Microplastic pollution has become a significant environmental concern globally, particularly in urban water bodies due to the discharge of plastic waste and runoff from various sources. The global distribution of microplastic, predominant polymer constituents, and variability in concentration are explored, emphasizing the need for standardized monitoring protocols and increased research efforts. This chapter provides a comprehensive examination of microplastic pollution in urban water bodies, focusing on its resources, detection, characterization, and implication for ecosystem health and human well-being. Furthermore, the chapter addresses emerging concerns regarding microplastic contamination in sources, highlighting the necessity for improved quality assurance in sampling and analysis. Traditional methods for assessing microplastic pollution often rely on visual identification, which can be time-consuming and prone to errors. Polymer analysis offers a promising approach to overcome these limitations by providing precise identification and quantification of microplastic in water samples. This chapter explores the principles and techniques of polymer analysis for assessing microplastic pollution in urban water bodies, highlighting its importance in understanding the extent and sources of contamination. Advanced analytical methods such as FTIR, Raman spectroscopy, SEM-EDS, and thermo-analytical methods are critically evaluated alongside innovative approaches like tagging methods and liquid chromatography. Furthermore, the chapter discusses the integration of polymer analysis with statistical modeling and geographic information systems (GIS) for comprehensive spatial mapping and risk assessment of microplastic pollution hotspots. Overall, this chapter provides valuable insights into the role of polymer analysis in advancing our knowledge of microplastic pollution and promoting sustainable management practices in urban water bodies.

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Polymer Analysis for Effective Assessment of Microplastic Pollution in Urban Water Bodies

  • Shital Thacker,
  • Edwin Pithawala,
  • Mahesh Vasava,
  • Hardik Shah

摘要

Microplastic pollution has become a significant environmental concern globally, particularly in urban water bodies due to the discharge of plastic waste and runoff from various sources. The global distribution of microplastic, predominant polymer constituents, and variability in concentration are explored, emphasizing the need for standardized monitoring protocols and increased research efforts. This chapter provides a comprehensive examination of microplastic pollution in urban water bodies, focusing on its resources, detection, characterization, and implication for ecosystem health and human well-being. Furthermore, the chapter addresses emerging concerns regarding microplastic contamination in sources, highlighting the necessity for improved quality assurance in sampling and analysis. Traditional methods for assessing microplastic pollution often rely on visual identification, which can be time-consuming and prone to errors. Polymer analysis offers a promising approach to overcome these limitations by providing precise identification and quantification of microplastic in water samples. This chapter explores the principles and techniques of polymer analysis for assessing microplastic pollution in urban water bodies, highlighting its importance in understanding the extent and sources of contamination. Advanced analytical methods such as FTIR, Raman spectroscopy, SEM-EDS, and thermo-analytical methods are critically evaluated alongside innovative approaches like tagging methods and liquid chromatography. Furthermore, the chapter discusses the integration of polymer analysis with statistical modeling and geographic information systems (GIS) for comprehensive spatial mapping and risk assessment of microplastic pollution hotspots. Overall, this chapter provides valuable insights into the role of polymer analysis in advancing our knowledge of microplastic pollution and promoting sustainable management practices in urban water bodies.