Holocene peatland and ice-core data constraints on the timing and magnitude of CO2 emissions from past land use.
Benjamin David StockerZicheng YuCharly MassaFortunat JoosPublished in: Proceedings of the National Academy of Sciences of the United States of America (2017)
CO2 emissions from preindustrial land-use change (LUC) are subject to large uncertainties. Although atmospheric CO2 records suggest only a small land carbon (C) source since 5,000 y before present (5 kyBP), the concurrent C sink by peat buildup could mask large early LUC emissions. Here, we combine updated continuous peat C reconstructions with the land C balance inferred from double deconvolution analyses of atmospheric CO2 and [Formula: see text]C at different temporal scales to investigate the terrestrial C budget of the Holocene and the last millennium and constrain LUC emissions. LUC emissions are estimated with transient model simulations for diverging published scenarios of LU area change and shifting cultivation. Our results reveal a large terrestrial nonpeatland C source after the Mid-Holocene (66 [Formula: see text] 25 PgC at 7-5 kyBP and 115 [Formula: see text] 27 PgC at 5-3 kyBP). Despite high simulated per-capita CO2 emissions from LUC in early phases of agricultural development, humans emerge as a driver with dominant global C cycle impacts only in the most recent three millennia. Sole anthropogenic causes for particular variations in the CO2 record ([Formula: see text]20 ppm rise after 7 kyBP and [Formula: see text]10 ppm fall between 1500 CE and 1600 CE) are not supported. This analysis puts a strong constraint on preindustrial vs. industrial-era LUC emissions and suggests that upper-end scenarios for the extent of agricultural expansion before 1850 CE are not compatible with the C budget thereafter.
Keyphrases
- climate change
- municipal solid waste
- smoking cessation
- life cycle
- human milk
- heavy metals
- skeletal muscle
- risk assessment
- particulate matter
- randomized controlled trial
- gene expression
- squamous cell carcinoma
- systematic review
- big data
- radiation therapy
- obstructive sleep apnea
- magnetic resonance imaging
- magnetic resonance
- human health
- subarachnoid hemorrhage
- single cell
- sewage sludge
- preterm infants
- artificial intelligence
- energy transfer
- data analysis
- quantum dots