Current and historical relationships between the tissue nitrogen content of a snowbed bryophyte and nitrogenous air pollution

Snowbed vegetation is under threat from atmospheric pollution. Most of the late lying snowbeds in Britain are in the central highlands of Scotland, coinciding with an area of very high deposition of nitrogenous air pollutants. Snow is a very efficient scavenger of atmospheric pollution and, due to the dynamics of snowmelt, much of the pollution load of a snow pack is released at very high concentrations in episodes known as 'acid flushes'. This study demonstrates the existence of a positive relationship between duration of snow-lie and tissue nitrogen content of Kiaeria starkei, a bryophyte characteristic of late snowbeds. An increase in the tissue nitrogen content of this bryophyte over this century is also shown, reflecting increasing air pollution. Maximum tissue nitrogen concentration in K. starkei is up to 50% greater than that recorded in other upland bryophyte species, demonstrating the exceptional threat of pollution to snowbed bryophytes. This has implications for the critical loads approach to pollution emission controls, as it indicates that some mountain communities are receiving higher pollution loadings than previously realised and therefore current exceedence of critical loads is probably greater than recognised at present.     

2003~2020年黄河内蒙古段干流水质演变趋势

为全面了解黄河流域内蒙古段近年来的水环境质量状况及其变化趋势,基于流域内5个监测断面2003~2020年的水质数据,使用主成分分析、聚类分析和长短时记忆模型等多源数据分析方法,结合改进的综合水质标识指数,探究了黄河流域水质的时空变化特征. 结果表明,流域水质状况整体向好并稳定. 时间特征方面,汛期和非汛期水质的主要影响因素存在显著差异,主要与农业灌溉用水和汛期水量增大有关;空间特征方面,可将5个监测断面归为3类,汛期的主要影响因素具有时间特征,而非汛期3类监测断面的水质差异主要由其周边城市的用水结构决定. LSTM模型的预测值变化趋势与真实值拟合效果良好,可对黄河内蒙古段的水质指标进行有效的预测评价,可为黄河干流各河段水质达标控制与管理提供科学依据.