资源环境科技发展态势分析平台

Manual measurements of nitrous oxide (N₂O) emissions with static chambers are commonly practised. However, they generally do not consider the diurnal variability of N₂O flux, and little is known about the patterns and drivers of such variability. We systematically reviewed and analysed 286 diurnal data sets of N₂O fluxes from published literature to (i) assess the prevalence and timing (day or night peaking) of diurnal N₂O flux patterns in agricultural and forest soils, (ii) examine the relationship between N₂O flux and soil temperature with different diurnal patterns, (iii) identify whether non-diurnal factors (i.e. land management and soil properties) influence the occurrence of diurnal patterns and (iv) evaluate the accuracy of estimating cumulative N₂O emissions with single-daily flux measurements. Our synthesis demonstrates that diurnal N₂O flux variability is a widespread phenomenon in agricultural and forest soils. Of the 286 data sets analysed, ~80% exhibited diurnal N₂O patterns, with ~60% peaking during the day and ~20% at night. Contrary to many published observations, our analysis only found strong positive correlations (R > 0.7) between N₂O flux and soil temperature in one-third of the data sets. Soil drainage property, soil water-filled pore space (WFPS) level and land use were also found to potentially influence the occurrence of certain diurnal patterns. Our work demonstrated that single-daily flux measurements at mid-morning yielded daily emission estimates with the smallest average bias compared to measurements made at other times of day, however, it could still lead to significant over- or underestimation due to inconsistent diurnal N₂O patterns. This inconsistency also reflects the inaccuracy of using soil temperature to predict the time of daily average N₂O flux. Future research should investigate the relationship between N₂O flux and other diurnal parameters, such as photosynthetically active radiation (PAR) and root exudation, along with the consideration of the effects of soil moisture, drainage and land use on the diurnal patterns of N₂O flux. The information could be incorporated in N₂O emission prediction models to improve accuracy.