scholarly journals THE DEVELOPMENT OF PORTABLE AIR QUALITY DETECTION

2020 ◽  
Vol 15 (Number 2) ◽  
pp. 12-19
Author(s):  
Siti Farah Hussin
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Good Condition ◽  
Ammonia Nitrogen ◽  
Detection Accuracy ◽  
Gas Temperature ◽  
Chemical Waste ◽  
Detection Range ◽  
Quality Detection ◽  
Temperature And Humidity

Air quality is very important to ensure the health of humans, plants, and even animals. The tragedy of chemical waste disposal in the Kim Kim river has resulted in air pollution in the surrounding area. Therefore, this innovation has been developed to produce a mobile device that has a low cost, detection of the gas in real-time, and overcome the problems faced due to chemical waste pollution such as shortness of breath, nausea, and vomiting. Portable air quality detection is an innovation used to detected and measured the connections between software and hardware that are required for analysis purposes. The outputs detected are carbon dioxide, benzene, alcohol, ammonia, nitrogen oxide, and smoke. Data analysis was done by making a comparison between the output values in LCD and Favoriot and Blynk. This project also can measure the value of temperature and humidity. The sensor used to detect gas readings is MQ135 gas sensor and for temperature and humidity sensor is DHT22 sensor. The value of gas, temperature, and humidity in the environment will be displayed on the website as well as on the phone applications. This innovation used two types of platforms to display the data, Favoriot in website platform and Blynk used on smartphones. In addition, this value will be recorded and stored on the website for future use by the users. The users will also be able to compare readings before and after to ensure that the air in the environment is in good condition. In addition, this project can warn users if the reading is at danger level. The buzzer will sound and users will be notified by email. For future recommendations, the A3OZ sensor can be used to achieve high precision values for O3 and NO2 readings with a detection range of 0-10 ppm and detection accuracy of 20 ppb

scholarly journals Domain adaptation based deep calibration of low-cost PM2.5 sensors

2021 ◽  
Author(s):  
Sonu Kumar Jha ◽  
Mohit Kumar ◽  
Vipul Arora ◽  
Sachchida Nand Tripathi ◽  
Vidyanand Motiram Motghare ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Domain Adaptation ◽  
Low Cost ◽  
Monitoring Network ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Proposed Model ◽  
Temperature And Humidity ◽  
Calibration Approach

<div>Air pollution is a severe problem growing over time. A dense air-quality monitoring network is needed to update the people regarding the air pollution status in cities. A low-cost sensor device (LCSD) based dense air-quality monitoring network is more viable than continuous ambient air quality monitoring stations (CAAQMS). An in-field calibration approach is needed to improve agreements of the LCSDs to CAAQMS. The present work aims to propose a calibration method for PM2.5 using domain adaptation technique to reduce the collocation duration of LCSDs and CAAQMS. A novel calibration approach is proposed in this work for the measured PM2.5 levels of LCSDs. The dataset used for the experimentation consists of PM2.5 values and other parameters (PM10, temperature, and humidity) at hourly duration over a period of three months data. We propose new features, by combining PM2.5, PM10, temperature, and humidity, that significantly improved the performance of calibration. Further, the calibration model is adapted to the target location for a new LCSD with a collocation time of two days. The proposed model shows high correlation coefficient values (R2) and significantly low mean absolute percentage error (MAPE) than that of other baseline models. Thus, the proposed model helps in reducing the collocation time while maintaining high calibration performance.</div>

scholarly journals Domain adaptation based deep calibration of low-cost PM2.5 sensors

2021 ◽  
Author(s):  
Sonu Kumar Jha ◽  
Mohit Kumar ◽  
Vipul Arora ◽  
Sachchida Nand Tripathi ◽  
Vidyanand Motiram Motghare ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Domain Adaptation ◽  
Low Cost ◽  
Monitoring Network ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Proposed Model ◽  
Temperature And Humidity ◽  
Calibration Approach

<div>Air pollution is a severe problem growing over time. A dense air-quality monitoring network is needed to update the people regarding the air pollution status in cities. A low-cost sensor device (LCSD) based dense air-quality monitoring network is more viable than continuous ambient air quality monitoring stations (CAAQMS). An in-field calibration approach is needed to improve agreements of the LCSDs to CAAQMS. The present work aims to propose a calibration method for PM2.5 using domain adaptation technique to reduce the collocation duration of LCSDs and CAAQMS. A novel calibration approach is proposed in this work for the measured PM2.5 levels of LCSDs. The dataset used for the experimentation consists of PM2.5 values and other parameters (PM10, temperature, and humidity) at hourly duration over a period of three months data. We propose new features, by combining PM2.5, PM10, temperature, and humidity, that significantly improved the performance of calibration. Further, the calibration model is adapted to the target location for a new LCSD with a collocation time of two days. The proposed model shows high correlation coefficient values (R2) and significantly low mean absolute percentage error (MAPE) than that of other baseline models. Thus, the proposed model helps in reducing the collocation time while maintaining high calibration performance.</div>

Urban Air Computing: For Air Quality Detection

2019 ◽  
Author(s):  
Nikhitha N ◽  
Rajashekara Murthy S.
Keyword(s):  
Air Quality ◽  
Urban Air ◽  
Quality Detection

Distribution of heterotrophic and autotrophic organisms in a biological aerated filter

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
O. González-Barceló ◽  
S. González-Martínez
Keyword(s):  
Municipal Wastewater ◽  
Wastewater Treatment Plants ◽  
Low Cost ◽  
Ammonia Nitrogen ◽  
Organic Load ◽  
Homogeneous Distribution ◽  
Municipal Wastewater Treatment ◽  
Filter Media ◽  
Aerated Filter ◽  
Secondary Settling

Biological aerated filtration is a viable option for small municipal wastewater treatment plants. A low cost filter media was obtained by triturating volcanic rock. An apparent porosity of 46 % and a specific surface area of 395 m2/m3·d were obtained once the filter was packed by using a grain size of 8.2 mm. The performance of the system, operated as a biological filter, was evaluated under an average organic load of 2.6±0.4 kgCODT/m3·d (6.7±1.1 gCODT/m2·d) without primary and secondary settling. The average CODT decreased from 220 mg/l in the influent to 88 mg/l in the effluent and the CODD was decreased from 148 mg/l in the influent to 50 mg/l in the effluent. The filter media, in combination with the biofilm, allowed a 75 % TSS removal. The ammonia nitrogen decreased from 51 mg/l in the influent to 33 mg/l in the effluent. The maximum flux coefficients of 9.3gCODdissolved/m2·d and 2.9gNH4-N/m2·d at the biofilm surface were used to simulate, with the Michaelis-Menten model, the profiles of dissolved COD, ammonium and nitrates through the aerated filter. It was possible to conclude that the backwashing procedure removed the excess biomass and was responsible for a homogeneous distribution of heterotrophic and autotrophic microorganisms along the filter depth.

scholarly journals Low-Cost Organic Adsorbents for Elemental Mercury Removal from Lignite Flue Gas

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2174
Author(s):  
Marta Marczak-Grzesik ◽  
Stanisław Budzyń ◽  
Barbara Tora ◽  
Szymon Szufa ◽  
Krzysztof Kogut ◽  
...  
Keyword(s):  
Flue Gas ◽  
Low Cost ◽  
Elemental Mercury ◽  
Mercury Content ◽  
Flue Gases ◽  
Mercury Removal ◽  
Gas Purification ◽  
Gas Temperature ◽  
Corn Straw ◽  
Flue Gas Purification

The research presented by the authors in this paper focused on understanding the behavior of mercury during coal combustion and flue gas purification operations. The goal was to determine the flue gas temperature on the mercury emissions limits for the combustion of lignites in the energy sector. The authors examined the process of sorption of mercury from flue gases using fine-grained organic materials. The main objectives of this study were to recommend a low-cost organic adsorbent such as coke dust (CD), corn straw char (CS-400), brominated corn straw char (CS-400-Br), rubber char (RC-600) or granulated rubber char (GRC-600) to efficiently substitute expensive dust-sized activated carbon. The study covered combustion of lignite from a Polish field. The experiment was conducted at temperatures reflecting conditions inside a flue gas purification installation. One of the tested sorbents—tire-derived rubber char that was obtained by pyrolysis—exhibited good potential for Hg0 into Hg2+ oxidation, resulting in enhanced mercury removal from the flue. The char characterization increased elevated bromine content (mercury oxidizing agent) in comparison to the other selected adsorbents. This paper presents the results of laboratory tests of mercury sorption from the flue gases at temperatures of 95, 125, 155 and 185 °C. The average mercury content in Polish lignite was 465 μg·kg−1. The concentration of mercury in flue gases emitted into the atmosphere was 17.8 µg·m−3. The study analyzed five low-cost sorbents with the average achieved efficiency of mercury removal from 18.3% to 96.1% for lignite combustion depending on the flue gas temperature.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

Recent advancements in low-cost portable sensors for urban and indoor air quality monitoring

2021 ◽  
Author(s):  
A. Hernández-Gordillo ◽  
S. Ruiz-Correa ◽  
V. Robledo-Valero ◽  
C. Hernández-Rosales ◽  
S. Arriaga
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Portable Sensors
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