Optimum sampling time and frequency for measuring N2O emissions from a rain-fed cereal cropping system

Area of Science:

• Agricultural Science
• Environmental Science
• Soil Science

Background:

• Annual soil nitrous oxide (N2O) emissions are typically calculated using manual static chamber methods.
• Temporal variability in N2O emissions (diurnal and daily) introduces uncertainty in up-scaling static chamber data.
• Accurate estimation of cumulative N2O emissions is crucial for climate change mitigation and agricultural management.

Purpose of the Study:

• To determine the optimal sampling time of day for estimating daily mean N2O emissions.
• To identify the most effective sampling frequency for reliable annual cumulative N2O emission estimates.
• To assess the impact of rainfall events on sampling strategy efficacy.

Main Methods:

• Utilized automatic gas sampling chambers to measure sub-daily N2O emissions over three years in a subtropical cereal crop system.
• Analyzed data by dividing into eight time periods to identify optimal sampling times.
• Simulated various sampling frequencies (pre-set and rainfall-based) to estimate annual cumulative N2O emissions.

Main Results:

• Mid-morning (09:00-12:00) sampling best approximated daily mean N2O emissions, considering practical daylight sampling.
• Triweekly sampling offered high accuracy (± 4% error) but was labor-intensive.
• A weekly sampling schedule, augmented with triweekly sampling post-rainfall, achieved similar accuracy (± 5% error) with reduced effort.

Conclusions:

• Appropriate timing of intermittent sampling can satisfactorily estimate annual cumulative soil N2O emissions.
• A hybrid sampling strategy (weekly + rainfall-triggered) offers an efficient and accurate approach.
• Understanding temporal emission patterns is key to refining greenhouse gas inventory methods in agriculture.