Related papers: Estimating daily nitrogen dioxide level: Exploring…
We develop and implement a numerical model to simulate the effect of photovoltaic asphalt on reducing the concentration of nitrogen monoxide due to the presence of heavy traffic in an urban environment. The contributions in this paper are…
The societal impact of traffic is a long-standing and complex problem. We focus on the estimation of ozone production due to vehicular traffic. For this, we couple a system of conservation laws for vehicular traffic, an emission model, and…
Recent studies have shown associations between redlining policies (1935-1974) and present-day fine particulate matter (PM$_{2.5}$) and nitrogen dioxide (NO$_2$) air pollution concentrations. In this paper, we reevaluate these associations…
The development of low-cost sensors and novel calibration algorithms offer new opportunities to supplement existing regulatory networks to measure air pollutants at a high spatial resolution and at hourly and sub-hourly timescales. We use a…
Air pollution is an emerging problem that needs to be solved especially in developed and developing countries. In Vietnam, air pollution is also a concerning issue in big cities such as Hanoi and Ho Chi Minh cities where air pollution comes…
Urban air quality is a major concern today. Concentrations of pollutants, such as nitrogen dioxide, must be monitored to ensure that they do not exceed hazardous thresholds. For this reason, scarse reference stations, which are generally…
Precise and high-resolution carbon dioxide (CO$_2$) emission data is of great importance of achieving the carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO$_2$ Emission…
Pollutant emissions have been a topic of interest in the last decades. Not only environmentalists but also governments are taking rapid action to reduce emissions. As one of the main contributors, the transport sector is being subjected to…
Environmental data often take the form of a collection of curves observed sequentially over time. An example of this includes daily pollution measurement curves describing the concentration of a particulate matter in ambient air. These…
The first goal of this study is to quantify the magnitude and spatial variability of air quality changes in the US during the COVID-19 pandemic. We focus on two federally regulated pollutants, nitrogen dioxide (NO2), and fine particulate…
Air pollution poses a critical health threat in cities worldwide, with nitrogen dioxide levels in Cork, Ireland exceeding World Health Organization safety standards by up to $278\%$. This study leverages artificial intelligence to predict…
The nonlinear features of the relationships between concentrations of aerosol and volatile organic compounds (VOC) and oxides of nitrogen (NOx) in urban environments are derived directly from data of long-term routine measurements of NOx,…
Road-traffic NO2 hotspots are still often modelled with static emissions and generic temporal profiles, although near-road concentrations respond strongly to rapidly changing traffic conditions. Here, we test whether detector-informed…
Few studies quantify how traffic management dynamically reshapes modal split and emission-exposure outcomes over pollution severities. This paper proposes a novel day-to-day assignment model integrating exposure cost, which includes…
Air pollution is a major global environmental health threat, in particular for people who live or work near pollution sources. Areas adjacent to pollution sources often have high ambient pollution concentrations, and those areas are…
Air quality monitoring requires to produce accurate estimation of nitrogen dioxide or fine particulate matter concentration maps, at different moments. A typical strategy is to combine different types of data. On the one hand, concentration…
Acknowledging the effects of outdoor air pollution, the literature inadequately addresses indoor air pollution's impacts. Despite daily health risks, existing research primarily focused on monitoring, lacking accuracy in pinpointing indoor…
This study develops a Bayesian hierarchical model to explore the effects of air pollution on respiratory and cardiovascular mortality in Los Angeles County. The model takes into account various pollutants such as PM2.5, PM10, CO, SO2, NO2…
Statistical techniques used in air pollution modelling usually lack the possibility to understand which predictors affect air pollution in which functional form; and are not able to regress on exceedances over certain thresholds imposed by…
Traffic emissions are known to contribute significantly to air pollution around the world, especially in heavily urbanized cities such as Singapore. It has been previously shown that the particulate pollution along major roadways exhibit…