| 1. |
- Devaprasad, M., et al.
(författare)
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Characterization of paddy-residue burning derived carbonaceous aerosols using dual carbon isotopes
- 2023
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 864
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Tidskriftsartikel (refereegranskat)abstract
- A large scale paddy-residue burning (PRB) happens every year in the northwest Indo-Gangetic Plain (IGP) during the post-monsoon season, and winds transport pollutants from the source region up to the northern Indian Ocean affecting air quality of the IGP and marine region. In this study, day-night pairs of fine aerosol samples (n = 69) were collected during October–November over Patiala (30.2°N, 76.3°E, 250 m amsl), a site located in the source region of PRB. Carbonaceous aerosols (CA) were characterised using chemical species and dual carbon isotopes (13C and 14C) to estimate bio vs non-bio contributions and understand their characteristics. Percentage of bio fraction (fbio, estimated using 14C) in CA varied from 74 % to 87 % (avg: 80 ± 3) during days and 71 % to 96 % (avg: 85 ± 7 %) during nights. Further, the fbio was found to be better correlated with aerosol mass spectrometer derived f60 compare to levoglucosan (LG) or nssK+, suggesting f60 a useful proxy for PRB. The δ13C varied from −27.7 ‰ to −26.0 ‰ (avg: −27.0 ± 0.4 ‰) and − 28.7 ‰ to −26.4 ‰ (avg: −27.5 ± 0.7 ‰) during day and night, respectively. Measured δ13C of the samples was found to be more enriched than expected by 0.3 to 2.0 ‰, indicating the presence of aged CA also in Patiala even during PRB period. From fbio versus δ13C correlation, and from Miller-Trans plot, δ13C of PRB is found to be −28.9 ± 1.1 ‰, which also infers that Miller-Trans plot can be used to understand source isotopic signature in the absence of radiocarbon measurements in aerosols. Further, the characteristics ratios of organic carbon (OC) to elemental carbon (EC) (11.9 ± 4.1), LG to potassium (K+) (0.84 ± 0.15), OC/LG (19.7 ± 2.0) and K+/EC (0.75 ± 0.27) were calculated by considering samples with fbio higher than 0.90, which can be used for source apportionment studies. Such studies are crucial in assessing the effects of PRB on regional air quality and climate.
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| 2. |
- Kumar, Varun, et al.
(författare)
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Highly time-resolved chemical speciation and source apportionment of organic aerosol components in Delhi, India, using extractive electrospray ionization mass spectrometry
- 2022
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 22:11, s. 7739-7761
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winter. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the total AMS SOA (i.e. MO-OOA + LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major SOA component during the daytime, with a 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during the nighttime. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during the daytime and 36.1 % of total SOA mass (11.2 % of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass (11.7 % and 8.5 % of total OA mass), respectively, during the daytime and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass), respectively, during the nighttime. A simple dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the daytime suggests an increased OA toxicity and health-related consequences for the general public.
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| 3. |
- Singh, Atinderpal, et al.
(författare)
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Wintertime oxidative potential of PM2.5 over a big urban city in the central Indo-Gangetic Plain
- 2023
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Ingår i: Science of the Total Environment. - 0048-9697 .- 1879-1026. ; 905
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Tidskriftsartikel (refereegranskat)abstract
- Indo-Gangetic Plain (IGP) experiences a heavy load of particulate pollution impacting the 9 % of the global population living in this region. The present study examines the dithiothreitol (DTT) assay-based oxidative potential (OP) of PM2.5 and the major sources responsible for the observed OP over the central IGP (Kanpur) during winter. The volume normalized OP (OPV) of PM2.5 varied from 2.7 to 10 nmol DTT min(-1) m(-3) (5.5 +/- 1.5) and mass normalized OP (OPM) of PM2.5 varied from 19 to 58 pmol DTT min(-1) mu g(-1) (34 +/- 8.0), respectively. Major sources of PM2.5 were identified using the positive matrix factorization (PMF) and the contribution of these sources to observed OP was estimated through multivariate linear regression of OPv with PMF-resolved factors. Although the PM2.5 mass was dominated by secondary aerosols (SA, 28 %), followed by crustal dust (CD, 24 %), resuspended fine dust (RFD, 14 %), traffic emissions (TE, 8 %), industrial emissions (IE, 17 %), and trash burning (TB, 9 %), their proportionate contribution to OP (except SA) was different likely due to differences in redox properties of chemical species coming from these sources. The SA showed the highest contribution (23 %) to observed OP, followed by RFD (19 %), IE (8 %), TE & TB (5 %), CD (4 %), and others (36 %). Our results highlight the significance of determining the chemical composition of particulates along with their mass concentrations for a better understanding of the relationship between PM and health impacts. Such studies are still lacking in the literature, and these results have direct implications for making better mitigation strategies for healthier air quality.
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| 4. |
- Swain, Sidhartha Sekhar, et al.
(författare)
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Proportional impact prediction model of coating material on nitrate leaching of slow-release Urea Super Granules (USG) using machine learning and RSM technique
- 2024
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- An accurate assessment of nitrate leaching is important for efficient fertiliser utilisation and groundwater pollution reduction. However, past studies could not efficiently model nitrate leaching due to utilisation of conventional algorithms. To address the issue, the current research employed advanced machine learning algorithms, viz., Support Vector Machine, Artificial Neural Network, Random Forest, M5 Tree (M5P), Reduced Error Pruning Tree (REPTree) and Response Surface Methodology (RSM) to predict and optimize nitrate leaching. In this study, Urea Super Granules (USG) with three different coatings were used for the experiment in the soil columns, containing 1 kg soil with fertiliser placed in between. Statistical parameters, namely correlation coefficient, Mean Absolute Error, Willmott index, Root Mean Square Error and Nash–Sutcliffe efficiency were used to evaluate the performance of the ML techniques. In addition, a comparison was made in the test set among the machine learning models in which, RSM outperformed the rest of the models irrespective of coating type. Neem oil/ Acacia oil(ml): clay/sulfer (g): age (days) for minimum nitrate leaching was found to be 2.61: 1.67: 2.4 for coating of USG with bentonite clay and neem oil without heating, 2.18: 2: 1 for bentonite clay and neem oil with heating and 1.69: 1.64: 2.18 for coating USG with sulfer and acacia oil. The research would provide guidelines to researchers and policymakers to select the appropriate tool for precise prediction of nitrate leaching, which would optimise the yield and the benefit–cost ratio.
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