DOI: 10.5061/dryad.280gb5mvx
title: Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India

description: The oxidative potential (OP) of particulate matter (PM) is a major driver
 of PM-associated health effects. In India, the emission sources defining
 PM-OP, and their local/regional nature, have yet to be established. To
 address this gap, we determined the geographical origin, sources of PM,
 and its OP at five Indo-Gangetic Plain (IGP) sites inside and outside
 Delhi. Our findings reveal that although uniformly high PM concentrations
 were recorded across the entire region, local emission sources and
 formation processes dominate PM pollution. PM-OP is overwhelmingly driven
 by OA from incomplete combustion of biomass and fossil fuels, including
 traffic. These findings suggest that addressing local inefficient
 combustion processes can effectively mitigate PM health exposure in
 Northern India.
description: The data of five main figures is provided. Raw
 data used in the study is also provided. The data was
 collected using different advanced mass spectrometric techniques and
 relevant softwares were used to analyze the data. Details are provided in
 the materials and methods section.
description: # Local incomplete combustion emissions define the PM2.5 oxidative
 potential in Northern India Main figures: Fig. 1. Summary of fine
 particulate matter (PM2.5) chemical composition and source contributions. 
 Figure 1b. The averaged relative mass contribution of different chemical
 constituents (here, EC is elemental carbon and OA is organic aerosols) to
 PM2.5 mass are shown for warm and cold period. Next, we represent the
 contribution of OA sources (CPOA- Cold season primary organic aerosol,
 BBOA- Biomass burning oragnic aerosol, UOOA- Urban oxygenated organic
 aerosol, COOA- cold oxygenated organic aerosol and HOA- Hydrocarbon-like
 organic aerosol) to OA. Further, contribution of different OA and
 elemental sources to oxidative potential (AAv, DTTv and DCFHv) are shown.
 Figure 1c. The non-fossil fraction of diffferent OA sources, OA and EC in
 warm and cold period are shown. Fig. 2. Spatial and temporal variation in
 fine particulate matter (PM2.5) and its species. The right hand panel
 shows site-wise PM2.5, Nitrate, Sulfate, Ammonium, Chloride, trace
 elements and EC mass anomalies (averaged +/- 1 standard deviation) over
 the period of Jan- May, 2018. The right hand side panel shows site-wise
 10th, 25th, 75th and 95th percentile and median values of same parameters
 (as in right panel). Fig. 3. Spatial and temporal variation in organic
 aerosol (OA) sources and oxidative potential (OP). The right hand panel
 shows site-wise source-specific OAs (COOA, UOOA, CPOA, BBOA and HOA) mass
 and OP (AAv, DTTv and DCFHv) anomalies (averaged +/- 1 standard deviation)
 over the period of Jan- May, 2018. The right hand side panel shows
 site-wise 10th, 25th, 75th and 95th percentile and median values of same
 parameters (as in right panel). Fig. 4. Near-molecular level organic
 aerosol (OA) source composition. Figure 4a,b,d,g. It represents the carbon
 numer plot for BBOA, showing the relative intensity of dominant species
 containing CHNO and CHO in the specified OA source. These intensities are
 plotted against the number of carbon atoms (Nc) for different H:C ratios.
 Figure 4 c,e,h. It represents the mass defect plot for CHNO containing
 species for different OA sources (CPOA, COOA and UOOA). The colors of the
 marker represent the number of carbon atoms and marker size represents
 relative signal intensity. Figure 4 f,i. It represents the mass defect
 plot for CHO containing species for different OA sources (COOA and UOOA).
 The colors of the marker represent the number of carbon atoms and marker
 size represents relative signal intensity. Fig. 5. Fig. 5: Drivers of fine
 particulate matter (PM2.5) and its oxidative potential (OPv). Figure 5a.
 Spatially averaged relative contribution of different species such as
 inorganics, source specific OAs and elements to PM2.5 mass concentration
 and oxidative potential (OPv, DTTv and DCFHv). Figure 5b,c,d. The
 comparison of PM2.5 mass and OPv in five different regions of the world
 (India, China, Spain, France and Switzerland). The
 "India_Delhi2018_Rawdata.xlsx" contains the following: * PM2.5
 chemical composition sheet contains PM2.5 mass concentration, WSOC, OC,
 EC, inorganics (SO4, NO3, Cl - anions, Na, K - cations), inorganic carbon,
 TC_f (TC fossil), TC)_nf (TC non-fossil), EC_f (EC fossil), EC_nf (EC
 non-fossil), Oxidative potential (mass normalized:
 nmolDTT.min-1.µg-1,nmolAA.min-1.µg-1,DCFH nmol [H202] equiv per µg; Volume
 normalized: nmolDTT.min-1.m-3,nmolAA.min-1.m-3, nmol [H202] equiv.m-3
 air), targeted Organic marker compounds measured by LC-MS and GC-MS,
 elements measured by ICP-MS along with sampling site details and date of
 sampling. * The sources sheet contains mass concentration of OA and
 elemental sources (HOA,BBOA,CPOA,COOA,UOOA,Cu-Cd rich,Pd-Sn-Sb rich and K+
 -Na+ rich). * The AMS PMF input sheet contains signal intensity data and
 error matrix of all fitted ions (m/z) measured by LTof-AMS. * The EESI PMF
 input sheet contains signal intensity data and error matrix of all fitted
 ions (m/z) measured by EESI-ToF-MS. The cells containing "n/a"
 can be read as not applicable.