Saharan Dust Pollution: Implications for the Sahel?

The main source of atmospheric mineral dust is the Sahara desert, which produces about half of the yearly global mineral dust.1 About 12% of the Saharan dust moves northwards to Europe, 28% westwards to the Americas, and 60% southwards to the Gulf of Guinea. Saharan dust storms can lead to particulate matter (PM) levels that exceed internationally recommended levels. Recently, special attention has been paid to the mineral PM air pollution of dust storms, which may be a serious health threat. We took a systematic review of the literature to find relevant studies on the effects of Saharan dust on air quality or human health. We searched the ISI web of knowledge database using “PM10,” “PM2.5” or “health” AND “dust storm,” “sand storm,” “African dust,” “Saharan dust,” or “dust events” without restrictions. The search extended from January 1999 to December 2008. We selected 97 articles of which 72 studied PM air pollution in Europe, 13 in the Americas, 7 in the Near East and Asia, and 4 considered international data. Only one specifically addressed air pollution in the Sahel. Four focused on human health effects—2 in the Mediterranean and 2 in the Caribbean

Factors influencing creep model equation selection

During the course of the EU-funded Advanced-Creep Thematic Network, ECCC-WG1 reviewed the applicability and effectiveness of a range of model equations to represent the accumulation of creep strain in various engineering alloys. In addition to considering the experience of network members, the ability of several models to describe the deformation characteristics of large single and multi-cast collations of e(t,T,s) creep curves have been evaluated in an intensive assessment inter-comparison activity involving three steels, 214CrMo (P22), 9CrMoVNb (Steel-91) and 18Cr13NiMo (Type-316). The choice of the most appropriate creep model equation for a given application depends not only on the high-temperature deformation characteristics of the material under consideration, but also on the characteristics of the dataset, the number of casts for which creep curves are available and on the strain regime for which an analytical representation is required. The paper focuses on the factors which can influence creep model selection and model-fitting approach for multi-source, multi-cast datasets