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We recently presented a new hybrid method of assessing temporally and spatially resolved PM2.5 exposure for epidemiological studies by combining 1 km × 1 km resolution satellite-retrieved aerosol optical depth (AOD) measurements with traditional land use terms, meteorological variables, and their interactions (Kloog et al. 2014a).
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In the present research, available long-term meteorological and hydrometrical parameters, 45 years from 1966 1967 to 2011 2012 water years, were gathered and analyzed.
The on-site investigations include a long-term meteorological observation, runoff monitoring, assessment on forest growth and health, and characterization of site conditions.
Moreover, the majority of the above methods need long-term meteorological data, such as total solar irradiance, air temperature, and wind speed, for their operations.
The solution can be obtained by using available long-term meteorological data for the design-site and manufacturer data for the system components.
Specifically, the accidental radioactivity release is subdivided into consecutive one-hour Gaussian segments, each driven by a short-term meteorological forecast for the respective hours.
These include "design of policy mechanisms that modify long-term development, as well as improved use of short-term meteorological forecasts of fire behaviour during years with high fire season severity".
Reports of a variety of short-term meteorological responses to changes in the global electric circuit associated with a set of disparate inputs are analyzed.
This study utilized long-term meteorological and river discharge records in the SRB to assess spatiotemporal variability and trends in temperature, precipitation, and discharge.
At the second step, the results from the wind tunnel testing, in conjunction with the statistical analysis results of long-term meteorological wind data recorded in Guangzhou, are applied for the performance assessment of these wind turbines for power generation.
The transmission loads, calculated by using measured long-term meteorological data for selected cities, are fed into an economic model (P1−P2 method) in order to determine the optimum insulation thickness.
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CEO of Professional Science Editing for Scientists @ prosciediting.com