Economic benefits from decreased mercury emissions: Projections for 2020

Anthropogenic processes have increased the exposure of humans and wildlife to toxic methyl mercury (MeHg). Mercury emissions will increase by about 25% between 2005 and 2020, if the present trajectory is maintained. A global assessment of societal damages caused by the ingestion of methyl mercury, based merely on loss of IQ (Intelligence Quotient), suggests that the annual cost will be approximately US$3.7 billion (2005 dollars) in 2020. The corresponding cost of damages resulting from the inhalation of methyl mercury is estimated at US$2.9 million (2005 dollars). Under a higher degree of emission control such as in the case of the Extended Emission Control (EXEC) and the Maximum Feasible Technological Reduction (MFTR) scenarios, total emissions could decrease in the period 2005–2020 by about 50–60%. The corresponding annual benefits in 2020 are estimated to be about US$1.8–2.2 billion (2005 dollars). Large economic benefits can be achieved by reducing global mercury emissions.     

Does the effect of low temperature on osmoregulation by the prawn Palaemon elegans Rathke, 1837 explain winter migration offshore?

Osmoregulation by the European glass prawn Palaemon elegans Rathke, 1837 was impaired at low temperature (2°C) and high salinities (full strength sea water 35 PSU). Under these conditions, small individuals showed stronger osmoregulatory ability than larger individuals. This observation could partially explain differences in winter migrations off the UK coast where mainly large P. elegans go offshore, leaving smaller individuals in high shore rock pools, a finding consistent with winter experiments in situ.     

NOAA satellite data: a useful tool for macro inventory

This article discusses some of the demonstrated and potential uses of data from satellites with large fields of view and high frequency of coverage, such as NOAA AVHRR data and Nimbus-7 CZCS data. The use of such data is discussed for three types of applications: (a) stratification, (b) change detection, and (c) area estimation. It is concluded that such data have considerable promise as an aid to a variety of large-area inventory and monitoring tasks.