A Preliminary Assessment of the Impacts of Multiple Temporal-scale Variations in Particulate Matter on its Source Apportionment

Abstract. Time series of pollutant concentrations consist of variations at different time scales that are attributable to many processes/sources (data noise, source intensities, meteorological conditions, climate, etc.). Improving the knowledge of the impact of multiple temporal-scale components on pollutant variations and pollution levels can provide useful information for suitable mitigation strategies for pollutant control during a high pollution episode. To investigate the source factors driving these variations, the Kolmogorov-Zurbenko (KZ) filter was used to decompose the time series of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and chemical species into intra-day, diurnal, synoptic, and baseline temporal-scale components (TS components). The synoptic TS component has the largest amplitude and relative contributions (about 50 %) to the total variance of SO42−, NH4+, and OC concentrations. The diurnal TS component has the largest relative contributions to the total variance of PM2.5, NO3−, EC, Ca, and Fe concentrations, ranging from 32 % to 47 %. To investigate the source impacts on PM2.5 from different TS components, four datasets RI (intra-day removed), RD (diurnal removed), RS (synoptic removed), and RBL (baseline removed) were created by respectively removing the intra-day, diurnal, synoptic, and baseline TS component from the original datasets. Multilinear Engine 2 (ME-2) and/or principal component analysis was applied to these four datasets as well as the original datasets for source apportionment. ME-2 solutions using the original and RI dataset identify crustal dust contributions. For the solutions from original, RI, RD, and RS datasets, the total primary source impacts are close, ranging from 35.1 to 40.4 μg m−3 during the entire sampling period. For the secondary source impacts, solutions from the original, RI and RD dataset give similar source impacts (about 30 μg m−3), which were higher than the impacts derived from the RS datasets (21.2 μg m−3).

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Sources of ultrafine particles and chemical species along a traffic corridor: comparison of the results from two receptor models

Environmental Chemistry ◽

10.1071/en12149 ◽

2013 ◽

Vol 10 (1) ◽

pp. 54 ◽

Cited By ~ 11

Author(s):

Adrian J. Friend ◽

Godwin A. Ayoko ◽

Daniel Jager ◽

Megan Wust ◽

E. Rohan Jayaratne ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Chemical Composition ◽

Human Health ◽

Size Distribution ◽

Source Apportionment ◽

Chemical Species ◽

Principal Component ◽

Composition Analysis ◽

Receptor Models

Environmental context Identifying the sources responsible for air pollution is crucial for reducing the effect of the pollutants on human health. The sources of the pollutants were found here by applying two mathematical models to data consisting of particle size distribution and chemical composition data. The identified sources could be used as the basis for controlling or reducing emissions of air pollution into the atmosphere. Abstract Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. In this investigation, the sources of particles measured at two sites in Brisbane, Australia, were identified by analysing particle number size distribution data, chemical species concentrations and meteorological data with two source apportionment models. The source apportionment results obtained by positive matrix factorisation (PMF) and principal component analysis–absolute principal component scores (PCA–APCS) were compared with information from the gaseous chemical composition analysis. Although PCA–APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources were identified by both methods and these include: traffic 1, traffic 2, local traffic, biomass burning and two unassigned factors. Thus motor vehicle related activities had the greatest effect on the data with the average contribution from nearly all sources to the measured concentrations being higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology that utilised a combination of three types of data related to particulate matter to determine the sources and combination of two receptor models could assist future development of particle emission control and reduction strategies.

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Factors affecting aerosol size distribution during various dental procedures

10.1101/2021.07.30.21261399 ◽

2021 ◽

Author(s):

Shruti Choudhary ◽

Michael J Durkin ◽

Daniel C Stoeckel ◽

Heidi M Steinkamp ◽

Martin H Thornhill ◽

...

Keyword(s):

Particulate Matter ◽

High Speed ◽

High Volume ◽

Routine Care ◽

Mitigation Strategies ◽

Aerosol Size Distribution ◽

Dental Clinic ◽

Factors Affecting ◽

Dental Procedures ◽

The Impact

Objectives: To determine the impact of various aerosol mitigation interventions and establish duration of aerosol persistence in a variety of dental clinic configurations. Methods: We performed aerosol measurement studies in endodontic, orthodontic, periodontic, pediatric, and general dentistry clinics. We used an optical aerosol spectrometer and wearable particulate matter sensors to measure real-time aerosol concentration from the vantage point of the dentist during routine care in a variety of clinic configurations (e.g, open bay, single room, partitioned operatories). We compared the impact of aerosol mitigation strategies [ventilation and high-volume evacuation (HVE)] and prevalence of particulate matter in the dental clinic environment before, during and after high-speed drilling, slow speed drilling and ultrasonic scaling procedures. Results: Conical and ISOVAC HVE were superior to standard tip evacuation for aerosol-generating procedures. When aerosols were detected in the environment, they were rapidly dispersed within minutes of completing the aerosol-generating procedure. Few aerosols were detected in dental clinics, regardless of configuration, when conical and ISOVAC HVE were used. Conclusions: Dentists should consider using conical or ISOVAC HVE rather than standard tip evacuators to reduce aerosols generated during routine clinical practice. Furthermore, when such effective aerosol mitigation strategies are employed, dentists need not leave dental chairs fallow between patients as aerosols are rapidly dispersed. Clinical Significance: ISOVAC HVE is highly effective in reducing aerosol emissions. With adequate ventilation and HVE use, dental fallow time can be reduced to 5 minutes.

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CHARACTERIZATION OF AIRBORNE PARTICULATE MATTER TO ASSESS THE IMPACT ON DEGRADATION OF CULTURAL HERITAGE: THE TROPAEUM TRAIANI MONUMENT

Journal of Science and Arts ◽

10.46939/j.sci.arts-21.3-b02 ◽

2021 ◽

Vol 21 (3) ◽

pp. 807-818

Author(s):

CRISTIANA RADULESCU ◽

RODICA MARIANA ION ◽

CLAUDIA STIHI ◽

IOANA DANIELA DULAMA ◽

CRISTINA MIHAELA NICOLESCU ◽

...

Keyword(s):

Particulate Matter ◽

Airborne Particulate Matter ◽

Principal Component ◽

Physicochemical Analysis ◽

Non Invasive ◽

Four Seasons ◽

Matrix Assessment ◽

The Impact ◽

Closed Environment

The present paper is focused on the microclimatic investigation and weather-climatic phenomena matrix assessment, which can be generated for heritage objectives at different spatial and temporal resolutions, correlated with physicochemical analysis of the particulate matter (PM2.5-10). In the literature the importance of atmospheric PM monitoring in the proximity of monuments is not yet sufficiently highlighted. In this respect, the microclimatic investigation of the Tropaeum Traiani Monument (Adamclisi, Romania) was performed to assess the suitability of a closed environment, located outdoors, according to the conservation requirements of heritage materials. The monitoring campaigns (four seasons, e.g., from summer of the year 2018 to spring of the year 2019) were carried out by non-invasive measuring equipment. The collected data were used to investigate the hygrothermal and chemical behavior inside and outside of Tropaeum Traiani Monument, built in 109, to assess the risks on the oldest structural material. Principal component analysis (PCA) was performed by IBM SPSS Statistics software to assess the similarities between the microclimatic parameters.

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Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions

Geoscientific Model Development ◽

10.5194/gmd-13-1787-2020 ◽

2020 ◽

Vol 13 (4) ◽

pp. 1787-1807 ◽

Cited By ~ 2

Author(s):

Matthieu Pommier ◽

Hilde Fagerli ◽

Michael Schulz ◽

Alvaro Valdebenito ◽

Richard Kranenburg ◽

...

Keyword(s):

Particulate Matter ◽

Emission Reduction ◽

Total Concentration ◽

Large Fraction ◽

Mitigation Strategies ◽

Grid Cells ◽

Source Attribution ◽

European Cities ◽

Guideline Value ◽

The Impact

Abstract. A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline value. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a country source contribution forecasting system aimed at assessing the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0), which allows the consideration of differences in the source attribution. We also compared the PM10 concentrations, and both models present satisfactory agreement in the 4 d forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in situ observations. The correlation coefficients reach values of up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; the values are 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models underpredict the highest hourly concentrations measured by the urban stations (mean underestimation of 36 %), which is to be expected given the relatively coarse model resolution used (0.25∘ longitude × 0.125∘ latitude). For the source attribution calculations, LOTOS-EUROS uses a labelling technique, while the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions, and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 %, and 50 %) for the reduced emissions in the EMEP/MSC-W model were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. one model grid cell, nine grid cells, and grid cells covering the definition given by the Global Administrative Areas – GADM). We found that the combination of a 15 % emission reduction and a larger domain (nine grid cells or GADM) helps to preserve the linearity between emission and concentrations changes. The nonlinearity, related to the emission reduction scenario used, is suggested by the nature of the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this nonlinearity is observed in the NO3-, NH4+, and H2O concentrations, which is related to gas–aerosol partitioning of the species. The use of a 15 % emission reduction and of a larger city domain also causes better agreement on the determination of the main country contributors between both country source calculations. Over the 34 European cities investigated, PM10 was dominated by domestic emissions for the studied episode (1–9 December 2016). The two models generally agree on the dominant external country contributor (68 % on an hourly basis) to PM10 concentrations. Overall, 75 % of the hourly predicted PM10 concentrations of both models have the same top five main country contributors. Better agreement on the dominant country contributor for primary (emitted) species (70 % is found for primary organic matter (POM) and 80 % for elemental carbon – EC) than for the inorganic secondary component of the aerosol (50 %), which is predictable due to the conceptual differences in the source attribution used by both models. The country contribution calculated by the scenario approach depends on the chemical regime, which largely impacts the secondary components, unlike the calculation using the labelling approach.

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Multivariate statistic and time series analyses of grain-size data in quaternary sediments of Lake El'gygytgyn, NE Russia

Climate of the Past ◽

10.5194/cp-9-2459-2013 ◽

2013 ◽

Vol 9 (6) ◽

pp. 2459-2470 ◽

Cited By ~ 17

Author(s):

A. Francke ◽

V. Wennrich ◽

M. Sauerbrey ◽

O. Juschus ◽

M. Melles ◽

...

Keyword(s):

Time Series ◽

Grain Size ◽

Far East ◽

Principal Component ◽

Sediment Supply ◽

Multivariate Statistic ◽

Lake El’Gygytgyn ◽

Lake Center ◽

The Impact ◽

Size Data

Abstract. Lake El'gygytgyn, located in the Far East Russian Arctic, was formed by a meteorite impact about 3.58 Ma ago. In 2009, the International Continental Scientific Drilling Program (ICDP) at Lake El'gygytgyn obtained a continuous sediment sequence of the lacustrine deposits and the upper part of the impact breccia. Here, we present grain-size data of the past 2.6 Ma. General downcore grain-size variations yield coarser sediments during warm periods and finer ones during cold periods. According to principal component analysis (PCA), the climate-dependent variations in grain-size distributions mainly occur in the coarse silt and very fine silt fraction. During interglacial periods, accumulation of coarser material in the lake center is caused by redistribution of clastic material by a wind-induced current pattern during the ice-free period. Sediment supply to the lake is triggered by the thickness of the active layer in the catchment and the availability of water as a transport medium. During glacial periods, sedimentation at Lake El'gygytgyn is hampered by the occurrence of a perennial ice cover, with sedimentation being restricted to seasonal moats and vertical conduits through the ice. Thus, the summer temperature predominantly triggers transport of coarse material into the lake center. Time series analysis that was carried out to gain insight into the frequency of the grain-size data showed variations predominately on 98.5, 40.6, and 22.9 kyr oscillations, which correspond to Milankovitch's eccentricity, obliquity and precession bands. Variations in the relative power of these three oscillation bands during the Quaternary suggest that sedimentation processes at Lake El'gygytgyn are dominated by environmental variations caused by global glacial–interglacial variations (eccentricity, obliquity), and local insolation forcing and/or latitudinal teleconnections (precession), respectively.

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Challenges in estimating the impact of vaccination with sparse data

10.1101/302224 ◽

2018 ◽

Author(s):

Kayoko Shioda ◽

Cynthia Schuck-Paim ◽

Robert J. Taylor ◽

Roger Lustig ◽

Lone Simonsen ◽

...

Keyword(s):

Time Series ◽

Time Series Data ◽

Simulation Analysis ◽

Principal Component ◽

Population Level ◽

Series Data ◽

Synthetic Control ◽

Vaccine Impact ◽

Pca Method ◽

The Impact

ABSTRACTBackgroundThe synthetic control (SC) model is a powerful tool to quantify the population-level impact of vaccines, because it can adjust for trends unrelated to vaccination using a composite of control diseases. Because vaccine impact studies are often conducted using smaller subnational datasets, we evaluated the performance of SC models with sparse time series data. To obtain more robust estimates of vaccine effects from noisy time series, we proposed a possible alternative approach, “STL+PCA” method (seasonal-trend decomposition plus principal component analysis), which first extracts smoothed trends from the control time series and uses them to adjust the outcome.MethodsUsing both the SC and STL+PCA models, we estimated the impact of 10-valent pneumococcal conjugate vaccine (PCV10) on pneumonia hospitalizations among cases <12 months and 80+ years of age during 2004-2014 at the subnational level in Brazil. The performance of these models was also compared using simulation analyses.ResultsThe SC model was able to adjust for trends unrelated to PCV10 in larger states but not in smaller states. The simulation analysis confirmed that the SC model failed to select an appropriate set of control diseases when the time series were sparse and noisy, thereby generating biased estimates of the impact of vaccination when secular trends were present. The STL+PCA approach decreased bias in the estimates for smaller populations.ConclusionsEstimates from the SC model might be biased when data are sparse. The STL+PCA model provides more accurate evaluations of vaccine impact in smaller populations.

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Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182111608 ◽

2021 ◽

Vol 18 (21) ◽

pp. 11608

Author(s):

Worku Tefera ◽

Abera Kumie ◽

Kiros Berhane ◽

Frank Gilliland ◽

Alexandra Lai ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Source Apportionment ◽

Biomass Burning ◽

Addis Ababa ◽

Atmospheric Particulate Matter ◽

Motor Vehicles ◽

Soil Dust ◽

Rain Season ◽

The Impact

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June–September) and short rain season (February–April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public’s health.

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Use of multivariate time series techniques to estimate the impact of particulate matter on the perceived annoyance

Atmospheric Environment ◽

10.1016/j.atmosenv.2019.117080 ◽

2020 ◽

Vol 222 ◽

pp. 117080 ◽

Cited By ~ 1

Author(s):

Milena Machado ◽

Valdério Anselmo Reisen ◽

Jane Meri Santos ◽

Neyval Costa Reis Junior ◽

Severine Frère ◽

...

Keyword(s):

Time Series ◽

Particulate Matter ◽

Multivariate Time Series ◽

The Impact

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Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 – Part.1 The country contributions

10.5194/gmd-2019-87 ◽

2019 ◽

Author(s):

Matthieu Pommier ◽

Hilde Fagerli ◽

Michael Schulz ◽

Alvaro Valdebenito ◽

Richard Kranenburg ◽

...

Keyword(s):

Particulate Matter ◽

Total Concentration ◽

Large Fraction ◽

Correlation Coefficients ◽

Grid Cell ◽

Primary Component ◽

Mitigation Strategies ◽

Grid Cells ◽

European Cities ◽

The Impact

Abstract. A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a source apportionment forecasting system aimed to assess the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0) which allows to consider differences in the source attribution. We also compared the PM10 concentrations and both models present satisfactory agreement in the 4day-forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in-situ observations. The correlation coefficients reach values up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; and 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models under-predict the highest hourly concentrations measured by the urban stations (mean underestimation by 36 %), predictable with the relatively coarse model resolution used (0.25° longitude × 0.125° latitude). For the source receptor calculations, the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 % and 50 %) in the reduced emissions were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. 1 model grid cell, 9 grid cells and the grid cells covering the definition given by the Global Administrative Area – GADM). We found that by combining the use of the 15 % factor and of a larger domain for the city edges (9 grid cells or GADM), it helps to reduce the impact of non-linearity on the chemistry which is seen in the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this non-linearity is observed in the NO3−, NH4+ and H2O concentrations, which is related to gas-aerosol partitioning of the species. The use of a 15 % factor and of a larger city domain also gives a better agreement in the determination of the main country contributors between both country source receptor calculations. During the studied episode, dominated by the influence of the domestic emissions for the 34 European cities investigated and occurring from December 01st to 09th 2016, the two models agree 68 % of the time (on hourly resolution) on the country, having been the dominant contributor to PM10 concentrations. 75 % of the hourly predicted PM10 concentrations by both models, have the same top 5 main country contributors. Better results are found in the determination the dominant country contributor for the primary component (70 % for POM and 80 % for EC) than for the secondary inorganic aerosols (50 %).

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Effect of socioeconomic status on the association between air pollution and mortality in Bogota, Colombia

Salud Pública de México ◽

10.21149/spm.v56i4.7357 ◽

2014 ◽

Vol 56 (4) ◽

pp. 371 ◽

Cited By ~ 3

Author(s):

Luis Camilo Blanco-Becerra ◽

Víctor Miranda-Soberanis ◽

Albino Barraza-Villarreal ◽

Washington Junger ◽

Magali Hurtado-Díaz ◽

...

Keyword(s):

Air Pollution ◽

Socioeconomic Status ◽

Time Series ◽

Particulate Matter ◽

Ecological Study ◽

Aerodynamic Diameter ◽

Components Analysis ◽

The Impact ◽

The Relationship ◽

Respiratory Causes

Objective. To evaluate the modification effect of socioeconomic status (SES) on the association between acute exposure to particulate matter less than 10 microns in aerodynamic diameter (PM10) and mortality in Bogota, Colombia. Materials and methods. A time-series ecological study was conducted (1998-2006). The localities of the cities were stratified using principal components analysis, creating three levels of aggregation that allowed for the evaluation of the impact of SES on the relationship between mortality and air pollution. Results. For all ages, the change in the mortality risk for all causes was 0.76% (95%CI 0.27-1.26) for SES I (low), 0.58% (95%CI 0.16-1.00) for SES II (mid) and -0.29% (95%CI -1.16-0.57) for SES III (high) per 10µg/m3 increment in the daily average of PM10 on day of death. Conclusions. The results suggest that SES significantly modifies the effect of environmental exposure to PM10 on mortality from all causes and respiratory causes.

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