Cleaning up nitrogen pollution may reduce future carbon sinks

A Bayesian Synthesis Inversion of Carbon Cycle Observations: How Can Observations Reduce Uncertainties about Future Sinks?

The strengths of future carbon dioxide (CO 2) sinks are highly uncertain. A sound characterization of this uncertainty and how they might be reduced is crucial for the design of efficient carbon management strategies. Here a Bayesian synthesis inversion of historical carbon cycle observations is used to (i) estimate probability density functions (PDFs) of key carbon cycle parameters, (ii) deriv...

Robust relationship between yields and nitrogen inputs indicates three ways to reduce nitrogen pollution

The Nitrogen Footprint Tool Network: A Multi-Institution Program To Reduce Nitrogen Pollution

Anthropogenic sources of reactive nitrogen have local and global impacts on air and water quality and detrimental effects on human and ecosystem health. This article uses the Nitrogen Footprint Tool (NFT) to determine the amount of nitrogen (N) released as a result of institutional consumption. The sectors accounted for include food (consumption and upstream production), energy, transportation,...

Territorial Rights and Carbon Sinks

Scholars concerned with abuses of the "resource privilege" by the governments of developing states sometimes call for national sovereignty over the natural resources that lie within its borders. While such claims may resist a key driver of the "resource curse" when applied to mineral resources in the ground, and are often recognized as among a people's territorial rights, their implications dif...

Cleaning up after yourself

Performing cleanup actions such as restoring a variable or closing a file used to be impossible to guarantee in Forth before Forth-94 gave us catch. Even with catch, the cleanup code can be skipped due to user interrupts if you are unlucky. We introduce a construct that guarantees that the cleanup code is always completed. We also discuss a cheaper implementation approach for cleanup code than ...