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Mitigation of PM2.5 and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period

机译:Delhi中PM2.5和臭氧污染的减轻:季风前期敏感性研究

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Fine particulate matter?(PM2.5) and surface ozone?(O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model?(WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100000?emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region?(NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50%) would reduce PM2.5 by 15%–20% but lead to a 20%–25% increase in O3. However, we show that reducing NCR regional emissions by 25%–30% at the same time would further reduce PM2.5 by 5%–10% in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.
机译:细颗粒物质?(PM2.5)和表面臭氧?(o3)是德里等大型空气污染物,但合适的缓解策略的设计是具有挑战性的。减少PM2.5的一些策略可以具有增加O3的显着副作用。在这里,我们展示了一种用于调查Delhi中PM2.5和O3对PM2.5和O3对PM2.5和O3的影响的数值框架。我们使用高斯流程仿真来为区域空气质量模型产生计算有效的代理?(WRF-Chem)。这使我们能够进行全局敏感性分析,以确定空气污染的主要来源,并产生基于排放部门的污染物响应措施,以告知缓解政策发展。基于100000多个?仿真在季风前期(高峰季节),我们的全球敏感性分析表明,德里市地区的当地交通排放以及国家资本区域排放的区域运输?(NCR)周围德里是影响德里PM2.5和O3的主导因素。它们在白天共同控制O3峰值和PM2.5浓度。区域交通们在夜间提供约80%的PM2.5变异。仅减少德里的交通排放(例如50%)将减少PM2.5减少15%-20%,但o3导致o3增加20%-25%。但是,我们表明,同时将NCR区域排放量减少25%-30%将在德里进一步减少5%-10%,避免O3增加。本研究提供了科学证据,支持对地方和区域规模对照的联合协调,以实现PM2.5的有效减少,同时最大限度地降低德里o3增加的风险。
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