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The presence of high levels of atmospheric pollutants in the air of several urban centres of developed and developing countries has caused great concern among authorities and public opinion. The book provides a comprehensive review of the field of urban pollution. Further, it offers insights into specific issues such as the use of receptor modeling for volatile organic compounds, the role and the mechanism of the formation of nitrous acid in urban atmospheres, and the evaluation of the dynamics of the boundary layer. It is an invaluable source of information for anyone interested in environmental pollution and management of the urban atmosphere, in particular for people in government or research institutions concerned with environmental protection, monitoring and impact assessment

Ever since air pollution became a national concern in the 1950's, more and more emphasis has been placed on collection of representative air samples for many purposed, to include (1) evaluation of the degree to which national ambient air quality standards are being met and (2) to monitor maximum emission levels from point sources. Until recently efforts were directed toward qualitative methods of siting monitors for representative sampling. Since the dispersion of effluents is most complex, the quality of the data collected on the basis of judgment and, more or less, incremental siting about the source, has become suspect. Furthermore, with the increasing demands for monitoring due to international growth in network monitoring systems, amendments to the Clean Air Act and the legislation on the Prevention of Significant Deteoriation of Air Quality, it is not cost-effective to encircle point sources with large numbers of equally spaced monitors. This paper discussed the history of air pollution concerns that have resulted in the need for monitoring; the development of siting techniques through largely qualitative measures; and finally, summarizes three quantitative methodologies for monitoring point sources. Emphasis is placed on the methodology developed by Noll, et al., (1977), based on the author's belief that this methodology represents the state of the art.

[EN] Recently, Unmanned Aerial Vehicles (UAVs) have become a cheap alternative to sense pollution values in a certain area due to their flexibility and ability to carry small sensing units. In a previous work, we proposed a solution, called Pollution-driven UAV Control (PdUC), to allow UAVs to autonomously trace pollutant sources, and monitor air quality in the surrounding area. However, despite operational, we found that the proposed solution consumed excessive time, especially when considering the battery lifetime of current multi-rotor UAVs. In this paper, we have improved our previously proposed solution by adopting a space discretization technique. Discretization is one of the most efficient mathematical approaches to optimize a system by transforming a continuous domain into its discrete counterpart. The improvement proposed in this paper, called PdUC-Discretized (PdUC-D), consists of an optimization whereby UAVs only move between the central tile positions of a discretized space, avoiding monitoring locations separated by small distances, and whose actual differences in terms of air quality are barely noticeable. We also analyze the impact of varying the tile size on the overall process, showing that smaller tile sizes offer high accuracy at the cost of an increased flight time. Taking into account the obtained results, we consider that a tile size of 100 x 100 meters offers an adequate trade-off between flight time and monitoring accuracy. Experimental results show that PdUC-D drastically reduces the convergence time compared to the original PdUC proposal without loss of accuracy, and it also increases the performance gap with standard mobility patterns such as Spiral and Billiard. ; This work was partially supported by the "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a Retos de la Sociedad, Proyecto I+D+I TEC2014-52690-R", the framework of the DIVINA Challenge Team, which is funded under the Labex MS2T program. Labex MS2T is supported by the French Government, through the ...

This document presents the thesis proposal for obtaining the Master of Science in Intelligent Systems. Technology, industry and government forecasts coincide that the planet will withstand a maximum of 50 years at the rate of current air pollution. Air pollution has reached critical levels causing major impacts on health and economy across the globe. Environmental monitoring and control agencies, as well as industries, require a reliable and cost-effective tool that is easy to deploy where required to assess contamination levels, and on that basis, take the necessary actions. Current measurement methods using pressurized balloons, satellite imagery, or earth stations result in considerable investment, as well as providing low spatial and temporal resolution. There are also systems for measuring air pollution using Unmanned Air Vehicles (UAV), which are financed by large government institutions or international organizations whose budget and resources allow costly implementations. Other related works are limited to the capture of atmospheric data using the UAVs and offline analysis. This work presents the design and implementation of an open-source UAV-based platform for measuring atmospheric pollutants and an algorithm for the localization of the air pollutant sources with the use of a UAV and in-line processing of the pollutants data. The development of the UAV-based platform includes: the UAV mounting and characterization and the control system to guide the navigation of the vehicle, the appropriate sensors selection and integration to the UAV, the data transmission from the sensors onboard the UAV to the ground station, and the implementation of the user interface which is based on a web design. The algorithm for the air pollutant source localization is based on a metaheuristic component, to follow the increasing gradient of the pollutant concentration, and complemented with a probabilistic component to concentrate the searching to the most promising areas in the targeted environment. The results of this work are: Outdoors experiments of the UAV-based platform for the air pollutant monitoring and indoor experiments to validate the algorithm for the source localization. The results show effectiveness and robustness of the UAV-based platform and of the algorithm for the source identification.

This paper discusses the air quality control in the current legislation of the Republic of Serbia and compares it with the relevant EU legislation, Framework and Daughter Directives of the air quality monitoring and management. QA/QC components, instrumentation and methodologies of the air quality control in RS are not yet structured and harmonized with EU requirements. The limit and target values for air pollutants notified in EU legislation may be partly comparable with relevant requirements in RS legislation.

One of the main concerns of the last century is regarding the air pollution and its effects caused on human health. Its impact is particularly evident in cities and urban areas where governments are trying to mitigate its effects. Although different solutions have been already proposed, citizens continue to report bad conditions in the areas in which they live. This paper proposes a solution to support governments in monitoring the city pollution through the combination of user feedbacks/reports and real-time data acquired through dedicated mobile IoT sensors dynamically re-located by government officials to verify the reported conditions of specific areas. The mobile devices leverage on dedicated sensors to monitor the air quality and capture main roads traffic conditions through machine learning techniques. The system exposes a mobile application and a website to support the collection of citizens' reports and show gathered data to both institutions and end-users. A proof-of-concept of the proposed solution has been prototyped in a medium-sized university campus. Both the performance and functional validation have demonstrated the feasibility and the effectiveness of the system and allowed the definition of some lessons learned, as well as future works.