scholarly journals PM<sub>1</sub> composition and source apportionment at two sites in Delhi, India across multiple seasons

2020 ◽  
Author(s):  
Ernesto Reyes-Villegas ◽  
Upasana Panda ◽  
Eoghan Darbyshire ◽  
James M. Cash ◽  
Rutambhara Joshi ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Organic Aerosols ◽  
India Meteorological Department ◽  
Urban Environments ◽  
Traffic Emissions ◽  
Significant Information ◽  
Post Monsoon ◽  
Significant Difference ◽  
Aerosol Source

Abstract. Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as result of anthropogenic activities. Organic aerosols (OA) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, which we would expect that the apportionment and concentrations will vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need of multi-site measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulphate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of VOC, black carbon, NOx and CO were performed. Positive matrix factorization (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OA (HOA) related to traffic emissions, biomass burning OA (BBOA), cooking OA (COA) and secondary OA (SOA). A composition-based estimate of PM1 is defined by combining BC and NR-PM1 (C-PM1 = BC + NR-PM1). No significant difference was observed on C-PM1 concentrations between sites; OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m−3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42− showed a high contribution over pre-monsoon and monsoon seasons while NO3− and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls traffic emissions control offers the greatest opportunity. PMF-AMS mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

scholarly journals PM<sub>1</sub> composition and source apportionment at two sites in Delhi, India, across multiple seasons

2021 ◽  
Vol 21 (15) ◽  
pp. 11655-11667
Author(s):  
Ernesto Reyes-Villegas ◽  
Upasana Panda ◽  
Eoghan Darbyshire ◽  
James M. Cash ◽  
Rutambhara Joshi ◽  
...  
Keyword(s):  
Air Quality ◽  
Black Carbon ◽  
Source Apportionment ◽  
Organic Aerosols ◽  
Urban Environments ◽  
Significant Information ◽  
Post Monsoon ◽  
Aerosol Mass ◽  
Significant Difference ◽  
Aerosol Source

Abstract. Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

scholarly journals Organic aerosol source apportionment by offline-AMS over a full year in Marseille

2017 ◽  
Author(s):  
Carlo Bozzetti ◽  
Imad El Haddad ◽  
Dalia Salameh ◽  
Kaspar Rudolf Daellenbach ◽  
Paola Fermo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Mediterranean Sea ◽  
Source Apportionment ◽  
Organic Aerosol ◽  
Aerodynamic Diameter ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Aerosol Source

Abstract. We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France) which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). PM2.5 (particulate matter with an aerodynamic diameter

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

scholarly journals Source Apportionment of Fine Organic and Inorganic Atmospheric Aerosol in an Urban Background Area in Greece

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 330 ◽  
Author(s):  
Manousos Ioannis Manousakas ◽  
Kalliopi Florou ◽  
Spyros N. Pandis
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Fine Particulate Matter ◽  
Organic Aerosols ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Aerosol Mass ◽  
Aerosol Mass Spectrometry ◽  
Five Factors ◽  
Potential Risks

Fine particulate matter (PM) originates from various emission sources and physicochemical processes. Quantification of the sources of PM is an important step during the planning of efficient mitigation strategies and the investigation of the potential risks to human health. Usually, source apportionment studies focus either on the organic or on the inorganic fraction of PM. In this study that took place in Patras, Greece, we address both PM fractions by combining measurements from a range of on- and off-line techniques, including elemental composition, organic and elemental carbon (OC and EC) measurements, and high-resolution Aerosol Mass Spectrometry (AMS) from different techniques. Six fine PM2.5 sources were identified based on the off-line measurements: secondary sulfate (34%), biomass burning (15%), exhaust traffic emissions (13%), nonexhaust traffic emissions (12%), mineral dust (10%), and sea salt (5%). The analysis of the AMS spectra quantified five factors: two oxygenated organic aerosols (OOA) factors (an OOA and a marine-related OOA, 52% of the total organic aerosols (OA)), cooking OA (COA, 11%) and two biomass burning OA (BBOA-I and BBOA-II, 37% in total) factors. The results of the two methods were synthesized, showcasing the complementarity of the two methodologies for fine PM source identification. The synthesis suggests that the contribution of biomass burning is quite robust, but that the exhaust traffic emissions are not due to local sources and may also include secondary OA from other sources.

scholarly journals Subtle Changes or Dramatic Perceptions of Air Pollution in Sydney during COVID-19

Environments ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 2
Author(s):  
Peter Brimblecombe ◽  
Yonghang Lai
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
New South ◽  
Human Mobility ◽  
Ground Level ◽  
Physical Reality ◽  
Social Perceptions ◽  
Search Terms ◽  
South Wales ◽  
Significant Difference

The COVID-19 pandemic made it critical to limit the spread of the disease by enforcing human isolation, restricting travel and reducing social activities. Dramatic improvements to air quality, especially NO2, have often characterised places under COVID-19 restrictions. Air pollution measurements in Sydney in April 2019 and during the lockdown period in April 2020 show reduced daily averaged NO2 concentrations: 8.52 ± 1.92 and 7.85 ± 2.92 ppb, though not significantly so (p1~0.15) and PM2.5 8.91 ± 4.94 and 7.95 ± 2.64 µg m−3, again a non-significant difference (p1~0.18). Satellite imagery suggests changes that parallel those at ground level, but the column densities averaged over space and time, in false-colour, are more dramatic. Changed human mobility could be traced in increasing times spent at home, assessed from Google Mobility Reports and mirrored in decreased traffic flow on a major road, suggesting compliance with the restrictions. Electricity demand for the State of New South Wales was low under lockdown in early April 2020, but it recovered rapidly. Analysis of the uses of search terms: bushfires, air quality, haze and air pollution using Google Trends showed strong links between bushfires and pollution-related terms. The smoke from bushfires in late 2019 may well have added to the general impression of improved air quality during lockdown, despite only modest changes in the ground level measurements. This gives hints that successful regulation of air quality requires maintaining a delicate balance between our social perceptions and the physical reality.

scholarly journals Assessment of Seasonal Variability in Soil Nutrients and Its Impact on Soil Quality under Different Land Use Systems of Lower Shiwalik Foothills of Himalaya, India

2021 ◽  
Vol 13 (3) ◽  
pp. 1398
Author(s):  
Tavjot Kaur ◽  
Simerpreet Kaur Sehgal ◽  
Satnam Singh ◽  
Sandeep Sharma ◽  
Salwinder Singh Dhaliwal ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Quality ◽  
Surface Soil ◽  
Sandy Loam ◽  
Monsoon Season ◽  
Soil Layer ◽  
Seasonal Effects ◽  
Land Use Systems ◽  
Post Monsoon ◽  
Significant Difference

The present study was conducted to investigate the seasonal effects of five land use systems (LUSs), i.e., wheat–rice (Triticum aestivum—Oryza sativa) system, sugarcane (Saccharum officinarum), orange (Citrus sinensis) orchard, safeda (Eucalyptus globules) forest, and grassland, on soil quality and nutrient status in the lower Satluj basin of the Shiwalik foothills Himalaya, India. Samples were analyzed for assessment of physico-chemical properties at four soil depths, viz., 0–15, 15–30, 30–45, and 45–60 cm. A total of 120 soil samples were collected in both the seasons. Soil texture was found to be sandy loam and slightly alkaline in nature. The relative trend of soil organic carbon (SOC), macro- and micro-nutrient content for the five LUSs was forest > orchard > grassland > wheat–rice > sugarcane, in the pre- and post-monsoon seasons. SOC was highly correlated with macronutrients and micronutrients, whereas SOC was negatively correlated with soil pH (r = −0.818). The surface soil layer (0–15 cm) had a significantly higher content of SOC, and macro- and micro-nutrients compared to the sub-surface soil layers, due to the presence of more organic content in the soil surface layer. Tukey’s multiple comparison test was applied to assess significant difference (p < 0.05) among the five LUSs at four soil depths in both the seasons. Principle component analysis (PCA) identified that SOC and electrical conductivity (EC) were the most contributing soil indicators among the different land use systems, and that the post-monsoon season had better soil quality compared to the pre-monsoon season. These indicators helped in the assessment of soil health and fertility, and to monitor degraded agroecosystems for future soil conservation.

scholarly journals Regional Scale Impact of the COVID-19 Lockdown on Air Quality: Gaseous Pollutants in the Po Valley, Northern Italy

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 264 ◽  
Author(s):  
Giovanni Lonati ◽  
Federico Riva
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Regional Scale ◽  
High Volume ◽  
Ambient Air ◽  
Northern Italy ◽  
Traffic Emissions ◽  
Gaseous Pollutants ◽  
Po Valley ◽  
Concentration Levels

The impact of the reduced atmospheric emissions due to the COVID-19 lockdown on ambient air quality in the Po Valley of Northern Italy was assessed for gaseous pollutants (NO2, benzene, ammonia) based on data collected at the monitoring stations distributed all over the area. Concentration data for each month of the first semester of 2020 were compared with those of the previous six years, on monthly, daily, and hourly bases, so that pre, during, and post-lockdown conditions of air quality could be separately analyzed. The results show that, as in many other areas worldwide, the Po Valley experienced better air quality during 2020 spring months for NO2 and benzene. In agreement with the reductions of nitrogen oxides and benzene emissions from road traffic, estimated to be −35% compared to the regional average, the monthly mean concentration levels for 2020 showed reductions in the −40% to −35% range compared with the previous years, but with higher reductions, close to −50%, at high-volume-traffic sites in urban areas. Conversely, NH3 ambient concentration levels, almost entirely due the emissions of the agricultural sector, did not show any relevant change, even at high-volume-traffic sites in urban areas. These results point out the important role of traffic emissions in NO2 and benzene ambient levels in the Po Valley, and confirm that this region is a rather homogeneous air basin with urban area hot-spots, the contributions of which add up to a relatively high regional background concentration level. Additionally, the relatively slow response of the air quality levels to the sudden decrease of the emissions due to the lockdown shows that this region is characterized by a weak exchange of the air masses that favors both the build-up of atmospheric pollutants and the development of secondary formation processes. Thus, air quality control strategies should aim for structural interventions intended to reduce traffic emissions at the regional scale and not only in the largest urban areas.

scholarly journals Development of PM<sub>2.5</sub> source impact spatial fields using a hybrid source apportionment air quality model

2015 ◽  
Vol 8 (7) ◽  
pp. 2153-2165 ◽  
Author(s):  
C. E. Ivey ◽  
H. A. Holmes ◽  
Y. T. Hu ◽  
J. A. Mulholland ◽  
A. G. Russell
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Large Scale ◽  
Major Ions ◽  
Current Knowledge ◽  
Direct Method ◽  
Hybrid Approach ◽  
Sensitivity Analyses ◽  
Adjustment Factors ◽  
The Impact

Abstract. An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). There is also a growing desire to directly use source impact estimates in health studies; however, source impacts cannot be directly measured. Several limitations are inherent in most source apportionment methods motivating the development of a novel hybrid approach that is used to estimate source impacts by combining the capabilities of receptor models (RMs) and chemical transport models (CTMs). The hybrid CTM–RM method calculates adjustment factors to refine the CTM-estimated impact of sources at monitoring sites using pollutant species observations and the results of CTM sensitivity analyses, though it does not directly generate spatial source impact fields. The CTM used here is the Community Multiscale Air Quality (CMAQ) model, and the RM approach is based on the chemical mass balance (CMB) model. This work presents a method that utilizes kriging to spatially interpolate source-specific impact adjustment factors to generate revised CTM source impact fields from the CTM–RM method results, and is applied for January 2004 over the continental United States. The kriging step is evaluated using data withholding and by comparing results to data from alternative networks. Data withholding also provides an estimate of method uncertainty. Directly applied (hybrid, HYB) and spatially interpolated (spatial hybrid, SH) hybrid adjustment factors at withheld observation sites had a correlation coefficient of 0.89, a linear regression slope of 0.83 ± 0.02, and an intercept of 0.14 ± 0.02. Refined source contributions reflect current knowledge of PM emissions (e.g., significant differences in biomass burning impact fields). Concentrations of 19 species and total PM2.5 mass were reconstructed for withheld observation sites using HYB and SH adjustment factors. The mean concentrations of total PM2.5 at withheld observation sites were 11.7 (± 8.3), 16.3 (± 11), 8.59 (± 4.7), and 9.2 (± 5.7) μg m−3 for the observations, CTM, HYB, and SH predictions, respectively. Correlations improved for concentrations of major ions, including nitrate (CMAQ–DDM (decoupled direct method): 0.404, SH: 0.449), ammonium (CMAQ–DDM: 0.454, SH: 0.492), and sulfate (CMAQ–DDM: 0.706, SH: 0.730). Errors in simulated concentrations of metals were reduced considerably: 295 % (CMAQ–DDM) to 139 % (SH) for vanadium; and 1340 % (CMAQ–DDM) to 326 % (SH) for manganese. Errors in simulated concentrations of some metals are expected to remain given the uncertainties in source profiles. Species concentrations were reconstructed using SH results, and the error relative to observed concentrations was greatly reduced as compared to CTM-simulated concentrations. Results demonstrate that the hybrid method along with a spatial extension can be used for large-scale, spatially resolved source apportionment studies where observational data are spatially and temporally limited.

scholarly journals Chemical characterization of fine particular matter in Changzhou, China and source apportionment with offline aerosol mass spectrometry

2016 ◽  
Author(s):  
Zhaolian Ye ◽  
Jiashu Liu ◽  
Aijun Gu ◽  
Feifei Feng ◽  
Yuhai Liu ◽  
...  
Keyword(s):  
Trace Elements ◽  
Organic Matter ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Major Ions ◽  
Chemical Properties ◽  
Chemical Characterization ◽  
Water Soluble ◽  
Traffic Emissions ◽  
Aerosol Mass

Abstract. Knowledge on aerosol chemistry in densely populated regions is critical for reduction of air pollution, while such studies haven't been conducted in Changzhou, an important manufacturing base and polluted city in the Yangtze River Delta (YRD), China. This work, for the first time, performed a thorough chemical characterization on the fine particular matter (PM2.5) samples, collected during July 2015 to April 2016 across four seasons in Changzhou city. A suite of analytical techniques were employed to characterize organic carbon / elemental carbon (OC / EC), water-soluble organic carbon (WSOC), water-soluble inorganic ions (WSIIs), trace elements, and polycyclic aromatic hydrocarbons (PAHs) in PM2.5; in particular, an Aerodyne soot particle aerosol mass spectrometer (SP-AMS) was deployed to probe the chemical properties of water-soluble organic aerosols (WSOA). The average PM2.5 concentrations were found to be 108.3 μg m−3, and all identified species were able to reconstruct ~ 80 % of the PM2.5 mass. The WSIIs occupied about half of the PM2.5 mass (~ 52.1 %), with SO42−, NO3− and NH4+ as the major ions. On average, nitrate concentrations dominated over sulfate (mass ratio of 1.21), indicating influences from traffic emissions. OC and EC correlated well with each other and the highest OC / EC ratio (5.16) occurred in winter, suggesting complex OC sources likely including both secondarily formed and primarily emitted OA. Concentrations of eight trace elements (Mn, Zn, Al, B, Cr, Cu, Fe, Pb) can contribute up to 6.0 % of PM2.5 during winter. PAHs concentrations were also high in winter (140.25 ng m−3), which were predominated by median/high molecular weight PAHs with 5- and 6-rings. The organic matter including both water-soluble and water-insoluble species occupied ~ 20 % PM2.5 mass. SP-AMS determined that the WSOA had an average atomic oxygen-to-carbon (O / C), hydrogen-to-carbon (H / C), nitrogen-to-carbon (N / C) and organic matter-to-organic carbon (OM / OC) ratios of 0.36, 1.54, 0.11, and 1.74, respectively. Source apportionment of WSOA further identified two secondary OA (SOA) factors (a less oxidized and a more oxidized OA) and two primary OA (POA) factors (a nitrogen enriched hydrocarbon-like traffic OA and a cooking-related OA). On average, the POA contribution overweighed SOA (55 % vs. 45 %), indicating the important role of local anthropogenic emissions to the aerosol pollution in Changzhou. Our measurement also shows the abundance of organic nitrogen species in WSOA, and the source analyses suggest these species likely associated with traffic emissions, which warrants more investigations on PM samples from other locations.

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