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A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic

机译:使用手机流量得出的模型和人口密度数据进行的动态城市空气污染人口暴露评估研究

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A dynamic city-wide air pollution exposure assessment study has been carried out for the urban population of Rome, Italy, by using time resolved population distribution maps, derived by mobile phone traffic data, and modelled air pollutants (NO2, O-3 and PM2.5) concentrations obtained by an integrated air dispersion modelling system. More than a million of persons were tracked during two months (March and April 2015) for their position within the city and its surroundings areas, with a time resolution of 15 min and mapped over an irregular grid system with a minimum resolution of 0.26 x 034 Km(2). In addition, demographics information (as gender and age ranges) were available in a separated dataset not connected with the total population one. Such BigData were matched in time and space with air pollution model results and then used to produce hourly and daily resolved cumulative population exposures during the studied period. A significant mobility of population was identified with higher population densities in downtown areas during daytime increasing of up to 1000 people/Km(2) with respect to nigh-time one, likely produced by commuters, tourists and working age population. Strong variability (up to +/- 50% for NO2) of population exposures were detected as an effect of both mobility and time/spatial changing in pollutants concentrations. A comparison with the correspondent stationary approach based on National Census data, allows detecting the inability of latter in estimating the actual variability of population exposure. Significant underestimations of the amount of population exposed to daily PM2.5 WHO guideline was identified for the Census approach. Very small differences (up to a few mu g/m(3)) on exposure were detected for gender and age ranges population classes. (C) 2016 Elsevier Ltd. All rights reserved.
机译:通过使用时间分辨的人口分布图(通过手机流量数据得出)以及模拟的空气污染物(NO2,O-3和PM2),对意大利罗马的城市人口进行了动态的全市空气污染暴露评估研究.5)通过集成的空气扩散模型系统获得的浓度。在两个月内(2015年3月和2015年4月),对超过一百万的人在城市及其周边地区的位置进行了跟踪,时间分辨率为15分钟,并以最小分辨率为0.26 x 034的不规则网格系统进行了映射公里(2)。此外,人口统计信息(按性别和年龄范围)可在与总人口无关的单独数据集中获得。此类BigData在时间和空间上与空气污染模型结果相匹配,然后用于在研究期间产生每小时和每天解决的累积人口暴露。人口的显着流动被确定为市中心地区的人口密度较高,白天通勤者,游客和工作年龄人口可能会产生比白天高出近1000人/ Km(2)的现象。由于迁移率和污染物浓度随时间/空间变化的影响,检测到了人口暴露的强烈变异性(NO2高达+/- 50%)。与基于国家人口普查数据的对应平稳方法进行比较,可以检测后者无法估计人口暴露的实际变异性。对于普查方法,发现每天低至暴露于PM2.5的WHO指南的人群数量被低估了。对于性别和年龄范围的人口类别,检测到的暴露差异很小(最高几微克/平方米(3))。 (C)2016 Elsevier Ltd.保留所有权利。

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