Abstract
Abstract. The effect of particulate matter is increasingly gaining significance due to its harmful effects on human and urban ecosystems. In view of it, many communities worldwide are collecting air quality data privately to influence their policy makers to make stricter provisions for reducing harmful emissions and thereby improving their quality of life. Likewise, in many German cities, a community of air quality monitors which rely on low-cost PM Sensors is gathering momentum. Such communities possess privately-owned & low-cost air quality monitoring devices that claim to accurately measure PM concentrations and are openly accessible via internet. One such initiative is an air quality monitoring network viz. “luftdaten.info”, which contains of more than 300 low-cost sensors that consistently obtains PM data, colloquially referred as fine dust, in the city of Stuttgart as well as its surrounding districts. Besides, eight stations are continuously monitoring PM concentration in Stuttgart; these are operated by the State Environmental Agency (LuBW- Landesanstalt für Umwelt Baden-Württemberg). Stuttgart University of Applied Sciences (HFT) has currently installed 7 low-cost PM sensors to monitor and study PM concentration in one of its projects. This study endeavors to relate PM 2.5 and PM 10.0 using low-cost sensors. It intends to investigate the reliability of the measured PM concentration using such low-costs sensors once these are placed horizontally and vertically apart and comparing the measures of the 7 sensors. Another objective is to compare the PM concentration measurements with a meteorological station operated by the State of Baden-Wuerttemberg in the vicinity. A correlation analysis is performed to develop understanding of relationships of PM concentration with meteorological parameters, viz. with respect to ambient temperature, air pressure, humidity, wind speed and wind direction. Furthermore, it attempts to develop a regression model using above listed meteorological parameters. Finally, deficiencies in the measurement of low-costs and its placement effects are commented. Further suggestions are made for improving the data capturing and analytical procedures while using low-cost sensors.
Highlights
Fine dust consists of a complex mixture of solid and liquid particles and is divided into different fractions depending on their size
When the sensor recordings of PM concentration were analyzed for all sensors to study the pattern, it is found that for a typical day, PM concentration showed peaks between 2200 to 2300 hours, similar peaks were observed from 0700 to 0800 hours (Fig.5)
The PM concentration data is needed to processed based on the days of the week, month
Summary
Fine dust consists of a complex mixture of solid and liquid particles and is divided into different fractions depending on their size. Particulate matter is released from engines - primarily from diesel engines - and from brake and tire abrasion and from the whirling up of dust from the road surface Another big source of PM is agriculture: the emissions of gaseous precursors, in particular ammonia emissions from animal husbandry, contribute to the formation of secondary fine dust. Depending on the size and penetration depth of the particles, the health effects of particulate matter are different. They range from mucosal irritation, local inflammation in the trachea and bronchi or the pulmonary alveoli to increased plaque formation in the blood vessels, thrombosis or changes in the regulatory function of the autonomic nervous system (heart rate variability). The measurements of the low-cost sensors are compared with the state-owned meteorological sensor in the vicinity (located in Bad Cannstatt)
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