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首页> 外文期刊>Nature environment and pollution technology >A GIS-Based Methodology to Determine Effect of Vehicular Pollution at Ward Level: Case Study of Jaipur City
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A GIS-Based Methodology to Determine Effect of Vehicular Pollution at Ward Level: Case Study of Jaipur City

机译:基于GIS的方法,以确定病房污染在病房污染的影响:斋浦尔市案例研究

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To determine appropriate measures to reduce air pollution in any urban city, the first essential requirement is to estimate the spatial distribution of air pollution parameters in that area. In absence of air monitoring stations, alternative methods are required for the same. In the present work, a GISbased methodology is presented to estimate the level of NO2 based on the road density of the road network of different categories of roads. Road network GIS layer and measured levels of the average value of NO2 for the year 2019 at 12 air pollution monitoring stations of Jaipur city are used to develop a large number of possible linear regression models for estimation of NO2 values based on road density values. Akaike Information Criterion (AIC) and adjusted r2 values are used to evaluate and arrive at the best-fitted model. Values from the cities of Jodhpur and Kota are used to validate the model. Using this model, NO2 levels are determined at 91 wards of Jaipur city and the output is compared with the similar map derived based on interpolation of NO2 values at the 12 monitoring stations. It is concluded that the methodology developed in this study generates better estimates of NO2 at the ward levels.
机译:为确定减少任何城市城市空气污染的适当措施,第一个基本要求是估计该地区空气污染参数的空间分布。在没有空气监测站的情况下,相同的替代方法是必需的。在目前的工作中,提出了一种基于不同类别的道路道路网络的道路密度来估计NO2水平的GISBASED方法。道路网GIS层和2019年NO2的平均值的测量水平在斋浦尔市的12个空气污染监测站,用于开发大量可能的线性回归模型,用于估计基于道路密度值的NO2值。 Akaike信息标准(AIC)和调整后的R2值用于评估并到达最佳拟合模型。来自焦门和kota城市的价值用于验证模型。使用此模型,NO2级别在斋浦尔市的91个病房中确定,并将输出与基于12个监测站的NO2值插值导出的类似地图进行比较。得出结论,本研究中开发的方法产生了在病房水平的NO2的更好估计。

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