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Anthropogenic sulphur dioxide load over China as observed from different satellite sensors

机译:不同卫星传感器观测到的中国人为二氧化硫负荷

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China, with its rapid economic growth and immense exporting power, has been the focus of many studies during this previous decade quantifying its increasing emissions contribution to the Earth's atmosphere. With a population slowly shifting towards enlarged power and purchasing needs, the ceaseless inauguration of new power plants, smelters, refineries and industrial parks leads infallibly to increases in sulphur dioxide, SO2, emissions. The recent capability of next generation algorithms as well as new space-borne instruments to detect anthropogenic SO2 loads has enabled a fast advancement in this field. In the following work, algorithms providing total SO2 columns over China based on SCIAMACHY/Envisat, OMI/Aura and GOME2/MetopA observations are presented. The need for post processing and gridding of the SO2 fields is further revealed in this work, following the path of previous publications. Further, it is demonstrated that the usage of appropriate statistical tools permits studying parts of the datasets typically excluded, such as the winter months loads. Focusing on actual point sources, such as megacities and known power plant locations, instead of entire provinces, monthly mean time series have been examined in detail. The sharp decline in SO2 emissions in more than 90% -95% of the locations studied confirms the recent implementation of government desulphurisation legislation; however, locations with increases, even for the previous five years, are also identified. These belong to provinces with emerging economies which are in haste to install power plants and are possibly viewed leniently by the authorities, in favour of growth. The SO2 load seasonality has also been examined in detail with a novel mathematical tool, with 70% of the point sources having a statistically significant annual cycle with highs in winter and lows in summer, following the heating requirements of the Chinese population. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在过去十年中,中国以其快速的经济增长和巨大的出口能力成为许多研究的重点,量化了其对地球大气层的不断增加的排放贡献。随着人口逐渐转向扩大的电力和购买需求,新的发电厂,冶炼厂,精炼厂和工业园区的不断落成导致了二氧化硫,SO2和排放物的增加。下一代算法以及新的星载仪器检测人为SO2负荷的最新功能使该领域得以快速发展。在以下工作中,将介绍基于SCIAMACHY / Envisat,OMI / Aura和GOME2 / MetopA观测值提供中国SO2总列的算法。遵循先前出版物的路径,这项工作进一步揭示了对SO2字段进行后处理和网格化的需求。此外,证明了使用适当的统计工具可以研究通常排除的数据集部分,例如冬季负荷。重点关注实际的点源(例如特大城市和已知的发电厂位置),而不是整个省份,详细研究了每月平均时间序列。在超过90%-95%的研究地区,SO2排放量急剧下降,这证实了政府最近实施的脱硫立法;但是,即使在过去的五年中,也发现了数量增加的地区。这些属于新兴经济体的省份,它们急于安装发电厂,当局可能宽容地看待它们以支持增长。还使用一种新颖的数学工具对二氧化硫负荷的季节性进行了详细的检查,其中有70%的点源具有统计上显着的年周期,其中遵循中国人口的供暖要求,冬季高,夏季低。 (C)2016 Elsevier Ltd.保留所有权利。

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