scholarly journals Air pollution monitoring with secure low-cost Vehicular Sensor Networks

2019 ◽  
Vol 29 ◽  
pp. 03007
Author(s):  
György KolumbÁn-Antal ◽  
Vladko Lasak ◽  
Razvan Bogdan ◽  
Bogdan Groza

Counteracting the effects of air quality degradation is one of the main challenges in large cities today. To achieve such a goal, the first step is to control the emissions of various pollutant gases which in turn requires their concentrations to be measured such that proper methods can be applied. In this work we present a low cost urban air pollution monitoring system which we developed as proof-of-concept in Timisoara, Romania. The proposed solution is a Vehicular Sensor Network (VSN), with affordable midclass sensor nodes being installed on moving vehicles, ideally on the public transportation busses. The system measures temperature, humidity, the concentration of CO2 and dust, along with Volatile Organic Compounds (VOC). The aim of collecting weather data is to build correlations between air pollution levels and different weather conditions. In addition to technical constraints for measuring air quality, one of the challenges that we address is to implement secure transmissions between the devices. This raises several difficulties on microcontrollers that we use due to their low memory and computational resources. To answer both privacy and security issues, the proposed data transmission protocol of the measuring system, builds upon a modified version of the Station to Station (STS) protocol which allows secure tunnelling in an anonymous manner.

2020 ◽  
Author(s):  
Farid RAHAL ◽  
Noureddine BENABADJI ◽  
Mohamed BENCHERIF ◽  
Mohamed Menaouer BENCHERIF

Abstract In Algeria, air pollution is classified as a major risk by the law. However, this risk is underestimated because there is no operational network for measuring air quality on a continuous basis.Despite the heavy investments made to equip several cities with these measurement systems, they are out of order due to a lack of continuous financial support.The alternative to the absence of these air pollution measurement networks can come from the recent development of electrochemical sensor technologies for air quality monitoring which arouses a certain interest because of their miniaturization, low energy consumption and low cost.We developed a low-cost outdoor carbon monoxide analyzer called APOMOS (Air pollution Monitoring System) based on electrochemical sensor managed by microcontroller. An application developed with the Python language makes it possible to manage process and analyze the collected data.In order to validate the APOMOS system, the recorded measurements are compared with measurements taken by a conventional analyzer.Comparison of the measurements resulting from conventional analyzer and those resulting from the APOMOS system gives a coefficient of determination of 98.39 %.Two versions of this system have been designed. A fixed version and another embedded, equipped with a GPS sensor. These 2 variants were used in the city of Oran in Algeria to measure the concentration of carbon monoxide continuously.The targeted pollutant is carbon monoxide. However, the design of the APOMOS system allows its evolution in an easy way in order to integrate other sensors concerning the various atmospheric pollutants.


Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1215
Author(s):  
Grazia Fattoruso ◽  
Martina Nocerino ◽  
Domenico Toscano ◽  
Luigi Pariota ◽  
Giampiero Sorrentino ◽  
...  

Urban air pollution continues to represent a primary concern for human health, despite significant efforts by public authorities for mitigating its effects. Regulatory monitoring networks are essential tools for air pollution monitoring. However, they are sparse networks, unable to capture the spatial variability of the air pollutants. For addressing this issue, networks of low cost stations are deployed, supplementing the regulatory stations. Regarding this application, an important question is where these stations are installed The objective of this study was to generate a site suitability map for the development of a network of low cost multi-sensor stations across a city for a spatially dense urban air quality monitoring. To do that, a site suitability analysis was developed based on two geographical variables properly selected for representing the impact of urban pollutant sources and urban form on the pollutant concentrations. By processing information about emissions patterns and street canyon effects, we were able to identify air quality hotspot areas supposed to show high spatial variability. Low cost monitoring stations, there located, are able to provide that informative content, which is lacking for both regulatory monitoring networks and predictive modelling for high resolution air quality mapping.


2022 ◽  
Vol 14 (1) ◽  
pp. 584
Author(s):  
Priyanka Nadia deSouza

Low-cost sensors are revolutionizing air pollution monitoring by providing real-time, highly localized air quality information. The relatively low-cost nature of these devices has made them accessible to the broader public. Although there have been several fitness-of-purpose appraisals of the various sensors on the market, little is known about what drives sensor usage and how the public interpret the data from their sensors. This article attempts to answer these questions by analyzing the key themes discussed in the user reviews of low-cost sensors on Amazon. The themes and use cases identified have the potential to spur interventions to support communities of sensor users and inform the development of actionable data-visualization strategies with the measurements from such instruments, as well as drive appropriate ‘fitness-of-purpose’ appraisals of such devices.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10041
Author(s):  
Zenon Nieckarz ◽  
Jerzy A. Zoladz

The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM10) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM10 have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM10 concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM10 in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m−3. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.


2020 ◽  
Author(s):  
Rishabh Bajaj ◽  
Rishav Sen ◽  
Anik Sengupta ◽  
Aryama Sen ◽  
Sayan Karmakar ◽  
...  

Data in Brief ◽  
2021 ◽  
pp. 107127
Author(s):  
Jose M. Barcelo-Ordinas ◽  
Pau Ferrer-Cid ◽  
Jorge Garcia-Vidal ◽  
Mar Viana ◽  
Ana Ripoll

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 290
Author(s):  
Akvilė Feiferytė Skirienė ◽  
Žaneta Stasiškienė

The rapid spread of the coronavirus (COVID-19) pandemic affected the economy, trade, transport, health care, social services, and other sectors. To control the rapid dispersion of the virus, most countries imposed national lockdowns and social distancing policies. This led to reduced industrial, commercial, and human activities, followed by lower air pollution emissions, which caused air quality improvement. Air pollution monitoring data from the European Environment Agency (EEA) datasets were used to investigate how lockdown policies affected air quality changes in the period before and during the COVID-19 lockdown, comparing to the same periods in 2018 and 2019, along with an assessment of the Index of Production variation impact to air pollution changes during the pandemic in 2020. Analysis results show that industrial and mobility activities were lower in the period of the lockdown along with the reduced selected pollutant NO2, PM2.5, PM10 emissions by approximately 20–40% in 2020.


Author(s):  
Eric S. Coker ◽  
Ssematimba Joel ◽  
Engineer Bainomugisha

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m3 (IQR: 45.4-73.0 µg/m3; median= 57.5 µg/m3). For the ML LUR models, RMSE values ranged between 5.43 µg/m3 - 15.43 µg/m3 and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R2=0.92) and produced the lowest RMSE (5.43 µg/m3) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.


Author(s):  
Aneri A. Desai

In Indian metropolitan cities, the extensive growth of the motor vehicles has resulted in the deterioration of environmental quality and human health. The concentrations of pollutants at major traffic areas are exceeding the permissible limits. Public are facing severe respiratory diseases and other deadly cardio-vascular diseases In India. Immediate needs for vehicular air pollution monitoring and control strategies for urban cities are necessary. Vehicular emission is the main source of deteriorating the ambient air quality of major Indian cities due to rapid urbanization. Total vehicular population is increased to 15 Lacks as per recorded data of Regional Transport Organization (RTO) till 2014-2015. This study is focused on the assessment of major air pollution parameters responsible for the air pollution due to vehicular emission. The major air pollutants responsible for air pollution due to vehicular emissions are PM10, PM2.5, Sox, Nox, HC, CO2 and CO and Other meterological parameters like Ambient temperature, Humidity, Wind direction and Wind Speed. Sampling and analysis of parameters is carried out according to National Ambient Air Quality Standards Guidelines (NAAQS) (2009) and IS 5128.


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