Microplastics & Mitigation: Science to Solutions
From Detection to Remediation: Advancing Science and Technology to Combat Microplastic Pollution.
About This Course
Microplastics and nanoplastics (MNPs) have emerged as a major global environmental challenge affecting ecosystems, human health, and industrial systems. This 3-day advanced workshop bridges analytical chemistry, environmental toxicology, AI-powered data analysis, and mitigation engineering to provide participants with a complete workflow—from microplastic detection to real-world remediation strategies.
Participants will explore cutting-edge techniques such as automated μ-Raman spectroscopy and QCL-based spectral fingerprinting for particle identification, evaluate ecological and human health risks through advanced in-vitro models, and develop engineering solutions for mitigation using biomaterials, advanced filtration systems, and bioremediation pathways.
Hands-on sessions in Google Colab will demonstrate how machine learning, computer vision, and simulation techniques can accelerate microplastic research and policy decision-making.
Aim
To equip researchers and professionals with advanced analytical, AI-driven, and engineering approaches for detecting microplastics, assessing their ecological and health impacts, and developing sustainable mitigation strategies.
Workshop Structure
📅 Day 1: Precision Characterization & Analytical Workflows
- Objective: Mastering the transition from environmental sampling to high-fidelity data
- Advanced Spectral Fingerprinting: Leveraging Quantum Cascade Laser (QCL) and automated μ-Raman spectroscopy for sub-micron particle identification
- The Weathering Paradigm: Analyzing the “Eco-corona” effect—how biological and chemical biofilms alter the toxicological profile of aged polymers
- Data Harmonization: Implementing ISO/TC 61/SC 14 standards for global inter-laboratory reproducibility
- 💻 Technical Practicum 01 (Google Colab): AI-Driven Spectroscopy Interpretation
- Implementing a machine learning (Random Forest/SVM) pipeline to automate classification of unknown polymers against the Open Specy database, reducing manual processing time by 80%
📅 Day 2: Ecotoxicology & The Human Health Frontier
- Objective: Assessing biological risk through the lens of bio-accumulation and translocation
- Advanced In-Vitro Modeling: Utilizing Organ-on-a-Chip and 3D cell culture models to simulate MNP translocation across the human intestinal and blood-brain barriers
- Atmospheric Flux & Tire-Wear Particles: Modeling the long-range transport and deposition of “invisible” microplastics in urban and polar regions
- Regulatory Compliance: A deep dive into the 2026 EU Microplastics Restriction and its impact on the cosmetics, detergent, and agricultural sectors
- 💻 Technical Practicum 02 (Google Colab): Computer Vision for Morphology Quantification
- Deploying a pre-trained YOLOv10 neural network to perform real-time counting, sizing, and shape-factor analysis (sphericity vs. fiber) from microscopic image datasets
📅 Day 3: Mitigation Engineering & Circular Economy Solutions
- Objective: Engineering a plastic-neutral future through innovation and remediation
- Next-Generation Materials: Designing for degradability—Polyhydroxyalkanoates (PHAs) and cellulose-based structural alternatives with zero-microplastic footprint
- Industrial Filtration Architecture: Engineering biomimetic captures and advanced oxidation processes (AOPs) for high-efficiency wastewater treatment
- Bioremediation & Enzymatic Pathways: Assessing the commercial viability of PETase and microbial consortia for localized plastic waste neutralization
- 💻 Technical Practicum 03 (Google Colab): Intervention Impact Simulation
- Using Monte Carlo simulations to model the efficacy of different industrial filtration strategies on long-term environmental concentration trends, supporting data-driven policy decisions
Who Should Enrol?
-
Researchers, environmental scientists, chemists, and sustainability professionals working on plastic pollution.
-
PhD scholars and academicians in environmental science, materials science, toxicology, or marine studies.
-
Policymakers, regulatory experts, and industry professionals interested in plastic sustainability.
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Basic familiarity with Python or data analysis is helpful but not required.
Important Dates
Registration Ends
May 28, 2026
IST 4 : 30 PM
Workshop Dates
May 28, 2026 – May 30, 2026
IST 5 : 30 PM
Workshop Outcomes
Characterize and classify microplastics using advanced spectroscopy and AI tools.
Apply computer vision to quantify microplastic morphology from microscopy images.
Evaluate ecological and human health risks associated with microplastic exposure.
Design mitigation strategies including biomaterials, filtration systems, and enzymatic degradation.
Model long-term environmental impacts of intervention strategies using simulation techniques.
Recording fee
Participants in India
₹2,499
Participants outside India
$50
- All session recordings
- Study material
- Certificate after completion
- 1-year access
The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.
Frequently asked questions
Will I get the recording?
Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).
What if I miss a live session?
Watch the recording in your dashboard and send your questions to the mentor through the support desk.
Do I get a certificate?
Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.
Which fee category applies to me?
Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.
How can I pay?
By card, UPI or PayPal on the payment page; international bank transfer is also available there.
What is the refund policy?
See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy
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