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A Study on Effects of Weather, Vehicular Traffic and Other Sources of Particulate Air Pollution on the City of Delhi for the Year 2015

机译:2015年天气,车辆交通和其他微粒污染源对德里市的影响研究

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In the year 2014, WHO declared Delhi City as the worst polluted in the world. In December 2015, PM 2.5 levels in Delhi were at 295 microgram/m3 and PM10 levels were at 470 microgram/m3 resulting in Air Quality Index at a severely high 430-435. Air pollution is responsible for 10,000 to 30,000 deaths in Delhi every year. A critical convergence of public concern, policymaker attention, and academic contribution is now taking place to address this issue. Reducing emissions of PM2.5 not only has an immediate effect on air quality, but also mitigates near-term climate change and helps achieve food security. Data gathered over three year (2013-2015) on particulate air pollution PM 2.5 in Delhi reveals a systematic wave-like pattern each year. PM 2.5 rises and falls with rhythmic precision in winter and summer with a minimum range of values in the monsoon when the Delhi air is washed clean by rainfall. These waves of air pollution change are found to be nearly synchronous with a combination of weather factors, specifically ambient air temperature and dew point, modeled appropriately as a ‘weather index’. A near linear relationship is shown to exist between the air pollution (PM 2.5) level and the ‘weather index’ for the year 2015. So far, weather is not ascribed to be one of the primary reasons for unusually high particulate air pollution in Delhi, but merely a factor that influences air pollution. This study attempts to fill this gap Baseline Reference PM 2.5 measurements were obtained from published sources from a air quality monitoring sensor located in an elite, less densely populated locality near Delhi’s wooded Reserve Forest ridge, somewhat secluded from Delhi’s zones of high density traffic, industries and thermal power stations. Air quality measurements at this sensor location are routinely taken at hourly intervals throughout the year. The distance of the Reference Sensor from main sources of air pollution results in longer transport time from source to sensor, enabling the polluted air to be well modulated by weather. These weather-modulated measurements were compared with other reliable published data by the Government of India’s Central Pollution Monitoring Board from sensors at 10 other locations on the ground-level at kerb-sides of roads with high density vehicular traffic; and much closer to the commercialized and industrialized areas of the city. The street-located sensors record near instantaneous PM 2.5 measurements at the very starting place of air pollution so that the transport time interval required for deep modulation by weather may be presumed to be too short. Using the “weather index” property, theoretical values of air pollution, if there were no modulation by weather, were calculated from the Reference sensor values. These theoretical values are compared with aggregated experimental values of air pollution from sensor locations on the kerb-side of the roads so that were not modulated by weather. They are found to be in reasonably close (within 9%) agreement. Thus the validity of an exact relationship between PM 2.5 with the ‘weather factor’ determined by ambient air temperature and dew point is established ; and thereafter validated by measurements for seven different sources of air pollution at 10 locations in three seasons of year 2015: summer, monsoon and winter.
机译:2014年,世卫组织宣布德里市为世界上污染最严重的城市。 2015年12月,德里的PM 2.5浓度为295微克/立方米,PM10的浓度为470微克/立方米,导致空气质量指数达到430-435的极高水平。空气污染每年在德里造成10,000至30,000人死亡。解决这个问题的公众关注,决策者的关注和学术贡献的关键融合正在发生。减少PM2.5的排放不仅对空气质量有直接影响,而且可以减轻近期的气候变化并有助于实现粮食安全。过去三年(2013-2015)收集的关于德里空气中PM 2.5颗粒物污染的数据揭示了每年的系统波浪状模式。冬季和夏季,PM 2.5的上升和下降具有精确的节奏,当德里的空气被雨水冲洗干净时,季风中的PM 2.5最小。人们发现,这些空气污染变化浪潮几乎与各种天气因素(尤其是周围的空气温度和露点)的组合同步,并适当地建模为“天气指数”。事实证明,2015年的空气污染水平(PM 2.5)与“天气指数”之间存在近似线性关系。到目前为止,天气并没有归因于德里异常高的颗粒空气污染的主要原因之一,但仅仅是影响空气污染的一个因素。这项研究试图填补这一空白。基准参考PM 2.5测量值是从空气质量监测传感器的公开数据中获得的,该传感器位于德里树木繁茂的自然保护区附近一个人口稀少的精英地区,与新兴的高密度交通区,工业区隔离和火力发电厂。一年中,该传感器位置的空气质量测量通常按小时间隔进行。参考传感器与主要空气污染源之间的距离会导致从源到传感器的更长的运输时间,从而使受污染的空气能够被天气很好地调节。印度政府中央污染监测委员会将这些经过天气调节的测量结果与其他可靠的公开数据进行了比较,这些数据来自高密度车辆交通路边路边地面上其他10个位置的传感器;并且更靠近城市的商业化和工业化地区。位于街道上的传感器在空气污染的最开始的位置记录了近乎瞬时的PM 2.5测量值,因此可以推测天气进行深度调制所需的运输时间间隔太短。使用“天气指数”属性,如果没有通过天气进行调制,则可以从参考传感器值中计算出空气污染的理论值。将这些理论值与道路路边传感器位置的空气污染汇总实验值进行比较,从而不受天气影响。发现它们之间的关系相当合理(不超过9%)。因此,建立了PM 2.5与由周围空气温度和露点确定的“天气因素”之间精确关系的有效性;然后在2015年的三个季节(夏季,季风和冬季)对10个地点的7种不同的空气污染源进行了测量验证。

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