scholarly journals Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 804
Author(s):  
Abdul Samad ◽  
Freddy Ernesto Melchor Mimiaga ◽  
Bernd Laquai ◽  
Ulrich Vogt
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Urban Areas ◽  
Low Cost ◽  
Test Chamber ◽  
Ambient Air ◽  
High Relative Humidity ◽  
Ambient Air Quality ◽  
Drying Efficiency ◽  
The Impact

Air pollution in urban areas is a huge concern that demands an efficient air quality control to ensure health quality standards. The hotspots can be located by increasing spatial distribution of ambient air quality monitoring for which the low-cost sensors can be used. However, it is well-known that many factors influence their results. For low-cost Particulate Matter (PM) sensors, high relative humidity can have a significant impact on data quality. In order to eliminate or reduce the impact of high relative humidity on the results obtained from low-cost PM sensors, a low-cost dryer was developed and its effectiveness was investigated. For this purpose, a test chamber was designed, and low-cost PM sensors as well as professional reference devices were installed. A vaporizer regulated the humid conditions in the test chamber. The low-cost dryer heated the sample air with a manually adjustable intensity depending on the voltage. Different voltages were tested to find the optimum one with least energy consumption and maximum drying efficiency. The low-cost PM sensors with and without the low-cost dryer were compared. The experimental results verified that using the low-cost dryer reduced the influence of relative humidity on the low-cost PM sensor results.

Characterization of Ambient Air Quality in Selected Urban Areas in Uganda: A Low-Cost Approach

2021 ◽  
Author(s):  
Deo Okure ◽  
Engineer Bainomugisha ◽  
Nancy Lozano-Gracia ◽  
Maria Edisa Soppelsa
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Cost Approach

scholarly journals IMPACT OF URBAN LAND USES AND ACTIVITES ON THE AMBIENT AIR QUALITY IN KLANG VALLEY, MALAYSIA FROM 2014 TO 2020

2020 ◽  
Vol 18 (14) ◽  
Author(s):  
Oliver Hoon Leh Ling ◽  
Marlyana Azyyati Marzukhi ◽  
Jie Kwong Qi ◽  
Nurul Ashikin Mabahwi
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Air Pollutants ◽  
Ambient Air ◽  
Air Pollutant ◽  
Land Uses ◽  
Ambient Air Quality ◽  
Residential Areas ◽  
Klang Valley ◽  
The Impact

Ambient air in the urban area normally is more polluted than less developed areas. This is due to the concentration of urban activities, such as industrial, transportations and commercial or business activities. A study about the impact of urban land uses and activities on the levels of air pollutants in Malaysia’s most urbanised and most developed region that is Klang Valley was conducted. Data of Air Pollutant Index (API) and average concentration of selected air pollutants were used to analyse the ambient air quality of the selected five (5) cities or towns in Klang Valley. The air quality condition of the five (5) cities or towns were related to the land use distributions of the cities or towns with a purpose to understand the impact of land uses on the ambient air quality. Furthermore, the changes of ambient air quality before and after Movement Control Order (MCO) were analysed to examine the impact of human activity changes on the ambient air quality. The study found that a city or a town with more industrial and transportation land uses with fewer greens was more polluted than the area with less industrial and transportation land uses with more greens. However, this finding did not apply to all areas due to effect of winds on the distribution of air pollutants. Besides that, because of MCO, most people stayed at home with the mode of “work from home” that caused air pollutant levels in urban areas to decrease due to less urban activities. Nevertheless, there was a risk of an increase in air pollution levels in residential areas due to the concentration of activities, especially driving motor vehicles in residential areas. A recommendation is given to encourage “work from home” and reduce dependency on auto-mobile in residential areas in order to improve the air quality in urban areas.

scholarly journals Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3338
Author(s):  
Ivan Vajs ◽  
Dejan Drajic ◽  
Nenad Gligoric ◽  
Ilija Radovanovic ◽  
Ivan Popovic
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Relative Humidity ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Lower Accuracy ◽  
Wide Range ◽  
The Impact ◽  
Monitoring Stations

Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors are being introduced as complementary, air quality monitoring stations. These sensors are, however, not reliable due to the lower accuracy, short life cycle and corresponding calibration issues. Recent studies have shown that low-cost sensors are affected by relative humidity and temperature. In this paper, we explore methods to additionally improve the calibration algorithms with the aim to increase the measurement accuracy considering the impact of temperature and humidity on the readings, by using machine learning. A detailed comparative analysis of linear regression, artificial neural network and random forest algorithms are presented, analyzing their performance on the measurements of CO, NO2 and PM10 particles, with promising results and an achieved R2 of 0.93–0.97, 0.82–0.94 and 0.73–0.89 dependent on the observed period of the year, respectively, for each pollutant. A comprehensive analysis and recommendations on how low-cost sensors could be used as complementary monitoring stations to the reference ones, to increase spatial and temporal measurement resolution, is provided.

The Concentration Characteristics of PM10 and PM2.5 in Eight Cities of China in March, 2013

2013 ◽  
Vol 807-809 ◽  
pp. 20-23 ◽  
Author(s):  
Tao Sheng ◽  
Jian Wu Shi ◽  
Sen Lin Tian ◽  
Li Mei Bi ◽  
Hao Deng ◽  
...  
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Negative Correlation ◽  
Ambient Air ◽  
Quality Standard ◽  
Meteorological Factor ◽  
Urban Air ◽  
Ambient Air Quality ◽  
Ambient Air Quality Standard

According to the information of air quality which published by the urban air quality real-time publishing platform, the concentration characteristics of PM10 and PM2.5 were studied in Kunming (KM), Changsha (CS), Hangzhou (HZ), Shanghai (SH), Harbin (HEB), Beijing (BJ), Wuhan (WH) and Guangzhou (GZ). The results show that the concentrations of PM10 and PM2.5 exceeded the Ambient Air Quality Standard (GB3095-2012) in varying degrees in March, 2013. The concentrations of PM10 in Wuhan is the highest, reached 164μg/m3, exceeded the standard by 9.3%; the concentrations of PM2.5 is much higher in Wuhan, Changsha and Beijing, the average concentrations were 96μg/m3, 103μg/m3 and 110μg/m3, exceeded the standard by 28.0%, 37.3% and 46.7% respectively. The correlation of PM10 with PM2.5 in most of these cities was good in March. The correlation analysis of pollutant with meteorological factor in Hangzhou, Shanghai, Beijing and Guangzhou was also studied, the results show that the concentrations of PM10 and PM2.5 are weakly positive correlation with temperature in the four cities, negative correlation with relative humidity without Beijing, and negative correlation with wind speed.

scholarly journals Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique

2019 ◽  
Vol 19 (17) ◽  
pp. 11303-11314 ◽  
Author(s):  
Tuan V. Vu ◽  
Zongbo Shi ◽  
Jing Cheng ◽  
Qiang Zhang ◽  
Kebin He ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Action Plan ◽  
Ambient Air ◽  
Meteorological Conditions ◽  
Assessment Process ◽  
Pollutant Emissions ◽  
Ambient Air Quality ◽  
Clean Air ◽  
The Impact

Abstract. A 5-year Clean Air Action Plan was implemented in 2013 to reduce air pollutant emissions and improve ambient air quality in Beijing. Assessment of this action plan is an essential part of the decision-making process to review its efficacy and to develop new policies. Both statistical and chemical transport modelling have been previously applied to assess the efficacy of this action plan. However, inherent uncertainties in these methods mean that new and independent methods are required to support the assessment process. Here, we applied a machine-learning-based random forest technique to quantify the effectiveness of Beijing's action plan by decoupling the impact of meteorology on ambient air quality. Our results demonstrate that meteorological conditions have an important impact on the year-to-year variations in ambient air quality. Further analyses show that the PM2.5 mass concentration would have broken the target of the plan (2017 annual PM2.5<60 µg m−3) were it not for the meteorological conditions in winter 2017 favouring the dispersion of air pollutants. However, over the whole period (2013–2017), the primary emission controls required by the action plan have led to significant reductions in PM2.5, PM10, NO2, SO2, and CO from 2013 to 2017 of approximately 34 %, 24 %, 17 %, 68 %, and 33 %, respectively, after meteorological correction. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion. Our results indicate that the action plan has been highly effective in reducing the primary pollution emissions and improving air quality in Beijing. The action plan offers a successful example for developing air quality policies in other regions of China and other developing countries.

scholarly journals Ambient air quality in an urban area and its effects on plants and human beings: a case study of Tiruchirappalli, India

1970 ◽  
Vol 6 (2) ◽  
pp. 13-19 ◽  
Author(s):  
Sirajuddin M Horaginamani ◽  
M Ravichandran
Keyword(s):  
Air Pollution ◽  
Developing Countries ◽  
Air Quality ◽  
Human Health ◽  
Urban Area ◽  
Urban Areas ◽  
Ambient Air ◽  
Control Measures ◽  
Human Beings ◽  
Ambient Air Quality

Though water and land pollution is very dangerous, air pollution has its own peculiarities, due to its transboundary dispersion of pollutants over the entire world. In any well planned urban set up, industrial pollution takes a back seat and vehicular emissions take precedence as the major cause of urban air pollution. Air pollution is one of the serious problems faced by the people globally, especially in urban areas of developing countries like India. All these in turn lead to an increase in the air pollution levels and have adverse effects on the health of people and plants. Western countries have conducted several studies in this area, but there are only a few studies in developing countries like India. A study on ambient air quality in Tiruchirappalli urban area and its possible effects selected plants and human health has been undertaken, which may be helpful to bring out possible control measures. Keywords: ambient air quality; respiratory disorders; APTI; human health DOI: 10.3126/kuset.v6i2.4007Kathmandu University Journal of Science, Engineering and Technology Vol.6. No II, November, 2010, pp.13-19

scholarly journals Research on Air Quality Analysis Based on Cluster Methods

2021 ◽  
Vol 898 (1) ◽  
pp. 012024
Author(s):  
Zhaoni Li ◽  
Jian Zheng
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Quality Analysis ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Republic Of China ◽  
Pollution Levels ◽  
Analysis Process ◽  
Cluster Methods ◽  
The Impact

Abstract Research on air quality analysis is a hot field. Here we describe an analysis process based on cluster methods for the data of ambient air quality. In this paper, we use the process to cluster on the air quality data which from the National Urban Air Quality Report in December 2020 on the official website of the Ministry of Ecology and Environment of the People’s Republic of China. We find that cities in different clusters with different main pollutants and pollution levels. Ambient air quality analysis aims to provide guidance for reducing the impact of air pollution on health.

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