Air pollutant concentrations

About: Air pollutant concentrations is a research topic. Over the lifetime, 1652 publications have been published within this topic receiving 36138 citations.

Air pollution is a global problem with local solutions

Abstract: VIEWPOINT | Mario Molina Air pollution is a global problem with local solutions Air pollution is a serious problem in cities across the developing world. Th ere are, however, examples of cities that have taken advantage of existing technologies to partially mitigate the problem. With 20 million people, Mexico City is the world’s second largest city aft er Tokyo. It is also situated in a valley where polluted air tends to become trapped. As a result, it has long suff ered from pollution problems that have adversely aff ected public health. Mexico City’s health problems became so acute in the 1990s that they prompted the government to take action. Emission standards were set and vehicles were required to undergo inspections twice a year. In addition, new vehicles had to be equipped with catalytic converters that signifi cantly reduce noxious tail-pipe emissions. Leaded fuel damages catalytic converters; so, the introduction of catalytic converters also led to the widespread use of lead-free gasoline. Motor vehicles produce three-quarters of Mexico City’s air pollution. As a result, the measures taken have created noticeable improvements in air quality. In China, where large cities also suff er from excessive air pollution, the situation is diff erent. A larger portion of the air pollution is due to emissions from power plants and industrial facilities. Technologies also exist to curb emissions from these sources; however, power plants and industrial facilities drive economic growth in China, where, for example, one new coal-fi red steam plant is being added to the electric grid every 7–10 days. Th e Chinese government made an enormous eff ort to improve air quality in Beijing for the Olympics. We can only hope that this eff ort will spread to other cities as well.

An Innovative Method to Allocate Air-Pollution-Related Taxes, Using Aermod Modeling (case study: Besat Power Plant).

Abstract: The present study applies the model of American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD) to investigate NO2 emissions from Besat thermal power plant, which is fuelled by natural gas to function. Results indicate that the simulated concentration of NO2 based on AERMOD, does not exceed NO2 concentration limit, set by the Iranian Ambient Air Quality Standard. This shows that NO2 emissions from Besat power plant do not have any significant impact on nearby communities. The natural-gas-based power plant is capable of reducing the air pollution level. It also can decrease the hospital treatment costs, thus protecting public health. The modeling results shows that natural-gas-based power plant as a clean technology in power generation. Also, the AERMOD model has been used to determine the pollution source matrix of Besat power plant. An innovative idea has been implemented to not only determine air-pollution-related taxes and complexities but to solve the legal problem associated with it, also. As for the complexities, their determination entails two different methods: one, based on city's boundaries along with simulated amount of air pollutant concentrations in each receptor, and the other, based on the population of each receptor (i.e., the cities of Varamin, Eslamshahr, and Nasirshahr), which plays a vital role. According to the first approach, Varamin has the lion's share in the air pollution, caused by Best power plant. However, the second approach surprisingly shows that the largest portion belongs to Eshalmshahr, indicating the significant influence of its population.

Machine Learning algorithms for air pollutants forecasting

Abstract: Air pollution represents an issue that raises many concerns nowadays, as it has various negative effects on the environment and the economy worldwide. Because of the rapid urbanization, cities are suffering from polluted air, so it is important to predict future air quality. For this purpose, new applications of artificial intelligence should be employed. In this paper, we will present several Machine Learning algorithms, the possible software that can be used for them and the applications used in the field of air quality. Based on the research in the field, we propose SVR, ARIMA and LSTM, 3 Machine Learning models, which can be used to predict air pollution. These algorithms have been tested using time-series for PM 10 and PM 2.5 particles. The results showed that SVR and ARIMA algorithms are the most suitable in forecasting air pollutant concentrations.

Control strategies for vehicular NOx emissions in Guangzhou, China

Abstract: Guangzhou is a city in southern China that has experienced very rapid economic development in recent years. The city's air has very high concentrations of various pollutants, including sulphur dioxide (SO2), oxides of nitrogen (NOx), ozone (O3) and particulate. This paper reviews the changes in air quality in the city over the past 15 years, and notes that a serious vehicular-related emissions problem has been superimposed on the traditional coal-burning problem evident in most Chinese cities. As NOx concentrations have increased, oxidants and photochemical smog now interact with the traditional SO2 and particulate pollutants, leading to increased health risks and other environmental concerns. Any responsible NOx control strategy for the city must include vehicle emission control measures. This paper reviews control strategies designed to abate vehicle emissions to fulfill the city's air quality improvement target in 2010. A cost-effectiveness analysis suggests that, while NOx emission control is expensive, vehicular emission standards could achieve a relatively sizable emissions reduction at reasonable cost. To achieve the 2010 air quality target of NOx, advanced implementation of EURO3 standards is recommended, substituting for the EURO2 currently envisioned in the national regulations. Related technical options, including fuel quality improvements and inspection/maintenance (I/M) upgrades (ASM or IM240), are assessed as well.