Land use regression (LUR) models are widely used in epidemiological and environmental
studies to estimate humans' exposure to air pollution within urban areas. However, the early …

Cities foster economic growth. However, growing cities also contribute to air pollution and
climate change. The paper provides a perspective regarding the opportunity available in …

Exposure to outdoor fine particulate matter (PM2. 5) is a leading risk factor for mortality. We
develop global estimates of annual PM2. 5 concentrations and trends for 1998–2018 using …

Based on the rapid spread of the CoViD-2019, a lockdown was declared in the whole
Northern Italy by the Government. The application of increasingly rigorous containment …

Background Machine learning algorithms have very high predictive ability. However, no
study has used machine learning to estimate historical concentrations of PM 2.5 (particulate …

Background Air pollutants are suggested to be related to type 2 diabetes (T2D). Since
several high quality papers on air pollutants and T2D have been published beyond the last …

Empirical spatial air pollution models have been applied extensively to assess exposure in
epidemiological studies with increasingly sophisticated and complex statistical algorithms …

We estimated global fine particulate matter (PM2. 5) concentrations using information from
satellite-, simulation-and monitor-based sources by applying a Geographically Weighted …

Background PM 2· 5 air pollution is associated with increased risk of diabetes; however, a
knowledge gap exists to further define and quantify the burden of diabetes attributable to PM …

With the rapid development of the digital economy, understanding the relationship between
the digital economy and the environment is increasingly important for sustainable …