Engineering Commons^™

Pollutant Forecasting Using Neural Network-Based Temporal Models, Richard Pike

Masters Theses & Specialist Projects

The Jing-Jin-Ji region of China is a highly industrialized and populated area of the country. Its periodic high pollution and smog includes particles smaller than 2.5 μm, known as PM2.5, linked to many respiratory and cardiovascular illnesses. PM2.5 concentration around Jing-Jin-Ji has exceeded China’s urban air quality safety threshold for over 20% of all days in 2017 through 2020.

The quantity of ground weather stations that measure the concentrations of these pollutants, and their valuable data, is unfortunately small. By employing many machine learning strategies, many researchers have focused on interpolating finer spatial grids of PM2.5, or hindcasting PM2.5. However, …

Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar

Turkish Journal of Electrical Engineering and Computer Sciences

Smart cities are an important concept for urban development. This concept addresses many current critical urban problems including traffic and environmental pollution. As utilization of the Internet of things and technology in smart cities increases, large volumes of big data are generated and collected by sensors embedded at different places in the city, which present a real-time display of what is happening throughout the city at all times. Such data should be processed and analyzed as a response to ensure effectiveness and improvement in quality of provided services; correct use and analysis of such data is valuable. Big data mining …

Purdue Airsense: An Affordable Way To Measure And Study Air Pollution, Stephane Junior Nouafo Wanko, Shadi Tariq Azouz, Ruihang Du, Brandon Boor, Greg Michalski

The Summer Undergraduate Research Fellowship (SURF) Symposium

Air pollution is a major health hazard worldwide, accounting for one-eighth of all deaths in 2012 (World Health Organization). Globally, there is a severe lack of ground-based spatiotemporal monitoring of gaseous and particulate air pollutants, particularly in Africa, South and Central America, and the Middle East. This is in great part due to the high costs of air quality instrumentation that meet accuracy and reliability criteria set by monitoring agencies. The air quality data that is available is often not presented to the public in a user-friendly manner. Taking advantage of recent developments in low-cost sensing technologies, an integrated sensor …

Ocena Wpływu Rozdzielczości Siatki Obliczeniowej Na Wyniki Modelowania Rozprzestrzeniania Się Zanieczyszczeń W Powietrzu, Mateusz Rzeszutek, Robert Oleniacz, Marian Mazur

Robert Oleniacz

In this study are presented the results of the assessment of the impact of grid resolution on the results of computational modeling of the dispersion of air pollutants. Calculations were performed using Gaussian, non-stationary puff model CALPUFF. Four different grids resolution were analyzed. Networks were established on the basis of SRTM3 terrain and land cover classes of CLC, 2006. Analysis of results of spatial distribution of concentrations of air pollutants obtained in a regular computing grid was performed using statistical indicators recommended by the U.S. EPA. The study shows the applicability of particular computational grids in the system modeling transport …

Determination Of Optimal Spatial Databases For The Area Of Poland To The Calculation Of Air Pollutant Dispersion Using The Calmet/Calpuff Model, Robert Oleniacz, Mateusz Rzeszutek

Robert Oleniacz

The paper presents a methodology for the preparation of three-dimensional spatial data and land use data for the purpose of modeling pollutant dispersion in the ambient air using a group of geophysical preprocessors of the CALMET/CALPUFF modeling system and the GIS software. Some space information data sources available to Poland were specified and their characteristics and availability were discussed. Particular attention was turned to the SRTM3 and GTOPO30 elevation data as well as the CLC2006 and GLCC land use data, for the preparation of computational grids of different resolutions. Groups of programs which can be used in order to form …

Ocena Wpływu Nowo Budowanej Spalarni Odpadów Komunalnych W Krakowie Na Jakość Powietrza Z Wykorzystaniem Modelu Calmet/Calpuff, Mateusz Rzeszutek, Robert Oleniacz

Robert Oleniacz

The chapter presents the results of the evaluation the impact on air quality for the newly built Municipal Solid Waste Thermal Treatment Plant in Krakow (Poland) whose construction started in autumn 2013. Air pollution impact assessment was performed for air emissions adopted at the levels of emission limit values applicable for waste incineration. Modeling of air pollutant dispersion was carried out using the system of CALMET/CALPUFF models. For this purpose, the terrain elevation data from Shuttle Radar Topography Mission (SRTM3) and data of land use from Corine Land Cover 2006 (CLC 2006) were adopted with a resolution of about 100 …

Zmiany W Metodyce Modelowania Rozprzestrzeniania Się Zanieczyszczeń W Powietrzu Opartej Na Modelu Gaussa, Robert Oleniacz, Marek Bogacki

Robert Oleniacz

The paper presents the changes that have occurred in December 2002 in the Polish reference modeling methodology (based on the stationary Gaussian atmospheric dispersion model) used for the air quality impact assessment in Poland since the 60s of the 20th century. Discusses the changes that have occurred in the preparation of data for the simulation, the procedure used in shortened and full range of calculation, the algorithms of initial computations and the results of calculations.

English Title: Changes in the methodology of modeling the pollutant dispersion in the air based on the Gaussian model.

Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control …