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10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data

机译:使用高分辨率卫星数据估算的美国东南部PM2.5浓度的10年时空趋势

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摘要

Long-term PM2.5 exposure has been associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of the spatiotemporally continuous distribution of PM2.5 concentrations are important. Satellite-retrieved aerosol optical depth (AOD) has been increasingly used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, previous studies indicated that an inherent disadvantage of many AOD products is their coarse spatial resolution. For instance, the available spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) AOD products are 10 and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm based on MODIS measurements was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5–AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US centered at the Atlanta metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted annually, and we obtained model fitting R2 ranging from 0.71 to 0.85, mean prediction error (MPE) from 1.73 to 2.50 μg m−3, and root mean squared prediction error (RMSPE) from 2.75 to 4.10 μg m−3. In addition, we found cross-validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 μgm−3, and RMSPE from 3.12 to 5.00 μgm−3, indicating a good agreement between the estimated and observed values. Spatial trends showed that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. Our time-series analysis showed that, for the 10-year study period, the PM2.5 levels in the southeastern US have decreased by ∼20 %. The annual decrease has been relatively steady from 2001 to 2007 and from 2008 to 2010 while a significant drop occurred between 2007 and 2008. An observed increase in PM2.5 levels in year 2005 is attributed to elevated sulfate concentrations in the study area in warm months of 2005.
机译:长期暴露于PM2.5与各种不良健康后果有关。但是,大多数地面监测仪都位于城市地区,导致真实区域PM2.5水平的潜在偏差。为了促进流行病学研究,准确估算PM2.5浓度在时空上的连续分布非常重要。由于其全面的空间覆盖范围,卫星提取的气溶胶光学深度(AOD)已越来越多地用于PM2.5浓度估算。然而,先前的研究表明,许多AOD产品的固有缺点是其粗糙的空间分辨率。例如,中分辨率成像光谱仪(MODIS)和多角度成像光谱仪(MISR)AOD产品的可用空间分辨率分别为10 km和17.6 km。本文使用了一种新的AOD产品,该产品通过基于MODIS测量的多角度大气校正(MAIAC)算法检索到的1 km空间分辨率。通过合并MAIAC AOD,气象领域和土地利用变量作为预测因子,开发了一个两阶段模型来说明PM2.5-AOD关系中的时空变化。我们的研究区域位于美国东南部,以亚特兰大都会区为中心,从不同来源收集了2001年至2010年的数据。每年进行一次模型拟合,获得的模型拟合R 2 范围为0.71至0.85,平均预测误差(MPE)为1.73至2.50μgm −3 ,并且根均方根预测误差(RMSPE)为2.75至4.10μgm -3 。此外,我们发现交叉验证R 2 的范围为0.62至0.78,MPE为2.00至3.01μgm -3 ,RMSPE为3.12至5.00μgm- 3 ,表明估计值和观察值之间有很好的一致性。空间趋势表明,PM2.5高水平发生在城市地区和主要公路沿线,而低浓度出现在农村或山区。我们的时间序列分析表明,在为期10年的研究期内,美国东南部的PM2.5水平下降了约20%。从2001年到2007年以及从2008年到2010年,每年的下降相对稳定,而在2007年到2008年之间则出现了显着下降。2005年PM2.5含量的明显增加归因于研究区在温暖月份的硫酸盐浓度升高2005年。

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