Spatial and seasonal variations of carbon emissions in an urban lake: Flux sensitivity and sampling optimization based on high-resolution measurements

Abstract

Understanding the dynamics of pCO₂ and pCH₄ is important for evaluating carbon emissions from the aquatic environment. While temporal dynamics of pCO₂ and pCH₄ have been extensively studied, there is a noticeable gap in the literature concerning their spatial characteristics. In this study, we used boat-mounted sensors to directly measure pCO₂ and pCH₄ with high spatial resolution across seasons in Xuanwu Lake (XWL), an urban lake in Nanjing, China. Additionally, water chemistries were measured at selected sites for correlation analysis. Sensitivity analysis was performed to assess the effects of measurement location and density on carbon flux estimates.

Results show that continuous on-board measurements innovatively captured the spatial distribution of pCO₂ and pCH₄. Both gases varied significantly across seasons, exhibiting pronounced spatial heterogeneity. Peak emissions occurred in summer, with the lowest CO₂ in spring and CH₄ in fall. Both pCO₂ and pCH₄ increased from the lake center to the shoreline, with the largest fluctuations near the shore. In total, XWL acted as a net source of CO₂ and CH₄, with mean diffusive fluxes of 11.4 ± 10.1 and 3.0 ± 0.3 mmol∙m⁻²∙d⁻¹, respectively. Furthermore, sensitivity analysis showed that lake-wide flux calculations depend on measurement locations and sample size. pCO₂ exhibited greater heterogeneity than pCH₄, necessitating different sampling thresholds. The optimal threshold for capturing lake-wide CO₂ flux was 18–30 samples per km², while this density was sufficient for CH₄ flux estimates. Our study highlights that both CO₂ and CH₄ exhibit significant spatial and temporal heterogeneity, necessitating high-resolution sampling for accurate flux assessments. The sampling strategy presented could guide future studies, as sampling in the intermediate zone effectively reduces the number of samples needed while maintaining accuracy.