It is likely that exposure surrogates from monitoring stations with various limitations are not
sufficient for epidemiological studies covering large areas. Moreover, the spatiotemporal …

Introduction: The World Health Organization (WHO) recently revised its health guidelines for
Nitrogen dioxide (NO2) air pollution, reducing the annual mean NO2 level to 10 μg/m3 (5.3 …

Developing suitable exposure estimates for air pollution health studies is problematic due to
spatial and temporal variation in concentrations and often limited monitoring data. Though …

Air pollution is inextricable from human activity patterns. This is especially true for nitrogen
oxide (NO x), a pollutant that exists naturally and also as a result of anthropogenic factors …

Resolving spatial variability in ambient air pollutant and quantifying contributing factors are
critical to human exposure assessment and effective pollution control. Data-driven …

Land use regression model (LUR) is one of the most commonly used methods to project the
spatial concentration of ambient pollutants. The number and location of samples are two key …

Background Understanding spatial variation of air pollution is critical for public health
assessments. Land Use Regression (LUR) models have been used increasingly for …

Previous studies have reported that intra-urban variability of NO2 concentrations is even
higher than inter-urban variability. In recent years, an increasing number of studies have …

Kriging interpolation and land use regression (LUR) have characterized the spatial
variability of long-term nitrogen dioxide (NO 2), but there has been little research on …

Land use regression (LUR) models have been used in epidemiology to determine the fine-
scale spatial variation in air pollutants such as nitrogen dioxide (NO 2) in cities and larger …