A203-02
Source apportionment of regional aerosols and spatial variability from The 2nd Nepal Ambient Measurement and Source Testing Experiment [NAMaSTE]-2 in the Kathmandu valley, Nepal
Abstract:
The mean PM2.5 at these sites across the campaign is 65.2 µg m-3, exceeding the 24-hour WHO threshold of 25 µg m-3. Overnight PM2.5 concentrations increase up to 379.8 µg m-3 due to confinement from temperature inversions. Strong afternoon westerly winds are the main transport out of the valley , diluting PM2.5 concentrations to below 50 µg m-3.
The first site, Dhulikhel, along the valley rim, has minimal urban influence. Mean PM1 here is 47.9 µg m-3 ranging from 10.3 to 148.3 µg m-3. PM1 is composed of 54% Organic Aerosol (OA), 15% Black Carbon (BC), 5% Brown Carbon (BrC), 8% SO4, 10% NO3, 6% NH4, 2% Chl. PMF analysis on the OA factors this fraction into 57% oxygenated OA (OOA), 15% trash burning (TBOA), and 10% from local sulfate containing OA (LSOA), the remainder is biomass burning and hydrocarbon like OA (BBOA, HOA).
A 2nd site, Ratnapark, is at the busiest intersection in the city center. The mean PM1 is 102.2 µg m-3 ranging from 7.4 to 323.2 µg m-3. PM1 composition from AMS measurements are 45% OA, 1% BrC, 26% BC, 8% SO4, 7% NO3, 7% NH4, 7% Chl. OOA from PMF makes up a smaller fraction of the OA at Ratnapark, 34%, with 24% from HOA, and 18% from BBOA. TBOA makes up 14% of OA, and LSOA only 10%. The fraction of BBOA and HOA at this site is twice that of Dhulikhel.
The 3rd site, Lalitpur, a suburban site, has direct influence from industry. The mean PM1 at this site is 105.9 µg m-3 ranging from 14.2 to 369.4 µg m-3. PM1 is dominated by OA, similar to other sites, with composition proportionally 45% OA, 22% BC, 13% SO4, 9% NO3, 8% NH4, 4% Chl. OOA is 40% of OA at Lalitpur, with HOA 24%, and LSOA a further 17%. BBOA is 13% here, and TBOA only 6%. Primary emission of sulfates from coal combustion has a 60% greater impact at Lalitpur compared to other sites.
Differences in aerosol composition at each location suggests that multi-site measurements are essential to understand spatial variability and air quality in areas with sparse measurement infrastructure.