A transfer function was used to model the experimental data of inhibitor performance.

Judicious application of nitrogen (N) fertilizers in crop production is critical for reducing the nitrate pollution of groundwater and greenhouse gas emissions. It is, thus, important to improve the nitrogen use efficiency under the reduced application of nitrogen. A genotypic variation in N-uptake and N-use efficiency particularly under low N-input conditions exists across crops that can be deciphered and exploited for environmentally sustainable farming without any significant penalty of yield and quality. The present research conducted under the nutrient solution culture aimed to explore the inherent variability in the growth response of ten genetically diverse wheat varieties to low fertilizer N-application (N-, 10 μM N) in comparison to N sufficient control (N+, 8.5 mM N) viz., a viz., the activity of various key N-assimilating enzymes and to delineate the indirect effect of low N on uptake and partitioning of other major macronutrients viz., P, K, S, which may indirectly regulate the N-use efficiency. A notable increase in sulfur, potassium, and phosphorus content was observed under nitrogen-deficient conditions. Varieties such as Carnamah and HD 2824 exhibit a significant increase in shoot phosphorus content, emphasizing their potential to optimize phosphorus acquisition and utilization efficiency under nutrient-limited conditions. The findings highlight the complex interplay between nutrient availability and plant responses, showcasing varietal-specific adaptations to nitrogen limitations.