Environmental Analysis

Webinar Date/Time: Wednesday, September 17, 2025 Morning Session: 10:00 AM EST | 7:00 AM PST | 3:00 PM BST | 4:00 PM CEST Afternoon Session: 1:00 PM EST | 10:00 AM PST | 6:00 PM BST | 7:00 PM CEST

Researchers in China developed a novel "water quality fingerprint spectrum" to analyze complex water pollution data in Lake Shahu, revealing key pollution drivers like tourism and offering a scalable framework for improved environmental management.

A new study used advanced techniques, including µ-Raman spectroscopy and machine learning, to map and predict microplastic pollution on São Paulo’s urban beaches.

A new study has confirmed the presence of multiple microplastic types in human amniotic fluid using a dual-method approach, raising concerns about potential long-term impacts on fetal development.

Researchers from Nanjing University of Information Science & Technology have introduced a breakthrough AI-enhanced multimodal strategy for real-time detection of polyamide microplastics contaminated with heavy metals.

A new study published in Geoderma demonstrates that combining soil spectroscopy with radar-derived vegetation indices and environmental data significantly improves the accuracy of soil organic carbon predictions in Brazil’s semi-arid regions.

A new study published in the Journal of South American Earth Sciences reveals how microbial activity, low pH conditions, and sediment chemistry in Brazil’s São Carlos Shale uniquely preserved diverse Upper Cretaceous fossils, offering fresh insights into the paleoenvironment of the Bauru Basin.

A recent study presented a dual-method approach combining confocal micro-Raman spectroscopy and Nile Red-assisted fluorescence microscopy to enhance the accuracy and throughput of microplastics detection in environmental samples.

Researchers from Cranfield University and partners from industry demonstrated the feasibility of using advanced, non-destructive imaging techniques to analyze and standardize organo-mineral fertilizers.

Researchers from Jinan University and Guangzhou Customs Technology Center have developed a cost-effective UV-vis spectroscopy and machine learning method to accurately identify recycled PET content as low as 10%, advancing sustainable packaging and circular economy efforts.

Shanghai researchers develop high-accuracy machine learning system to identify colorless microplastics across varied environments.

A new study published in Marine Pollution Bulletin reveals significant microplastic contamination at 5000-meter depths in the Central Indian Ocean Basin, highlighting the widespread reach of plastic pollution and the urgent need for regulatory action.

Researchers from Tohoku University, Shibaura Institute of Technology, and Shizuoka University unveil advanced sorting system using NIR, THz, and machine learning for improved recycling outcomes.

A study published in Chemosphere by researchers at the Technical University of Denmark demonstrates that fluorescence spectroscopy can serve as a rapid, on-site screening tool for detecting pharmaceutical contaminants in groundwater.

Researchers from several Chinese universities have developed a low-cost, red mud-based catalyst doped with manganese oxides that efficiently oxidizes toluene at lower temperatures, offering a sustainable solution for air pollution control and industrial waste reuse.

Researchers at the Sinopec Research Institute have developed a novel method using virtually generated mid-infrared spectra to accurately quantify plastic blends, offering a faster, scalable solution for recycling and environmental monitoring.

Webinar Date/Time: Tue, Jun 10, 2025 11:00 AM EDT

A new study published in Chemosphere by researchers at Bharathidasan University reveals alarming seasonal microplastic (MP) contamination in fish and shellfish from India's Pichavaram Mangroves.

A recent review article highlights the promise of near-infrared (NIR) spectroscopy for on-farm analysis of liquid organic manure.

A new study published in Geoderma Regional by J. A. Arias-Rios and colleagues at IFAB demonstrates that near-infrared (NIR) spectroscopy is a rapid, cost-effective tool for assessing soil and tree traits critical to forest ecosystem monitoring and management.

Webinar Date/Time: Tuesday, May 27, 2025 at 11:00 AM EST

Here is a collection of recent studies that used spectroscopic techniques in environmental analysis.

A recent study demonstrated the utility of Raman spectroscopy and machine learning (ML) algorithms to classify plastic types found in waste of electric and electronic equipment (WEEE) streams.

A new study recently demonstrated how micro-PIXE spectroscopy can effectively trace the elemental sources of air pollution in urban and indoor environments in India.

In a recent study published in Marine Pollution Bulletin, a team of researchers from several Spain and Portugal universities and institutions (Rovira i Virgili University, Universitat de Barcelona, University of Porto, and Institut d'Investigació Sanitaria Pere Virgili (IISPV) assessed microplastic (MP) contamination along the Mediterranean coastline.

University of Granada researchers compared different methods and their effectiveness in classifying ink found in historical documents.

A new approach to analyzing bituminous coals was created using Fourier transform infrared spectroscopy.

A new study published in Chemical Engineering Journal by researchers from Northeast Agricultural University in China reveals that biochar aging, influenced by environmental factors like UV exposure and wet-dry cycles, alters dissolved organic matter composition and affects its effectiveness in remediating cadmium-contaminated soil.

Spectroscopy sat down with Samiksha Singh to discuss her team’s latest research in microplastics research, which provided insight into how marine monitoring can improve mitigation of plastic pollution.

Researchers at Zhengzhou Police University have developed an AI-powered Raman spectroscopy method that achieves 100% accuracy in identifying plastic beverage bottles.