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Prediction of PM2.5 hourly concentrations in Beijing based on machine learning algorithm and ground-based LiDAR

Fang Zhiyuan, Yang Hao, Li Cheng, Cheng Liangliang, Zhao Ming, Xie Chenbo

Archives of Environmental Protection

2021

Vol. 47, no. 3

98--107

The prediction of PM2.5 is important for environmental forecasting and air pollution control. In this study, four machine learning methods, ground-based LiDAR data and meteorological data were used to predict the ground-level PM2.5 concentrations in Beijing. Among the four methods, the random forest (RF) method was the most effective in predicting ground-level PM2.5 concentrations. Compared with BP neural network, support vector machine (SVM), and various linear fitting methods, the accuracy of the RF method was superior by 10%. The method can describe the spatial and temporal variation in PM2.5 concentrations under different meteorological conditions, with low root mean square error (RMSE) and mean square deviation (MD), and the consistency index (IA) reached 99.69%. Under different weather conditions, the hourly variation in PM2.5 concentrations has a good descriptive ability. In this paper, we analyzed the weights of input variables in the RF method, constructed a pollution case to correspond to the relationship between input variables and PM2.5, and analyzed the sources of pollutants via HYSPLIT backward trajectory. This method can study the interaction between PM2.5 and air pollution variables, and provide new ideas for preventing and forecasting air pollution.

Mobile monitoring system for gaseous air pollution

Katulski R. J., Namieśnik J., Stefański J., Sadowski J., Wardencki W., Szymańska K.

Metrology and Measurement Systems

2009

Vol. 16, nr 4

677-682

The concept of a mobile monitoring system for chemical agents control in the air is presented. The proposed system can be applied to measure industrial and car traffic air pollution. A monitoring station is relatively small and can be placed on cars or public transportation vehicles. Measured concentrations of air pollutants are collected and transferred via the GSM network to a central data base. Exemplary results from a measurement series in Gdańsk are also presented.

Czujniki chemiczne w monitoringu gazowych zanieczyszczeń powietrza

Chachulski B.

Chemia i Inżynieria Ekologiczna

1998

Vol. 5, nr 4

267-279

Niniejsza praca jest przeglądem praktycznych zastosowań czujników chemicznych w monitoringu gazowych zanieczyszczeń powietrza. Przedstawione zostały charakterystyki analityczne głównych grup czujników: elektrochemicznych, elektrycznych, optycznych, termochemicznych i masowych. Szczegółowo została omówiona grupa elektrochemicznych czujników gazów, a wśród nich mające obecnie najszersze zastosowanie czujniki amperometryczne oraz staoelektrolitowe, potencjometryczne czujniki tlenu.

Present work reviews the application of chemical gas sensors in monitoring of air pollutants. The fundamental classes of sensors are presented with particlar reference to their practical use in continuous environmental analysis. The analytical characteristics of the electrochemical, electrical, optical, thermochemical, and gravimetrical sensors are discussed and compared. The special attention is paid to the most common class, i.e. to the electrochemical sensors and the amperometric and potentiometric sensors of oxygen pressure are presented in details.