[海口臭氧度统计预测模型的建立和有效评估]
Chuan-Bo Fu1,2, Jian-Xing Lin3, Jia-Xiang Tang3
1Hainan Institute of Meteorological Science, Haikou 570203, China.
Huan jing ke xue= Huanjing kexue
|April 17, 2024
概括
这项研究开发了海口8小时平均臭氧 (O3-8h) 度的预测模型. 英国石油公司的神经网络模型表现最好,准确地捕捉季节性变化和污染水平.
科学领域:
- 大气化学和物理大气化学和物理
- 环境科学与工程环境科学与工程
- 数据科学和机器学习
背景情况:
- 臭氧 (O3) 是一个重要的空气污染物,对人类健康和生态系统产生不利影响.
- 准确预测8小时平均臭氧 (O3-8h) 度对于空气质量管理至关重要.
- 现有的预测模型可能需要改进,以考虑复杂的气象和地理因素.
研究的目的:
- 为了确定海口O3-8h度的关键气象预测指标.
- 构建和评估用于O3-8h预测的多重线性回归 (MLR),支持向量机 (SVM) 和BP神经网络 (BPNN) 模型.
- 评估这些模型在捕捉季节变化和不同污染水平方面的表现.
主要方法:
- 利用海口的O3度数据和2015-2020年ERA5再分析数据来选择15个关键预测因素.
- 开发了MLR,SVM和BPNN模型来预测O3-8h度.
- 使用相关系数,根平均平方误差 (RMSE) 和真实技能统计 (TS) 评分来评估模型性能.
主要成果:
- 相对湿度 (RH1000),风向 (WD1000) 和南部风 (v875) 与O3-8h有显著的相关性.
- 这三种模型都成功预测了季节性O3-8h变化,冬季度更高.
- BPNN模型实现了最低的RMSE (22.29μg·m-3) 和最高的相关系数 (0.733),超过了SVM (0.724) 和MLR (0.591).
结论:
- 与SVM和MLR相比,BPNN模型在预测海口O3-8h度方面表现出更高的准确性.
- 开发的模型有效地预测了季节性臭氧变化,对于较轻的污染水平,性能得到了改进.
- 湿度和风力等主要气象因素显著影响O3-8h水平,为空气质量预报提供了宝贵的见解.
更多相关视频
09:46Production and Measurement of Organic Particulate Matter in the Harvard Environmental Chamber
Published on: November 18, 2018
7.3K
10:25Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
Published on: June 28, 2016
10.6K
相关概念视频
Hess's Law
45.1K
There are two ways to determine the amount of heat involved in a chemical change: measure it experimentally, or calculate it from other experimentally determined enthalpy changes. Some reactions are difficult, if not impossible, to investigate and make accurate measurements for experimentally. And even when a reaction is not hard to perform or measure, it is convenient to be able to determine the heat involved in a reaction without having to perform an experiment.
45.1K
Precipitation and Co-precipitation
1.8K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.8K
Measurement of Air Content in Concrete
143
Air content measurement in concrete is critical for ensuring structural integrity and durability of concrete structures, especially in environments prone to severe weather conditions. Accurate air content analysis optimizes concrete's resistance to freeze-thaw cycles and enhances its workability and strength. Several methods are standardized under ASTM guidelines to measure the air content in fresh concrete, each suitable for different concrete types and conditions.
The pressure method,...
The pressure method,...
143
Regression Analysis
5.7K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.7K
Precipitation Titration Curve: Analysis
1.1K
The precipitation titration curve demonstrates the change in concentration of one reactant with the volume of titrant added. During the titration of chloride ions with silver nitrate, the precipitation titration curve is divided into three regions: before, at, and after the equivalence point. Before the equivalence point, low redissolution of the sparingly soluble silver chloride precipitate gives a low silver ion concentration. However, in the second region, representing the equivalence point,...
1.1K
Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
