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首页> 外文期刊>International Journal of Environment and Pollution >An investigation on correlation between traffic and climate variables with the amount of SO_2 and NO_2 pollutants and estimation of their emission using regression modelling analysis method (case study: Mazandaran - Iran)
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An investigation on correlation between traffic and climate variables with the amount of SO_2 and NO_2 pollutants and estimation of their emission using regression modelling analysis method (case study: Mazandaran - Iran)

机译：使用回归模型分析方法研究交通和气候变量与SO_2和NO_2污染物的量之间的相关性并估算排放量（案例研究：Mazandaran-伊朗）

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摘要

Nowadays, one of the main reasons that contribute towards the worsening of air pollution is the growing expansion of transportation. The necessity of managing and controlling the air pollution by carrying out a scientific research and applying numerical methods to maintain a stable system is undeniable. In this research, the analysis and modelling of SO_2 and NO_2 pollutants were studied. The parameters that influenced the concentration of the pollutants were determined in accordance with the traffic (the amount of traffic and speed), and climate (precipitation, humidity, temperature and wind velocity) and their relationship was investigated by regression modelling analysis (using SPSS 16 software), then, to estimate the amount of these pollutants in the future years a mathematical model was introduced. As a result, the amount of meaningfulness of regression was equal to 95% and the amount of participation of data in the model was equal to 91.5%. Currently, this model has proven to be successful.
机译：如今，导致空气污染恶化的主要原因之一是交通运输的增长。不可否认，必须通过科学研究和采用数值方法来维持稳定的系统来管理和控制空气污染。本研究对SO_2和NO_2污染物的分析和建模进行了研究。根据交通量（交通量和速度）和气候（降水，湿度，温度和风速）确定影响污染物浓度的参数，并通过回归模型分析（使用SPSS 16）研究它们之间的关系。软件），然后，为了估算未来几年中这些污染物的数量，引入了数学模型。结果，回归的有意义程度等于95％，模型中数据的参与程度等于91.5％。目前，该模型已被证明是成功的。

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