Spatiotemporal Variability of Oxygen Isotope Anomaly in near Surface Air CO2 over Urban, Semi-Urban and Ocean Areas in and around Taiwan

ABSTRACT

The most commonly used tracers to probe the atmospheric and biogeochemical cycles of CO₂ are ¹⁶O¹²C¹⁶O, ¹⁶O¹³C¹⁶O, and ¹⁶O¹²C¹⁸O. Considering the number and diversity of sources and sinks affecting CO₂, these tracers are not always sufficient to constrain the fluxes of CO₂ between the atmosphere and biosphere/hydrosphere. In this context, ¹⁶O¹²C¹⁷O species was introduced but has rarely been used due to difficulties associated with its accurate measurement in natural samples. This tracer, expressed as an abundance anomaly in ¹⁷O, defined by ∆¹⁷O = ln(1 + δ¹⁷O) – 0.516 × ln(1 + δ¹⁸O) can independently constrain the fluxes associated with the terrestrial processes. The advantage of utilizing ∆¹⁷O over δ¹⁸O alone lies on the sensitivity of the former to the rates of biogeochemical processes involving multiple water reservoirs with spatial and temporal isotopic heterogeneities. To employ all the three oxygen isotopes for estimating fluxes of CO₂, sources and processes affecting their partitioning have to be identified and quantified. Here, we measured ∆¹⁷O values in near surface atmospheric CO₂ from Taiwan in urban and semi-urban areas and over the South China Sea. Strong spatiotemporal variation was seen, with an average ∆¹⁷O value of 0.332‰ and a mean variation of 0.043‰ (relative to V-SMOW; 1-σ standard deviation for a total of 140 samples). The large variation reflects combinations of distinct air masses carrying CO₂ from sources having different ∆¹⁷O values: negative from combustion emissions, positive from the stratosphere, and a positive water-CO₂ equilibration value from isotope exchange with leaf/soil/ocean waters. We observed that the variation of the semi-urban ∆¹⁷O values is largely affected by local biogeochemistry and stratospheric intrusion with only minor influence from anthropogenic emissions. This is the first oxygen anomaly study for near surface CO₂ covering diverse source characteristics and has enormous potential in air CO₂ source identification and constraining the global carbon budget.