HYSPLIT Modelling Approach for the Assessment of PM2.5 over Indian Subcontinent
Authors: Verma Rulan 
Published: March 2020

&lt;p&gt;Rulan Verma&lt;sup&gt;1&lt;/sup&gt;,Salim Alam&lt;sup&gt;2&lt;/sup&gt;,&amp;#160;William Bloss&lt;sup&gt;2&lt;/sup&gt;, Prashant Kumar&lt;sup&gt;3&lt;/sup&gt;, Mukesh Khare&lt;sup&gt;1*&lt;/sup&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;&amp;#160;1 &lt;/sup&gt;Department of Civil Engineering, Indian Institute of Technology Delhi, India&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;sup&gt;2 &lt;/sup&gt;School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom&lt;/p&gt;&lt;p&gt;&lt;sup&gt;3&lt;/sup&gt; Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, University of Surrey, Guilford, United Kingdom&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;mukeshk@civil.iitd.ac.in&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;ABSTRACT&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;The Delhi-National Capital Region of India is home to approximately 46 million people. With rapid development, this region is experiencing widespread urbanization and industrialization. It is expected to become the most populous region in the world by 2027 (World Population Prospects 2019, UN). With rapid growth, the region is facing severe challenges of air pollution. Delhi-NCR is amongst the most polluted regions in the world. PM&lt;sub&gt;2.5 &lt;/sub&gt;is recognized as a prominent pollutant in the region. Ambient air pollution is recognized as a class I carcinogen and is one of the highest risk factors for premature deaths worldwide.&amp;#160; Understanding the effects of local and global meteorology would help in the identification of source pathways and source areas of pollutant dispersion. This paper presents a methodology for modelling and assessment of PM&lt;sub&gt;2.5 &lt;/sub&gt;over the Indian subcontinent using NOAA&amp;#8217;s Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). To develop the approach, PM&lt;sub&gt;2.5&lt;/sub&gt; data collected over a period of 32 days at IIT Delhi supersite (28.54&amp;#176;N,77.19&amp;#176;E) were utilized.&amp;#160; PM&lt;sub&gt;2.5 &lt;/sub&gt;mass concentrations&amp;#160;were monitored using PM&lt;sub&gt;2.5&lt;/sub&gt; samplers and a TEOM (Tapered Element Oscillating Microbalance) monitor. Meteorological data were obtained through the Global Data Assimilation System (GDAS) which places observations into a gridded model space.770 air mass back trajectories were generated and clustered into mean trajectories using the cluster analysis function of HYSPLIT. PM&lt;sub&gt;2.5&lt;/sub&gt; monitored during winters (15/01/2018-15/02/2018) was correlated with clustered back trajectories to understand the effect of local and global meteorology. The time-series of PM&lt;sub&gt;2.5 &lt;/sub&gt;were correlated with different clusters to understand the impact of winds coming from different regions and heights. Major advection source pathways for PM&lt;sub&gt;2.5 &lt;/sub&gt;were identified. The study found that 59% of the time, PM&lt;sub&gt;2.5 &lt;/sub&gt;transport was affected by wind movements from north-west of supersite moving through Pakistan-Punjab-Haryana-supersite. During this period PM&lt;sub&gt;2.5 &lt;/sub&gt;concentration at supersite were 169&amp;#177;73 &amp;#956;g/m&lt;sup&gt;3&lt;/sup&gt;. The highest PM&lt;sub&gt;2.5 &lt;/sub&gt;concentration of 237&amp;#177;81 &amp;#956;g/m&lt;sup&gt;3 &lt;/sup&gt;were observed when the winds were recirculating locally. Wind roses produced using meteorological data obtained from &amp;#160;Indian Meteorological Department stations conforms with the wind flow in GDAS. This methodology can be utilized in other regions for quantifying the major source pathways and source areas for air pollutant dispersion. This understanding would help in framing hotspot and airshed based interventions and mitigation strategies to control air pollution.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;KEYWORDS: PM&lt;sub&gt;2.5&lt;/sub&gt;; AIR POLLUTION; HYSPLIT; MONITORING; DISPERSION; SOURCE PATHWAYS; METEOROLOGY; MODELLING; SOURCE REGIONS&lt;/p&gt;