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Stubble burn area estimation and its impact on ambient air quality of Patiala Ludhiana district Punjab India

机译:印度旁遮普邦Patiala和Ludhiana区的发茬燃烧面积估计及其对周围空气质量的影响

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摘要

Stubble burning during October and November, results in the extensive formation of smoke cloud over the Punjab region, and maybe one of the main reasons behind the increase in air pollution levels in these areas. The manual detection and estimation are tedious, lengthy and unpractical, so several researchers have been using remote sensing and GIS technique to estimate stubble burn areas and forest fires. Thus, in the present study, an attempt has been made to detect and estimate the stubble burn area. Landsat 8 OLI images are used to detect the stubble burn area for the year 2014-18 for Patiala and Ludhiana, which are major rice producing districts of Punjab. Normalize Burn Ratio (NBR) index have been used to determine the burned area in an image using a statistical threshold technique (2σ approach). The results have been validated using available as well as collected Ground Control Points (GCPs) and accuracy assessment has been conducted by generating an error matrix. It has been estimated that the stubble burn area was reduced by 32% and 40% during the study period for Patiala and Ludhiana regions, respectively. The monthly variation for various pollutants (RSPM, NO and SO ) during the study period has also been studied and analyzed. The distinct increase in pollutant levels has been observed during each stubble burning period. The results also indicate that the amount of emitted RSPM and NO was higher than the emitted SO during stubble burning. The wind rose diagrams have also been plotted.
机译:10月和11月燃烧的残茬会导致旁遮普地区形成大量烟雾云,这可能是这些地区空气污染水平上升的主要原因之一。手动检测和估算是繁琐,冗长且不切实际的,因此,一些研究人员一直在使用遥感和GIS技术估算麦茬烧伤面积和森林火灾。因此,在本研究中,已经尝试检测和估计残茬燃烧面积。 Landsat 8 OLI图像用于检测旁遮普省的主要水稻产区Patiala和Ludhiana的2014-18年发茬燃烧面积。归一化刻录率(NBR)索引已用于使用统计阈值技术(2σ方法)确定图像中的刻录区域。已使用可用的和收集的地面控制点(GCP)对结果进行了验证,并且通过生成误差矩阵进行了准确性评估。据估计,在研究期间,Patiala和Ludhiana地区的麦茬燃烧面积分别减少了32%和40%。还研究了分析期内各种污染物(RSPM,NO和SO)的月变化。在每个残茬燃烧期都观察到污染物水平的明显增加。结果还表明,在残茬燃烧过程中,RSPM和NO的排放量高于SO。还绘制了风玫瑰图。

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