Spatial and temporal variability of greenhouse gas ebullition from temperate freshwater fish ponds

温室气体 甲烷 温带气候 环境科学 二氧化碳 大气科学 空间变异性 生态学 生物 数学 统计 地质学
作者
Carolin Waldemer,Matthias Koschorreck
出处
期刊:Aquaculture [Elsevier]
卷期号:574: 739656-739656 被引量:16
标识
DOI:10.1016/j.aquaculture.2023.739656
摘要

Fish ponds with their typically high carbon and nutrient inputs are relevant sources of greenhouse gases. However, not much is known about gas bubble emissions (ebullition) and their high spatiotemporal variability. This is the first study which quantified diffusive and ebullitive greenhouse gas emissions from temperate fish ponds. To improve greenhouse gas estimates, we investigated the diurnal and spatial variability of diffusive and ebullitive fluxes in 12 extensively to semi-intensively managed fish ponds near Bautzen, Germany. Emissions differed greatly between the different ponds but methane was consistently the predominant greenhouse gas. The feeding sites were hotspots with one order of magnitude higher ebullition rates compared to other parts of the ponds. At these hotspots, ebullitive fluxes of up to 38 L/m2d were measured with a mean bubble methane content of 79%, corresponding to a methane flux of 1.24 mol/m2d. Methane accounted for 90% of the global warming potential in one fish pond but carbon dioxide emissions of up to 242 mmol/m2d at the feeding sites were also significant. Nitrous oxide fluxes, in contrast, were low with 5 ± 9 μmol/m2d. Greenhouse gas ebullition decreased exponentially along a transect from the feeding site into the pond and showed some diurnal fluctuations. While diffusion was higher during night, ebullition rates increased in the morning, presumably caused by higher benthivorous fish activity. Our results highlight the potential of temperate fish ponds as significant greenhouse gas sources and ebullition as a significant pathway. For robust quantification, both small scale spatial and temporal variability as well as the hotspot of the feeding area must be considered.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
哈哈哈完成签到,获得积分10
1秒前
1秒前
简单如容发布了新的文献求助10
1秒前
NNNuow完成签到,获得积分10
2秒前
2秒前
wind发布了新的文献求助10
3秒前
西出阳关发布了新的文献求助10
3秒前
嗯嗯完成签到 ,获得积分10
3秒前
李婷婷发布了新的文献求助30
3秒前
匿天完成签到,获得积分20
3秒前
礼乐发布了新的文献求助10
3秒前
3秒前
4秒前
温茶发布了新的文献求助10
4秒前
5秒前
5秒前
闪闪羊完成签到 ,获得积分10
5秒前
5秒前
DXDXJX发布了新的文献求助10
5秒前
5秒前
罗_应助明理的绿柏采纳,获得10
5秒前
shi hui应助清风采纳,获得10
5秒前
星空办公室完成签到,获得积分10
6秒前
BB发布了新的文献求助10
6秒前
6秒前
月月发布了新的文献求助10
7秒前
km完成签到,获得积分10
7秒前
7秒前
Selenge发布了新的文献求助10
7秒前
充电宝应助Millian采纳,获得10
8秒前
小刺猬xcw完成签到,获得积分10
8秒前
9秒前
9秒前
安详语琴完成签到,获得积分10
10秒前
忧郁难胜发布了新的文献求助10
10秒前
10秒前
徐若楠发布了新的文献求助10
10秒前
10秒前
11秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Handbook on Inequality and Social Capital 800
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3546888
求助须知:如何正确求助?哪些是违规求助? 3123917
关于积分的说明 9357332
捐赠科研通 2822504
什么是DOI,文献DOI怎么找? 1551513
邀请新用户注册赠送积分活动 723546
科研通“疑难数据库(出版商)”最低求助积分说明 713791