Carbon choices determine US cities committed to futures below sea level.
Benjamin H StraussScott KulpAnders LevermannPublished in: Proceedings of the National Academy of Sciences of the United States of America (2015)
Anthropogenic carbon emissions lock in long-term sea-level rise that greatly exceeds projections for this century, posing profound challenges for coastal development and cultural legacies. Analysis based on previously published relationships linking emissions to warming and warming to rise indicates that unabated carbon emissions up to the year 2100 would commit an eventual global sea-level rise of 4.3-9.9 m. Based on detailed topographic and population data, local high tide lines, and regional long-term sea-level commitment for different carbon emissions and ice sheet stability scenarios, we compute the current population living on endangered land at municipal, state, and national levels within the United States. For unabated climate change, we find that land that is home to more than 20 million people is implicated and is widely distributed among different states and coasts. The total area includes 1,185-1,825 municipalities where land that is home to more than half of the current population would be affected, among them at least 21 cities exceeding 100,000 residents. Under aggressive carbon cuts, more than half of these municipalities would avoid this commitment if the West Antarctic Ice Sheet remains stable. Similarly, more than half of the US population-weighted area under threat could be spared. We provide lists of implicated cities and state populations for different emissions scenarios and with and without a certain collapse of the West Antarctic Ice Sheet. Although past anthropogenic emissions already have caused sea-level commitment that will force coastal cities to adapt, future emissions will determine which areas we can continue to occupy or may have to abandon.
Keyphrases
- climate change
- municipal solid waste
- life cycle
- healthcare
- randomized controlled trial
- heavy metals
- wastewater treatment
- computed tomography
- magnetic resonance
- systematic review
- machine learning
- intellectual disability
- magnetic resonance imaging
- big data
- autism spectrum disorder
- artificial intelligence
- data analysis
- genetic diversity