This book provides an overview of air quality in Albania evaluated by moss biomonitoring and metals atmospheric deposition. It is based on the concentration data onto 51 elements in moss samples collected during 2010/2011 moss biomonitoring survey conducted at the same time with European moss biomonitoring survey. The elements under investigation were determined by using ICP-AES and ENAA analytical techniques. Moss species Hypnum cupressiforme (Hedw) sps., a carpet-forming bryophyte, was used as bioindicator of trace metal atmospheric deposition. The goal of this study was to identify factors leading to the high levels of trace metals in at-mospheric deposition in Albania, to identify the risk factors and the origin of trace metals in atmos-pheric deposition. It may help the policy makers and regulators to take proper decisions to protect the public health and the environment. The distribution pattern of the elements was visualized by using the geographic information system, GIS 10.2.The predicted trends of the distribution were calculated by using time series (linear model) and the areas with high concentration of certain met-als were suggested for monitoring and to be under control.

   

This book provides an overview of air quality in Albania evaluated by moss biomonitoring and metals atmospheric deposition. It is based on the concentration data onto 51 elements in moss samples collected during 2010/2011 moss biomonitoring survey conducted at the same time with European moss biomonitoring survey. The elements under investigation were determined by using ICP-AES and ENAA analytical techniques. Moss species Hypnum cupressiforme (Hedw) sps., a carpet-forming bryophyte, was used as bioindicator of trace metal atmospheric deposition. The goal of this study was to identify factors leading to the high levels of trace metals in at-mospheric deposition in Albania, to identify the risk factors and the origin of trace metals in atmos-pheric deposition. It may help the policy makers and regulators to take proper decisions to protect the public health and the environment. The distribution pattern of the elements was visualized by using the geographic information system, GIS 10.2.The predicted trends of the distribution were calculated by using time series (linear model) and the areas with high concentration of certain met-als were suggested for monitoring and to be under control.