Related papers: A PM2.5 concentration prediction framework with ve…
Ambient concentrations of many pollutants are associated with emissions due to human activity, such as road transport and other combustion sources. In this paper we consider air pollution as a multi--level phenomenon within a Bayesian…
Development of air pollution models for large regions is a priority for population-based epidemiologic studies. The rapid development of big data information systems and machine learning algorithms have opened new grounds for refinements of…
Ambient exposure to fine particulate matters of diameters smaller than 2.5{\mu}m (PM2.5) has been identified as one critical cause for respiratory disease. Disparities in exposure to PM2.5 among income groups at individual residences are…
Forecasting PM$_{2.5}$ concentration is important to solving air pollution problems in Wuhan. This paper proposes a PM$_{2.5}$ concentration forecast model based on nonlinear regression, including a single-value forecast model and an…
Air pollution is the origination of particulate matter, chemicals, or biological substances that brings pain to either humans or other living creatures or instigates discomfort to the natural habitat and the airspace. Hence, air pollution…
The patterns of particulate matter with diameters that are generally 2.5 micrometers and smaller (PM2.5) are heterogeneous in China nationwide but can be homogeneous region-wide. To reduce the adverse effects from PM2.5, policymakers need…
The influence of human activity own the earth's atmospheric composition has never been more pronounced. Anthropogenic pollution is in fact the largest effector of the observed evolving atmospheric composition (Wallace, 2006). PM2.5 is a…
Air pollution is a pressing environmental risk to public health, particularly in cities where population density and pollution levels are high. Traditional methods for exposure analysis often rely on census data, but recent studies…
In this paper we propose a multiscale traffic model, based on the family of Generic Second Order Models, which integrates multiple trajectory data into the velocity function. This combination of a second order macroscopic model with…
Pollution in urban areas can have significant adverse effects on the health and well-being of citizens, with traffic-related air pollution being a major concern in many cities. Pollutants emitted by vehicles, such as nitrogen oxides, carbon…
Air pollution stands as the fourth leading cause of death globally. While extensive research has been conducted in this domain, most approaches rely on large datasets when it comes to prediction. This limits their applicability in…
The road freight sector is responsible for a large and growing share of greenhouse gas emissions, but reliable data on the amount of freight that is moved on roads in many parts of the world are scarce. Many low- and middle-income countries…
Air pollution remains one of the most formidable environmental threats to human health globally, particularly in urban areas, contributing to nearly 7 million premature deaths annually. Megacities, defined as cities with populations…
Rapid urbanization with poor city planning has resulted in severe air pollution in low- and middle-income countries' urban areas. Given the adverse impacts of air pollution, many responses have been taken, including migration to another…
Air pollution has been linked to elevated levels of risk aversion. This paper provides the first evidence showing that such effect reduces life-threatening risky behaviors. We study the impact of air pollution on traffic accidents caused by…
Air pollution by Nitrogen Oxides (NOx) is a major concern in large cities as it has severe adverse health effects. However, the statistical properties of air pollutants are not fully understood. Here, we use methods borrowed from…
Urbanization enables economic growth but also harms the environment through degradation. Traditional methods of detecting environmental issues have proven inefficient. Machine learning has emerged as a promising tool for tracking…
Air pollution is a vital issue emerging from the uncontrolled utilization of traditional energy sources as far as developing countries are concerned. Hence, ingenious air pollution forecasting methods are indispensable to minimize the risk.…
High concentration episodes for NO$_2$ are increasingly dealt with by authorities through traffic restrictions which are activated when air quality deteriorates beyond certain thresholds. Foreseeing the probability that pollutant…
The main motivation of this work is to assess the validity of a LWR traffic flow model to model measurements obtained from trajectory data, and propose extensions of this model to improve it. A formulation for a discrete dynamical system is…