Development of historic monthly land use regression models of SO2, NOx and suspended particulate matter for birth cohort ELSPAC

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F23%3A00130568" target="_blank" >RIV/00216224:14310/23:00130568 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1352231023001140?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1352231023001140?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.atmosenv.2023.119688" target="_blank" >10.1016/j.atmosenv.2023.119688</a>

Result language

angličtina

Original language name

Development of historic monthly land use regression models of SO2, NOx and suspended particulate matter for birth cohort ELSPAC

Original language description

Vulnerable windows in child development in utero and after birth are critical time points for uncovering the links between environment and health. Particular attention is paid to the first 1000 days of life from conception to the second year of life.The ELSPAC (European Longitudinal Study of Pregnancy and Childhood) birth cohort, launched in the early 1990s, is a rich source of longitudinal data about health and life events, based mainly in Brno, Czechia. There are currently no air quality concentration maps that can be used to assess exposure to air pollutants for this period of the 1990s in Central Europe. Simply transferring current models to the 1990's is burdened with the error introduced by the temporal change in emission sources and land use of the area. Therefore, Czech air quality monitoring data were used to develop monthly land use regression (LUR) models, which combine collected spatial variables with monitoring data to predict the variation in exposures to pollutants. Monthly pollutant concentrations were regressed against the GIS-based potential predictor variables to develop LUR models, following a supervised forward linear regression, with several predefined constraints.We constructed 180 LUR monthly models for sulphur dioxide (SO2), nitrogen oxides (NOx) and suspended particulate matter (SPM) for 1990-1994, that completely cover the first 1000 days for all ELSPAC study par-ticipants. The final models showed, on average reasonably good performance (adjusted R2 = 0.59 with hold-out validation (HOV) R2 = 0.40 for SO2; adjusted R2 = 0.75 with HOV R2 = 0.35 for NOx; and adjusted R2 = 0.61 with HOV R2 = 0.31 for SPM; with a mean number of stations of 74, 38 and 41, respectively). For these models, roads and greenness were predominantly selected as the best predictors.The modelled exposures will serve in many subsequent ELSPAC epidemiological studies, but our models may be also used in other Czech and possibly other Central European cities in that period.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

<a href="/en/project/EF17_043%2F0009632" target="_blank" >EF17_043/0009632: CETOCOEN Excellence</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Atmospheric Environment

ISSN

1352-2310

e-ISSN

—

Volume of the periodical

301

Issue of the periodical within the volume

May 2023

Country of publishing house

GB - UNITED KINGDOM

Number of pages

11

Pages from-to

1-11

UT code for WoS article

000953490800001

EID of the result in the Scopus database

2-s2.0-85149475804