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Atmospheric Dispersion of PM2.5 Precursor Gases from Two Major Thermal Power Plants in Andhra Pradesh, India

机译:印度安得拉邦两个主要火电厂的PM2.5前驱体气体的大气弥散

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Fine particulate matter (PM2.5) predominantly comprises sulphates and nitrates, which results from sulphur dioxide (SO2) and nitrogen oxide (NOx) gases that are emanated from excessive industrial activities and transport systems. PM2.5 is known to affect respiratory health in humans. Coal-fired thermal power plants are a major source of SO2 and NOx gases. Evaluation of the dispersion characteristics of these precursor gases from the power plants would help understand the vulnerability. Meteorological conditions that prevail over the region would influence the dispersion characteristics. In this study, dispersion of SO2 and NO from two major coal-fired thermal power plants in Andhra Pradesh, India have been studied using an integrated modeling approach of the Advanced Research Weather Research & Forecasting (ARW) model and Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Meteorological conditions are obtained at 3-km resolution using the ARW model and dispersions of SO2 and NO is computed using the HYSPLIT model for the four seasons of winter, summer, monsoon and post-monsoon. Forward trajectories produced by the HYSPLIT model show diurnal variations and dispersion patterns show seasonal variations indicating the influence of meteorological conditions. Dispersion characteristics show high dispersion in winter due to calm and stable atmospheric conditions to insignificant in summer season due to stronger winds and higher atmospheric instability. The study establishes the usefulness of integrated meteorological and dispersion models for the evaluation of pollutant dispersion.
机译:细颗粒物(PM2.5)主要包含硫酸盐和硝酸盐,这是由于过度的工业活动和运输系统产生的二氧化硫(SO2)和氮氧化物(NOx)气体产生的。已知PM2.5会影响人类呼吸系统健康。燃煤火力发电厂是SO2和NOx气体的主要来源。对来自发电厂的这些前体气体的扩散特性进行评估将有助于理解该漏洞。在该地区盛行的气象条件将影响散布特性。在这项研究中,使用高级研究天气研究与预报(ARW)模型和混合单颗粒拉格朗日综合模型的综合建模方法,研究了印度安得拉邦两个主要燃煤火力发电厂的SO2和NO的扩散情况。轨迹(HYSPLIT)模型。使用ARW模型以3 km的分辨率获得气象条件,并使用HYSPLIT模型计算冬季,夏季,季风和季风后四个季节的SO2和NO弥散。由HYSPLIT模型产生的前向轨迹显示出日变化,而散布图则显示出季节性变化,表明了气象条件的影响。色散特性表明,由于大气条件稳定和稳定,冬季的色散较高,而夏季由于风强和大气不稳定性较高,因此散度很小。该研究建立了综合的气象和扩散模型对污染物扩散评估的有用性。

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