Environmental Chemistry

1. Analytical Methods in Environmental Chemistry
   1. Sampling techniques
      1. Design of sampling protocols
         1. Importance of sampling strategy and plan
         2. Considerations for representative sampling
      2. Air sample collection
         1. Ambient air sampling
            1. Passive vs. active sampling techniques
            2. Low-volume vs. high-volume samplers
         2. Indoor air quality sampling
      3. Water sample collection
         1. Surface water sampling
            1. Grab vs. composite sampling
            2. Equipment for sampling (e.g., bailers, samplers)
         2. Groundwater sampling
            1. Well construction and sampling considerations
            2. Decontamination procedures for sampling equipment
      4. Soil sample collection
         1. Methods of soil sampling (auger, core)
         2. Depth profiling and composite sampling techniques
         3. Contaminant-specific sampling considerations
      5. Quality assurance and control in sampling
         1. Blanks, duplicates, and spiking
         2. Chain of custody procedures
   2. Analytical techniques
      1. Chromatography
         1. Gas Chromatography (GC)
            1. Basics and principles of GC
            2. Column types and selection criteria
            3. Detectors used in GC (FID, ECD, MS)
         2. High-Performance Liquid Chromatography (HPLC)
            1. Principles of HPLC separation
            2. Types of HPLC columns (C18, ion-exchange)
            3. Detectors used in HPLC (UV, fluorescence, RI)
      2. Spectroscopy
         1. Atomic Absorption Spectroscopy (AAS)
            1. Flame AAS vs. graphite furnace AAS
            2. Calibration techniques and interference correction
         2. Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
            1. Multi-element analysis capability
            2. Interference management and mitigation strategies
         3. Ultraviolet/Visible Spectroscopy (UV/Vis)
            1. Absorbance principles and applications
            2. Use in chemical speciation and concentration determination
      3. Electrochemical methods
         1. Potentiometry and ion-selective electrodes
            1. Principle of measurement and common applications
            2. Selection and care of electrodes
         2. Voltammetry and related techniques
            1. Principles and types (cyclic voltammetry, anodic stripping)
            2. Sensitivity and specificity considerations
   3. Sample preparation methods
      1. Pre-treatment processes
         1. Filtration, centrifugation, and homogenization
         2. Importance of sample preservation
      2. Extraction techniques
         1. Liquid-liquid extraction (LLE)
            1. Solvent selection and partitioning principles
         2. Solid-phase extraction (SPE)
            1. Cartridge selection and elution processes
         3. Microwave-assisted and supercritical fluid extraction
      3. Digestion methods for metals analysis
         1. Acid digestion procedures
         2. Use of microwave vs. conventional heating
   4. Data interpretation and statistical analysis
      1. Calibration and standardization
         1. Instrument calibration curves
         2. Use of reference standards and control solutions
      2. Quality control and assurance
         1. Control charts and process capability analysis
         2. Determining method detection limits and quantitation limits
      3. Statistical tools in data analysis
         1. Descriptive statistics and error analysis
         2. Application of regression analysis and analysis of variance (ANOVA)
      4. Uncertainty analysis
         1. Propagation of uncertainty in analytical processes
         2. Reporting and interpreting uncertainty in results
   5. Advancements and emerging technologies
      1. Miniaturization in analytical devices
         1. Lab-on-a-chip and portable instruments
         2. Applications in field analysis
      2. High-throughput analysis technologies
         1. Robotics in sample preparation and analysis
         2. Automated data handling and processing systems
      3. Emerging analytical techniques
         1. Hyphenated techniques (e.g., LC-MS, GC-MS-MS)
         2. Developments in non-destructive analysis methods
      4. Integration of AI in analysis
         1. Machine learning for pattern recognition
         2. AI in predictive modeling and method development