Contamination of surface water by rapid industrialization, natural and anthropogenic activities is ofgreat concern over the last few decades. Nowadays, canal water systems are no exception to thisform of contamination, which results in water quality degradation. To classify the canal water basedon the Bureau of Indian Standards (BIS), it was thought to develop a quick and inexpensive approachas an alternative to the time-consuming analysis approach. With this motivation, the present studyexplores building a machine learning model for water quality classification of a major canal namelythe Talaldanda canal operating in the state of Odisha, India. The water quality class is predicted usingsupervised machine learning (ML) prediction models for the new canal water input parameters. Thewater quality parameters such as pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), andtotal coliform (TC) at six strategic locations of the canal from the year 2013-2020 were collected fromOdisha State Pollution Control Board for the training phase. The supervised ML models used in thestudy are Decision Tree (DT), Neural Network (NN), k-NN (k-Nearest Neighbor), Naïve Bayes (NV),Support Vector Machine (SVM), and Random Forest (RF). The predictions of the models are evaluatedusing the Orange-3.29.3 data analytics tool. When analyzing the performance parameters by samplingthe training data into training and testing using cross-validation, the results show that DT has a higherclassification accuracy (CA) of 96.6 percent than other ML models. In addition, the likelihood of DTcorrectly predicting water quality class for the testing dataset is higher than that of other predictionmodels.

The current rapid urbanization, industrialization, and expansion of urban construction patterns have resulted in a large number of residual plaques in the urban area, including both the original plaques that are extremely fragmented and the new plaques that are metabolized by urban production, especially natural habitat patches are more pronounced. Ecological restoration of residual plaques plays an important role in maintaining biodiversity, protecting native species, providing ecological services, revitalizing land resources, inheriting regional characteristics, shaping urban image, and improving the ecological environment. Therefore, research on the subject is necessary and urgent. The topic is based on the ecological survey of urban residual patches and the study of the characteristic attributes of current urbanization, defining the connotation, extension, type, characteristics, and influencing factors of urban residual patches, and analyzing the process of fragmentation of residual plaques in cities and their artificial interference relationship. From the macro, meso, and micro scales, from the top level of ecological planning, the whole process of life cycle management, and the moderately disturbed bottom layer of ecological engineering nodes, three levels are restored, theoretical integration guidance and technical restoration. Based on the three dimensions of the continuous symbiosis of nature, cost control of the economy, and public participation of the society, repair and activate the remaining plaques of the city to provide technical support for the construction and sustainable development of urban ecological civilization.

Water quality evaluation is a critical component of water environmental quality management, and conducting water quality assessments for reservoirs is quite practical. The inaccuracy induced by information overlap of several water quality measures is rarely taken into account in current water quality assessment systems. To solve this problem, the Principal component analysis-Rank sum ratio (PCA-RSR) water quality evaluation model was used to quantitatively evaluate the water quality of the Daheiting reservoir based on the monitoring data of different water layers in 2019. The results show that the water quality of Daheiting reservoir in 2019 is slightly better than that of the end of the reservoir, due to the influence of human factors downstream of the Upper Panjiakou Dam and the topography of the Luan River System, and the water quality from the dam head to the reservoir tail shows a decreasing trend. The PCA-RSR model has a good correlation with the traditional water quality indexes (WQI) system, which can avoid errors caused by overlapping information among the indexes while also taking into account the weight of the environmental factors of the study area. It is feasible and has some practical value in reservoir water quality evaluation..

This paper presents numerical simulations regarding the transport characteristics of soil salt. It has been recognized in recent years that the growth and output of crops in the irrigation area of the lower reaches of the Yellow River are affected by the decreased fertility of soil as a result of the transport of soil salt, due to the long-term farming, fertilization of farmland which contains a high proportion of sands. Accordingly, numerical simulations by Hydrus are carried out, in which, based on the similarity principle, two-dimensional convection-diffusion partial-differential governing equations of unsteady flow in saturated-unsaturated porous media are applied to depict the motion parameters’ spatial variability of soil water in the irrigation area. And the van Genuchten equation is adopted to express the relationship between volumetric water content and soil hydraulic conductivity and negative soil water pressure. The irrigation basin of the People’s Victory Canal, which is downstream of the Yellow River, is investigated in detail as an example. The findings revealed that soil salt in the irrigation region is transferred by water diffusion, with irrigation and fertilization being the primary causes of downward migration and salt accumulation. It benefits the soil in irrigation areas and protects groundwater.

The present study critically investigated the effect of meteorological parameters on the mass concentration of Ultrafine Particulate Matter (PM1) between October 2018 and September 2019 (n=102) in a semiarid region of Rajasthan, India. The concentration of PM1 ranged between 72-110.85 μg.m-3 with distinct seasonal variation. Higher PM1 concentrations are closely linked to decreased wind speeds and colder temperatures, according to the findings. The winter season showed the highest concentration followed by post monsoon and pre monsoon season. The cumulative effect of environmental variables such as temperature, relative humidity, and wind speed, as well as the height of the planetary boundary layer, was investigated using multiple regression analysis (HPBL). A significant negative correlation (p < 0.001) with HPBL and wind speed was observed in all three seasons. The temperature was found to have a significant (p<0.001) negative correlation during winters whereas in other seasons there was a positive but no significant (p>0.001) relationship. Relative humidity showed a negative relationship during withers and pre-monsoon season. The multiple regression model indicated a significant negative (p<0.001) relationship with HPBL in winters (R2=0.70) explaining the 70% effect of HPBL on mass concentration of PM1.During the post-monsoon (R2 = 0.69) and pre-monsoon (R2= 0.91) explains 69% and 91% effect of HPBL on mass concentrations of PM1.The results indicate that the concentration of PM1 cannot be explained by a single meteorological parameter but all the parameters show a cumulative effect.

The world is facing a greater issue in the disposal of waste plastics and there is an intense need for research on alternate and sustainable solutions for environmental issues. Waste plastic can be used as aggregates or as a protective layer over aggregates to increase their strength. The aggregate used in flexible pavements was investigated in this study, as well as the use of Geo-Polymer to improve the pavement’s strength and durability. The design of the pavement is done according to the Indian standard codes IRC. Dense bituminous macadam and base courses are taken into account as per the design criteria. The geo-polymer flexible pavement was tested for properties such as the wearing test. Other fundamental tests for aggregate and bitumen used in pavements include specific gravity, flash point, fire point, ductility, softening point, penetration test, water absorption test, bonding strength, durability, and temperature resistance. When geo-polymer plastic bitumen is heated and put as a coating over the base course, it allows the user the air gaps with additional plastic and binds over the aggregate, resulting in increased road stability, smoothness, and vehicle braking effects. It is concluded that with 5% addition of the geo-polymer with bitumen has performed well in all aspects of the bitumen characteristics.

Microplastics (MPs), widely present in aquatic ecosystems, can be ingested by numerous organisms, but their toxicity remains poorly understood. Toxicity of environmental MPs from 2 beaches located on the Guadeloupe archipelago, Marie Galante (MG) and Petit-Bourg (PB) located near the North Atlantic gyre, was evaluated. A first experiment consisted in exposing early life stages of zebrafish (Danio rerio) to MPs at 1 or 10 mg/L. The exposure of early life stages to particles in water induced no toxic effects except a decrease in larval swimming activity for both MPs exposures (MG or PB). Then, a second experiment was performed as a chronic feeding exposure over 4 months, using a freshwater fish species, zebrafish, and a marine fish species, marine medaka (Oryzias melastigma). Fish were fed with food supplemented with environmentally relevant concentrations (1% wet weight of MPs in food) of environmental MPs from both sites. Chronic feeding exposure led to growth alterations in both species exposed to either MG or PB MPs but were more pronounced in marine medaka. Ethoxyresorufin-O-deethylase (EROD) and acetylcholinesterase (AChE) activities were only altered for marine medaka. Reproductive outputs were modified following PB exposure with a 70 and 42% decrease for zebrafish and marine medaka, respectively. Offspring of both species (F1 generation) were reared to evaluate toxicity following parental exposure on unexposed larvae. For zebrafish offspring, it revealed premature mortality after parental MG exposure and parental PB exposure produced behavioural disruptions with hyperactivity of F1 unexposed larvae. This was not observed in marine medaka offspring. This study highlights the ecotoxicological consequences of short and long-term exposures to environmental microplastics relevant to coastal marine areas, which represent essential habitats for a wide range of aquatic organisms.

In fish, the gut microbiome plays a crucial role in homeostasis and health and is affected by several organic and inorganic environmental contaminants. Amphidromous fish are sentinel species, particularly exposed to these stressors. We used whole metagenome sequencing to characterize the gut microbiome of wild European eels (Anguilla anguilla) at a juvenile stage captured from three sites with contrasted pollution levels in term of heavy metals and persistent organic pollutants. The objectives were to identify what parameters could alter the gut microbiome of this catadromous fish and to explore the potential use of microbiota as bioindicators of environment quality. We identified a total of 1079 microbial genera. Overall, gut microbiome was dominated by Proteobacteria, Firmicutes and Actinobacteria. Alpha and beta diversity were different amongst sites and could be explained by a reduced number of environmental and biological factors, specifically the relative abundance of fish preys in eels’ diet, PCB101, γHCH (lindane), transnonachlor and arsenic. Furthermore, we identified a series of indicator taxa with differential abundance between the three sites. Changes in the microbial communities in the gut caused by environmental pollutants were previously undocumented in European eels. Our results indicate that microbiota might represent another route by which pollutants affect the health of these aquatic sentinel organisms.

The impact of microplastics (MP) has attracted much attention from the scientific community and many laboratory assessments have been made of their effects on aquatic organisms. To produce MP from real environmental plastic waste, which would enable more realistic experiments, we used plastic pearl farming equipment from French Polynesian lagoons. Here, the pearl oyster Pinctada margaritifera could encounter MP coming from their breakdown in its surrounding environment. We tested an established method based on mechanical cryogenic grinding and liquid sieving. Our desired size range was 20–60 μm, corresponding to the optimal particle size ingested by P. margaritifera. The protocol was effective, generating MP particles of 20–60 μm (∼17,000–28,000 MP μg−1), but also produced too many smaller particles. The peak in the desired size range was thus flattened by the many small particles <3 μm (∼82,000–333,000 MP μg−1; 53–70% of total analysed particles), visible at the limit of Coulter counter analysis (cut-off point: 2 μm). Laser diffraction analysis (cut-off point: 0.4 μm) provided greater detail, showing that ∼80–90% of the total analysed particles were <1 μm. Diverging particle size distributions between those expected based on sieving range and those really observed, highlight the need to perform fine-scaled particle size distribution analyses to avoid underestimating the number of small micro- and nanoplastics (MNP) and to obtain an exact estimation of the fractions produced. Size and microstructure characterization by scanning electron microscopy suggested spontaneous particle self-assembly into crystal superstructures, which is the supposed cause of the divergence we observed. Overall, our results emphasize that particle self-assembly is a technical hurdle requiring further work and highlight the specific need to finely characterize the size distribution of MNP used in ecotoxicological experiments to avoid overestimating effects.

We measured phytoplankton primary production and heterotrophic bacterial activities on microplastics and seawater in the Northwestern Mediterranean Sea during two 3-month spring periods over 2 consecutive years. Microorganisms growing on a 5 mm diameter low density polyethylene films (LDPE; 200 μm thick) faced two contrasting conditions depending on the year. Spring 2018 was characterized by consistent nutrient inputs and bloom development. In spring 2019, nutrient inputs and bloom were low. For the first time, we observed a clear coupling between primary production and heterotrophic prokaryote production on microplastics during both years, but with different intensity between years that reflected the crucial role of the trophic environmental conditions (nutrient supply) in shaping microbial activities on plastics. We found that high primary production on plastics could support the whole (net autotrophy) or the majority of the bacterial carbon demand needed for heterotrophic activities, supplemented by other carbon sources if surrounding waters are highly productive. We propose that microbial activity on plastics influences the microbial community in the surrounding seawater, especially when the environmental conditions are less favorable. An illustrative image of the role of plastics in the environment could be that of an inverter in an electrical circuit that mitigates both positive and negative variations. Our results highlight the potential role of the plastisphere in shaping biogeochemical cycles in the context of increasing amounts of plastic particles in the marine environment.