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首页> 外文期刊>Environment international >Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology
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Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology

机译：使用精细解析的卫星数据，土地利用变量和气象估算意大利（2006-2012）的每日PM10浓度

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摘要

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (ACID) from the Multi Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10 measurements, land use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2 = 0.65 and little bias (average slope of predicted VS observed PM10 = 0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PIVim levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. (C) 2016 Elsevier Ltd. All rights reserved.
机译：空气污染，特别是颗粒物（PM）的健康影响已得到广泛研究。但是，大多数研究都依赖于位于城市地区的少数监测器进行短期评估，或依靠土地使用/分布模型进行长期评估，这些监测器多数还是在城市。最近，精细分解的卫星数据的可获得性提供了一个机会，可以估算出时空范围较宽的空气污染物的日浓度。意大利缺乏一种可靠且经过验证的高分辨率时空分辨颗粒物模型。自然和人为来源的复杂地形和空气混合物是巨大的挑战，难以解决。我们将来自大气校正的多角度实施（MAIAC）算法，地面PM10测量，土地利用变量和气象参数的气溶胶光学深度（ACID）的精细解析数据合并到一个四阶段混合模型框架中，以得出每日估算值2006年至2012年，整个意大利的1-km2网格PM10浓度。我们通过每年应用10倍交叉验证（CV）来检查模型的性能。我们的模型显示出良好的拟合度，平均CV-R2 = 0.65，偏差很小（观察到的PM10的预测VS的平均斜率= 0.99）。在意大利北部（波谷）和大型城市（例如罗马），背景监测站以及冬季，样本外预测更为准确。最终的浓度图显示特定地区（波河谷，主要工业区和大都市区）的平均PIVim水平最高，并且随着时间的推移呈下降趋势。我们对整个意大利的PM10浓度的每日预测将首次允许估算全国范围内空气污染的长期和短期影响，即使在缺乏监测数据的地区也是如此。 （C）2016 Elsevier Ltd.保留所有权利。

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  • 来源
    《Environment international》 |2017年第2期|234-244|共11页
  • 作者

    Stafoggia Massimo; Schwartz Joel; Badaloni Chiara; Bellander Tom; Alessandrini Ester; Cattani Giorgio; de Donato Francesca; Gaeta Alessandra; Leone Gianluca; Lyapustin Alexei; Sorek-Hamer Meytar; de Hoogh Kees; Di Qian; Forastiere Francesco; Kloog Itai;

  • 作者单位

    Lazio Reg Hlth Serv ASL Roma 1, Dept Epidemiol, Via C Colombo 112, I-00147 Rome, Italy|Karolinska Inst, Inst Environm Med, Stockholm, Sweden;

    Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, Cambridge, MA USA;

    Lazio Reg Hlth Serv ASL Roma 1, Dept Epidemiol, Via C Colombo 112, I-00147 Rome, Italy;

    Karolinska Inst, Inst Environm Med, Stockholm, Sweden|Stockholm Cty Council, Ctr Occupat & Environm Med, Stockholm, Sweden;

    Lazio Reg Hlth Serv ASL Roma 1, Dept Epidemiol, Via C Colombo 112, I-00147 Rome, Italy;

    Italian Natl Inst Environm Protect & Res, Rome, Italy;

    Lazio Reg Hlth Serv ASL Roma 1, Dept Epidemiol, Via C Colombo 112, I-00147 Rome, Italy;

    Italian Natl Inst Environm Protect & Res, Rome, Italy;

    Italian Natl Inst Environm Protect & Res, Rome, Italy;

    NASA, GSFC, Greenbelt, MD USA;

    Technion, Civil & Environm Engn, Haifa, Israel|Ben Gurion Univ Negev, Dept Geog & Environm Dev, Beer Sheva, Israel;

    Swiss Trop & Publ Hlth Inst, Basel, Switzerland|Univ Basel, Basel, Switzerland;

    Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, Cambridge, MA USA;

    Lazio Reg Hlth Serv ASL Roma 1, Dept Epidemiol, Via C Colombo 112, I-00147 Rome, Italy;

    Ben Gurion Univ Negev, Dept Geog & Environm Dev, Beer Sheva, Israel;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Aerosol Optical Depth; Air pollution; Epidemiology; Exposure assessment; Particulate matter; Satellite;

    机译：气溶胶光学厚度空气污染流行病学暴露评估颗粒物卫星;

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