Metallic species in ambient particulate matter at rural and urban location of Delhi

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).

Two-year systematic investigation reveals alterations induced on chemical and bacteriome profile of PM2.5 by African dust incursions to the Mediterranean atmosphere

PM_2.5 atmospheric samples were regularly collected between January 2013 and March 2015 at a central location of Eastern Mediterranean (Island of Crete) during African dust events (DES) and periods of absence of such episodes as controls (CS). The elemental composition and microbiome DES and CS were thoroughly investigated. Fifty-six major and trace elements were determined by inductively coupled plasma-mass spectrometry. Relative mass abundances (RMA) of major crustal elements and lanthanoids were higher in DES than in CS. Conversely in CS, RMAs were higher for most anthropogenic transition metals. Lanthanum-to-other lanthanoids concentration ratios for DES approached the corresponding reference values for continental crust and several African dust source regions, while in CS they exceeded these values. USEPA's UNMIX receptor model, applied in all PM_2.5 samples, established that African dust is the dominant contributing source (by 80%) followed by road dust/fuel oil emissions (17%) in the receptor area. Potential source contribution function (PSCF) identified dust hotspots in Tunisia, Libya and Egypt. The application of 16S rRNA gene amplicon sequencing revealed high variation of bacterial composition and diversity between DES and CS samples. Proteobacteria, Actinobacteria and Bacteroides were the most dominant in both DES and CS samples, representing ~88% of the total bacterial diversity. Cutibacterium, Tumebacillus and Sphingomonas dominated the CS samples, while Rhizobium and Brevundimonas were the most prevalent genera in DES. Mutual exclusion/co-occurrence network analysis indicated that Sphingomonas and Chryseobacterium exhibited the highest degrees of mutual exclusion in CS, while in DES the corresponding species were Brevundimonas, Delftia, Rubellimicrobium, Flavobacterium, Blastococcus, and Pseudarthrobacter. Some of these microorganisms are emerging global opportunistic pathogens and an increase in human exposure to them as a result of environmental changes, is inevitable.

Gridded distribution of total suspended particulate matter (TSP) and their chemical characterization over Delhi during winter

In the present study, total suspended particulate matter (TSP) samples were collected at 47 different sites (47 grids of 5 × 5 km² area) of Delhi during winter (January-February 2019) in campaign mode. To understand the spatial variation of sources, TSP samples were analyzed for chemical compositions including carbonaceous species [organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC)], water-soluble total nitrogen (WSTN), water-soluble inorganic nitrogen (WSIN), polycyclic aromatic hydrocarbons (16 PAHs), water-soluble inorganic species (WSIS) (F^-, Cl^-, SO₄^2-, NO₂^-, NO₃^-, PO₄^3-, NH₄⁺, Ca²⁺, Mg²⁺, Na⁺, and K⁺), and major and minor trace elements (B, Na, Mg, Al, P, S, Cl, K, Ca, Ti, Fe, Zn, Cr, Mn, Cu, As, Pd, F, and Ag). During the campaign, the maximum concentration of several components of TSP (996 μg/m³) was recorded at the Rana Pratap Bagh area, representing a pollution hotspot of Delhi. The maximum concentrations of PAHs were recorded at Udhyog Nagar, a region close to heavily loaded diesel vehicles, small rubber factories, and waste burning areas. Higher content of Cl^- and Cl^-/Na⁺ ratio (>1.7) suggests the presence of nonmarine anthropogenic sources of Cl^- over Delhi. Minimum concentrations of OC, EC, WSOC, PAHs, and WSIS in TSP were observed at Kalkaji, representing the least polluted area in Delhi. Enrichment factor <5.0 at several locations and a significant correlation of Al with Mg, Fe, Ti, and Ca and C/N ratio indicated the abundance of mineral/crustal dust in TSP over Delhi. Principal component analysis (PCA) was also performed for the source apportionment of TSP, and extracted soil dust was found to be the major contributor to TSP, followed by biomass burning, open waste burning, secondary aerosol, and vehicular emissions.

A comprehensive review of domestic-open waste burning: recent trends, methodology comparison, and factors assessment

Open burning is a waste management practice performed by many people worldwide, especially in developing countries. Lack of detailed data of open burning practices may lead to a misinterpretation during data analysis, especially when estimating global/local emissions and assessing risks. This study presents a comprehensive review of current research trends, methodological assessments, and factors behind open waste burning practices from published literature. This review used systematic methods such as PRISMA 2020 methodology, a bibliometric approach, and qualitative content analysis to determine and assess 84 articles related to open burning. The results show that environmental risks and emission factors related to open burning incidents at the landfill or residential level are preferable topics that will be rising in the years to come. Coupling methods such as a transect-based approach with a questionnaire survey and mobile-static plume sampling to determine the activities and incidents as baseline data for risk assessment will help researchers gain a robust dataset of open burning emission inventory. In addition, it was found that environmental knowledge and awareness levels influence open burning practices, thereby opening up opportunities for future research.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10163-022-01430-9.

Seasonal variation and sources of carbonaceous species and elements in PM2.5 and PM10 over the eastern Himalaya

The study represents the seasonal characteristics (carbonaceous aerosols and elements) and the contribution of prominent sources of PM2.5 and PM10 in the high altitude of the eastern Himalaya (Darjeeling) during August 2018-July 2019. Carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), and water soluble organic carbon (WSOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Cr, Ni, Mo, Cl, P, S, K, Zr, Pb, Na, Mg, Ca, and B) in PM2.5 and PM10 were analyzed to estimate their possible sources. The annual concentrations of PM2.5 and PM10 were computed as 37±12 μg m-3 and 58±18 μg m-3, respectively. In the present case, total carbonaceous species in PM2.5 and PM10 were accounted for 20.6% of PM2.5 and 18.6% of PM10, respectively, whereas trace elements in PM2.5 and PM10 were estimated to be 15% of PM2.5 and 12% of PM10, respectively. Monthly and seasonal variations in mass concentrations of carbonaceous aerosols and elements in PM2.5 and PM10 were also observed during the observational period. In PM2.5, the annual concentrations of POC and SOC were 2.35 ± 1.06 μg m-3 (66% of OC) and 1.19±0.57 μg m-3 (34% of OC), respectively, whereas annual average POC and SOC concentrations in PM10 were 3.18 ± 1.13 μg m-3 (63% of OC) and 2.05±0.98 μg m-3 (37% of OC), respectively. The seasonal contribution of POC and SOC were ranging from 55 to 77% and 33 to 45% of OC in PM2.5, respectively, whereas in PM10, the seasonal contributions of POC and SOC were ranging from 51 to 73% and 37 to 49% of OC, respectively. The positive relationship between OC & EC and OC & WSOC of PM2.5 and PM10 during all the seasons (except monsoon in case of PM10) indicates their common sources. The enrichment factors (EFs) and significant positive correlation of Al with othe crustal elements (Fe, Ca, Mg, and Ti) of fine and coarse mode aerosols indicate the influence of mineral dust at Darjeeling. Principal component analysis (PCA) resolved the four common sources (biomass burning + fossil fuel combustion (BB + FFC), crustal/soil dust, vehicular emissions (VE), and industrial emissions (IE)) of PM2.5 and PM10 in Darjeeling.

Variation in chemical composition and sources of PM2.5 during the COVID-19 lockdown in Delhi

The Government of India (GOI) announced a nationwide lockdown starting 25th March 2020 to contain the spread of COVID-19, leading to an unprecedented decline in anthropogenic activities and, in turn, improvements in ambient air quality. This is the first study to focus on highly time-resolved chemical speciation and source apportionment of PM_2.5 to assess the impact of the lockdown and subsequent relaxations on the sources of ambient PM_2.5 in Delhi, India. The elemental, organic, and black carbon fractions of PM_2.5 were measured at the IIT Delhi campus from February 2020 to May 2020. We report source apportionment results using positive matrix factorization (PMF) of organic and elemental fractions of PM_2.5 during the different phases of the lockdown. The resolved sources such as vehicular emissions, domestic coal combustion, and semi-volatile oxygenated organic aerosol (SVOOA) were found to decrease by 96%, 95%, and 86%, respectively, during lockdown phase-1 as compared to pre-lockdown. An unforeseen rise in O₃ concentrations with declining NO_x levels was observed, similar to other parts of the globe, leading to the low-volatility oxygenated organic aerosols (LVOOA) increasing to almost double the pre-lockdown concentrations during the last phase of the lockdown. The effect of the lockdown was found to be less pronounced on other resolved sources like secondary chloride, power plants, dust-related, hydrocarbon-like organic aerosols (HOA), and biomass burning related emissions, which were also swayed by the changing meteorological conditions during the four lockdown phases. The results presented in this study provide a basis for future emission control strategies, quantifying the extent to which constraining certain anthropogenic activities can ameliorate the ambient air. These results have direct relevance to not only Delhi but the entire Indo-Gangetic plain (IGP), citing similar geographical and meteorological conditions common to the region along with overlapping regional emission sources. SUMMARY OF MAIN FINDINGS: We identify sources like vehicular emissions, domestic coal combustion, and semi-volatile oxygenated organic aerosol (SVOOA) to be severely impacted by the lockdown, whereas ozone levels and, in turn, low-volatility oxygenated organic aerosols (LVOOA) rise by more than 95% compared to the pre-lockdown concentrations during the last phase of the lockdown. However, other sources resolved in this study, like secondary chloride, power plants, dust-related, hydrocarbon-like organic aerosols (HOA), and biomass burning related emissions, were mainly driven by the changes in the meteorological conditions rather than the lockdown.

Characteristics, sources, and health risks of PM2.5-bound trace elements in representative areas of Northern Zhejiang Province, China

This study aimed to characterize PM_2.5-bound trace elements in Northern Zhejiang Province (NZP), one of the most economically prosperous regions in China, and assess the associated health risks for the general populations. A year-long sampling campaign was conducted at four sites representative of urban, suburban, and rural areas of NZP. The average of the sum of twenty trace elements in PM_2.5 was 2.8 ± 0.4 μg m^-3, dominated by K, Al, Fe, Mg, Zn, and V (>100 ng m^-3). The highest total elements' concentration occurred in winter, followed by autumn, spring, and summer. Enrichment factors and principal component analysis (PCA) revealed that the major sources of trace elements in NZP were fossil fuel combustion, biomass burning, crustal dust, traffic, and industrial emissions. Elevated concentrations of certain elements reflected featured sources in different areas, e.g., V and Ni from heavy oil combustion in the port city, and Cu, Fe and Ba from traffic emissions in urban areas. Arsenic (As) represented the major non-cancer risk driver as its hazard quotient was 8.7. The cumulative cancer risk from all the carcinogenic elements was 1.7 × 10^-3 in NZP, exceeding the upper limit (10^-4) of the acceptable risk range. As and Cr contributed 33% and 66%, respectively, and thus were regarded as cancer risk drivers. The high health risks from PM_2.5-bound elements warrant future actions to control their emissions in this region. Priorities should target industrial operations and coal combustion emissions, as informed by the risk drivers.

Review of the Newly Developed, Mobile Optical Sensors for Real-Time Measurement of the Atmospheric Particulate Matter Concentration

Due to the adverse effects on human health and the environment, air quality monitoring, specifically particulate matter (PM), has received increased attention over the last decades. Most of the research and policy actions have been focused on decreasing PM pollution and the development of air monitoring technologies, resulting in a decline of total ambient PM concentrations. For these reasons, there is a continually increasing interest in mobile, low-cost, and real-time PM detection instruments in both indoor and outdoor environments. However, to the best of the authors’ knowledge, there is no recent literature review on the development of newly designed mobile and compact optical PM sensors. With this aim, this paper gives an overview of the most recent advances in mobile optical particle counters (OPCs) and camera-based optical devices to detect particulate matter concentration. Firstly, the paper summarizes the particulate matter effects on human health and the environment and introduces the major particulate matter classes, sources, and characteristics. Then, it illustrates the different theories, detection methods, and operating principles of the newly developed portable optical sensors based on light scattering (OPCs) and image processing (camera-based sensors), including their advantages and disadvantages. A discussion concludes the review by comparing different novel optical devices in terms of structures, parameters, and detection sensitivity.

Geochemical characteristics of trace elements in size-resolved coastal urban aerosols associated with distinct air masses over tropical peninsular India: Size distributions and source apportionment

Trace elements in atmospheric particulate matter play a significant role in air quality, health and biogeochemical cycles. The present study reports on geochemical characteristics of size-resolved trace elements in PM₁₀ aerosols collected under different air masses over a coastal urban location in peninsular India. A contrast in elemental distribution was observed for the particle size above 7.0 μm and below 1.1 μm under the influence of northeasterly air masses as characterized by Al > Fe > Zn and Fe > Al > Zn, respectively. The concentrations of the crustal elements (Al, Fe, Ti, P, Ba, Co) were high and illustrated by a unimodal size distribution with a peak in coarse mode (>2.0 μm) during northwesterly air masses. On the other hand, combustion-derived metals (Cu, Zn, Cd, Sb, and Pb) were maximized under northeasterly air masses, characterized by unimodal size distribution with a peak in fine mode (<2.0 μm). The enrichment factor (EF) analysis reveals the contribution of anthropogenic emissions to Cd, Sb, Pb, Zn, Cu, Cr, Ni, As, and Sn metals, particularly to the high enrichment of trace metals in fine mode. These results suggest that crustal emissions are major sources of trace metals in coarse mode aerosols; whereas combustion derived anthropogenic emissions contribute to the fine mode aerosols. The positive matrix factorization (PMF) analysis revealed that crustal sources (52-90%) were most abundant for particles >7.0 μm, whereas combustion related emissions such as vehicular and traffic sources are predominant for particles <1.1 μm. The present study demonstrates that trace metals in coastal urban aerosols are affected by changes in emission sources/strengths and regional transport of air masses originated from the northeasterly and northwesterly parts of the tropical Indian subcontinent.

Quantifying the Deposition of Airborne Particulate Matter Pollution on Skin Using Elemental Markers

Airborne particulate matter (PM) pollution is an environmental and health concern. The health impact of PM pollution has typically focused on the respiratory system. The impact of PM pollution on skin has been largely understudied due to the lack of a quantitative method to measure the deposition on skin. This manuscript presents a method to quantify PM pollution on skin using elemental markers as a proxy for PM. Skin tape strips were collected from forehead and buttock of 100 outdoor workers in Beijing, China. Skin samples were analyzed for 19 elemental markers using inductively coupled plasma mass spectrometry. To determine the specific elemental signature of PM for the region, air samples were collected over 7 days for PM < 2.5 μm (PM_2.5) and analyzed for the same 19 elements as the skin samples. An enrichment factor was calculated for each element and the potential source was evaluated. Using the elemental markers unique to PM pollution for the region, the PM concentration deposited on skin was determined to be 0.621-2.53 μg PM_2.5 /cm². This method can be re-applied in different regions and the PM concentration on skin can inform future studies on the health impact of air pollution on skin.

Assessment of occupational exposure to fine particulate matter in dental prosthesis laboratories in Kocaeli, Turkey

Dental prosthesis laboratories (DPLs) are among the workplaces where predominantly manual production takes place. In such working environments, during the manual manufacturing process, which involves fine smoothing and polishing of dental prostheses, fine particulate matter is released into the ambient air. In this study, the particulate matter (PM) concentrations and elemental content of the fine particles in the working ambient air were identified in six DPLs in Kocaeli, Turkey. PM_2.5 mass concentrations, measured in all the DPLs, ranged between 80.8 and 1645 μg/m³ (mean 414 ± 406). As a result of the analyses performed with an ICP-MS device (Perkin Elmer Elan®DRC-e), trace elements of Be, Cd, Hg, and, notably, Co, Cr, Mo, and Ni were found. The researchers calculated the excess lifetime cancer risks and total hazard indexes. The average total cancer risk for all the DPLs was 8 × 10^-3, which is higher than the acceptable limit of 1.0 × 10^-6, and the total hazard index was 187, which is greater than the acceptable limit of 1.0. Considering these high-level risks, the study concluded that there is a need for new production methods, and strict application of occupational health and safety measures, to reduce the fine particle exposure of the workers in the laboratories. In addition, there are prescribed limit values for particulate matter only for respirable particles in working environments. The establishment of limit values, especially for PM_2.5 concentrations, is important for the protection of the health of the employees.

Heavy metal capture from the suspended particulate matter by Morus alba and evidence of foliar uptake and translocation of PM associated zinc using radiotracer (65Zn)

In urban set up, increasing combustion and processing activities have contaminated the air with toxic heavy metals which are generally enriched on atmospheric particulate matter. Vegetation around urban area act as a sink where such metal enriched particles generally deposit on the foliar surfaces, however, role of vegetation in uptake of metals adhered on the atmospheric particulate matter is yet not explored properly and is important to study to evaluate their role as bio-remediator. The undertaken work examines the foliar surface of Morus alba for its potential to deposit and accumulate atmospheric heavy metals. Further, to understand foliar uptake mechanism and translocation of atmospheric metal enriched on particulate matter a simulated experiment was conducted by labeling the known particle size (45 μm and 120 μm) with radio labeled ⁶⁵Zn, applied on the tagged leaf with two particle loads, 25 mg and 50 mg. The study showed that owing to its rough foliar surface with trichomes and grooves, Morus alba efficiently trap heavy metal enriched particles and was capable of accumulating metals from particulate matter into different plant parts. It was recorded that ⁶⁵Zn adhered on different size particles was taken up by tagged leaf of mulberry and majorly translocated to the lower stem and roots. It was also inferred from the study that both particle size and particle load significantly affect the foliar uptake and translocation of atmospheric heavy metal. The study focuses on the fact that urban avenue trees are capable of taking up atmospheric heavy metals and can play a crucial role in improving air quality.

Relationships between chemical elements of PM2.5 and O3 in Shanghai atmosphere based on the 1-year monitoring observation

Mass level of fine particles (PM_2.5) in main cities in China has decreased significantly in recent years due to implementation of Chinese Clean Air Action Plan since 2013, however, O₃ pollution is getting worse than before, especially in megacities such as in Shanghai. In this work, O₃ and PM_2.5 were continuously monitored from May 27, 2018 to March 31, 2019. Our data showed that the annual average concentration of PM_2.5 and O₃ (O₃-8 hr, maximum 8-hour moving average of ozone days) was 39.35 ± 35.74 and 86.49 ± 41.65 µg/m³, respectively. The concentrations of PM_2.5 showed clear seasonal trends, with higher concentrations in winter (83.36 ± 18.66 µg/m³) and lower concentrations in summer (19.85 ± 7.23 µg/m³), however, the seasonal trends of O₃ were different with 103.75 ± 41.77 µg/m³ in summer and 58.59 ± 21.40 µg/m³ in winter. Air mass backward trajectory, analyzing results of potential source contribution function model and concentration weighted trajectory model implied that pollutants from northwestern China contributed significantly to the mass concentration of Shanghai PM_2.5, while pollutants from areas of eastern coastal provinces and South China Sea contributed significantly to the mass level of ozone in Shanghai atmosphere. Mass concentration of twenty-one elements in the PM_2.5 were investigated, and their relationships with O₃ were analyzed. Mass level of ozone had good correlation with that of Ba (r = 0.64, p < 0.05) and V (r = 0.30, p > 0.05), suggesting vehicle emission pollutants contribute to the increasing concentration of ozone in Shanghai atmosphere.

Source apportionment of PM10 by positive matrix factorization model at a source region of biomass burning

To determine the contribution of different particulate sources in PM₁₀ mass concentration at semi urban site, source apportionment study was carried out from 7 May 2015 to 9 June 2016. PM₁₀ samples were analyzed for 18 species (NO₃^-, SO₄^2-, Cl^-,Na⁺, K⁺, Al, Ti, Mn, Fe, Mg, V, Ni, Cu, Zn, Ba, Pb, Cr, Ca). The study was specifically designed to apportion the sources of air pollution where main exposure is from crop residue burning. The particulate matter (PM₁₀) samples were analyzed for mass and chemical composition, with Potassium as biomarker for crop residue burning. Sulfate SO₄^2-) and potassium ion (K⁺) species dominated the concentration of characterized species. K⁺ and Cl^- were identified as reliable markers for crop residue burning while Zn, Pb, Al, Ni and Cu were identified as markers for vehicular exhaust. The results of Positive matrix factorization (PMF) model gives the five major sources as probable sources of PM₁₀ pollution. The highest contribution in PM₁₀ mass concentration was found to be sulfate (24.39 ± 10.42), and potassium (24.02 ± 09.56) and chloride (07.07 ± 05.47), which combined accounts for nearly 60% of the total PM₁₀ mass fraction. The highest source contribution was from Industrial emission source (22.9%), with almost same contribution from biomass burning (21.2%), and resuspended dust (20.7%) and followed by vehicular emissions (19.0%) and least from secondary aerosols (16.2%).

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).

Spatio-temporal variation of air pollutants around the coal mining areas of Jharia Coalfield, India

Jharia Coalfield (JCF) is one of the oldest coalfields in the eastern part of India and falls under critically polluted areas as per CPCB/MoEFCC Notification. Therefore, a study of air pollution and its management is the demand of the day. This study had been undertaken to know the current status of JCF concerning air quality. Ambient air quality monitoring with reference to particulate matter (PM₁₀ and PM_2.5), SO₂, NO_x and trace elements had been conducted in the coal mining areas of JCF. The study area was divided into two groups, mainly fire and non-fire for the sampling of air. Principal component analysis (PCA) identified coal mine fire as a major source of air pollution in the mining areas of JCF. Air quality index (AQI) was calculated which revealed that the air quality index of coal mine fire-affected areas was nearly 1.5 times higher than that of the non-mine fire areas. Graphical abstract.

The impact of polar fraction of the fine particulate matter on redox responses in different rat tissues

Particulate matter (PM) contains different chemical substances that have been associated with health effects and an increased risk of mortality due to their toxicity. In this study, fine particulate matter (PM_2.5) samples were collected in a region with rural characteristics (Seropédica (Se)) and another with some industries (Duque de Caxias (DC)) (Brazil, RJ). Rats were exposed to PM_2.5 extracts daily for 25 days at different dilutions: 10×, 5×, and a concentrated solution (CS). Biochemical analyses were investigated for total antioxidant capacity (ACAP), lipid peroxidation (LPO) levels, reduced glutathione (GSH) concentration, activity of glutamate cysteine ligase (GCL), and activity of glutathione S-transferase (GST). The liver showed a significant increase in GCL (DC-5×, DC-CS and Se-CS) and GST activities (DC-CS and Se-CS) in both regions when compared to the control group. In the renal cortex, GCL activity decreased in most of the tested groups while GST activity increased only in the 5× groups of both regions (DC and Se). In the renal medulla, GCL activity decreased for Se-10× and DC-CS but increased for Se-5×, and GST activity increased in the Se-10×, DC-5×, and DC-CS groups. Lung GCL increased in all groups for both regions. Moreover, this organ also showed an increase in GST activity when higher metal concentrations were present (5× and CS). TBARS levels were increased for all tissues in most tested concentrations. These data indicate that soluble compounds (e.g., metals) from PM_2.5 sampled in areas with different pollution indexes can change the redox status and cause damage to different tissues.

Atmospheric bulk deposition of heavy metal(loid)s in central south China: Fluxes, influencing factors and implication for paddy soils

The depositions of heavy metal(loid)s (HMs) were measured in an urban agglomeration of China to investigate the fluxes, influencing factors, sources, and potential effects of these HMs. Our results showed that the deposition fluxes of As and Cd were higher in this area than in other regions. In the area, 59.63% of the total deposition fluxes of the Cr, Cu, Ni, Pb and Zn were observed in the wet season (March to July). Lower total fluxes of HMs were observed at the rural site. Principal component analysis (PCA) results showed that the As, Cd, Pb, and Zn might originate from the same anthropogenic sources, including traffic and industrial sources, and that the Cr, Cu, and Ni might come from natural sources. Correlation analysis and redundancy analysis (RDA) showed that rainfall, wind speed, and PMs were critical factors influencing the atmospheric bulk deposition of HMs. For the paddy soil, the input fluxes of HMs by deposition, accounted for 38.66-84.57% (except for Cr) of the total input fluxes. The prediction indicated that the accumulation of HMs in surface soil will notably increase over the next decades due to the influence of atmospheric deposition.

Spatial differences in ambient coarse and fine particles in the Monterrey metropolitan area, Mexico: Implications for source contribution

The ambient air of the Monterrey Metropolitan Area (MMA) in Mexico frequently exhibits high levels of PM₁₀ and PM_2.5. However, no information exists on the chemical composition of coarse particles (PM_c = PM₁₀ - PM_2.5). A monitoring campaign was conducted during the summer of 2015, during which 24-hr average PM₁₀ and PM_2.5 samples were collected using high-volume filter-based instruments to chemically characterize the fine and coarse fractions of the PM. The collected samples were analyzed for anions (Cl^-, NO₃^-, SO₄^2-), cations (Na⁺, NH₄⁺, K⁺), organic carbon (OC), elemental carbon (EC), and 35 trace elements (Al to Pb). During the campaign, the average PM_2.5 concentrations did not showed significance differences among sampling sites, whereas the average PM_c concentrations did. In addition, the PM_c accounted for 75% to 90% of the PM₁₀ across the MMA. The average contribution of the main chemical species to the total mass indicated that geological material including Ca, Fe, Si, and Al (45%) and sulfates (11%) were the principal components of PM_c, whereas sulfates (54%) and organic matter (30%) were the principal components of PM_2.5. The OC-to-EC ratio for PM_c ranged from 4.4 to 13, whereas that for PM_2.5 ranged from 3.97 to 6.08. The estimated contribution of Secondary Organic Aerosol (SOA) to the total mass of organic aerosol in PM_2.5 was estimated to be around 70-80%; for PM_c, the contribution was lower (20-50%). The enrichment factors (EF) for most of the trace elements exhibited high values for PM_2.5 (EF: 10-1000) and low values for PM_c (EF: 1-10). Given the high contribution of crustal elements and the high values of EFs, PM_c is heavily influenced by soil resuspension and PM_2.5 by anthropogenic sources. Finally, the airborne particles found in the eastern region of the MMA were chemically distinguishable from those in its western region. Implications: Concentration and chemical composition patterns of fine and coarse particles can vary significantly across the MMA. Public policy solutions have to be built based on these observations. There is clear evidence that the spatial variations in the MMA's coarse fractions are influenced by clearly recognizable primary emission sources, while fine particles exhibit a homogeneous concentration field and a clear spatial pattern of increasing secondary contributions. Important reductions in the coarse fraction can come from primary particles' emission controls; for fine particles, control of gaseous precursors-particularly sulfur-containing species and organic compounds-should be considered.

Distribution and potential ecological risk assessment of trace elements in the stream water and sediments from Lanmuchang area, southwest Guizhou, China

Trace elements contamination in sediment is regarded as the global crisis with a large share in developing countries like China. Water and sediment samples were collected during (2016) from Qingshui Stream and analyzed for major physicochemical properties and trace elements by using ICP-MS. Our result of sediments showed that studied trace elements (except Pb, Cd, Co) had a concentration higher than Chinese sediment guideline as well as stream water data for studied trace elements (except Cr, Pb, Cd, Cu, and Zn) had a higher concentration than the maximum permissible safe limit of WHO. Contamination factor (CF) confirmed a moderate to high contamination in the sediment samples due to As and Tl, respectively. The values of pollution load index (PLI) were found above one (> 1), describing the progressive sediment quality decline. Pearson correlation showed that there was a significant positive association between Tl and As (r = 0.725, p < 0.05) in sediment samples. Results revealed that water-rock interaction, weathering of Tl sulfide mineralization, and hydrogeological conditions were major sources of stream water and sediments contamination in the study area. This experimental study contributes to a better understanding of the geochemistry and prevention of trace element contamination in sediments from Lanmuchang area.

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

The present work is the ensuing part of the study on spatial and temporal variations in chemical characteristics of PM₁₀ (particulate matter with aerodynamic diameter ≤ 10 μm) over Indo Gangetic Plain (IGP) of India. It focuses on the apportionment of PM₁₀ sources with the application of different receptor models, i.e., principal component analysis with absolute principal component scores (PCA-APCS), UNMIX, and positive matrix factorization (PMF) on the same chemical species of PM₁₀. The main objective of this study is to perform the comparative analysis of the models, obtained mutually validated outputs and more robust results. The average PM₁₀ concentration during January 2011 to December 2011 at Delhi, Varanasi, and Kolkata were 202.3 ± 74.3, 206.2 ± 77.4, and 171.5 ± 38.5 μg m^-3, respectively. The results provided by the three models revealed quite similar source profile for all the sampling regions, with some disaccords in number of sources as well as their percent contributions. The PMF analysis resolved seven individual sources in Delhi [soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), biomass burning (BB), sodium and magnesium salt (SMS), fossil fuel combustion, and industrial emissions (IE)], Varanasi [SD, VE, SA, BB, SMS, coal combustion, and IE], and Kolkata [secondary sulfate (Ssulf), secondary nitrate, SD, VE, BB, SMS, IE]. However, PCA-APCS and UNMIX models identified less number of sources (besides mixed type sources) than PMF for all the sampling sites. All models identified that VE, SA, BB, and SD were the dominant contributors of PM₁₀ mass concentration over the IGP region of India.

Chemical characterization and quantitativ e assessment of source-specific health risk of trace metals in PM1.0 at a road site of Delhi, India

This study presents the concentration of submicron aerosol (PM_1.0) collected during November, 2009 to March, 2010 at two road sites near the Indian Institute of Technology Delhi campus. In winter, PM_1.0 composed 83% of PM_2.5 indicating the dominance of combustion activity-generated particles. Principal component analysis (PCA) proved secondary aerosol formation as a dominant process in enhancing aerosol concentration at a receptor site along with biomass burning, vehicle exhaust, road dust, engine and tire tear wear, and secondary ammonia. The non-carcinogenic and excess cancer risk for adults and children were estimated for trace element data set available for road site and at elevated site from another parallel work. The decrease in average hazard quotient (HQ) for children and adults was estimated in following order: Mn > Cr > Ni > Pb > Zn > Cu both at road and elevated site. For children, the mean HQs were observed in safe level for Cu, Ni, Zn, and Pb; however, values exceeded safe limit for Cr and Mn at road site. The average highest hazard index values for children and adults were estimated as 22 and 10, respectively, for road site and 7 and 3 for elevated site. The road site average excess cancer risk (ECR) risk of Cr and Ni was close to tolerable limit (10^-4) for adults and it was 13-16 times higher than the safe limit (10^-6) for children. The ECR of Ni for adults and children was 102 and 14 times higher at road site compared to elevated site. Overall, the observed ECR values far exceed the acceptable level.

Seasonal variations in size distribution, water-soluble ions, and carbon content of size-segregated aerosols over New Delhi

Size distribution, water-soluble inorganic ions (WSII), and organic carbon (OC) and elemental carbon (EC) in size-segregated aerosols were investigated during a year-long sampling in 2010 over New Delhi. Among different size fractions of PM₁₀, PM_0.95 was the dominant fraction (45%) followed by PM_3-7.2 (20%), PM_7.2-10 (15%), PM_0.95-1.5 (10%), and PM_1.5-3 (10%). All size fractions exceeded the ambient air quality standards of India for PM_2.5. Annual average mass size distributions of ions were specific to size and ion(s); Ca²⁺, Mg²⁺, K⁺, NO₃^-, and Cl^- followed bimodal distribution while SO₄^2- and NH₄⁺ ions showed one mode in PM_0.95. The concentrations of secondary WSII (NO₃^-, SO₄^2-, and NH₄⁺) increased in winters due to closed and moist atmosphere whereas open atmospheric conditions in summers lead to dispersal of pollutants. NH₄⁺and Ca²⁺were dominant neutralization ions but in different size fractions. The summer-time dust transport from upwind region by S SW winds resulted in significantly high concentrations of PM_0.95 and PM_3-7.2 and PM_7.2-10. This indicted influence of dust generation in Thar Desert and its transport is size selective in nature in downwind direction. The mixing of different sources (geogenic, coal combustions, biomass burning, plastic burning, incinerators, and vehicular emissions sources) for soluble ions in different size fractions was noticed in principle component analysis. Total carbon (TC = EC + OC) constituted 8-31% of the total PM_0.95 mass, and OC dominated over EC. Among EC, char (EC1) dominated over soot (EC2 + EC3). High SOC contribution (82%) to OC and OC/EC ratio of 2.7 suggested possible role of mineral dust and high photochemical activity in SOC production. Mass concentrations of aerosols and WSII and their contributions to each size fraction of PM₁₀ are governed by nature of sources, emission strength of source(s), and seasonality in meteorological parameters.

Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^-3 (range 25.1-429.8 μg m^-3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ∼17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.

Chemical characteristics of trace metals in PM10 and their concentrated weighted trajectory analysis at Central Delhi, India

Trace metals associated with PM₁₀ aerosols and their variation during day and nighttime as well as during different seasons have been studied for the year 2012. PCA analysis suggested 5 PCs, which accounted for 86.8% cumulative variance. PC1 accounted for 30% with a significant loading of metals of anthropogenic origin, while PC2 showed 28% variance with the loading of metals of crustal origin. These trace metals showed seasonal distinct day and night time characteristics. The concentrations of Cu, Pb, and Cd were found to be higher during nighttime in all the seasons. Only Fe was observed with significantly higher mean concentrations during daytime of all seasons except monsoon. The highest mean values of Cu, Cd, Zn, and Pb during post-monsoon might be attributed to winds advection over the regions of waste/biomass burning and industrial activities in Punjab and Haryana regions. Furthermore, concentration weighted trajectory analysis suggested that metals of crustal origin were contributed by long-range transport while metals of anthropogenic and industrial activities were contributed by regional/local source regions.

Chemical characterization of PM1.0 aerosol in Delhi and source apportionment using positive matrix factorization

Fine aerosol fraction (particulate matter with aerodynamic diameter <= 1.0 μm (PM)_1.0) over the Indian Institute of Technology Delhi campus was monitored day and night (10 h each) at 30 m height from November 2009 to March 2010. The samples were analyzed for 5 ions (NH₄⁺, NO₃^-, SO₄^2-, F^-, and Cl^-) and 12 trace elements (Na, K, Mg, Ca, Pb, Zn, Fe, Mn, Cu, Cd, Cr, and Ni). Importantly, secondary aerosol (sulfate and nitrate) formation was observed during dense foggy events, supporting the fog-smog-fog cycle. A total of 76 samples were used for source apportionment of PM mass. Six factors were resolved by PMF analyses and were identified as secondary aerosol, secondary chloride, biomass burning, soil dust, iron-rich source, and vehicular emission. The geographical location of the sources and/or preferred transport pathways was identified by conditional probability function (for local sources) and potential source contribution function (for regional sources) analyses. Medium- and small-scale metal processing (e.g. steel sheet rolling) industries in Haryana and National Capital Region (NCR) Delhi, coke and petroleum refining in Punjab, and thermal power plants in Pakistan, Punjab, and NCR Delhi were likely contributors to secondary sulfate, nitrate, and secondary chloride at the receptor site. The agricultural residue burning after harvesting season (Sept-Dec and Feb-Apr) in Punjab, and Haryana contributed to potassium at receptor site during November-December and March 2010. The soil dust from North and East Pakistan, and Rajasthan, North-East Punjab, and Haryana along with the local dust contributed to soil dust at the receptor site, during February and March 2010. A combination of temporal behavior and air parcel trajectory ensemble analyses indicated that the iron-rich source was most likely a local source attributed to emissions from metal processing facilities. Further, as expected, the vehicular emissions source did not show any seasonality and was local in origin.

Study on Airborne Heavy Metals in Industrialized Urban Area of Delhi, India

This study assessed the concentrations of airborne heavy metals (HMs) in particulate matter with a cutoff size of 10 µm (i.e., PM₁₀) in an industrialized urban area (Naraina Industrial Area) of New Delhi, India. The samples were collected from January to December, 2011. The annual mean concentrations of selected HMs were as follows As (0.002 ± 0.002), Cd (0.030 ± 0.020), Co (0.003 ± 0.002), Cr (0.170 ± 0.081), Cu (0.183 ± 0.120), Fe (4.774 ± 1.889), Mn (0.258 ± 0.145), Ni (0.170 ± 0.146), Pb (0.345 ± 0.207) and Zn (1.806 ± 1.042) µg/m³. The seasonal trend for HMs followed the order postmonsoon > winter > premonsoon > monsoon. Principal component analysis-multiple linear regression (PCA-MLR) suggested the three major emission sources: industrial emission (70 %), mobile and stationary combustion sources (16 %), and suspended/re-suspended dust (14 %). Mean seasonal concentrations of PM₁₀ exceeded both the 24-hour and annual Indian National Ambient Air Quality Standards (NAAQS) of 60 and 100 µg/m³, respectively, in all four seasons. Mean seasonal Ni concentrations in Delhi ambient air also exceeded the 24-h annual NAAQS of 0.020 µg/m³ during all four seasons. Mean Pb concentrations exceeded the annual NAAQS of 0.50 µg/m³ only during the post monsoon season. The high levels of Ni- and Pb-contaminated PM₁₀ would appear to present the possibility of significant health risks.

Spatio-temporal variation in chemical characteristics of PM10 over Indo Gangetic Plain of India

The paper presents the spatio-temporal variation of chemical compositions (organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ionic components (WSIC)) of particulate matter (PM10) over three locations (Delhi, Varanasi, and Kolkata) of Indo Gangetic Plain (IGP) of India for the year 2011. The observational sites are chosen to represent the characteristics of upper (Delhi), middle (Varanasi), and lower (Kolkata) IGP regions as converse to earlier single-station observation. Average mass concentration of PM10 was observed higher in the middle IGP (Varanasi 206.2 ± 77.4 μg m(-3)) as compared to upper IGP (Delhi 202.3 ± 74.3 μg m(-3)) and lower IGP (Kolkata 171.5 ± 38.5 μg m(-3)). Large variation in OC values from 23.57 μg m(-3) (Delhi) to 12.74 μg m(-3) (Kolkata) indicating role of formation of secondary aerosols, whereas EC have not shown much variation with maximum concentration over Delhi (10.07 μg m(-3)) and minimum over Varanasi (7.72 μg m(-3)). As expected, a strong seasonal variation was observed in the mass concentration of PM10 as well as in its chemical composition over the three locations. Principal component analysis (PCA) identifies the contribution of secondary aerosol, biomass burning, fossil fuel combustion, vehicular emission, and sea salt to PM10 mass concentration at the observational sites of IGP, India. Backward trajectory analysis indicated the influence of continental type aerosols being transported from the Bay of Bengal, Pakistan, Afghanistan, Rajasthan, Gujarat, and surrounding areas to IGP region.

Source Apportionment of PM2.5 in Delhi, India Using PMF Model

Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122 ± 94.1 µg m(-3). Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3 %), followed by soil dust (20.5 %), vehicle emissions (19.7 %), biomass burning (14.3 %), fossil fuel combustion (13.7 %), industrial emissions (6.2 %) and sea salt (4.3 %).

Exposure to particulate matter in India: A synthesis of findings and future directions

Air pollution poses a critical threat to human health with ambient and household air pollution identified as key health risks in India. While there are many studies investigating concentration, composition, and health effects of air pollution, investigators are only beginning to focus on estimating or measuring personal exposure. Further, the relevance of exposures studies from the developed countries in developing countries is uncertain. This review summarizes existing research on exposure to particulate matter (PM) in India, identifies gaps and offers recommendations for future research. There are a limited number of studies focused on exposure to PM and/or associated health effects in India, but it is evident that levels of exposure are much higher than those reported in developed countries. Most studies have focused on coarse aerosols, with a few studies on fine aerosols. Additionally, most studies have focused on a handful of cities, and there are many unknowns in terms of ambient levels of PM as well as personal exposure. Given the high mortality burden associated with air pollution exposure in India, a deeper understanding of ambient pollutant levels as well as source strengths is crucial, both in urban and rural areas. Further, the attention needs to expand beyond the handful large cities that have been studied in detail.

Source identification and metallic profiles of size-segregated particulate matters at various sites in Delhi

A study of elemental composition in the ambient air of Delhi was carried out in the monsoon, winter and summer seasons at four different sites from August 2012 to April 2013 in the size ranges <1, 1-2.5, 2.5-10 and >10 μm using "Dekati PM10" impactor. At each site, three samples were collected and were analyzed by energy-dispersive X-ray fluorescence (EDXRF). The presence of elements was found to be very common and highly concentrated in aerosol particles at all the sites, which are Na, Al, Si, K, Ca, Zn and Ba. Total suspended particulate matters (TSPMs) of fine particles were found high in comparison to coarse particles at all seasons. The TSPM of fine particles was found to be varied in the range from 303.6 to 416.2 μg/m(3). Similarly, the range of coarse TSPM was observed from 162.9 to 262.8 μg/m(3). Correlation matrices were observed between fine (size ranges <1 and 1-2.5 μm) and coarse (size ranges 2.5-10 and >10 μm) size particles for all elements with seasons. Source apportionments of elements were carried out using MS Excel 2010 through XLSTAT software. The source apportionments between fine and coarse particles were carried out through factor analysis and dominated sources found to be crustal re-suspension and industrial activities.

Temporal variability of MODIS aerosol optical depth and chemical characterization of airborne particulates in Varanasi, India

Temporal variation of airborne particulate mass concentration was measured in terms of toxic organics, metals and water-soluble ionic components to identify compositional variation of particulates in Varanasi. Information-related fine particulate mass loading and its compositional variation in middle Indo-Gangetic plain were unique and pioneering as no such scientific literature was available. One-year ground monitoring data was further compared to Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 retrieved aerosol optical depth (AOD) to identify trends in seasonal variation. Observed AOD exhibits spatiotemporal heterogeneity during the entire monitoring period reflecting monsoonal low and summer and winter high. Ground-level particulate mass loading was measured, and annual mean concentration of PM2.5 (100.0 ± 29.6 μg/m(3)) and PM10 (176.1 ± 85.0 μg/m(3)) was found to exceed the annual permissible limit (PM10: 80 %; PM2.5: 84 %) and pose a risk of developing cardiovascular and respiratory diseases. Average PM2.5/PM10 ratio of 0.59 ± 0.18 also indicates contribution of finer particulates to major variability of PM10. Particulate sample was further processed for trace metals, viz. Ca, Fe, Zn, Cu, Pb, Co, Mn, Ni, Cr, Na, K and Cd. Metals originated mostly from soil/earth crust, road dust and re-suspended dust, viz. Ca, Fe, Na and Mg were found to constitute major fractions of particulates (PM2.5: 4.6 %; PM10: 9.7 %). Water-soluble ionic constituents accounted for approximately 27 % (PM10: 26.9 %; PM2.5: 27.5 %) of the particulate mass loading, while sulphate (8.0-9.5 %) was found as most dominant species followed by ammonium (6.0-8.2 %) and nitrate (5.5-7.0 %). The concentration of toxic organics representing both aliphatic and aromatic organics was determined by organic solvent extraction process. Annual mean toxic organic concentration was found to be 27.5 ± 12.3 μg/m(3) (n = 104) which constitutes significant proportion of (PM2.5, 17-19 %; PM10, 11-20 %) particulate mass loading with certain exceptions up to 50 %. Conclusively, compositional variation of both PM2.5 and PM10 was compared to understand association of specific sources with different fractions of particulates.

Temporal Variation and Concentration Weighted Trajectory Analysis of Lead in PM10 Aerosols at a Site in Central Delhi, India

Ambient levels of lead (Pb) in PM10 were studied at a site in Central Delhi for the period of one year during day and night. The annual mean concentration of lead has been observed as 625 and 1051 ng/m3 during day and night time, respectively. The seasonal averaged concentrations of Pb have followed the order winter > postmonsoon > summer > monsoon. Highest levels of lead have been observed in winter with 31% samples exceeding the CPCB-NAAQS value as 1000 ng/m3. Lead levels during winter have been found to be 5.7 times higher than in monsoon, which might be attributed to prevailing meteorological conditions and more biomass burning. The low levels of Pb during summer might be attributed to its higher dispersion in the atmosphere. A sharp rise of Pb during postmonsoon might be linked to the local nonpoint sources, more biomass burning, and shifting of boundary layer. However, the higher concentrations of lead were observed during night time in all the seasons of the year as compared to those of the day time. To identify the potential source regions of Pb, Concentration Weighted Trajectories (CWT) have been plotted which showed higher influence of local sources during winter and postmonsoon while showing distant sources during summer.

The effect of particle size, location and season on the toxicity of urban and rural particulate matter

Particulate matter (PM) varies in chemical composition and mass concentration based on a number of factors including location, season, source and particle size. The aim of this study was to evaluate the in vitro and in vivo toxicity of coarse and fine PM simultaneously collected at three rural and two urban sites within the metropolitan New York City (NYC) region during two seasons, and to assess how particle size and elemental composition affect toxicity. Human pulmonary microvascular endothelial (HPMEC-ST1.6R) and bronchial epithelial (BEAS-2B) cell lines were exposed to PM (50 μg/mL) and analyzed for reactive oxygen species (ROS). Mice (FVB/N) were exposed by oropharyngeal aspiration to 50 µg PM, and lavage fluid was analyzed for total protein and PMN influx. The ROS response was greater in the HPMEC-ST1.6R cell line compared to BEAS-2B cells, but the responses were significantly correlated (p < 0.01). The ROS response was affected by location, locale and the location:size interaction in both cell lines, and an additional association for size was observed from HPMEC-ST1.6R cells. Urban fine PM generated the highest ROS response. In the mouse model, inflammation was associated with particle size and by a season:size interaction, with coarse PM producing greater PMN inflammation. This study showed that the aerodynamic size, locale (i.e. urban versus rural), and site of PM samples affected the ROS response in pulmonary endothelial and epithelial cells and the inflammatory response in mice. Importantly, these responses were dependent upon the chemical composition of the PM samples.

Application of zirconium-iridium permanent modifier for the simultaneous determination of lead, cadmium, arsenic, and nickel in atmospheric particulate matter by multi-element electrothermal atomic absorption spectrometry

A novel and robust method for the simultaneous determination of lead, cadmium, arsenic, and nickel in atmospheric particulate matter by multi-element electrothermal atomic absorption spectrometry was developed, using zirconium-iridium coating as permanent modifier (140 μg Zr and 4 μg Ir). After 300 atomization cycles, it was necessary to add 2 μg of Ir. Due to the varying concentrations of Pb in atmospheric particulate matter, lead was monitored at two wavelengths, at the less sensitive line of 261.4 nm for high concentration samples (>20 μg L(-1)) or at 283.3 nm for the low concentration samples. Matrix-matched calibration had to be performed for quantitative recoveries (96-102 %). Following this approach, the four elements were determined in atmospheric particulate matter samples from an industrial area near the city of Athens in two different time periods (cold-warm) with limits of detection of 5.5 ng m(-3) for Pb at 261.4 nm and 0.29 ng m(-3) at 283.3 nm, 0.019 ng m(-3) for Cd, 0.14 ng m(-3) for As, and 0.22 ng m(-3) for Ni. Lead, Cd, and As levels were very low, whereas Ni content was at comparable levels with other areas worldwide.

Monitoring of trace metals and pharmaceuticals as anthropogenic and socio-economic indicators of urban and industrial impact on surface waters

The research focuses on the monitoring of trace metals and pharmaceuticals as potential anthropogenic indicators of industrial and urban influences on surface water. This study includes analysis of tracers use for the indication of water pollution events and discussion of the detection method of these chemicals. The following criteria were proposed for the evaluation of indicators: specificity (physical chemical properties), variability (spatial and temporal), and practicality (capacity of the sampling and analytical techniques). The combination of grab and passive water sampling (i.e., diffusive gradient in the thin film and polar organic chemical integrated samplers) procedure was applied for the determination of dissolved and labile trace metals (Ag, Cd, Cr, Cu, Ni, Pb, and Zn) and pharmaceuticals (carbamazepine, diazepam, paracetamol, caffeine, diclofenac, and ketoprofen). Samples were analyzed using inductively coupled plasma mass spectrometry (MS; trace metals) and liquid chromatography-tandem MS electrospray ionization+/- (pharmaceuticals). Our results demonstrate the distinctive spatial and temporal patterns of trace elements distribution along an urban watercourse. Accordingly, two general groups of trace metals have been discriminated: "stable" (Cd and Cr) and "time varying" (Cu, Zn, Ni, and Pb). The relationship Cd >> Cu > Ag > Cr ≥ Zn was proposed as an anthropogenic signature of the industrial and urban activities pressuring the environment from point sources (municipal wastewaters) and the group Pb-Ni was discussed as a relevant fingerprint of the economic activity (industry and transport) mainly from non-point sources (runoff, atmospheric depositions, etc.). Pharmaceuticals with contrasting hydro-chemical properties of molecules (water solubility, bioaccumulation, persistence during wastewater treatment processes) were discriminated on conservative, labile, and with combined properties in order to provide information on wastewater treatment plant efficiency, punctual events (e.g., accidents on sewage works, runoff), and uncontrolled discharges. Applying mass balance modeling, medicaments were described as relevant socio-economic indicators, which can give a picture of main social aspects of the region.

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eskişehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.

Chemical characterization of PM₁₀ and PM₂.₅ mass concentrations emitted by heterogeneous traffic

In this paper, the chemical characterization of PM₁₀ and PM₂.₅ mass concentrations emitted by heterogeneous traffic in Chennai city during monsoon, winter and summer seasons were analysed. The 24-h averages of PM₁₀ and PM₂.₅ mass concentrations, showed higher concentrations during the winter season (PM₁₀=98 μg/m³; PM₂.₅=74 μg/m³) followed by the monsoon (PM₁₀=87 μg/m³; PM₂.₅=56 μg/m³) and summer (PM₁₀=77 μg/m³; PM₂.₅=67 μg/m³) seasons. The assessment of 24-h average PM₁₀ and PM₂.₅ concentrations was indicated as violation of the world health organization (WHO standard for PM₁₀=50 μg/m³ and PM₂.₅=25 μg/m³) and Indian national ambient air quality standards (NAAQS for PM₁₀=100 μg/m³ and PM₂.₅=60 μg/m³). The chemicals characterization of PM₁₀ and PM₂.₅ samples (22 samples) for each season were made for water soluble ions using Ion Chromatography (IC) and trace metals by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) instrument. Results showed the dominance of crustal elements (Ca, Mg, Al, Fe and K), followed by marine aerosols (Na and K) and trace elements (Zn, Ba, Be, Ca, Cd, Co, Cr, Cu, Mn, Ni, Pb, Se, Sr and Te) emitted from road traffic in both PM₁₀ and PM₂.₅ mass. The ionic species concentration in PM₁₀ and PM₂.₅ mass consists of 47-65% of anions and 35-53% of cations with dominance of SO₄²⁻ ions. Comparison of the metallic and ionic species in PM₁₀ and PM₂.₅ mass indicated the contributions from sea and crustal soil emissions to the coarse particles and traffic emissions to fine particles.

Measurement and modeling of concentrations of ambient air particles, chromium, copper and lead pollutants concentrations, as well as dry deposition in central Taiwan

The main purpose of this investigation was to monitor ambient air particles and metallic elements (Cr, Cu and Pb) in total suspended particulates (TSP) concentration, dry deposition. Furthermore, the calculated/measured dry deposition flux ratios of ambient air particles and metallic elements (Cr, Cu and Pb) were evaluated using three dry deposition models at five characteristic sampling sites for the 2009-2010. The results show that the average concentrations of metallic elements Cr, Cu and Pb in TSP were highest at Bei-shi (suburban/coastal) and the lowest at Gao-mei (wetland) among the five characteristic sampling sites during the years 2009-2010. This study also shows that the mean rates of dry deposition of metallic elements Cr and Cu were highest at Quan-xing (industrial) and lowest at Bei-shi (suburban/coastal) and Chang-hua (downtown). Finally, the Noll and Fang model was found to yield better predictions of the dry deposition of ambient air particles and metallic elements Cr and Cu than any of the other deposition models.