Journal of Environmental Analytical Chemistry

Pesticides play an essential role in modern agriculture, helping farmers manage pest populations and protect crops from diseases. However, the widespread and often indiscriminate use of pesticides has raised significant concerns regarding their environmental impact. One of the major routes through which pesticides enter the environment is agricultural runoff, a process by which water from rain or irrigation carries pesticides from fields into nearby water bodies. This contamination poses a serious threat to water quality, biodiversity, and public health. Consequently, it has become critical to develop reliable and efficient methods for detecting pesticides in agricultural runoff to monitor contamination levels and mitigate the associated risks. Chromatographic techniques have proven to be invaluable tools for pesticide analysis due to their high sensitivity, specificity, and ability to separate complex.

Green Analytical Techniques (GATs) have become increasingly significant in the field of environmental monitoring, driven by the rising awareness of environmental sustainability and the need for safer, more efficient analytical methods. As traditional analytical techniques often require hazardous chemicals, generate large amounts of waste, or consume considerable energy, GATs offer the potential for reducing environmental impact while maintaining high analytical performance. In this context, GATs encompass a wide range of approaches designed to minimize the use of toxic reagents, reduce waste, enhance energy efficiency, and use non-toxic materials wherever possible. The push toward green chemistry and green analytical chemistry stems from a growing concern over environmental degradation and human health issues linked to hazardous substances. Chemical industries, laboratories, and research organizations are increasingly focusing on adopting green alternatives to traditional analytical methods, which typically involve solvents, reagents, and processes that are detrimental to the environment. This paradigm shift in analytical chemistry is aligned with the broader principles of green chemistry, which advocate for processes that reduce or eliminate the use of hazardous chemicals and improve the sustainability of industrial practices.

The increasing volume of industrial waste generated by manufacturing, chemical processes, and energy production has raised significant concerns about environmental pollution and the long-term impact on ecosystems and human health. Industrial wastes often contain a diverse array of hazardous chemicals, many of which are resistant to natural degradation. Biodegradation, the process by which microorganisms break down organic substances into simpler compounds, offers a promising approach to mitigating the environmental impact of such waste. While biodegradation can reduce the toxicity and persistence of pollutants, the products resulting from these processes may still pose risks. Understanding and analyzing these biodegradation products is essential for assessing the efficacy of remediation efforts, as well as for evaluating potential environmental and health hazards. However, the identification and quantification of biodegradation products from industrial wastes present significant analytical challenges, including the complexity of the waste matrix, the variety of degradation pathways, and the limitations of existing detection methods.

The analysis of trace metals in environmental samples is an essential component of environmental monitoring, helping to assess pollution levels, determine ecosystem health, and guide regulatory measures. Trace metals, such as lead, mercury, arsenic, cadmium, and chromium, are toxic to both humans and wildlife even at low concentrations, making their detection and quantification a priority in environmental science. Traditional analytical techniques for trace metal analysis, such as Atomic Absorption Spectrometry (AAS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and Graphite Furnace Atomic Absorption Spectrometry (GFAAS), are highly sensitive and reliable. However, these methods often rely on the use of organic solvents and reagents that can be harmful to the environment and human health. As the environmental and health impacts of hazardous chemicals become increasingly evident, there has been growing interest in the development of eco-friendly solvent systems for trace metal analysis. This shift aims to reduce the ecological footprint of analytical practices, minimize the risks associated with chemical disposal, and ensure that the process of detecting and quantifying trace metals is more sustainable and safer for laboratory personnel and the broader environment.

Environmental forensics has emerged as a critical tool for understanding the sources and pathways of pollution in the environment. The increasing complexity of environmental contamination, coupled with the growing concerns about the impact of pollutants on human health and ecosystems, has led to the development of advanced analytical techniques aimed at identifying and tracing pollutants back to their sources. One such method that has gained significant attention in recent years is Isotope Ratio Mass Spectrometry (IRMS). This technique is particularly useful in environmental forensics because it provides a unique way to fingerprint pollutants, helping to distinguish between different sources of contamination and determine their origins. The application of IRMS in environmental forensics is particularly valuable in cases of diffuse pollution, where pollutants may come from a variety of sources, such as industrial activities, agricultural runoff, or urban waste. Isotopic signatures are natural variations in the isotopic composition of elements found in environmental samples. These variations arise from differences in the number of neutrons in the nucleus of an atom, which can lead to distinct isotopic ratios. For example, carbon, nitrogen, oxygen, sulfur, and hydrogen all have multiple isotopes that occur in nature, and these isotopes are present in varying proportions depending on the source and chemical processes involved in the formation of the pollutant. By measuring these isotopic ratios using mass spectrometry,

The ongoing environmental challenges posed by Persistent Organic Pollutants (POPs) in aquatic systems have gained considerable attention due to their long-lasting impacts on both the environment and human health. POPs, which include a wide variety of chemical substances, are characterized by their persistence in the environment, ability to bioaccumulate in living organisms, and potential to cause harm to ecosystems and human health. These pollutants can enter aquatic environments through various pathways, including industrial discharges, agricultural runoff, wastewater effluents, and atmospheric deposition. Once in water bodies, POPs can travel long distances, often reaching remote areas, making their monitoring and identification crucial for environmental protection and public health. As the impact of POPs becomes more widely recognized, there is an increasing demand for advanced analytical techniques to monitor their presence and quantify their concentrations in aquatic systems. One such powerful tool that has revolutionized the detection and characterization of POPs is High-Resolution Mass Spectrometry (HRMS

The contamination of soil and water by heavy metals is a critical environmental concern due to the toxicity and persistence of these elements. Heavy metals such as lead, mercury, cadmium, arsenic, and chromium pose significant risks to human health and the environment, often entering ecosystems through industrial activities, agricultural practices, mining, and waste disposal. These metals can accumulate in the soil and water, contaminating the food chain and harming aquatic life, plants, and animals. The detection and quantification of heavy metals in environmental samples are therefore essential for monitoring pollution levels, assessing environmental risks, and informing regulatory policies. Traditional methods for analyzing heavy metals, such as atomic absorption spectrometry (AAS) and inductively coupled plasma mass spectrometry (ICP-MS), are highly sensitive but often require expensive instrumentation, skilled operators, and time-consuming sample preparation procedures. In recent years, spectroscopy has emerged as an innovative tool for assessing soil and water contamination by heavy metals, offering several advantages, including portability, ease of use, non-destructive analysis, and the ability to provide rapid results. The use of spectroscopy in environmental monitoring has revolutionized the field by providing costeffective, real-time, and high-throughput methods for detecting heavy metal contamination.

The environmental impact of microplastics has become an increasingly urgent issue in recent years. These tiny plastic particles, typically less than 5 millimeters in diameter, are ubiquitous in the environment and have raised significant concerns due to their persistence, bioaccumulation potential, and ability to cause harm to ecosystems and human health. Microplastics enter the environment through a variety of sources, including the degradation of larger plastic items, industrial processes, and the shedding of microfibers from textiles. They can be found in virtually every ecosystem on Earth, from the deepest ocean trenches to remote Arctic ice, and have been detected in a wide range of environmental media, including air, water, soil, and sediments. Due to their small size, persistence, and diverse origins, microplastics are difficult to manage and pose complex challenges for environmental monitoring and regulation. As a result, there is a growing demand for analytical methods that can effectively detect and quantify microplastics in environmental samples. Microplastics are typically categorized based on their size, shape, and polymer composition.

The rapid industrialization and urbanization of the past century have led to significant environmental pollution, presenting challenges to human health and the ecosystems that sustain life. Traditional methods for detecting environmental pollutants, such as gas chromatography, high-performance liquid chromatography, and mass spectrometry, often require complex sample preparation, expensive instrumentation, and significant time to obtain results. This has underscored the need for more efficient, cost-effective, and rapid detection methods. In this context, nanomaterials have emerged as a promising solution, offering advanced capabilities for sensing and detecting emerging environmental pollutants. Nanomaterials, due to their unique properties at the nanoscale, enable the creation of highly sensitive and selective sensors capable of identifying low concentrations of pollutants that would otherwise be difficult to detect. The application of nanomaterials in sensor technology holds great potential for revolutionizing the detection and monitoring of environmental pollutants, especially in the face of emerging contaminants.

Volatile Organic Compounds (VOCs) are a diverse group of chemicals that can easily vaporize at room temperature, contributing significantly to air pollution in urban environments. These compounds, which include both humanmade and naturally occurring substances, are central to the understanding of air quality and public health. VOCs play a major role in the formation of groundlevel ozone and particulate matter, both of which have significant environmental and health implications. The presence of VOCs in urban air is influenced by a variety of sources, including traffic emissions, industrial processes, the use of household products, and natural sources such as plants and trees. However, the rapid urbanization that characterizes modern cities has led to a marked increase in the concentration of these compounds, necessitating effective monitoring systems to assess and mitigate their impact. Urban air quality management is often constrained by the limitations of traditional air monitoring techniques. Conventional methods, which include collecting air samples in canisters for later analysis in laboratories, are labor-intensive and time-consuming. These methods also lack the capability to provide real-time data, which is essential for understanding the dynamic nature of air pollution in urban environments.