Related papers: Air Pollution Forecasting in Bucharest
Accompanying rapid industrialization, humans are suffering from serious air pollution problems. The demand for air quality prediction is becoming more and more important to the government's policy-making and people's daily life. In this…
Weather conditions significantly influence the formation and dispersion of pollution variations. Here we study networks of pollution as well as climate networks and find that pollutants may not only have an impact close to their source but…
Air pollution has long been a serious environmental health challenge, especially in metropolitan cities, where air pollutant concentrations are exacerbated by the street canyon effect and high building density. Whilst accurately monitoring…
Predictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of information communicated to end users. Although applications of probabilistic prediction and…
Tracking and estimating Daily Fine Particulate Matter (PM2.5) is very important as it has been shown that PM2.5 is directly related to mortality related to lungs, cardiovascular system, and stroke. That is, high values of PM2.5 constitute a…
Weather is a phenomenon that affects everything and everyone around us on a daily basis. Weather prediction has been an important point of study for decades as researchers have tried to predict the weather and climatic changes using…
The environmental impacts of global warming driven by methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4. Several data-driven machine…
Purpose: This study aimed to investigate the correlation between air pollution and astigmatism, considering the detrimental effects of air pollution on respiratory, cardiovascular, and eye health. Methods: A longitudinal study was conducted…
Random disturbances such as air pollution may affect cognitive performance, which, particularly in high-stakes settings, may have severe consequences for an individual's productivity and well-being. This paper examines the short-term…
Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic and social growth. Forecasting air quality has become an increasingly important endeavor with significant social impacts,…
Low-cost particulate matter sensors (LCS) are an important source of air quality data, improving the spatial and temporal resolution of data gathered by sparsely placed official monitoring stations. Their readings, however, are subject to…
Air pollution in cities and the possibilities of reducing this pollution represents one of the most important factors that today's society has to deal with. This paper focuses on a systemic approach to traffic emissions with their relation…
Air pollution is a significant global health risk, contributing to millions of premature deaths annually. Nitrogen dioxide (NO2), a harmful pollutant, disproportionately affects urban areas where monitoring networks are often sparse. We…
Low-cost air pollution sensor networks are increasingly being deployed globally, supplementing sparse regulatory monitoring with localized air quality data. In some areas, like Baltimore, Maryland, there are only few regulatory (reference)…
Numerous countries have built urban stations for monitoring the amount of PM2.5 in the atmosphere. In Iraq, there aren't enough stations to monitor PM2.5 pollution levels across all governorates. As a result, satellite remote sensing data…
Cyclists travelling in urban areas are particularly at risk of harm from particulate emissions due to their increased breathing rate and proximity to vehicles. In this paper we combine human respiratory models with models of particulate…
Wildland fire smoke contains hazardous levels of fine particulate matter PM2.5, a pollutant shown to adversely effect health. Estimating fire attributable PM2.5 concentrations is key to quantifying the impact on air quality and subsequent…
One of the main contributors to air pollution is particulate matter (PMxy), which causes several COVID-19 related diseases such as respiratory problems and cardiovascular disorders. Therefore, the spatial and temporal trend analysis of…
We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality prediction. To explicitly embed physical processes into the learning framework, we identify two…
Air quality has become one of the main issues in public health and urban planning management, due to the proven adverse effects of high pollutant concentrations. Considering the mitigation measures that cities all over the world are taking…