Development and evaluation of land use regression models for black carbon based on bicycle and pedestrian measurements in the urban environment

Abstract

Land use regression (LUR) modelling is increasingly used in epidemiological studies to predict air pollution exposure. The use of stationary measurements at a limited number of locations to build a LUR model, however, can lead to an overestimation of its predictive abilities. We use opportunistic mobile monitoring to gather data at a high spatial resolution to build LUR models to predict annual average concentrations of black carbon (BC). The models explain a significant part of the variance in BC concentrations. However, the overall predictive performance remains low, due to input uncertainty and lack of predictive variables that can properly capture the complex characteristics of local concentrations. We stress the importance of using an appropriate cross-validation scheme to estimate the predictive performance of the model. By using independent data for the validation and excluding those data also during variable selection in the model building procedure, overly optimistic performance estimates are avoided.

Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

“…Fourth, urban morphology, i.e., the build density, street canyons, wind permeability, or the density of intersections are factors describing the geometry of the city and might play an important role in air pollution trapping (canyon effect) and noise propagation [39][40][41].…”

“…This method has already been proven to be useful in modelling cyclists' exposure to noise [57]. Nonlinear terms (e.g., splines) are regularly employed to model exposure to air pollution [40,41]. For space, a bivariate spline can be constructed from the coordinates of the sampling segments.…”

GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy

“…The selected criteria were: elevation, maximum temperature, minimum temperature, slope angle, rainfall, runoff coefficient, and slope, which were calculated by AHP through its pair-wise comparison matrix procedure. The weights of the criteria are calculated by Equations (6)(7)(8), where the inconsistency index = 0.05; it is desirable to have a value of less than 0.1.…”

“…The use of land for agriculture is considered critical areas in the scientific literature [1][2][3][4]. In general, land evaluation is the process of assessing the performance of land when used for a given purpose [5][6][7]. An evaluation of the climate, soil, and topographical components, along with an author's knowledge.…”

Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

“…The data required for these computations are extracted from CRAB (Agentschap voor Geografische Informatie Vlaanderen, 2013a; Agentschap voor Geografische Informatie Vlaanderen, 2013b), which is a geo-spatial data-layer containing all registered households in Flanders. Similar features have been used in (Hankey and Marshall, 2015;Van den Bossche et al, 2018). To obtain more holistic information of the influence of static sources of BC around a POI, geo-spatial information on land-use, extracted from Urban Atlas (Union, 2011;European Environment Agency, 2014), was used, distinguishing between land use classes park, low-urban and high-urban.…”