平流层臭氧对人类活动排放氯化物及氮氧化物的非线性响应

利用本文所建立的平流层下部臭氧异相光化学系统,研究硫酸气溶胶表面积浓度以及氯化物和氮氧化物的排放强度对系统状态的影响.光化系统由19种分别来自氧族、氢族、氮族、氯族和碳族的化学成分组成.研究结果指出,仅就气溶胶而言,它不是一个重要的决定光化系统行为的因子.然而,当它与奇氯ClOx或奇氮NOx的外源共同影响系统时,通过复杂的非线性光化学过程,它将使系统的行为发生重大变化.可以看到,在某些确定的参数范围内,系统存在多平衡态解,并构成一个“折叠"突变流型.     

耦合气溶胶气候模式FGOALS-f3-L模拟青藏高原地区气溶胶特性

基于新耦合气溶胶气候模式FGOALS-f3-L模拟分析了2002-2011年青藏高原地区气溶胶时空分布特征.结果表明:青藏高原地区,沙尘,硫酸盐,碳质气溶胶(包括黑碳,有机碳和混合碳)地表质量浓度分别占比为53.6％,32.2％,14.2％;在拉萨站点,模拟的气溶胶地表质量浓度被低估,尤其是黑碳和有机碳气溶胶;模拟的气...     

Variability in the structure of epiphytic assemblages of the Mediterranean seagrass Posidonia oceanica in relation to depth

The aim of the present study was to evaluate whether the variability in the structure of the epiphytic assemblages of leaves and rhizomes of the Mediterranean seagrass Posidonia oceanica differed between depths at a large spatial scale. A hierarchical sampling design was used to compare epiphytic assemblages at two different depths (10 and 20 m) in terms of both species composition and abundance and patterns of spatial variability in the Tuscan Archipelago (North Western Mediterranean Sea, Italy). Results showed significant differences in the structure of assemblages on rhizomes and leaves at different depths. These differences were related to species composition and abundance; differences were not significant for total biomass, total percentage cover and percentage cover of animals and algae. Whereas the higher variability was observed among shoots in all the studied systems, patterns of spatial variability at the other spatial scales investigated differed between the two studied depths. Moreover, in the present study, analogous patterns between depths resulted for both the assemblages of leaves and rhizomes, suggesting that factors that change with depth can be responsible for the spatial variability of both the assemblages (leaves and rhizomes), and operate regardless of the microclimatic conditions and the structure of assemblages.     

北京地区地基辐射计与卫星云特性参数对比研究

利用2019年MODIS卫星数据、葵花-8卫星数据和天空辐射计观测数据分析北京城区云光学特性的时空分布特征。结果表明,北京地区的云光学厚度(Cloud optical depth,COD)和云滴有效半径(Cloud drop effective radius,CER)呈现明显的季节变化特征。北京地区COD主要分布特征为南部地区较高而北部地区较低,且夏季COD值明显高于其他季节,最高值为20左右。CER在春季和夏季呈现相反的区域分布特征,春季北京地区南低北高,夏季北京地区南高北低,而秋冬季CER明显低于春夏两季。通过将天空辐射计观测数据与卫星观测结果对比分析发现二者在COD方面一致性较高, r分别为0.69和0.66,MODIS对于CER数据的一致性较差,r值为0.053而葵花-8一致性较好r值为0.53。     

基于MODIS数据的新疆大气气溶胶光学厚度时空变化分析

利用中分辨率成像光谱仪（Moderate-resolution Imaging Spectroradiometer,MODIS）大气气溶胶光学厚度产品数据，采用三角剖分算法、最近邻点搜索、插值法和趋势分析法，分析新疆气溶胶光学厚度（Aerosol Optical Depth,AOD）时空变化。结果表明：（1）新疆AOD总体呈下降趋势且地域差异明显，南疆AOD明显高于北疆，高值区主要集中在塔里木盆地边缘和天山北坡经济带。（2）北疆AOD年际变化不明显。2014年最高，2005年最低，年均值在0.15～0.18。南疆则呈明显的年际变化。最高值出现在2006年，为0.42；最低值出现在2017年，为0.22。（3）新疆AOD呈明显季节变化特征。春季最大，秋季最小。（4）2003—2019年南疆环塔里木盆地北部、东南边缘和北疆沿天山北坡经济带AOD增量明显。     

Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations

As most air quality monitoring sites are in urban areas worldwide, machine learning models may produce substantial estimation bias in rural areas when deriving spatiotemporal distributions of air pollutants. The bias stems from the issue of dataset shift, as the density distributions of predictor variables differ greatly between urban and rural areas. We propose a data-augmentation approach based on the multiple imputation by chained equations (MICE-DA) to remedy the dataset shift problem. Compared with the benchmark models, MICE-DA exhibits superior predictive performance in deriving the spatiotemporal distributions of hourly PM_2.5 in the megacity (Chengdu) at the foot of the Tibetan Plateau, especially for correcting the estimation bias, with the mean bias decreasing from –3.4 µg/m³ to –1.6 µg/m³. As a complement to the holdout validation, the semi-variance results show that MICE-DA decently preserves the spatial autocorrelation pattern of PM_2.5 over the study area. The essence of MICE-DA is strengthening the correlation between PM_2.5 and aerosol optical depth (AOD) during the data augmentation. Consequently, the importance of AOD is largely enhanced for predicting PM_2.5, and the summed relative importance value of the two satellite-retrieved AOD variables increases from 5.5% to 18.4%. This study resolved the puzzle that AOD exhibited relatively lower importance in local or regional studies. The results of this study can advance the utilization of satellite remote sensing in modeling air quality while drawing more attention to the common dataset shift problem in data-driven environmental research.