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, …

Comparative Investigations On Microextraction And Conventional Air Sampling Techniques: Challenges And Future Directions, Firoz Ahmed, Mehedi Hasan Roni, Ashiqur Rahman, Sayed M A Salam

Al-Bahir Journal for Engineering and Pure Sciences

Microextraction technique (e.g., solid phase microextraction, thin film microextraction, in-tube extraction) brings a revolutionary change in air sampling techniques over the recent few years. This advanced technique exhibits a high pollutant extraction rate, a low retention time, and a lower error margin compared to conventional air sampling techniques. The accuracy range of microextraction technique (MET) was recorded ~90-95% to isolate the volatile organic components, oxygenated and halogenated carbon particles from the air. However, the efficiency of MET increases additional >3-5% when employed by coupled with gas chromatography or gas chromatography-mass spectrometry. The conventional sampling techniques (e.g., bag sampling, grab sampling) …

Monitoring Pm2.5 Pollution In The North End Of Hartford, Ct, Jocelyn Phung, Kristina Wagstrom

Honors Scholar Theses

Particulate matter (PM) or particle pollution is one of the six criteria air pollutants that can cause harm to human health and the environment; yet, there is a lack of data in many areas of the United States. Particulate matter is a mixture of solid particles and liquid droplets suspended in the air (EPA). Exposure to PM2.5 has been linked to respiratory and cardiovascular conditions. People who live in urban areas are more likely to be exposed to particulate matter as many urban areas are known to have poor air quality. Our goal is to determine how particulate matter levels …

Combinedeepnet: A Deep Network For Multistep Prediction Of Near-Surface Pm2.5 Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan

Conference papers

PM2.5 is a type of air pollutant that can cause respiratory and cardiovascular problems. Precise PM2.5 ( μg/m3 ) concentration prediction may help reduce health concerns and provide early warnings. To better understand air pollution, a number of approaches have been presented for predicting PM2.5 concentrations. Previous research used deep learning models for hourly predictions of air pollutants due to their success in pattern recognition, however, these models were unsuitable for multisite, long-term predictions, particularly in regard to the correlation between pollutants and meteorological data. This article proposes the combine deep network (CombineDeepNet), which combines multiple deep networks, including a …