Matrix Completion With Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference

Inferring air quality from a limited number of observations is an essential task for monitoring and controlling air pollution. Existing inference methods typically use low spatial resolution data collected by fixed monitoring stations and infer the concentration of air pollutants using additional types of data, e.g., meteorological and traffic information. In this work, we focus on street-level air quality inference by utilizing data collected by mobile stations. We formulate air quality inference in this setting as a graph-based matrix completion problem and propose a novel variational model based on graph convolutional autoencoders. Our model captures effectively the spatio-temporal correlation of the measurements and does not depend on the availability of additional information apart from the street-network topology. Experiments on a real air quality dataset, collected with mobile stations, shows that the proposed model outperforms state-of-the-art approaches

Air monitoring network review

The purpose of the ambient air monitoring network is to sample air pollution in a variety of settings, assess the health and welfare effects, and assist in determining sources of air pollution. In general, six basic monitoring objectives and five measuring scales are used to determine the network design. Since it is physically and fiscally impossible to monitor the air in every location, representative samples must be obtained. These samples are determined by using the monitoring objectives and the spatial measurement scales. The network must be dynamic enough to maintain a current representative sample of the air quality. Air quality issues such as eight-hour ozone non-attainment boundaries and permits for new sources are diverse and controversial subjects for the citizens of Maricopa County. With its robust air monitoring network and mobile monitoring tools, the department strives to provide the most reliable and relevant air monitoring data to the public.Reports for 2001-2003 issued under the Department's earlier name: Maricopa County Environmental Services Department, Air Quality Division.Report for 2013 has cover title: Air Monitoring Final Network Pla

Risk Management in Air Protection in the Republic of Croatia

In the Republic of Croatia, according to the Air Protection Act, air pollution assessment is obligatory on the whole State territory. For individual regions and populated areas in the State a network has been established for permanent air quality monitoring. The State network consists of stations for measuring background pollution, regional and cross-border remote transfer and measurements as part of international government liabilities, then stations for measuring air quality in areas of cultural and natural heritage, and stations for measuring air pollution in towns and industrial zones. The exceeding of alert and information threshold levels of air pollutants are related to emissions from industrial plants, and accidents. Each excess represents a threat to human health in case of short-time exposure. Monitoring of alert and information threshold levels is carried out at stations from the state and local networks for permanent air quality monitoring according to the Air Quality Measurement Program in the State network for permanent monitoring of air quality and air quality measurement programs in local networks for permanent air quality monitoring. The State network for permanent air quality monitoring has a developed automatic system for reporting on alert and information threshold levels, whereas many local networks under the competence of regional and local self-governments still lack any fully installed systems of this type. In case of accidents, prompt action at all responsibility levels is necessary in order to prevent crisis and this requires developed and coordinated competent units of State Administration as well as self-government units. It is also necessary to be continuously active in improving the implementation of legislative regulations in the field of crises related to critical and alert levels of air pollutants, especially at local levels

A mobile application for assessment of air pollution exposure

In this paper the architecture of a mobile air quality monitoring system is introduced. A mobile application will act as a personal assistant, monitoring and giving advices about gas pollutants daily exposure. Currently in development stage as part of a larger air quality monitoring system project, the application will enable users to monitor their daily exposure to gas pollutants by combining user location data and urban air quality information provided by the network of fixed monitoring stations of the city of Palermo

Realtime Profiling of Fine-Grained Air Quality Index Distribution using UAV Sensing

Given significant air pollution problems, air quality index (AQI) monitoring has recently received increasing attention. In this paper, we design a mobile AQI monitoring system boarded on unmanned-aerial-vehicles (UAVs), called ARMS, to efficiently build fine-grained AQI maps in realtime. Specifically, we first propose the Gaussian plume model on basis of the neural network (GPM-NN), to physically characterize the particle dispersion in the air. Based on GPM-NN, we propose a battery efficient and adaptive monitoring algorithm to monitor AQI at the selected locations and construct an accurate AQI map with the sensed data. The proposed adaptive monitoring algorithm is evaluated in two typical scenarios, a two-dimensional open space like a roadside park, and a three-dimensional space like a courtyard inside a building. Experimental results demonstrate that our system can provide higher prediction accuracy of AQI with GPM-NN than other existing models, while greatly reducing the power consumption with the adaptive monitoring algorithm

Low-Cost Energy-Efficient Air Quality Monitoring System Using Wireless Sensor Network

Due to rapid industrialization and urbanization, Mauritius is witnessing an unprecedented increase in air pollution. The release of hazardous gases such as carbon monoxide and sulphur dioxide are not only harmful to the health of the population but are also causing irreversible impact to the environment. Currently, there are only two fixed air quality monitoring units on the island and therefore, air pollution cannot be monitored in real-time. The objective of this chapter is to describe the implementation of a low-cost and energy-efficient air quality monitoring system using wireless sensor network (WSN) that can be easily deployed in highly polluted areas of Mauritius. A Hierarchical Based Genetic Algorithm (HBGA) is proposed to address the issue of sensor nodes with limited energy. Based on hierarchical routing and genetic algorithm, HBGA has been designed to extend the lifetime of the network by minimizing the energy consumption. The proposed air quality monitoring system uses an air quality index that can be easily interpreted. The evaluation results confirm the potential of the proposed system for real-time temporal and spatial monitoring of air quality. Moreover, it possible for the general public to have access to the air quality monitoring results in real time