在印度东部的一个热带河流中评估水质和污染源分配:使用多变量统计工具和APCS-MLR受体模型进行的一项研究
Pratyush Ghosh1,2, Ashis Kumar Panigrahi3
1Department of Zoology, Chandernagore College, Hooghly, West Bengal, India. pratyushghosh2023@gmail.com.
Environmental monitoring and assessment
|August 30, 2024
概括
印度蒙德斯瓦里河的水质因污染而恶化,特别是在季风前的季节. 尽管如此,河水仍然适合用于灌目的.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 河流生态 河流生态
背景情况:
- 印度东部的蒙德斯瓦里河因人类活动而导致水质严重恶化.
- 广泛的农业用水需要评估河流是否适合灌.
研究的目的:
- 综合评估蒙德斯瓦里河目前的污染状况.
- 为了确定其水是否适合用于农业灌.
主要方法:
- 在两年 (2020-2022) 期间,每月在四个地点对17个参数进行水质监测.
- 应用主要组件分析/因子分析 (PCA/FA) 和绝对主要组件分数多重线性回归 (APCS-MLR) 受体建模,以确定污染源.
主要成果:
- 在季风前的季节,水质最恶化,SP3的污染水平最高 (BOD:5.36 mg/L,COD:44.72 mg/L).
- 观察到水质参数存在显著的空间和季节性变化 (P < 0.05).
- PCA/FA确定了四个主要污染源 (自然气候,家用废水,农业下水),占差异的81.5%;APCS-MLR证实了家用和农业排放是主要贡献者.
结论:
- 尽管受到污染,但蒙德斯瓦里河的水质指标仍在灌可接受的范围内.
- 这些发现可以为河流的生态恢复和管理制定可持续战略.
相关概念视频
Multiple Regression
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Quality of Water
In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
Testing Water Quality
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...


