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Sources of Air Pollution
Published in Subhash Verma, Varinder S. Kanwar, Siby John, Environmental Engineering, 2022
Subhash Verma, Varinder S. Kanwar, Siby John
Dust is a commonly used term applied to solid particles larger than colloidal particles that are capable of temporary suspension in air or other gases. These are formed by the natural disintegration of rock and soil or by mechanical processes such as grinding and spraying, with their size varying from 1 µm to 200 µm.
Cleaning of Organic Objects and Materials
Published in Radko Tiňo, Katarina Vizárová, František Krčma, Milena Reháková, Viera Jančovičová, Zdenka Kozáková, Plasma Technology in the Preservation and Cleaning of Cultural Heritage Objects, 2021
Radko Tiňo, Katarina Vizárová, František Krčma, Milena Reháková, Viera Jančovičová, Zdenka Kozáková
Dust is airborne particles that collect on the surface of an object and are not bound to a substrate or to each other. It can be removed with a dust cloth (lacquered tabletops), a soft natural bristle brush (inlaid or gilded surfaces), or a vacuum cleaner.
Coal Dust
Published in S. Komar Kawatra, Advanced Coal Preparation and Beyond, 2020
Dust towers provide a direct measurement of a dust suppressant’s ability to reduce airborne dust. Material can be dropped down a dust tower to subject it to a consistent set of mechanical forces. A countercurrent stream of air flowing up the dust tower will catch any generated fine particles and carry them to a side port at the top, which can be used to catch the dust. The dust can then be measured as practical, such as with a PM analyzer. The idea is to present a consistent test bed that can be used to compare the effectiveness of different dust suppressants.
Dust impact on the performance of solar photovoltaic module: a new prospect
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2023
Dust is a collection of small particles in the atmosphere that comes from various sources such as soil, pollen, and other organic matter as shown in Figure 1 (Vedulla, Geetha, and Senthil 2023). Dust particles are usually invisible to the naked eye but can be seen under a microscope. The particles are typically made up of a variety of materials, including minerals, metals, and organic matter (Alagoz and Apak 2020). Dust particles can be inhaled and can cause various health problems, such as respiratory issues, eye and skin irritation, and allergies (Cordero et al. 2018). Dust has a significant impact on the performance of PV modules (Alquthami and Menoufi 2019). Dust on the surface of the module reduces the amount of sunlight that reaches the module, reducing the output power and efficiency of the module (Kazem et al. 2013). Dust can also block air flow around the module, reducing cooling and increasing the internal temperature of the module. This can reduce the lifetime of the module and can also lead to hot spots, which can cause premature failures (Zaraket et al. 2019). Cleaning the modules regularly can help to reduce the impact of dust on performance (Kazem and Chaichan 2016).
Fault classification using deep learning based model and impact of dust accumulation on solar photovoltaic modules
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2023
Rahma Aman, M. Rizwan, Astitva Kumar
The impacts of six different types of dust pollutants: ash, laterite, stone dust, sandy, coal powder, and cement on the efficiency of photovoltaic panels. The performance of such devices is degraded by dust. The effect of dust deposition on the power production of solar PV modules was examined in eastern Saudi Arabia (Fan et al. 2021). The study found that solar PV modules kept dirty for over six months can lose up to 50% of their output which shows most significant defects in photovoltaic systems are investigated in this research (Adinoyi and Said 2013) (Sayyah et al., 2014). The methodologies for monitoring photovoltaic systems that have been developed in recent research and reviewed, assessed in order to highlight their differences, advantages, and limitations (Triki-Lahiani, Bennani-Ben Abdelghani, and Slama-Belkhodja 2018). The above literature survey helps in getting better knowledge of dust accumulation on solar panels. To detect dust deposition, thermal images have been used recently and several deep learning approaches are used to detect the fault. This paper proposes an AI-based fault distance estimation method using signal processing. The proposed approach procedure was developed through detailed analysis. Feature extraction was used to convert massive data sets into feature sets to reduce computational burden. After that, the most predictive features were selected from the entire set to increase precision and speed up training. A support vector machine (SVM) or neural network (NN) determined fault distance using the selected features (Ray and Salkuti 2022; Sinha, Ray, and Salkuti 2018).
Effects of electrode materials and dimensions of an electrostatic spray scrubber on water droplet charging for dust removal
Published in Journal of the Air & Waste Management Association, 2022
Xiaochuan Li, Reyna Madison Knight, Jeb S. Hocter, Bo Zhang, Lingying Zhao, Heping Zhu
Dust is a significant problem in mining, agricultural food production, building construction, and other industrial operations. Dust emissions negatively affect human and animal health as well as environmental quality (Ru, Zhao, and Hadlocon et al. 2017; Xiao et al. 2019; Xiaochuan et al. 2019). A variety of dust capture and removal methods and equipment with different working mechanisms have been invented for different industrial processes, such as filters, wet scrubbers, and electrostatic precipitators. However, the removal efficiencies of conventional gas cleaning systems, such as inertial scrubbers, bag filters, and electrostatic precipitators (Balachandran, Jaworek, and Krupa et al. 2003; Guo and Xue 2021; Huang and Chen 2002), rapidly decrease for fine particles with diameters smaller than 1 µm, known as submicron particles. The low removal efficiency for submicron particles cannot satisfy the environmental control requirements for industrial applications that can have significant concentrations of particulate matter (PM) in this size range. In addition, dust particles smaller than 2.5 microns pose a greater threat to human health. As more stringent environmental regulations are increasingly being implemented, there is an urgent need for a method to effectively remove fine dust particles from the air.