Development and testing of a rapid, sensitive, high-resolution tool to improve mapping of CO2 leakage at the ground surface

Locating and quantifying anomalous, deep-origin CO2 leakage from the soil to the atmosphere is typically accomplished by interpolating a dataset of point flux measurements, with overall accuracy and uncertainty strongly influenced by sample spacing relative to anomaly size and variability. To reduce this uncertainty we have developed the Ground CO2 Mapper, a low-cost complementary tool that rapidly measures, at high spatial resolution, the distribution of CO2 concentration at the ground-air contact as a proxy of CO2 flux. Laboratory tests show that the Mapper has a low noise level (2 sigma = 16 ppm) and fast response time (T90 = 1.55 s), while field tests at a small controlled-release site define a high level of reproducibility and sensitivity and illustrate the impact of wind and survey speed on instrument response. Modelling based on these results indicates that the Mapper has a greater than 60% probability of detecting an intersected 2 m wide anomaly having a maximum CO2 flux rate of 75 and 100 g m(-2) d(-1) at survey speeds of 2.5 and 4.8 km h-1, respectively, under the test conditions. Mea-surements in a large (4600 m2) grassland field where natural geogenic CO2 is leaking show how the Mapper can produce, in < 10% of the time, a more detailed map of CO2 flux distribution than a point flux survey conducted on a ca. 10 m grid spacing. Based on these results we believe the Ground CO2 Mapper can give a useful contribution to diffuse degassing studies in volcanic/geothermal areas and to monitoring of Carbon Capture and Storage (CCS) sites by reducing overall survey time, costs and uncertainty. Future work will test the Mapper's response and capabilities under more diverse site and meteorological conditions than those examined in this study.

Automated summary

Locating and quantifying deep-origin CO2 leakage is challenging due to measurement accuracy and uncertainty. The Ground CO2 Mapper, a low-cost tool developed in this study, can rapidly measure CO2 concentration distribution, improving the estimation accuracy of CO2 flux.