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Juxtaposing the spatiotemporal drivers of sediment CO2, CH4, and N2O effluxes along ecoregional, wet-dry, and diurnal gradients
Atmospheric Pollution Research ( IF 4.5 ) Pub Date : 2021-03-05 , DOI: 10.1016/j.apr.2021.03.002
Pelin Ertürk Arı , Nusret Karakaya , Fatih Evrendilek

Globally, lakes are facing greater drying rates than before the industrial revolution due to global climate change, water withdrawals, and land use and land cover changes. Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes of the lakeshore sediments still remain poorly represented and understood, with important implications for the global carbon (C) and nitrogen (N) budget closures. This study quantifies spatiotemporal dynamics and (non-)linear drivers of CO2, CH4, and N2O effluxes from sediments of 20 lakes along wet-dry lakeshore, diurnal, and ecoregional gradients in the western part of Turkey. Mean daily CO2, CH4, and N2O effluxes were estimated at 98.64 ± 386.47, 1.42 ± 1.71, and 0.12 ± 0.24 from wet sediments and at 393.60 ± 386.94, 0.82 ± 1.58, and 0.24 ± 0.22 from dry sediments, with an overall mean of 242.28 ± 404.1, 1.09 ± 1.53, and 0.18 ± 0.23 mmol m−2 d−1, respectively. The variability in the GHG effluxes was most sensitive to the interaction between latitude and wet-dry location. Out of 14 significant environmental drivers, the most important ones that minimized and maximized CO2, CH4, and N2O effluxes were PO4–P content, three-summer month standardized precipitation index, and redox potential, respectively, based on a random forest-based optimization.



中文翻译:

沿生态区域,干湿和昼夜梯度将沉积物CO 2,CH 4和N 2 O外流的时空驱动因素并置

在全球范围内,由于全球气候变化,取水量以及土地利用和土地覆盖的变化,湖泊面临比工业革命之前更高的干旱率。湖岸沉积物的二氧化碳(CO 2),甲烷(CH 4)和一氧化二氮(N 2 O)通量仍然表示和理解较差,这对全球碳(C)和氮(N)预算的关闭具有重要意义。这项研究量化了沿土耳其西部湿干湖岸,昼夜和生态区域梯度从20个湖泊的沉积物中CO 2,CH 4和N 2 O流出的时空动力学和(非线性)驱动力。每日平均CO 2,CH 4和N 2 O流出量估计从湿沉积物中为98.64±386.47、1.42±1.71和0.12±0.24,在干燥沉积物中为393.60±386.94、0.82±1.58和0.24±0.22,总平均值为242.28±404.1分别为1.09±1.53和0.18±0.23 mmol m -2 d -1。温室气体排放量的变化对纬度和干湿位置之间的相互作用最敏感。在14个重要的环境驱动因素中,使CO 2,CH 4和N 2 O流量最小化和最大化的最重要因素分别是PO 4 -P含量,三夏月标准化降水指数和氧化还原电势,基于基于随机森林的优化。

更新日期:2021-03-07
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