Jinfeng Chang

TL;DR: A global N2O inventory is presented that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N 2O emissions, using bottom-up, top-down and process-based model approaches.

TL;DR: In this article, the authors presented a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community.

TL;DR: This study assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO2 concentration on global soil N2 O emissions for the period 1861-2016 using a standard simulation protocol with seven process-based terrestrial biosphere models.

TL;DR: This study demonstrates the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.

TL;DR: A majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large.