Modeling population exposure to ultrafine particles in a major Italian urban area.

Int J Environ Res Public Health

Department of Science and High Technology, University of Insubria, via Valleggio 11, 22100 Como, Italy.

Published: October 2014

Average daily ultrafine particles (UFP) exposure of adult Milan subpopulations (defined on the basis of gender, and then for age, employment or educational status), in different exposure scenarios (typical working day in summer and winter) were simulated using a microenvironmental stochastic simulation model. The basic concept of this kind of model is that time-weighted average exposure is defined as the sum of partial microenvironmental exposures, which are determined by the product of UFP concentration and time spent in each microenvironment. In this work, environmental concentrations were derived from previous experimental studies that were based on microenvironmental measurements in the city of Milan by means of personal or individual monitoring, while time-activity patterns were derived from the EXPOLIS study. A significant difference was observed between the exposures experienced in winter (W: 28,415 pt/cm3) and summer (S: 19,558 pt/cm3). Furthermore, simulations showed a moderate difference between the total exposures experienced by women (S: 19,363 pt/cm3; W: 27,623 pt/cm3) and men (S: 18,806 pt/cm3; W: 27,897 pt/cm3). In addition, differences were found as a function of (I) age, (II) employment status and (III) educational level; accordingly, the highest total exposures resulted for (I) 55-59 years old people, (II) housewives and students and (III) people with higher educational level (more than 10 years of scholarity). Finally, significant differences were found between microenvironment-specific exposures.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4210999PMC
http://dx.doi.org/10.3390/ijerph111010641DOI Listing

Publication Analysis

Top Keywords

ultrafine particles
8
age employment
8
exposures experienced
8
total exposures
8
educational level
8
pt/cm3
6
exposures
5
modeling population
4
exposure
4
population exposure
4

Similar Publications

Soil microorganisms transform plant-derived C (carbon) into particulate organic C (POC) and mineral-associated C (MAOC) pools. While microbial carbon use efficiency (CUE) is widely recognized in current biogeochemical models as a key predictor of soil organic carbon (SOC) storage, large-scale empirical evidence is limited. In this study, we proposed and experimentally tested two predictors of POC and MAOC pool formation: microbial necromass (using amino sugars as a proxy) and CUE (by O-HO approach).

View Article and Find Full Text PDF

Relationship of modifiable risk factors with the incidence of thyroid cancer: a worldwide study.

BMC Res Notes

January 2025

Non-Communicable Diseases Research Center, Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.

Background: Thyroid cancer is one of the most common cancers of the endocrine system. The incidence of this cancer has increased in many countries. Many cases of thyroid cancer do not have any symptoms.

View Article and Find Full Text PDF

The superposition of heavy metals (HMs) from multiple anthropogenic sources in geochemical anomaly areas makes it difficult to discriminate prime sources in atmospheric HMs. This study utilized a combination of microscopic features, positive matrix factorisation, and Pb isotope fingerprints to trace the main sources of HMs bound to total suspended particulates (TSP) at a pollution site (Msoshui: MS) and control site (Lushan: LS) in northwestern Guizhou. The results reveal that the concentrations of Cd, Pb, Cr, As, Cu, Ni, and Zn in the TSP of LS are 3.

View Article and Find Full Text PDF

This paper proposes a hybridized model for air quality forecasting that combines the Support Vector Regression (SVR) method with Harris Hawks Optimization (HHO) called (HHO-SVR). The proposed HHO-SVR model utilizes five datasets from the environmental protection agency's Downscaler Model (DS) to predict Particulate Matter ([Formula: see text]) levels. In order to assess the efficacy of the suggested HHO-SVR forecasting model, we employ metrics such as Mean Absolute Percentage Error (MAPE), Average, Standard Deviation (SD), Best Fit, Worst Fit, and CPU time.

View Article and Find Full Text PDF

Understanding the composition of mercury (Hg) in the atmosphere is important for confirming its sources and to preventing and reduce the production. To explore the morphological distribution characteristics of wet Hg concentrations in Xi'an Shaanxi Province, China, total Hg (THg), dissolved Hg (DTHg), reactive Hg (RTHg) and particulate-bound Hg (PTHg) (Hg insoluble in water) were measured at 72 precipitation in Xi'an from September 2020 to July 2022, and their average concentrations were 3.035 ± 3.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!