Modelling carbon dioxide gas emission from Notopterus chitala fish ponds by stella software

Van So Nguyen, Anh Tuan Le
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Abstract

The rapid development of the areas of ​​Notopterus chitala fish ponds in Hau Giang province in recent years has raised a question about greenhouse gas emissions, in the form of total carbon dioxide equivalents (CO2e). There are many parameters that affect greenhouse gas emissions in a fish pond, such as amount of feed, dissolved oxygen (DO), chemical oxygen demand (COD) in the water, pH, water temperature, windy velocity and sunlight reaching the pond surface. In this study, a System Thinking, Experimental Learning Laboratory with Animation, shortly called as Stella is applied as a visual programming language for system dynamics modelling in order to find the relationship between simulated CO2 and measured CO2 in Notopterus chitala fish pond. Three ponds were used for measuring average pH, temperature, feeds, DO, COD and phytoplankton inside the ponds while windy speed and light intensity data were collected from a Weather Station nearby. The results of model calibration and validation showed that the Stella 8.0 can be used as predictable tool for the change in time of CO2 emission during 240 days of fishing. Model can help fishing farmers to adjust the quantity of feeds and control the water quality in their Notopterus chitala fish ponds to reduce greenhouse gas emissions appropriately.
利用 stella 软件模拟鳙鱼池塘的二氧化碳气体排放
近年来,后江省鳙鱼池塘面积的快速发展引发了以总二氧化碳当量(CO2e)为形式的温室气体排放问题。影响鱼塘温室气体排放的参数有很多,如饲料量、溶解氧 (DO)、水中化学需氧量 (COD)、pH 值、水温、风速和到达池塘表面的阳光。在本研究中,应用了系统思维、带动画的实验学习实验室(简称为 Stella)作为系统动力学建模的可视化编程语言,以找出鳙鱼池塘中模拟的二氧化碳与测量的二氧化碳之间的关系。使用三个池塘测量池塘内的平均 pH 值、温度、饲料、溶解氧、化学需氧量和浮游植物,同时从附近的气象站收集风速和光照强度数据。模型校准和验证结果表明,Stella 8.0 可用作预测 240 天捕鱼过程中二氧化碳排放时间变化的工具。该模型可帮助渔业养殖户调整饲料投放量和控制鱼塘水质,从而适当减少温室气体排放。
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