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.

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.

The current investigation assessed the capability of a well-adapted and enriched bacterial strain known as Bacillus brevis for the biodegradation of phenanthrene. To enhance the removal efficiency of phenanthrene, employed Response Surface Methodology (RSM) in conjunction with a Box-Behnken design (BBD) model. The experiments were designed to explore the impact of pH (6.0 to 9.0), temperature (20 to 40°C), initial phenanthrene concentration (50 and 100 ppm), and incubation time (7 to 21 days) on biodegradation of phenanthrene. The highest level of phenanthrene biodegradation, approximately 55.0%, was achieved by Bacillus brevis when the optimal conditions were met as pH of 7.0, temperature 30oC, and initial phenanthrene concentration (70 ppm) after 21 days of incubation time. This study underscores the significance of employing statistical tools like RSM to enhance the microbial degradation of contaminants.

There is a pressing demand for the introduction of environmentally safe technologies for the industries that supply the basic needs of industrialized societies. Advanced Oxidation Processes may become one of the answers to these uprising pollution management problems in the near future. The present investigation aimed to reduce the refractory organics present in the biologically treated (Activated Sludge Process) tannery effluent using Photocatalysis. The optimum time, pH, dosage of H2O2, and mass of NPAC required for the effective treatment using photocatalysis were found to be 60 mins, 8, 0.2 mg.L-1, and 1g. 100 mL-1, respectively. Although the efficiency of homogeneous photocatalysis was found to be higher than that of heterogeneous photocatalysis, the biodegradability was higher in the latter, with a value of 0.26. The experimental results have proved that photocatalysis could be a promising technology to reduce the refractory organics present in the tannery effluent.

Isotopes are atoms of an element having the same atomic number but different mass numbers. Isotopes in hydrology and water resources are used for identifying its occurrence, movement, residence times, recharge, and discharge process. Stable isotopes of hydrogen(δ2H) and oxygen(δ2O) are used for identifying the surface and groundwater interactions as they constitute hydrogen and oxygen. In this study oxygen and hydrogen stable isotopes are used to identify surface and groundwater interaction in Old Mahabalipuram Road (OMR) regions of Chengalpattu district. The precipitation, lake, surface, and groundwater were collected during pre-monsoon, monsoon, and post-monsoon seasons. The collected sample is analyzed for stable isotopic compositions of oxygen and hydrogen seasonal-wise. The measured stable isotopic compositions during pre-monsoon season of stable oxygen are -4.29 to -2.00 and stable hydrogen are -29.39 to -24.67. The isotopic compositions during monsoon season range from -4.72 to -4.00 and for hydrogen ranges from -29.39 to -23.50. During monsoon season the depletion of isotopic composition is seen and the enrichment of isotopic composition is observed during pre-monsoon season. The variation in stable isotopic composition of oxygen and hydrogen are observed. A Groundwater Water Meteoric Water Line (GMWL) is developed for the study area, and it is compared with a Local Meteoric Water Line (LMWL) for better interpretation of the results. A slight deviation is observed from that of GMWL to LMWL mostly due to isotopic depletion and evaporation effects. From the analysis, a good correlation exists between precipitation and surface water in the study area indicating about recharge mechanism existing in the study area. The groundwater recharge is observed during monsoon seasons and discharge is more towards the pre-monsoon seasons.

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.

River dredging is crucial for mitigating the risk of floods by enhancing the water-carrying capacity of rivers. Nevertheless, the key difficulty lies in the appropriate disposal of dredged material, resulting in escalated costs. Predominantly consisting of silt, the dredged material demonstrates constrained bearing capacity and strength. Nonetheless, there is a prospect to derive value from excavated sediments, with potential applications in diverse public works projects. The processed product derived from dredged material can serve diverse purposes, such as filling railway and highway embankments, as well as the subgrade of pavements. The comprehensive study involved analyzing the fundamental properties of the dredged material collected from the Allochibagh flood channel of the Jhelum River. The analysis focused on determining the basic geotechnical properties of the soil mass. The tests unveiled the fine and cohesive nature of the dredged soil. To enhance its properties, sand was introduced as a stabilizing agent in varying proportions. The investigation revealed an initial augmentation in compressive strength as the proportion of sand increased, attaining an optimal mixture whereafter the strength declined. This study explores the utilization of sand as a stabilizing agent for dredged soil to enhance its strength and optimize its application. The process of stabilizing dredged soil with sand demands a thorough examination of hydrogeological processes, the specific characteristics of the dredged soil, and the intricate transport of contaminants. This formal and multidisciplinary effort seeks to elevate the overall stability of the soil.

The study’s findings serve as a crucial foundation for policymakers, environmentalists, and stakeholders to take necessary actions and develop sustainable waste management strategies tailored to the specific challenges faced in the Western Province of Sri Lanka, contributing to broader global efforts to mitigate the growing waste crisis. It’s a significant concern that the volume of waste is expected to triple by 2050, and the current waste management practices seem insufficient to handle this growth sustainably. The study indicates a per capita waste generation of 0.43 kg in Sri Lanka, with the Western Province at a higher rate of 0.53 kg. This data points to the urgency of addressing waste management practices in this region, especially considering its significance in the country’s GDP. The results also show that the total municipal waste generation in the Western Province is 3248 kg per day whereas the recovery is only 25% (803 kg) in terms of recycling and composting. Burning, burying, and open dumping are highlighted as other prevailing practices for managing waste, which have adverse impacts on the environment and public health. Further research is recommended to identify and address these unaccounted waste streams, especially those at the household level.

Outdoor air pollution causes a lot of health problems for humans. Particulate Matter 2.5 (PM2.5), due to its small size, can enter the human respiratory system with ease and cause significant health effects on humans. This makes PM2.5 significant among the various air pollutants. Hence, it is important to measure the value of PM2.5 accurately for better management of air quality. Algorithms for deep learning and machine learning can be used to forecast air quality data. A model that minimizes the prediction error of the PM2.5 forecast is needed. In this paper, a PM2.5 concentration estimation model using Bi-LSTM (Bidirectional Long Short-Term Memory) with meteorological data as predictor variables is proposed. For a better estimation of PM2.5 values, the hyperparameters of the Bi-LSTM model used are tuned using the Osprey Optimization Algorithm (OOA), a recent meta-heuristic algorithm. The model that works with the optimal values of hyperparameters identified by OOA performed better than the other models when they are compared based on evaluation metrics like Mean-Squared Error and R2.

Bengawan Solo River water is a source of drinking water and raw materials for the government of Surakarta city, but the water has been mixed with domestic, industrial, and agricultural wastes. The waste contains estradiol-17 derived from urine and feces, both from livestock and humans as well as industries around the sub-watershed Bengawan Solo River. The content of estradiol-17 in the Bengawan Solo sub-watershed is quite high. This study is the first conducted in Bengawan Solo River to look at natural estrogens that are very rarely studied in the environment, which are likely could cause several health effects in humans and wildlife due to their relatively strong estrogenic potential and high levels in wastewater and river water. Therefore, research on the elimination of these compounds using effective, energy-efficient, and low-maintenance technologies for water treatment such as phytoremediation is highly expected. The purposes of this study were to identify estradiol, to measure the estradiol levels through HPLC tests as well as to test the effectiveness of phytoremediation with Portulaca plant as biological agents. The results show that the water of Bengawan Solo River contained estradiol substances ranging from 3.88 ppm to 5.76 ppm. The Portulaca plant species was effective at eliminating estrogenic waste up to 99.89%.