Source Apportionment of PM10 Over Three Tropical Urban Atmospheres at Indo-Gangetic Plain of India: An Approach Using Different Receptor Models

Uncovering sources, distribution, and seasonal patterns of trace element deposition: the elemental puzzle of the western Himalayas

The transport and deposition of atmospheric pollutants in the Himalayas have a adverse impact on the climate, cryosphere, ecosystem, and monsoon patterns. Unfortunately, there is a insufficiency of data on trace element concentrations and behaviors in the high-altitude Himalayan region, leading to limited research in this area. This study presents a comprehensive and detailed comprehension of trace element deposition, its spatial distribution, seasonal variations, and anthropogenic signals in the high-altitude Kashmir region of the Western Himalayas. Our investigation involved the analysis of 10 trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in glacier ice, snow pits, surface snow, and rainwater collected at various sites including Kolahoi, Thajwas, Pahalgam (Greater Himalayan ranges), and Kongdori and Shopian (Pir Panjal Ranges) during 2021. The study reveals distinct ranges of concentrations for the trace elements at different sampling sites. Our analysis of trace element concentration depth profiles in snow pits reveals seasonal fluctuations during the deposition year. The highest concentrations were found in the autumn (below 20 cm) and summer (top layer), compared to the winter concentration (10-20 cm). The high enrichment factors (EFs) suggest the severity of human-induced trace metal deposition in the western Himalayan region, relative to surrounding regions. Surprisingly, the concentrations and EFs of trace elements showed seasonal contradictions, with lower concentration values and higher EFs during the non-monsoon season and vice versa. A source apportionment analysis using the positive matrix factorization (PMF) technique identified five sources of trace element deposition in the region, including crustal sources (32.33%), coal combustion (15.62%), biomass burning (17.63%), traffic emission (18.8%), and industrial sources (15.6%). Additionally, the study incorporated backward trajectories coupled with δ18O using the NOAA HYSPLIT model to estimate moisture sources in the region, which suggests atmospheric pollutants predominately deposited from the large-scale atmospheric circulation from westerlies (75%) during non-monsoon season. These findings underscore the urgent need for enhanced monitoring and research efforts in the future.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218 m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77 µg m-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40 µg m-3; 24 h: 60 µg m-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and > monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19 µg m-3), Zn (0.49 µg m-3), Pb (0.43 µg m-3), Cr (0.21 µg m-3), Cu (0.21 µg m-3), Mn (0.07 µg m-3), and Ni (0.14 µg m-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQ values for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HI value exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Identification of sources of coarse mode aerosol particles (PM10) using ATR-FTIR and SEM-EDX spectroscopy over the Himalayan Region of India

This study attempts to examine the morphological, elemental and physical characteristics of PM10 over the Indian Himalayan Region (IHR) using FTIR and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. The study aimed at source identification of PM10 by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM10 was estimated as 63 ± 22 μg m-3; 53 ± 16 μg m-3; 67 ± 26 μg m-3 and 55 ± 11 μg m-3 over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively. ATR-FTIR spectrum analysis revealed the existence of inorganic ions (SiO44-, TiO2, SO42-, SO3-, NO3-, NO2-, CO32-, HCO3-, NH4+) and organic functional groups (C-C, C-H, C=C, C≡C, C=O, N-H, C≡N, C=N, O-H, cyclic rings, aromatic compounds and some heterogeneous groups) in PM10 which may arise from geogenic, biogenic and anthropogenic sources. The morphological and elemental characterization was performed by SEM-EDX, inferring for geogenic origin (Al, Na, K, Ca, Mg and Fe) due to the presence of different morphologies (irregular, spherical, cluster, sheet-like solid deposition and columnar). In contrast, particles having biogenic and anthropogenic origins (K, S and Ba) have primarily spherical with few irregular particles at all the study sites. Also, the statistical analysis ANOVA depicts that among all the detected elements, Na, Al, Si, S and K are site-specific in nature as their mean of aw% significantly varied for all the sites. The trajectory analysis revealed that the Uttarakhand, Jammu and Kashmir, the Thar Desert, Himachal Pradesh, Pakistan, Afghanistan, Nepal, Sikkim, the Indo-Gangetic Plain (IGP) and the Bay of Bengal (BoB) contribute to the increased loading of atmospheric pollutants in various locations within the IHR.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region (NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban site of Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81 µg m-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10 were entrenched to the receptor models to comprehend the possible sources of PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Spatiotemporal variability and health risk assessment of PM2.5 and NO2 over the Indo-Gangetic Plain: A three years long study (2019-21)

Studying the spatiotemporal variability of pollutants is necessary to identify the pollution hotspots with high health risk and enable the agencies to implement pollution abatement strategies in a targeted manner. Present study reports the spatio-temporal variability and health risk assessment (HRA) of PM2.5 (Particulate matter with aerodynamic diameter <2.5μm) and NO2 over IGP from 2019-2021. The HRA is expressed as passively smoked cigarettes (PSC) for four different health outcomes i.e., low birth weight (LBW), percentage decreased lung function (DLF) in school aged children, lung cancer (LC), and cardiovascular mortality (CM). The findings confirm very high PM2.5 and NO2 mass concentrations and high health risk over middle IGP and Delhi as compared to upper and lower IGP. Within Delhi, north Delhi region is the most polluted and at highest risk as compared to central and south Delhi. The health risk associated with PM2.5 over IGP is highest for DLF, equivalent to 21.63 PSCs daily, followed by CM (11.69), LBW (8.27) and LC (6.94). For NO2, the health risk is highest for DLF (3.09 PSCs) and CM (2.95), followed by LC (1.47) and LBW (1.04). PM2.5 and NO2 concentrations, along with the associated health risks, are highest during the post-monsoon and winter seasons and lowest during the monsoon season.

Understanding the influence of summer biomass burning on air quality in North India: Eight cities field campaign study

Near real-time monitoring of major air pollutants, i.e., particulate matter (PM₁₀, PM_2.5, PM₁), trace gases (O₃, CO, NO, NO₂, NO_x, NH₃, CO₂, SO₂) and Volatile Organic Compounds (VOCs: benzene, ethylbenzene, m-, p-xylene, o-xylene and toluene) along with climatological parameters was done in eight-cities field campaigns during the rabi (wheat) crop residue burning period in the northwest of Indo-Gangetic Plain (IGP) region. The phase-wise monitoring was done at eight locations representing rural, semi-urban and urban backgrounds. During the whole campaign, the semi-urban site (Sirsa) observed the highest average concentration of PM₁₀ (226 ± 111 μg m^-3) and PM_2.5 (91 ± 67 μg m^-3). The urban site (Chandigarh) reported the minimum concentrations of all the three size fractions of particulate matter with PM₁₀ as 89 ± 54 μg m^-3, PM_2.5 as 42 ± 22 μg m^-3 and PM₁ as 20 ± 13 μg m^-3 where the monitoring was done in the early phase of the campaign. The highest VOC concentration was recorded at the semi-urban (Sirsa) site, whereas the lowest was at a rural location (Fatehgarh Sahib). NH₃ concentration was observed highest in rural sites (31.7 ± 29.8 ppbv), which can be due to the application of fertilizers in agricultural activities. Visible Infrared Imaging Radiometer Suite (VIIRS) based fire and thermal anomalies, along with HYSPLIT back trajectory analysis, show that major air masses over monitoring sites (22 %-70 %) were from the rabi crop residue burning regions. The characteristic ratios and Principal component analysis (PCA) results show that diverse sources, i.e., emissions from crop residue burning, solid biomass fuels, vehicles and industries, majorly degrade the regional air quality. This multi-city study observed that semi-urban regions have the most compromised air quality during the rabi crop residue burning and need attention to address the air quality issues in the IGP region.

Variations in the concentration, source activity, and atmospheric processing of PM2.5-associated water-soluble ionic species over Jammu, India

Concentrations, sources, and atmospheric processing of water-soluble ionic species associated with PM_2.5 collected from 2015 to 2017 were studied in Jammu, an urban location in the North-Western Himalayan Region (NWHR). Being ecologically sensitive and sparsely studied for dynamics in PM_2.5 and associated WSIS, the present study is important for developing robust air pollution abatement strategies for the air-shed of NWHR. Twenty-four hourly PM_2.5 samples were collected on weekly basis at a receptor site and analyzed for WSIS using ion chromatography system. On annual basis, total sum of WSIS (ΣWSIS) contributed about 28.5% of PM_2.5, where the contribution of sulfate-nitrate-ammonium, a proxy for secondary inorganic aerosols (SIA), was found to be 18.7% of PM_2.5. The ΣWSIS and PM_2.5 concentration showed a seasonal cycle with the maximum concentration during winters and the minimum in summers. Mass fraction of ΣWSIS in PM_2.5 showed an anti-phase seasonal pattern indicating more source activity during summers. Season-wise, dominant WSIS constituting PM_2.5 were NO₃^-, SO₄^2-, NH₄⁺, and K⁺ during winters; whereas summer was marked with dominant contributions from SO₄^2-, NH₄⁺, Ca²⁺, and K⁺. Seasonal variability exhibited among SIA constituents underscored the crucial role of air temperature and relative humidity regime. It was observed that nss-K⁺ + NH₄⁺ were sufficient to neutralize most of the acidic species arising from precursor gases (NO_x and SO_x). Using principal component analysis, five major sources and processes, viz. (a) biomass burning activities, (b) secondary inorganic aerosol formation, (c) input from re-suspended dust, (d) transported dust, and (e) fertilizer residue, were identified for the emissions of PM_2.5-associated WSIS over Jammu. In future studies, impacts of dry and/or wet deposition of aerosol-associated WSIS on the crop productivity in the region should be studied.

Determination and assessment of elemental concentration in the atmospheric particulate matter: a comprehensive review

The elemental concentrations of atmospheric particulate matter (PM) have a detrimental effect on human health in which some elemental species have carcinogenic nature. In India, significant variations have found in the practices adapted from sampling to analysis for the determination and assessment of the elemental concentration in PM. Therefore, Indian studies (2011-2020) on the related domain are summarized to impart consistency in the field and laboratory practices. Further, a comparative analysis with other countries has also been mentioned in the relevant sections to evaluate its likeness with Indian studies. To prepare this study, literature has been procured from reputed journals. Subsequently, each step from sampling to analysis has thoroughly discussed with quality assurance and control (QA/QC) compliance. In addition, a framework has been proposed that showed field and laboratory analysis in an organized manner. Consequently, this study will provide benefit to novice researcher and improve their understanding about the related subject. Also, it will assist other peoples/bodies in framing the necessary decisions to carry out this study.

Chemical Composition and Source Apportionment of Total Suspended Particulate in the Central Himalayan Region

The present study analyzes data from total suspended particulate (TSP) samples collected during 3 years (2005–2008) at Nainital, central Himalayas, India and analyzed for carbonaceous aerosols (organic carbon (OC) and elemental carbon (EC)) and inorganic species, focusing on the assessment of primary and secondary organic carbon contributions (POC, SOC, respectively) and on source apportionment by positive matrix factorization (PMF). An average TSP concentration of 69.6 ± 51.8 µg m−3 was found, exhibiting a pre-monsoon (March–May) maximum (92.9 ± 48.5 µg m−3) due to dust transport and forest fires and a monsoon (June–August) minimum due to atmospheric washout, while carbonaceous aerosols and inorganic species expressed a similar seasonality. The mean OC/EC ratio (8.0 ± 3.3) and the good correlations between OC, EC, and nss-K+ suggested that biomass burning (BB) was one of the major contributing factors to aerosols in Nainital. Using the EC tracer method, along with several approaches for the determination of the (OC/EC)pri ratio, the estimated SOC component accounted for ~25% (19.3–29.7%). Furthermore, TSP source apportionment via PMF allowed for a better understanding of the aerosol sources in the Central Himalayan region. The key aerosol sources over Nainital were BB (27%), secondary sulfate (20%), secondary nitrate (9%), mineral dust (34%), and long-range transported mixed marine aerosol (10%). The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses were also used to identify the probable regional source areas of resolved aerosol sources. The main source regions for aerosols in Nainital were the plains in northwest India and Pakistan, polluted cities like Delhi, the Thar Desert, and the Arabian Sea area. The outcomes of the present study are expected to elucidate the atmospheric chemistry, emission source origins, and transport pathways of aerosols over the central Himalayan region.

Identification of Soil Heavy Metal Sources in a Large-Scale Area Affected by Industry

Heavy metals (HMs) in soil are some of the most serious pollutants due to their toxicity and nonbiodegradability. Especially across large-scale areas affected by industry, the complexity of pollution sources has attracted extensive attention. In this study, an approach based on zoning to analyze the sources of heavy metals in soil was proposed. Qualitative identification of pollution sources and quantification of their contributions to heavy metals in soil are key approaches in the prevention and control of heavy metal pollution. The concentrations of five HMs (Cd, Hg, As, Pb and Cr) in the surface soil of the Chenzhou industrial impact area were the research objects. Multiple methods were used for source identification, including positive matrix factorization (PMF) analysis combined with multiple other analyses, including random forest modeling, the geo-accumulation index method and hot spot analysis. The results showed that the average concentrations of the five heavy metals were 9.46, 2.36, 2.22, 3.27 and 1.05 times the background values in Hunan soil, respectively. Cd was associated with moderately to strongly polluted conditions, Hg, As and Pb were associated with unpolluted to moderately polluted conditions and Cr was associated with practically unpolluted conditions. The mining industry was the most significant anthropogenic factor affecting the content of Cd, Pb and As in the whole area, with contribution rates of 87.7%, 88.5% and 62.5%, respectively, and the main influence area was within 5 km from the mining site. In addition, we conducted hot spot analysis on key polluting enterprises and identified hot spots, cold spots, and areas insignificantly affected by enterprises, used this information as the basis for zoning treatment and discussed the sources of heavy metals in the three subregions. The results showed that Cd originated mainly from agricultural activities, with a contribution rate of 63.6%, in zone 3. As originated mainly from sewage irrigation, with a contribution rate of 65.0%, in zone 2, and the main influence area was within 800 m from the river. This element originated mainly from soil parent materials, with a contribution rate of 69.7%, in zone 3. Pb mainly originated from traffic emissions, with a contribution rate of 72.8%, in zone 3, and the main influence area was within 500 m from the traffic trunk line. Hg was mainly derived from soil parent materials with a contribution rate of 92.1% in zone 1, from agricultural activities with a contribution rate of 77.5% in zone 2, and from a mixture of natural and agricultural sources with a contribution rate of 74.2% in zone 3. Cr was mainly derived from the soil parent materials in the whole area, with a contribution rate of 90.7%. The study showed that in large-scale industrial influence areas, the results of heavy metal source analysis can become more accurate and detailed by incorporating regional treatment, and more reasonable suggestions can be provided for regional enterprise management and soil pollution control decision making.

Investigating the seasonal variability in source contribution to PM2.5 and PM10 using different receptor models during 2013-2016 in Delhi, India

The present work deals with the seasonal variations in the contribution of sources to PM_2.5 and PM₁₀ in Delhi, India. Samples of PM_2.5 and PM₁₀ were collected from January 2013 to December 2016 at an urban site of Delhi, India, and analyzed to evaluate their chemical components [organic carbon (OC), elemental carbon (EC), water-soluble inorganic components (WSICs), and major and trace elements]. The average concentrations of PM_2.5 and PM₁₀ were 131 ± 79 μg m^-3 and 238 ± 106 μg m^-3, respectively during the entire sampling period. The analyzed and seasonally segregated data sets of both PM_2.5 and PM₁₀ were used as input in the three different receptor models, i.e., principal component analysis-absolute principal component score (PCA-APCS), UNMIX, and positive matrix factorization (PMF), to achieve conjointly corroborated results. The present study deals with the implementation and comparison of results of three different multivariate receptor models (PCA-APCS, UNMIX, and PMF) on the same data sets that allowed a better understanding of the probable sources of PM_2.5 and PM₁₀ as well as the comportment of these sources with respect to different seasons. PCA-APCS, UNMIX, and PMF extracted similar sources but in different contributions to PM_2.5 and PM₁₀. All the three models extracted 7 similar sources while mutually confirmed the 4 major sources over Delhi, i.e., secondary aerosols, vehicular emissions, biomass burning, and soil dust, although the contribution of these sources varies seasonally. PCA-APCS and UNMIX analysis identified a less number of sources (besides mixed type) as compared to the PMF, which may cause erroneous interpretation of seasonal implications on source contribution to the PM mass concentration.

Climatological trends in satellite-derived aerosol optical depth over North India and its relationship with crop residue burning: Rural-urban contrast

Columnar Aerosol Optical Depths (AOD) over an urban area (Chandigarh) and a rural area (Khera, Fatehgarh Sahib district) situated in the Indo-Gangetic Plains (IGP) of India were analysed to study their temporal heterogeneity in terms of interannual, seasonal and monthly variations. Over the last few decades, IGP has become one of the global hotspots of air pollution due to the increased anthropogenic activities such as traffic, industries, agricultural waste burning etc. Level-2 AODs (550 nm) were retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard NASA's Terra and Aqua satellites, for a period of 14 years (2005-2018). The climatological mean Terra-MODIS (Aqua-MODIS) AOD over the urban location was ~0.497 ± 0.238 (0.474 ± 0.228), whereas over the rural location it was 0.542 ± 0.269 (0.534 ± 0.282). Linear trend analysis estimated an increase in annual mean Terra-MODIS (Aqua-MODIS) AOD at a rate of ~0.009 (0.013) per year over the urban site; whereas over the rural location the rate of increase was ~0.003 (0.004) per year. Results show that the observed increase is ~1.49% (2.41%) of climatological mean AOD over the urban location for Terra-MODIS (Aqua-MODIS), whereas, over the rural location, it was ~0.50% (0.67%). Using the HYSPLIT trajectory model, it was concluded that, during post-monsoon, the observed high AODs can be related to massive crop residue burning in the IGP region. These AOD trends can also be used to track the regional anthropogenic air-pollution changes. An empirical relation between AOD and PM₁₀ was established, which can be used to estimate PM₁₀ over the urban and rural areas of IGP (using MODIS AODs), complementing the sparse ground-based monitoring. Further, satellite-based air pollution data can be used for baseline assessment and understanding the impact of control policies such as National Clean Air Programme and to support formulate evidence-based pollution control strategies.

Influence of chemical aging on physico-chemical properties of mineral dust particles: A case study of 2016 dust storms over Delhi

The physico-chemical properties of dust particles collected During Dust Storm (DDS) and After Dust Storm (ADS) events were studied using Scanning Electron Microscope coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS), X-ray Fluorescence Spectroscopy (XRF) and X-ray Photoelectron Spectroscopy (XPS). Morphological and compositional change in dust particles were observed as they react with the anthropogenic pollutants present in the urban environment. The calcite rich particles were observed to transform into calcium chloride, calcium nitrate, and calcium sulfate on reacting with the chlorides, nitrates, and sulfates present in the urban atmosphere. The frequency distributions of Aspect Ratio (AR) for the DDS and ADS particles were observed to be bimodal (mode peaks at 1.2 and 1.5) and monomodal (mode peak at 1.1), respectively. The highly irregular shaped solid dust particles were observed to transform into nearly spherical semisolid particles in the urban environment. XPS analysis confirms the high concentration of oxides, nitrates, and chlorides at the surface of ADS samples which show the signatures of mineral dust particles aging. Species with a high value of imaginary part of refractive index (like Cr metal, Fe metal, Cr₂O_3, FeO, Fe₂O₃) were observed at the surface of dust particles. At 550 nm wavelength, the light-absorbing potential of the observed species along with black carbon (BC) was found to vary in the order; Cr metal > Fe metal > Cr₂O₃> FeO > BC > Fe₂O₃> FeOOH. The presence of the aforementioned species on the surface of ADS particles will tremendously affect the particle optical and radiative properties compared to that of DDS particles. The present work could reduce the uncertainty in the radiation budget estimations of mineral dust and assessment of their climatic impacts over Delhi.

Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: A four year study over Delhi, India

The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM_2.5 and PM₁₀) in Delhi, India from January 2013 to December 2016. The annual average concentrations of PM_2.5 and PM₁₀ were 131 ± 79 μg m^-3 (range: 17-417 μg m^-3) and 238 ± 106 μg m^-3 (range: 34-537 μg m^-3), respectively. PM_2.5 and PM₁₀ samples were chemically characterized to assess their chemical components [i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements] and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes ∼28% to the total PM_2.5 concentration and 24% to the total PM₁₀ concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM_2.5 and PM₁₀ were carried by north westerly winds (north-western Indo Gangetic Plains of India).

Influence of Vehicular Emissions (NO, NO2, CO and NMHCs) on the Mixing Ratio of Atmospheric Ammonia (NH3) in Delhi, India

Mixing ratios of atmospheric ammonia (NH₃), nitric oxide (NO), carbon monoxide (CO), nonmethane hydrocarbons (NMHCs), and methane (CH₄) were measured to investigate the vehicular emissions, which are a dominant source of atmospheric NH₃ in urban sites of Delhi, India from January 2013 to December 2014. The annual average mixing ratios of NH₃, NO, CO, NMHCs, and CH₄ were 21.2 ± 2.1 ppb, 21.2 ± 6.1 ppb, 1.89 ± 0.18 ppm, 0.67 ± 0.21 ppm and 3.11 ± 0.53 ppm, respectively. Considering NO as a tracer of vehicular plume, ambient NH₃ was correlated with NO during peak traffic hour in the morning (7:00-10:00 h) and evening (17:00-19:00 h) and observed significant positive correlation between them. Result reveals that the mixing ratio of atmospheric NH₃ significantly positive correlated with traffic related pollutants (NO, CO, and NHHCs) during all the seasons (winter, summer, and monsoon). During winter, the average mixing ratio of atmospheric NH₃ was increased by 1.2-3.5 ppb in the morning peak hour, whereas increased by 0.3-1.6 ppb in the evening peak hour. Similarly, an increase in NH₃ mixing ratio was observed during summer (morning: 1.2-2.7 ppb and evening: 1.5-1.6 ppb) and monsoon (morning: 0.4-3.6 ppb and evening: 0.9-1.4 ppb) seasons. The results emphasized that the traffic could be one of the dominant source of ambient NH₃ at the urban site of Delhi, as illustrated by positive relationships of NH₃ with traffic related co-pollutants (NO, CO and NMHCs).