首页> 外文期刊>Atmospheric Chemistry and Physics Discussions >Method development estimating ambient oxidized mercury concentration from monitored mercury wet deposition
【24h】

Method development estimating ambient oxidized mercury concentration from monitored mercury wet deposition

机译:方法开发估算环境氧化汞浓度从监测汞湿沉积

获取原文
           

摘要

To quantify mercury dry deposition, the Atmospheric Mercury Network (AMNet) of the National Atmospheric Deposition Program (NADP) was established recently to monitor the speciated atmospheric mercury (i.e. gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particulate-bound mercury (PBM)). However, the spatial coverage of AMNet is far less than the long-established Mercury Deposition Network (MDN) for wet deposition monitoring. The present study describes the first attempt linking ambient concentration of the oxidized mercury (GOM + PBM) with wet deposition aiming to estimate GOM + PBM roughly at locations and/or times where such measurement is not available but where wet deposition is monitored. The beta distribution function is used to describe the distribution of GOM + PBM and is used to predict GOM + PBM from monitored wet deposition. The mean, median, mode, standard deviation, and skewness of the fitted beta distribution parameters were generated using data collected in 2009 at multiple monitoring superstations. The established beta distribution function from the 2009 GOM + PBM data is used to construct a model that predicts GOM + PBM from wet deposition data. The model is validated using 2010 data at multiple stations, and the predicted monthly GOM + PBM concentrations agree reasonably well with measurements. The model has many potential applications after further improvements and validation using different data sets.
机译:为了量化汞干沉积,最近建立了国家大气沉积程序(NADP)的大气汞网(AMNET)监测了所指的大气汞(即气态元素汞(GEM),气态氧化汞(GOM)和颗粒状水星(PBM))。然而,AMNET的空间覆盖范围远远低于用于湿沉积监测的长期汞沉积网络(MDN)。本研究描述了将氧化汞(GOM + PBM)的第一次将环境浓度与湿沉积连接,旨在估计GOM + PBM大致在位置和/或这些测量不可用的位置,而是监测湿沉积的时间。 β分布函数用于描述GOM + PBM的分布,并用于预测来自监测的湿沉积的GOM + PBM。使用2009年在多种监测振缩的数据产生了拟合β分布参数的平均值,中值,模式,标准偏差和偏差。来自2009年GOM + PBM数据的已建立的测试函数函数用于构造一种从湿沉积数据预测GOM + PBM的模型。该模型在多个站点使用2010数据进行验证,预测的月度GOM + PBM集中浓度与测量相同。在使用不同的数据集进一步改进和验证之后,该模型具有许多潜在的应用。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号