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Multi-annual changes of NOx emissions in megacity regions: nonlinear trend analysis of satellite measurement based estimates

机译:大城市区域氮氧化物排放的多年变化:基于卫星测量的估计的非线性趋势分析

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摘要

Hazardous impact of air pollutant emissions from megacities on atmospheric composition on regional and global scales is currently an important issue in atmospheric research. However, the quantification of emissions and related effects is frequently a difficult task, especially in the case of developing countries, due to the lack of reliable data and information. This study examines possibilities to retrieve multi-annual NOx emissions changes in megacity regions from satellite measurements of nitrogen dioxide and to quantify them in terms of linear and nonlinear trends. By combining the retrievals of the GOME and SCIAMACHY satellite instrument data with simulations performed by the CHIMERE chemistry transport model, we obtain the time series of NOx emission estimates for the 12 largest urban agglomerations in Europe and the Middle East in the period from 1996 to 2008. We employ then a novel method allowing estimation of a nonlinear trend in a noisy time series of an observed variable. The method is based on the probabilistic approach and the use of artificial neural networks; it does not involve any quantitative a priori assumptions. As a result, statistically significant nonlinearities in the estimated NOx emission trends are detected in 5 megacities (Bagdad, Madrid, Milan, Moscow and Paris). Statistically significant upward linear trends are detected in Istanbul and Tehran, while downward linear trends are revealed in Berlin, London and the Ruhr agglomeration. The presence of nonlinearities in NOx emission changes in Milan, Paris and Madrid is confirmed by comparison of simulated NOx concentrations with independent air quality monitoring data. A good quantitative agreement between the linear trends in the simulated and measured near surface NOx concentrations is found in London.\ud\ud
机译:目前,大城市的空气污染物排放对区域和全球规模的大气成分的危险影响是大气研究中的一个重要问题。但是,由于缺乏可靠的数据和信息,对排放量和相关影响进行量化通常是一项艰巨的任务,特别是在发展中国家。这项研究研究了从卫星二氧化氮测量中检索大城市地区多年期NOx排放变化并量化其线性和非线性趋势的可能性。通过将国美和SCIAMACHY卫星仪器数据的检索结果与CHIMERE化学迁移模型进行的模拟相结合,我们获得了1996年至2008年期间欧洲和中东12个最大城市群的NOx排放估算时间序列然后,我们采用一种新颖的方法,可以估算观察变量的嘈杂时间序列中的非线性趋势。该方法基于概率方法和人工神经网络的使用;它不涉及任何定量的先验假设。结果,在5个特大城市(巴格达,马德里,米兰,莫斯科和巴黎)中检测到了估计的NOx排放趋势中具有统计意义的非线性。在伊斯坦布尔和德黑兰发现统计上显着的上升线性趋势,而在柏林,伦敦和鲁尔集聚区则发现下降线性趋势。通过将模拟的NOx浓度与独立的空气质量监测数据进行比较,可以确认米兰,巴黎和马德里的NOx排放变化存在非线性。在伦敦发现了模拟和测量的近地表NOx浓度的线性趋势之间的良好定量一致性。\ ud \ ud

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