A Numerical Examination of ¹⁴CO₂ Chamber Methodologies for Sampling at the Soil Surface

Radiocarbon is an exceptionally useful tool for studying soil-respired CO₂, providing information about soil carbon turnover rates, depths of production, and the biological sources of production through partitioning. Unfortunately, little work has been done to thoroughly investigate the possibility of inherent biases present in current measurement techniques, like those present in δ¹³CO₂ methodologies, caused by disturbances to the soil’s natural diffusive regime. This study investigates the degree of bias present in four ¹⁴C sampling chamber methods using a three-dimensional numerical soil-atmosphere CO₂ diffusion model. The four chambers were tested in an idealized, surrogate reality by assessing measurement bias with varying Δ¹⁴C and δ¹³C signatures of production, collar lengths, soil biological productivity rates, and soil diffusivities. The static and Iso-FD chambers showed almost no isotopic measurement bias, significantly outperforming dynamic chambers, which demonstrated biases up to 200‰ in some modeled scenarios. The study also showed that ¹³C and ¹⁴C diffusive fractionation are not a constant multiple of one another, but that the δ¹³C correction still works in diffusive scenarios because the change in fractionation is not large enough to impact measured Δ¹⁴C values during chamber equilibration.This is the publisher’s final pdf. The published article is copyrighted by the Arizona Board of Regents on behalf of the University of Arizona and can be found at: https://journals.uair.arizona.edu/index.php/radiocarbon/index

Hospital-level evaluation of the effect of a national quality improvement programme: time-series analysis of registry data.

BACKGROUND AND OBJECTIVES: A clinical trial in 93 National Health Service hospitals evaluated a quality improvement programme for emergency abdominal surgery, designed to improve mortality by improving the patient care pathway. Large variation was observed in implementation approaches, and the main trial result showed no mortality reduction. Our objective therefore was to evaluate whether trial participation led to care pathway implementation and to study the relationship between care pathway implementation and use of six recommended implementation strategies. METHODS: We performed a hospital-level time-series analysis using data from the Enhanced Peri-Operative Care for High-risk patients trial. Care pathway implementation was defined as achievement of >80% median reliability in 10 measured care processes. Mean monthly process performance was plotted on run charts. Process improvement was defined as an observed run chart signal, using probability-based 'shift' and 'runs' rules. A new median performance level was calculated after an observed signal. RESULTS: Of 93 participating hospitals, 80 provided sufficient data for analysis, generating 800 process measure charts from 20 305 patient admissions over 27 months. No hospital reliably implemented all 10 processes. Overall, only 279 of the 800 processes were improved (3 (2-5) per hospital) and 14/80 hospitals improved more than six processes. Mortality risk documented (57/80 (71%)), lactate measurement (42/80 (53%)) and cardiac output guided fluid therapy (32/80 (40%)) were most frequently improved. Consultant-led decision making (14/80 (18%)), consultant review before surgery (17/80 (21%)) and time to surgery (14/80 (18%)) were least frequently improved. In hospitals using ≥5 implementation strategies, 9/30 (30%) hospitals improved ≥6 care processes compared with 0/11 hospitals using ≤2 implementation strategies. CONCLUSION: Only a small number of hospitals improved more than half of the measured care processes, more often when at least five of six implementation strategies were used. In a longer term project, this understanding may have allowed us to adapt the intervention to be effective in more hospitals