TO ASSESS AND MITIGATE DUST IMPACTS ON KEY SECTORS OF SOCIETY AND ECONOMY
Sand and Dust Storms (SDS) can severely disrupt communications, as well as ground and air transportation. Even moderate dust concentrations affect solar radiation production systems, damage croplands, and compromise air quality and human health. There are many potential applications for SDS early warnings and products, which can be grouped into tactical, strategic, and research applications. The tactical applications focus on actions that can be taken in the short term, whenever forecasts predict SDS at a certain location and time. Strategic applications are those related to long-term planning and investments. Another potential application is to assist with post-dust storm assessments. National governments and international institutions need to know the precise causes of air quality degradation, epidemic outbreaks or crop damages.
Other scientific communities, such as the public health community, need spatially and temporally resolved dust data to attribute the effects of dust particles upon a range of ailments. The delivery of accurate information on past trends, current analysis and forecasts is a prerequisite for decision making at multiple time scales. However, this is not the only challenge. Other key impediments include a lack of understanding of the precise role of SDS upon certain sectors; the lack of products tailored to specific applications; the lack of awareness, understanding, capacity or structures in place to use the information, and the challenge of our reluctance to incorporating uncertain information or forecasts into management practices.
Our activities will focus on three particular communities inside this strategic goal.
SDS cause unhealthful levels of dust particles not only in arid and semi-arid environments but also in distant areas due to long-range transport. Health studies have generally focused on urban areas and only a few have quantified the effects of differentiated mineral dust upon human health. At present, there is little understanding on the factors (e.g. composition, particle size), exposure levels and biological mechanisms responsible for the observed health effects of dust, and there is a lack of studies in many areas where dust exposure is consistently high such as sub-Saharan Africa. The development of dust concentration and composition historical datasets (based on model predictions) will contribute to new health assessments.
The most direct impact of SDS upon agriculture is the loss of crop and livestock. With appropriate user consultation, SDS warning advisories, assessments and tools could help mitigation and adaptation actions to be taken in advance, including harvesting of maturing crops and sheltering livestock, changing the time of planting, strengthening infrastructure, and constructing windbreaks and shelterbelts. Another application is the use of accurate dust products to inform index insurance initiatives for farmers in North Africa. Weather-based index insurance is a promising tool for development, climate risk management and adaptation. However, poor data and uncertainties in climate information combined with inconsistent implementation practices threaten the viability of insurance as a larger scale adaptation instrument in developing countries.
Dust can severely affect solar energy production and the transport sector. Solar power forecasting prevents energy loss and improves the management of solar plants. With respect to the transport sector, SDS can have a substantial impact on air and road traffic through visibility reduction. Poor visibility conditions are a danger to aircraft landing and taking off, as well as to airport ground operations. Therefore, aerodromes operating in such conditions are required to set low visibility procedures (LVP) in force. This implies a reduced movement rate and, therefore, increased likelihood of delayed departures, diverted flights and airport operational problems. A precise prediction can minimize the time when LVP are in place and reduce their negative effects. With respect the solar energy production sector, recent studies have shown that the accuracy of existing weather models to predict solar irradiance is not always satisfactory and that a large proportion of the uncertainty can be attributed to the lack of accurate aerosol data.