LEE-Makina Mühendisliği-Doktora

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http://hdl.handle.net/11527/19373

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Konu "Air quality" ile LEE-Makina Mühendisliği-Doktora'a göz atma
  • Öge
    Development of QCM sensors for measuring particulate matter concentration
    (Graduate School, 2024-05-30) Javadzadehkalhoran, Majid ; Trabzon, Levent ; 503182013 ; Mechanical Engineering
    Particulate matter (PM) refers to a mixture of tiny solid particles and liquid droplets suspended in the air. These particles come in various sizes and compositions, and they can be made up of different substances including dust, dirt, soot, smoke, and liquid droplets. PM is typically categorized by size: PM10 includes particles with diameters that are 10 micrometers and smaller, while PM2.5 encompasses those with diameters that are 2.5 micrometers and smaller. These fine particles are of particular concern because they can penetrate deep into the lungs and even enter the bloodstream, posing significant health risks. PM1 is ultrafine particle (UFP), with a diameter of 1 µm or less. This is roughly 70-100 times smaller than the width of a human hair. PM1 particles can bypass the body's natural defenses much easier than PM2.5. Exposure to PM poses several significant health risks, primarily due to its ability to penetrate deep into the respiratory system and even enter the bloodstream. PM can irritate the respiratory tract, leading to conditions such as asthma, bronchitis, and other chronic respiratory diseases. Fine particles (PM2.5) can reach the alveoli in the lungs, causing inflammation and aggravating existing lung conditions. Long-term exposure to PM is linked to heart diseases, including heart attacks, arrhythmias, and hypertension. The particles can cause systemic inflammation and oxidative stress, which contribute to the development and progression of cardiovascular conditions. Studies have shown a correlation between PM exposure and premature mortality. People with pre-existing health conditions, the elderly, and children are particularly vulnerable to the harmful effects of PM. The severity of these health risks depends on several factors, including the concentration and composition of the particulate matter, the duration of exposure, and individual susceptibility. Reducing PM emissions through regulatory measures and personal protection strategies is crucial for mitigating these health risks. PM originates from a variety of sources, both natural and human-made. Key sources include combustion processes like emissions from vehicles, industrial facilities, power plants, residential heating or burning of biomass; construction activities such as dust from construction sites, demolition or road dust from vehicles traveling on unpaved roads; and natural sources like windblown dust, volcanic eruptions, and wildfires. Public awareness regarding air quality and the detrimental effects of particulate matter exposure has significantly increased in recent years. This has led to a surge in demand for reliable and accurate PM sensors for various applications, including indoor air quality monitoring, environmental monitoring, and occupational safety assessments. To ensure the effectiveness of these sensors, robust testing and evaluation procedures are crucial. However, conventional PM test setups often pose significant barriers due to their inherent limitations. Traditional PM test setups typically rely on large, complex equipment such as Scanning Mobility Particle Sizers (SMPS) and Aerosol Mass Spectrometers (AMS). While these instruments offer exceptional accuracy and detailed PM characterization, their high cost, operational complexity, and significant maintenance requirements make them inaccessible for many potential users. This limited accessibility hinders the widespread deployment and adoption of PM sensor technology, particularly for applications requiring real-time monitoring or deployment in resource-constrained settings. This thesis proposes a novel approach to address the challenges associated with conventional PM test setups. We introduce a cost-effective experimental setup specifically designed for PM sensor testing. This compact design prioritizes affordability and ease of use by leveraging readily available and commercially obtainable components. The core of the setup lies in a custom-made PM generator capable of producing PM from diverse sources, including dry powder, liquid suspension, and combustion. This versatility allows for a comprehensive evaluation of sensor performance under a wide range of PM types, simulating real-world scenarios encountered in various environments. A key innovation of this study lies in the combined use of Quartz Crystal Microbalance (QCM) and laser sensors within the test setup. Laser sensors are well-established for detecting larger PM due to their ability to measure particle size and number concentration based on light scattering principles. However, their sensitivity diminishes for ultra-fine PM, particularly those resembling smoke particles. By incorporating a QCM sensor, the setup gains the ability to effectively detect these smaller particles through mass accumulation on the sensor surface. This combined approach provides a more complete picture of PM concentration across a broader size spectrum, offering valuable insights into air quality. The subsequent sections of this thesis will delve into the details of the proposed experimental setup, including the design considerations for the PM generator and the selection criteria for the chosen sensor technologies. We will then present the findings from a comprehensive investigation into the performance of the QCM sensor under various PM sources and ambient conditions. In this thesis, an automatic aerosol generation setup was developed to maintain a stable PM concentration during experiments. This setup incorporates three different techniques for generating PM to investigate their effects on sensor response. In first technique the aerosol is generated from PM suspended in water. Dry chemical powders are initially mixed with water, and the mixture is then evaporated using a nebulizer. This aerosol passes through a custom-made PM dryer, which consists of a network of pipes running through a cylinder filled with silica gel grains. Moisture is removed from the mixture through diffusion as it travels through these pipes. The dried aerosols are then expelled from the PM chamber by an air pump. The second method is considered for creating dry aerosol from chemical powders. The powder is dispersed in a cylinder using pressurized air. Inside the cylinder, two small fans keep the particles suspended, creating a homogeneous mixture. The aerosol is then pushed out by a piston, which is controlled by a stepper motor and threaded bar. The third technique is used for smoke aerosol generation. Particles are produced by burning an incense stick and are collected in a smoke chamber. Similar to the method, the PM mixture exits the chamber via an air pump. All pumps and the stepper motor are controlled by a microcontroller connected to a computer. QCM is a compelling technology with potential applications in PM measurement, offering a unique approach that complements other established techniques. QCM technology holds promise for PM detection due to its distinct capabilities. Central to a QCM is a precisely crafted AT-cut quartz crystal, celebrated for its exceptional piezoelectric properties. These properties enable the crystal to convert mechanical stress into a measurable electrical signal, and conversely, an electrical voltage can cause the crystal to vibrate at a specific frequency. This characteristic frequency serves as a unique identifier, determined by the crystal's size, shape, and, most importantly, its mass. Continuously operating the QCM and implemented pump provides real-time resonance frequency data but does not directly indicate the rate of change in this frequency. To overcome this limitation and streamline the measurement process, this study introduces a novel method using pulsed pump operation. The pump delivers air intermittently, with brief idle periods in between. Each time the pump stops, the QCM's resonance frequency is recorded and compared to the frequency measured at the previous stop. To increase the sticking efficiency of particles, the surface of the QCM has been coated with a layer of grease. Applying this coating proved to be an effective strategy for enhancing sensor response, particularly for dry particles. The coating significantly improved particle adhesion, resulting in a stronger overall response. Furthermore, it reduced variations in sensor response due to differences in particle characteristics, ensuring more consistent performance across a wider range of PM types. The results will highlight the influence of factors such as PM composition, size, relative humidity (RH), and temperature on the sensor response. Finally, the study will discuss the complementary nature of QCM and laser sensors in PM detection, paving the way for the development of more robust and cost-effective PM monitoring systems. By offering a cost-effective and user-friendly alternative to existing test setups, this study has the potential to democratize PM sensor testing and accelerate the development of advanced air quality monitoring solutions. Variations in PM composition and size have a significant effect on the QCM response. Additionally, relative humidity (RH) can alter the sensor response by up to 22%. Although temperature changes in the airflow have minimal impact on the bare QCM response, increasing the temperature from 25°C to 30°C results in a 12% change in response for the grease-coated sensor. Notably, the QCM sensor performs best with small-sized smoke PMs, showing the least sensitivity to ambient conditions. Finally, the study will discuss the complementary nature of QCM and laser sensors in PM detection, paving the way for the development of more robust and cost-effective PM monitoring systems. By offering a cost-effective and user-friendly alternative to existing test setups, this study has the potential to democratize PM sensor testing and accelerate the development of advanced air quality monitoring solutions.