Glyphosate (N-[phosphonomethyl] glycine) pollution is mainly due to industrial drainage and unnecessary use for agricultural and residential weed control purposes, which in turn creates ecosystem and environmental toxins. There are very important research fields needed for decontamination in a sustainable way. In this chapter, we discuss an adsorption process of glyphosate from aqueous solution with influencing mechanisms, which are kinetics, isotherms, and thermodynamics. Reported results are depicted by consequence factors, namely pH, contact time, initial taken concentration, doses, etc. Adsorbents preparation and their characterization are elaborated, namely zero point charge (ZPC), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), etc. The review posits that glyphosate removal and comparisons between their adsorption capacity, removal percentage, and type of adsorbents are easily available. Outcome data have been described with kinetic models; basically, uses of pseudo-first order, pseudo-second order, intraparticle diffusion, and equilibrium studies for monolayer capacity have been achieved through Langmuir isotherm, which also gives an empirical relationship between glyphosate concentration and heterogeneous/homogeneous adsorbent surface. Present studies highlight plant-mediated adsorbents, nanomaterials, soils, and miscellaneous adsorbent materials, which are emphasized due to being lead nonpollutant, lower cost, and greener. A comparison of other related adsorbents, which do not use glyphosate adsorption, is not available in this study. However, the reviews surveyed more or less glyphosate adsorption papers and related papers of pesticides, supporting lead pesticide remediation.

Nanoscience is an interdisciplinary subject that has been one of the most dynamic disciplines in material science. Key features of nanoparticles are clusters of atoms in a size range within 1–100nm. Metal nanoparticles can be synthesized by physical, chemical, and biological routes. But the green or biological route for nanoparticle synthesis from a biological origin is of more interest than other ways, due to its environment friendliness, economically cheap, feasibility, and applications in various field. Several analytical tools were used for structure determination and characterization of synthesized nanoparticles.

The batch adsorption process is one of the most practical approaches used to adsorb pollutants from the liquid solution for the purification of water. This chapter presents literature of different adsorption types with its characteristics, including an overview of different factors influencing the batch process. This chapter also helps to understand the removal mechanism of the batch process through bulk solution transport, film diffusion transport, pore transport, and adsorption on available adsorption sites. Several experimental studies and mathematical modeling have been used to optimize the factors affecting the efficiency of batch process. Here, mathematical models of the pseudo-first-order and second-order kinetics model, Eovich's model, and the adsorption isotherm involve the concept of batch adsorption infinite bath and infinite bath.

The equilibrium adsorption of carbaryl insecticide was examined by several easily available natural adsorbents like Alluvial soil, Pistia stratiotes biodust, Lemna major biodust, neem bark dust, and eggshell powder to remove carbaryl from an aqueous environment. The batch experiments were achieved as different operating parameters. For overall validity of the process, response surface (RSM) and artificial neural network (ANN) models were used. The maximum amount of Carbaryl adsorbed onto different adsorbents is presented in this chapter. Adsorption isotherms, kinetics, and thermodynamics of the process were also provided. Finally, results showed that neem bark dust (NBD) has the maximum adsorption capacity of carbaryl. Because NBD is easily prepared, it can be a used as effective adsorbent for removal of the insecticide from contaminated water.

The advent of the new generation of low-cost lightweight and connected sensors made a paradigm shift in environmental studies. In particular, nomadic sensors allow for a very precise personalized measurement, by continuously quantifying the individual exposure to air pollution components. Moreover, a broad dissemination among volunteers of these devices, or their deployment on vehicle fleets, is becoming a credible solution. Another major interest of such sensor deployment is to densify the air quality monitoring network, indoor, as in the outdoor, which is today restricted to sparse nodes. However, this high spatiotemporal resolution raises several issues related to their analysis. After an overview of the projects relying on this technology, this chapter points out the remaining challenges to be addressed. Part of these challenges constitutes the research program of the ongoing project Polluscope in France.

Many countries are suffering from air pollution due to imbalanced urbanization, unregulated increase in transportation, and inorganic industrialization. Air pollution directly affects the ecosystem and climate thereby compromising the well-being of the citizens and cities. For this reason, predicting air pollution in advance has a great importance in supporting proactive plans and environmental management actions for decision makers. In the literature, many research efforts are focusing on predicting air pollutant concentrations. In this chapter, we present recent artificial intelligence-based air pollution prediction approaches. In this context, we comprehensively reviewed the literature and categorized the proposed prediction methods based on feature selection methods, air pollutant types, and learning models.

Water is an essential natural resource for the survival of living beings in the world. Freshwater bodies significantly support ecological and economic activities in each state or country, especially India, which has large number of rivers, lakes, ponds, and wetlands. Notably, lake water is critically polluted due to industrial effluents, encroachment, eutrophication, garbage dumping, poor drainage, and climate changes, which have a severe effect on water quality. Hence, monitoring and assessment of water quality over time is important for minimizing the negative effects to an ecosystem, and it greatly helps to sustain valuable aquatic species. In this chapter, an intelligent estimation model is developed using Kalman filter integrated with a synergistic fibroblast optimization (SFO) algorithm for forecasting water quality parameters. The developed predictive model is evaluated with real-time water samples collected from Ukkadam Periyakulam Lake, Coimbatore, and promising results provide qualitative information to enhance water quality in this lake.

The generation of heavy metal(loids) and its derivative compounds (such as oxides, carbides, sulfides, etc.) in increasing rate by various anthropogenic activities is of major global concern. In order to control this problems, the removal of metal(loids) from effluents is essential. Although several physicochemical methods (adsorption, electrodialysis, floatation, ion exchange) are available, effectiveness of these methods is poor and of high cost. Therefore, ecofriendly and green technology is required in this regard. Among various green synthesis techniques, biosorption drew great attention for scientific research as a novel method for industrial wastewater treatment to reduce or neutralize metal content. Most biosorption techniques utilize bio-based substrate materials (coconut fiber, waste tea leaves, seaweeds, yeast, molds, bacteria wool, crab shell, straw, coffee waste, etc.) as adsorbent to provide effective and sustainable treatment of wastewater. Therefore keeping in mind the mentioned scenario, the objectives of this review are to critically interpret and summarize the up-to-date works carried out in this regard by different scientists. Different parameters of biosorbent materials along with optimum treatment conditions have also been considered in this chapter. This can be helpful for future studies in exploring the novel biosorbent to treat the industrial wastewater using biosorption technology.

Today dyes, highly colored organic compounds, find widespread applications in industries like textile, food technology, leather tanning, paper, etc., for coloring products, light-harvesting solar cells, photoelectrochemical cells, etc. However, large usage of these dyes leads to their release as effluents that eventually contaminate drinking water sources and hampering the ecological system. The contaminated wastewater effluent exhibits detrimental effects related to human beings and environmental concern. Thus, the requirement for suitable cost-effective treatment methods for contaminated wastewater seems to be indispensable. To date, there are various treatment technologies that can be roughly categorized into three types: biological, physical, and chemical methods. Bear in mind that any dye depletion technique has its own merits and demerits; therefore, a combinatorial treatment method can be advantageous. Moreover, the role of nanotechnology in the dye degradation or removal process has been marked as a promising technique in comparison to existing processes. This chapter aims to compose various information about dye, dye effluent, and existing treatment technologies for wastewater.

Heavy metal is a term commonly envisaged to be those metals whose density surpasses 5g per cubic centimeter. An enormous number of elements fall into this group, but Cd, Cr, Cu, Ni, As, Pb, Hg, and Zn are those of relevance in an environmental context. Heavy metals cause serious health issues such as organ injury, nervous system impairment, reduced growth and development, cancer, and, in extreme cases, death. The release of large amounts of metals through industrial wastewater has become hazardous to living organisms as they easily absorb and accumulate heavy metals into their body due to its high solubility in an aquatic environment. Therefore, it is essential to treat metal-contaminated wastewater before its discharge to the environment. There are various types of treatment processes such as membrane partitioning, electrodialysis, chemical precipitation, ion exchange, electrochemical removal, photocatalytic process, and adsorption. Adsorption is acknowledged as a financially cheap practice for heavy metal expulsion from wastewater as it is economical, simple to deal with, and exceedingly productive. This chapter explain the adsorption technique by using biochar. Biochar is the carbon-rich residue left behind when biomass, for example, wood, fertilizer, or leaves, is heated in a shut vessel with next to zero accessible oxygen. In more methodical terms, biochar is obtained by thermal disintegration of organic material under partial or no source of oxygen (O2) and at comparatively low temperatures (<750°C). Use of biochar to industrial wastewater can potentially diminish heavy metals’ mobility due to the porous assemblage, large surface area, and high adsorption capacity of biochar. There are various materials present in our environment such as crop residue, animal waste, wood, manure, leaves, etc. can be used for biochar production. Production of biochar is a sustainable option for waste management as well as remediation of pollutants from polluted water.