マイクロプラスチック分析

マイクロプラスチックが高濃度で検出される場所は月単位で増え続けています。マイクロプラスチック汚染の分析は困難な作業ではあるものの、その重要性は高まるばかりです。

マイクロプラスチックについて

マイクロプラスチックとは?
 

定義によると、直径 5 mm 未満のポリマー粒子がマイクロプラスチック(MP)粒子と呼ばれています。また、その由来によって、一次粒子と二次粒子に分類されます。

マイクロプラスチックはどこから来るのか?私たちにどのような影響を与えるか?

マイクロプラスチック粒子 (MPP) は、一次粒子と二次粒子に分類されます。一次粒子は、例えば化粧品のピーリング粒子のように、産業用として特別に製造されたものです。

二次的粒子は、比較的大きなプラスチック部品が物理的、生物的、化学的に変性または劣化することで形成されたもので、環境中に放出されるマイクロプラスチックの最も大きな原因となります。主に、不適切に処理されたプラスチック廃棄物の分解、タイヤの摩耗、合成繊維の洗濯屑などがその要因です。

マイクロプラスチックは、河川敷、北極の氷、天然の肥料、土壌、さらには飲料水にさえも、顕著な量が含まれています。ここ数十年の間に、マイクロプラスチックは人間の食物連鎖にまで入り込んでいます。つまり、マイクロプラスチック粒子の遍在性は、私たちの環境にとって非常に大きな課題となっているのです。

Martin Löder 博士と Christian Laforsch 教授が率いるチームは、ドイツでも有数のマイクロプラスチック分析ラボを運営しています。

How to Analyze Microplastics

どのようにその痕跡をたどることができるのでしょうか?

海洋生物に対する脅威はほぼ理解されていますが、現時点ではその全容を把握することはできていません。しかし、海洋生物や魚に取り込まれることで、人間の食物連鎖がマイクロプラスチックによって汚染されることになります。MPP には問題のある可塑剤が含まれていたり、他の有機汚染物質を吸着する可能性があるため、長期的な影響は計り知れません。

ミリメートルサイズの粒子はすでに MPP とみなされており、肉眼でも識別することができますが、マイクロプラスチックを検出するための最も基本的な手法としては、まず光学顕微鏡の利用を挙げるべきでしょう。

しかし、この方法では、検出された MPP の影響や起源を調べるうえで特に重要となる化学的な情報は得られません。この問題に対して、赤外およびラマン分光法は、未知のポリマー粒子を数分以内に同定する可能性を提供し、さらに顕微鏡下での分析にも対応します。これに加え、FT-IR イメージングと機械学習アルゴリズムを用いた新しいアプローチでは、分析作業を大幅に簡略化すること可能です。

ブルカーのアプリケーションスタッフが、海塩中にマイクロプラスチックが混入していないか調査している様子。試料の準備からソフトウェアによる自動分析まで、マイクロプラスチック分析の基本を解説します。

 

What is the Best Way to Analyze Microplastics?

The typical workflow of microplastics analysis:

Basics steps involved in microplastics analysis. Samples must first be prepared according to their origin, then filtered using appropriate filters like aluminum oxide, then measured by FT-IR imaging and lastly, evaluated using machine learning.

The chemical analysis usually starts with a liquid sample that was prepared differently depending on its origin. This sample is filtered onto an IR-transparent substrate and measured in its entirety by FT-IR IMaging to capture all particles present on the filter. The Chemical Image is then analyzed automatically with a robust machine learning algorhythm.

FT-IR microscopy is the most common approach found in microplastic research. The workflow is super simple and the results provide high precision and, most of all, reliability. Especially FT-IR imaging by focal-plane array detectors is the state-of-the-art solution. If you want to know more about our FT-IR instrument setup, take a look at our FT-IR microscopes.

Why FT-IR imaging for microplastics analysis?

The Strengths of FT-IR Imaging

Infrared (IR) radiation interacts with the microplastic particles, creating characteristic IR absorption patterns. These patterns are then used to identify the particles. If you want to catch up on the basics of FT-IR, click here.

By far the biggest benefit of FT-IR is its exceptional reliability and easy application. Any kind of plastic particle (dark coloured, filled, fluorescent, ...) can be analyzed requiring minimal user effort.

True imaging detectors unlock the potential of FT-IR

But - when you combine FT-IR with a Focal-plane array (FPA) detector things get really interesting. The result is a very powerful imaging tool capable simplifying microplastics analysis to routine levels. To learn about FT-IR imaging, click here.

It comes down to a fully automated approach that can tolerate a lot of contamination on the filter (e.g. from a sediment) without any negative impact on the measurement results. Ultimately, FT-IR imaging ensures that no particle remains undetected, providing utmost reliability and measurement speed.

The secret to microplastics is the right compination of hard- and software

Besides the analytical method, the software is crucial to analyze microplastics. Traditionally, microplastics spectral reference libraries and provide statistical analysis of size, number and identity. But there is a limit to what such libraries can offer. If you need a very reliable and robust analysis, you must greatly increase the number of spectra within the library, which slows down the analysis considerably.

But in order to make microplastic analysis scalable and routine, data analysis must become faster and, above all, more intelligent. Using huge libraries is simply not practical when time is of the essence. That's why researchers have developed new methods that use machine learning, which fully exploit the immense potential of chemical imaging.

Here, instead of checking each spectrum individually for its identity, the entire FT-IR image is processed straight away. The intelligent algorithm analyzes the entire FT-IR image at once, making the analysis orders of magnitude faster and even more reliable. To bring this to market, Bruker teamed up with Purency to provide and end-to-end microplastic solution, that covers the instrumentation and software analysis for high-workload labs and researchers.

Learn why FT-IR imaging by FPA detectors is the gold standard in microplastic analysis.
The team led by Dr. Martin Löder and Prof. Christian Laforsch maintains one of the leading microplastics analysis laboratories in Germany.
Microscopic image of a sediment sample from a spanish river bed. A long, black fiber is clearly visible. Analysis will be performed by ATR-FT-IR without further sample preparation.

Guide to FT-IR Analysis of Microplastics

Guide to FT-IR Analysis of Microplastic Particles

We have already mentioned, that researchers and microplastics experts around the world count on FT-IR imaging. The reason for this is for one the straightforward, easy workflow, as well as the unmatched reliability, speed and precision that is offered by the technology. In the following, we will provide deeper insights into the basics of the analysis in the lab.

Step #1: Sample Preparation

After taking a sample, it might have to undergo pre-treatment, depending on the contamination from the source, and is atferwards filtered unto compatible filer materials. Very clean samples like drinking water are usually filtered directly onto a suitable filter. But environmental samples like ocean water, river sediments or soil may contain sand or plant material and must be prepared prior to FT-IR analysis.

To remove larger, non-micro particles, mutiple, differently-sized filters are used. These bigger particles are later analyzed by macroscopic FT-IR spectrometers like the ALPHA II. After this, the samples are treated with salt solutions of different concentrations, which is called density separation. During the process, sand and other non-plastic particles sink to the bottom and can be easily removed afterwards.

But what about more complex samples like fish or mussels? Such samples need an as complex treatment to remove all organic matter that is left after dissection. Typically, enzymatic digestions, acidic or alkaline treatment is performed prior to filtration.

Mesoplastic found on beach and sorted for FT-IR analysis.

Step #2: Filtration

We previously mentioned that aluminum oxide filters are the best choice for microplastics analysis. But of course there are other materials available, like silicon, PTFE, or gold-coated polycarbonate filters which all have distinct advantages and disadvanatges. However, since aluminium oxide filters have become the standard for FT-IR analysis of microplastics, we will also adhere to those standards in our website and videos.

Aluminium oxide filter loaded with microplastics.

Step #3: FT-IR Imaging Analysis

Out of the three avilalbe measurements modes of FT-IR (transmission, reflection and ATR) transmission is the most suited for a fast and hassle-free analysis. Why? Well, ATR is a contact based method and particles can stick to the crystal which requires a user to clean it, making it unsuitable for automation. In reflection, thicker particles are hard to measure and produce spectral artifacts, making it less reliable. Finally, analysis in transmission is contactless and will give good spectra in a short amount of time.

Same microplastic filter after FT-IR imaging analysis.

Step #4: Particle Classification and Data Evaluation

The use of machine learning in the analysis of microplastics is on the rise. With it, researchers have found a reliable way to make data evaluation easy to use for anyone. Following best practices, Bruker teamed up with Purency to promote the Microplastics Finder (MPF).The MPF is a software that automatically analyzes whole FT-IR images of microplastic samples within a few minutes. It yields a comprehensive statistics of all particles present on the filter and classifies them by number, identity and size. All with just one click.

The classifying algorhithm is was trained by real world data that has been evaluated by different microplastic experts. In short, it brings you their combined knowledge into your lab and at your fingertips. Hence, the Microplastics Finder is the optimal tool for routine analysis of microplastic samples and one of the most promising candidates for future standardizaton. The goal is, to guarantee comparability between different laboratories, researchers and analytical insitutes around the world, eleminating human bias altogether.

Particle statistics of the microplastics finder by Purency.