River networks play a crucial role in the global carbon cycle, as relevant sources of carbon dioxide (CO2) to the atmosphere. Advancements in high‐frequency monitoring in aquatic environments have enabled measurement of dissolved CO2 concentration at temporal resolutions essential for studying carbon variability and evasion from these dynamic ecosystems. Here, we describe the adaptation, deployment, and validation of an open‐source and relatively low‐cost in situ pCO2 sensor system for lotic ecosystems, the lotic‐SIPCO2. We tested the lotic‐SIPCO2 in 10 streams that spanned a range of land cover and basin size. Key system adaptations for lotic environments included prevention of biofouling, configuration for variable stage height, and reduction of headspace equilibration time. We then examined which input parameters contribute the most to uncertainty in estimating CO2 emission rates and found scaling factors related to the gas exchange velocity were the most influential when CO2 concentration was significantly above saturation. Near saturation, sensor measurement of pCO2 contributed most to uncertainty in estimating CO2 emissions. We also found high‐frequency measurements of pCO2 were not necessary to accurately estimate median emission rates given the CO2 regimes of our streams, but daily to weekly sampling was sufficient. High‐frequency measurements of pCO2 remain valuable for exploring in‐stream metabolic variability, source partitioning, and storm event dynamics. Our adaptations to the SIPCO2 offer a relatively affordable and robust means of monitoring dissolved CO2 in lotic ecosystems. Our findings demonstrate priorities and related considerations in the design of monitoring projects of dissolved CO2 and CO2 evasion dynamics more broadly.

中文翻译：

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Lotic-SIPCO2：采用开源二氧化碳传感器系统并检查各种溪流大小和土地利用的相关排放不确定性

河流网络在全球碳循环中发挥着至关重要的作用，因为二氧化碳（CO2）的相关来源2）到大气层。水生环境高频监测的进步使得溶解二氧化碳的测量成为可能2时间分辨率的浓度对于研究这些动态生态系统的碳变化和逃逸至关重要。在这里，我们描述了开源且成本相对较低的现场的适应、部署和验证p一氧化碳2Lotic 生态系统传感器系统，Lotic-SIPCO2。我们在跨越不同土地覆盖和盆地大小的 10 条溪流中测试了 Lotic-SIPCO2。针对液体环境的关键系统适应性包括防止生物污垢、可变阶段高度的配置以及减少顶空平衡时间。然后我们检查了哪些输入参数对 CO 估算的不确定性影响最大2排放率并发现与气体交换速度相关的比例因子在 CO 时影响最大2浓度明显高于饱和度。接近饱和，传感器测量p一氧化碳2对 CO 估算的不确定性贡献最大2排放。我们还发现高频测量p一氧化碳2考虑到 CO 的影响，没有必要准确估计中值排放率2我们的河流的状况，但每天到每周的采样就足够了。高频测量p一氧化碳2对于探索河流内代谢变异性、源分区和风暴事件动态仍然有价值。我们对 SIPCO2 的改造提供了一种相对实惠且可靠的溶解 CO 监测方法2在激流生态系统中。我们的研究结果表明了溶解二氧化碳监测项目设计中的优先事项和相关考虑因素2和二氧化碳2更广泛的逃避动态。