Danni Yuan , Siyue Li , Chen Ye , Wenzhi Liu , Jun Xu
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引用次数: 0
Abstract
Environmental warming and eutrophication pose significant challenges to shallow lake systems, where dissolved organic matter (DOM) serves as a diverse and intricate mixture of organic macromolecules, playing a pivotal role in aquatic ecosystems. Despite its complexity, comprehending the interplay between environmental changes and DOM composition alterations and their subsequent impacts on aqueous CO2 partial pressure (pCO2) is essential for a better understanding of carbon cycling. Yet, our current understanding in this realm remains limited. To address this gap, mesocosm systems were established to investigate how elevated water temperature and eutrophication, alongside changes in DOM composition, influence pCO2 dynamics. Results indicate that while temperature and nutrient levels do not directly influence pCO2 fluctuations, they indirectly affect aqueous pCO2 through their modulation of DOM composition. Elevated temperature and nutrient concentrations notably enhance both the production and degradation of indigenous protein-like organic matter and increase the accumulation of humic-like organic compounds, with phosphorus released from sediment playing a particularly significant role. Furthermore, the degradation rate of protein-like organic matter significantly exceeds its accumulation rate. On the other hand, the impact of water eutrophication on DOM composition surpasses that of temporal temperature variations, with a 2∼4 °C temperature rise showing minimal effects on DOM composition. Notably, the degradation of protein-like organic matter markedly increases aqueous pCO2, while the rise in humic-like organic matter in water exerts minimal influence on pCO2 concentrations. A comprehensive understanding of carbon cycling processes under environmental changes will facilitate effective management of lake ecosystems and the advancement of carbon mitigation technologies.
环境变暖和富营养化给浅水湖泊系统带来了巨大挑战,而溶解有机物(DOM)是有机大分子的一种多样而复杂的混合物,在水生生态系统中发挥着举足轻重的作用。尽管情况复杂,但理解环境变化与溶解有机物成分变化之间的相互作用及其对水体二氧化碳分压(pCO2)的影响,对于更好地理解碳循环至关重要。然而,我们目前对这一领域的了解仍然有限。为了填补这一空白,我们建立了中观宇宙系统,研究水温升高和富营养化以及 DOM 成分变化如何影响 pCO2 动态。结果表明,虽然温度和营养水平不会直接影响 pCO2 的波动,但它们会通过调节 DOM 成分间接影响水体 pCO2。温度和养分浓度的升高会明显促进本地蛋白质类有机物的产生和降解,并增加腐殖质类有机化合物的积累,其中沉积物释放的磷的作用尤为显著。此外,类蛋白质有机物的降解速度大大超过其积累速度。另一方面,水体富营养化对 DOM 组成的影响超过了时间温度变化的影响,温度上升 2∼4 °C 对 DOM 组成的影响微乎其微。值得注意的是,蛋白质类有机物的降解会显著增加水体中的 pCO2,而水中腐殖质类有机物的增加对 pCO2 浓度的影响微乎其微。全面了解环境变化下的碳循环过程将有助于有效地管理湖泊生态系统和推动碳减排技术的发展。
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.