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- UPC - IED - ESADE
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Our Solution
Raman Spectroscopy, a cornerstone in modern analytical chemistry, stands out as a non-destructive technique offering detailed insights into chemical composition, molecular structure, and crystalline phases of materials. It hinges on the inelastic scattering of light, known as the Raman effect, to identify molecular characteristics. The principle of Raman Spectroscopy is relatively straightforward: incident light interacts with a sample, causing molecular vibrations. These vibrations lead to changes in the energy of scattered light, providing a unique ‘fingerprint’ of the molecule.
The adaptation of Raman Spectroscopy in the context of the Pipe 4.0 initiative marks a significant innovation. This adaptation, tailored for microRaman analysis of solids, results in a reduced analysis time. A critical component of this system is the use of a specially designed filter kit in conjunction with an air pump. The filter, made of polycarbonate coated with aluminum, is optimized to minimize fluorescence and prevent burning of the sample, thus enhancing the optical contrast between the filter and microplastics (MPs). The porosity of the filter, typically around 5-6um, ensures effective trapping of particles while maintaining airflow. When in operation, the medium volume air sampling pump, set at a rate of approximately 15.0 ± 0.1 L/min, draws in air. The total operation time ranges between 1 to 2.5 hours, carefully balanced to avoid clogging the filter’s pores.
First we need to understand the graph we get:
In a Raman spectrum,
Peaks of the Spectrum
Each peak in the Raman spectrum corresponds to a specific vibration of the sample molecules.
The position of a peak (its wave number) indicates the nature of the molecular vibration, while the height or area under the peak indicates theamount of this molecular species present.
As from the spectroscopic properties of nylon or any type ofpolyester I can interpret if this nylon is in the sample and in what quantity.
Let’s analyze the Spectrum
Comparison between Different Samples
The Raman microscope is an innovative instrument that merges the capabilities of Raman spectroscopy with standard optical microscopy. This integration facilitates detailed analysis of samples at the microscopic level by combining various advanced components and techniques.
Comprehensive Configuration and Process
Image Modes and Resolution
Analytical Process
This comprehensive approach of integrating Raman spectroscopy with microscopy offers a powerful tool for detailed molecular analysis, applicable in various scientific and research fields.
In the sample collection room, technicians engage in the act of recollecting samples. This term encompasses the careful gathering of air samples that will later be analyzed for various contaminants, including microplastics and other pollutants. The process is methodical, ensuring that each sample accurately represents the air quality in the room at that time.
The process of sample collection, crucial for air quality analysis, involves a meticulous setup in separate rooms where the kits are located. The samples are gathered in a dedicated sampling room, and then, using a mobile cart, they are transported for analysis. This system ensures that the samples are not contaminated during transfer. In this setup, a pre-sampling stage is crucial to identify potential contaminants that might affect the accuracy of the Raman analysis. The filters, equipped with a cover for easy sample placement and removal, play a vital role in this process.
Before Raman analysis, there might be preparatory steps or techniques used, although these aren’t specified in your description. Typically, this could involve preparing the samples in a certain way to optimize them for Raman analysis.
An essential part of the process is what’s known as pre-sampling. This step is taken before the actual collection of air samples to prepare and ensure that the equipment is clean, functioning correctly, and free from contaminants that could skew the results. The pre-sampling phase sets the stage for accurate, reliable data collection.
Presampling solutions:
However, Raman Spectroscopy is not without its challenges. One significant limitation is the weakness of the Raman signal, which can be affected by photon impacts. Additionally, fluorescence interference, either intrinsic or from additives and impurities like coloring agents or degradation products, can complicate the analysis. Manual detection of microplastic areas using an optical microscope is often required, which can lead to false positives or negatives.
To mitigate these issues, several pre-sampling solutions have been developed. These include the use of non-linear Raman techniques, cleaning protocols to remove contaminants, photo-bleaching to degrade fluorescing agents, and algorithms designed to eliminate fluorescing agents. Image analysis software has been employed to detect particles, enabling the collection of Raman spectra only at those points. Techniques that enhance the contrast between particles and the filter are also used to map all particles in an area.
We employ Raman Spectroscopy, a technique renowned for its precision in chemical analysis. This method is particularly effective in identifying and quantifying microplastic particles. Crucially, we utilize an adaptation of the Pipe 4.0 technology, specifically modified for analyzing solids. This modification enhances the efficacy of Raman Spectroscopy in dealing with solid microplastic particles, making the analysis more accurate and efficient. By leveraging this advanced approach, we are able to reliably detect and measure the presence of microplastics in the air, providing vital insights into the extent of microplastic pollution in our environment.
This method represents a sophisticated approach to identifying and analyzing microplastics in environmental samples, leveraging advanced spectroscopic techniques to overcome the inherent challenges in such analyses. The ultimate goal is to accurately identify and quantify microplastics to understand their distribution and impact on the environment and human health.
The use of a polycarbonate (PC) filter coated with aluminum in the collection of microplastics is a strategic choice, driven by several key factors that make it particularly suitable for this purpose.
Polycarbonate is a type of thermoplastic polymer known for its strength, durability, and transparency. These properties make it an excellent choice for filtering applications, especially when dealing with microscopic particles like microplastics. The inherent strength of polycarbonate ensures that the filter can withstand the air flow and other physical stresses during the sampling process without breaking or deforming.
The aluminum coating on the polycarbonate filter brings additional benefits. Aluminum, being a metal, adds an extra layer of durability to the filter. More importantly, it plays a crucial role in minimizing fluorescence and preventing the burning of the sample during the Raman spectroscopy analysis. Fluorescence can interfere with the accuracy of Raman spectroscopy, as it may mask or distort the spectral signals of the microplastics. By reducing this fluorescence, the aluminum coating helps in obtaining clearer and more accurate readings.
Another advantage of the aluminum-coated polycarbonate filter is its ability to optimize optical contrast. This feature is particularly beneficial when using image analysis software to detect microplastic particles on the filter. The enhanced contrast makes it easier to differentiate the particles from the filter background, thereby facilitating more accurate detection and analysis.
The porosity of the filter, typically around 5-6 micrometers, is designed to effectively capture microplastic particles while allowing air to pass through. This pore size is a critical factor because it needs to be small enough to trap microplastics but large enough to maintain adequate airflow during the sampling process.
In summary, the choice of a polycarbonate filter coated with aluminum for microplastic collection is a well-considered decision. The combination of polycarbonate’s durability and transparency, enhanced by the aluminum coating’s ability to minimize fluorescence and optimize optical contrast, makes this type of filter highly effective in capturing microplastics from air samples. Its specific porosity further ensures that the filter can efficiently trap these particles without hindering airflow, making it an ideal tool in the study and analysis of microplastic pollution.
Polycarbonate is a type of thermoplastic polymer known for its strength, durability, and transparency. These properties make it an excellent choice for filtering applications, especially when dealing with microscopic particles like microplastics. The inherent strength of polycarbonate ensures that the filter can withstand the air flow and other physical stresses during the sampling process without breaking or deforming.
The aluminum coating on the polycarbonate filter brings additional benefits. Aluminum, being a metal, adds an extra layer of durability to the filter. More importantly, it plays a crucial role in minimizing fluorescence and preventing the burning of the sample during the Raman spectroscopy analysis. Fluorescence can interfere with the accuracy of Raman spectroscopy, as it may mask or distort the spectral signals of the microplastics. By reducing this fluorescence, the aluminum coating helps in obtaining clearer and more accurate readings.
Another advantage of the aluminum-coated polycarbonate filter is its ability to optimize optical contrast. This feature is particularly beneficial when using image analysis software to detect microplastic particles on the filter. The enhanced contrast makes it easier to differentiate the particles from the filter background, thereby facilitating more accurate detection and analysis.
The porosity of the filter, typically around 5-6 micrometers, is designed to effectively capture microplastic particles while allowing air to pass through. This pore size is a critical factor because it needs to be small enough to trap microplastics but large enough to maintain adequate airflow during the sampling process.
In summary, the choice of a polycarbonate filter coated with aluminum for microplastic collection is a well-considered decision. The combination of polycarbonate’s durability and transparency, enhanced by the aluminum coating’s ability to minimize fluorescence and optimize optical contrast, makes this type of filter highly effective in capturing microplastics from air samples. Its specific porosity further ensures that the filter can efficiently trap these particles without hindering airflow, making it an ideal tool in the study and analysis of microplastic pollution.
The filters used to collect samples of microplastics must be able to capture very small particles. We also considered other types of filter before selecting the Policarbonate one. For example, the Politetrafluoroethylene (PTFE) filters are commonly used because of their ability to capture tiny particles. Fiberglass or quartz filters can also be used.
Although we also had as an option:
This is an example of how could we apply this system, but it is obvious that we are going to make a specific analysis for each factory.
Depending on the day, we will do it at different times to have data on the amount of microplastics depending on the number of hours of exposure the person has and the tasks carried out in the factory at each hour of the day.
An example approach is the following:
1 | 9h, 17h |
2 | 10h, 16h |
3 | 11h, 15h |
4 | 12h, 14h |
The amount of time required for significant exposure to microplastics can vary depending on several factors:
There is no universally established standard for «how many hours» are required for significant exposure, but regular monitoring is recommended, for example before and after a work shift.
“Empowering Vietnam textile factories workers by reducing their overexposure to microplastics to avoid lung disseasses.”
Making the invisible impossible to ignore
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