Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strate
Widespread irreversible changes in surface temperature and precipitation in response to CO2 forcing | Nature Climate Change
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### Subjects
- Attribution
- Climate and Earth system modelling
## Abstract
Some climate variables do not show the same response to declining atmospheric CO2 concentrations as before the preceding increase. A comprehensive understanding of this hysteresis effect and its regional patterns is, however, lacking. Here we use an Earth system model with an idealized CO2 removal scenario to show that surface temperature and precipitation exhibit globally widespread irreversible changes over a timespan of centuries. To explore the climate hysteresis and reversibility on a regional scale, we develop a quantification method that visualizes their spatial patterns. Our experiments project that 89% and 58% of the global area experiences irreversible changes in surface temperature and precipitation, respectively. Strong irreversible response of surface temperature is found in the Southern Ocean, Arctic and North Atlantic Ocean and of precipitation in the tropical Pacific, global monsoon regions and the Himalayas. These global hotspots of irreversible chan
Abstract The purpose of this paper is to examine the causality between DUST, CO2 and temperature for the Vostok ice core data series [Vostok Data Series], dating from 420 000 years ago, and the EPICA C Dome data going back 800 000 years. In addition, the time-varying volatility and coefficient of variation in the CO2, dust and temperature is examined, as well as their dynamic correlations and interactions. We find a clear link between atmospheric C02 levels, dust and temperature, together with a bi-directional causality effects when applying both Granger Causality Tests (1969) and multi-directional Non-Linear analogues, i.e. Generalized Correlation. We apply both parametric and non-parametric statistical measures and testing. Linear interpolation with 100 years and 1000 years is applied to the three variables, in order to solve the problem of data points mismatch among them. The visualizations and descriptive statistics of the interpolated variables (using the two periods) show robustness in the results. The data analysis points out that variables are volatile, but their respective rolling mean and standard deviation remain stable. Additionally, 1000 years interpolated data suggests positive correlation between temperature and CO2, while dust is negatively correlated with both temperature and CO2. The application of the non-parametric Generalized Measure of Correlation to our data sets, in a pairwise fashion suggested that CO2 better explains temperature than temperature does CO2, that temperature better explains dust than dust does temperature, and finally that CO2 better explains dust than vice -versa. The latter two pairs of relationships are negative. The summary of the paper presents some avenues for further research, as well as some policy relevant suggestions.
Mathematical models indicate increasing atmospheric carbon dioxide causes an increase in surface temperature at a decreasing rate, and the rate of temperature decrease caused by increasing aerosols increases with aerosol concentration. (AL)
Despite scientists’ dire warnings about the catastrophic impacts of climate change, the greenhouse gases that cause it continue to be emitted in substantial amounts. While there is no question that deep, across the board cuts in greenhouse gas emissions are essential, many scientists now agree that simply cutting future emissions will not be enough. It will also be necessary to remove previously-emitted greenhouse gases from the atmosphere. This paper explores one greenhouse gas removal technique—enhanced weathering—which involves spreading finely ground silicate rocks or other materials with
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