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Taking into account the fact of global economic integration, this paper improves the RICE model and the MRICES model, and establishes a new integrated assessment model MRICES-2012, which takes Ramsey utility as the standard of fairness. Based on the model, schemes which meet the global emission mitigation targets as well as the interests of developing countries are simulated to assess the international fairness of emission reduction. Therefore, a new feasible scheme is proposed, which can not only reach the Copenhagen Consensus but also ensure interests of every country. Specifically speaking, the US and Japan cut emissions 80% and 70% respectively by 2050 relative to the 1990 level; the EU and other developed countries cut 80% by 2050 relative to 1990 level; high human development countries cut 50% by 2050 relative to 1990 level; all above-mentioned countries start emission reduction from 2020 and keep emission on 2050 level by 2100; China begins emission reduction from 2030 and cuts emission 15% by 2050 and 25% by 2100 relative to 2005 level; medium human development countries keep emission on 2020 level by 2100; low human development countries do not take part in reduction on emission intensity and global emission. [ABSTRACT FROM AUTHOR]

Remote sensing of ice phenology for small lakes is hindered by a lack of satellite observations with both high temporal and spatial resolutions. By merging multi-source satellite data over individual lakes, we present a new algorithm that successfully estimates ice freeze and thaw timing for lakes with surface areas as small as 0.13 km2 and obtains consistent results across a range of lake sizes. We have developed an approach for classifying ice pixels based on the red reflectance band of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, with a threshold calibrated against ice fraction from Landsat Fmask over each lake. Using a filter derived from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) surface air temperature product, we removed outliers in the time series of lake ice fraction. The time series of lake ice fraction was then applied to identify lake ice breakup and freezeup dates. Validation results from over 296 lakes in Maine indicate that the satellite-based lake ice timing detection algorithm perform well, with mean absolute error (MAE) of 5.54 days for breakup dates and 7.31 days for freezeup dates. This algorithm can be applied to lakes worldwide, including the nearly two million lakes with surface area between 0.1 and 1 km2. [ABSTRACT FROM AUTHOR]