热带河网中甲烷有氧氧化的环境决定因素

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-08-13 DOI:10.1016/j.watres.2024.122257
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引用次数: 0

摘要

有氧甲烷氧化(MOX)大大减少了内陆水体的甲烷(CH)排放量,因此是全球甲烷预算的一个重要决定因素。然而,人们对河流(大气中甲烷的重要天然来源)中甲烷氧化率的大小和控制却知之甚少。在这里,我们进行了一系列培养实验,以了解热带河流系统中 MOX 发生率的大小和环境控制。我们观察到,MOX速率(0.03 - 3.45 μmol ld)的变化很大,这是由一系列环境变量决定的。因此,我们根据培养实验的结果,建立了一个 MOX 经验模型,其中纳入了主要的环境驱动因素,包括温度、CH、总磷和溶解氧(O)浓度。我们发现,在所研究的热带河流网络中,MOX(活化能:0.66 ± 0.18 eV)对温度的依赖性低于沉积物甲烷生成(0.71 ± 0.21 eV)对温度的依赖性。此外,我们观察到 O 浓度与 MOX 之间存在非线性关系,最高 MOX 发生率为 135 μmol Ol,高于或低于这一 "最佳 O "浓度时,MOX 发生率呈逐渐下降趋势。我们的研究结果表明,与甲烷发生相比,MOX 的温度响应相对较低,加上有机污染导致的 O 浓度下降,可能会导致东南亚热带河流的 CH 排放增加。由于在常规的 CH 监测项目中,CH 氧化率的估算往往被忽视,因此本文建立的模型可能有助于将 MOX 氧化率纳入基于过程的河流 CH 预算模型中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Environmental determinants of aerobic methane oxidation in a tropical river network

Aerobic methane oxidation (MOX) significantly reduces methane (CH4) emissions from inland water bodies and is, therefore, an important determinant of global CH4 budget. Yet, the magnitude and controls of MOX rates in rivers – a quantitatively significant natural source of atmospheric CH4 – are poorly constrained. Here, we conducted a series of incubation experiments to understand the magnitude and environmental controls of MOX rates in tropical fluvial systems. We observed a large variability in MOX rate (0.03 - 3.45 μmol l-1d-1) shaped by a suit of environmental variables. Accordingly, we developed an empirical model for MOX that incorporate key environmental drivers, including temperature, CH4, total phosphorus, and dissolved oxygen (O2) concentrations, based on the results of our incubation experiments. We show that temperature dependency of MOX (activation energy: 0.66 ± 0.18 eV) is lower than that of sediment methanogenesis (0.71 ± 0.21 eV) in the studied tropical fluvial network. Furthermore, we observed a non-linear relationship between O2 concentration and MOX, with the highest MOX rate occuring ∼135 μmol O2l-1, above or below this “optimal O2” concentration, MOX rate shows a gradual decline. Together, our results suggest that the relatively lower temperature response of MOX compared to methanogenesis along with the projected decrease of O2 concentration due to organic pollution may cause elevated CH4 emission from tropical southeast Asian rivers. Since estimation of CH4 oxidation is often neglected in routine CH4 monitoring programs, the model developed here may help to integrate MOX rate into process-based models for fluvial CH4 budget.

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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
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.
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