scholarly journals Air Particulate Matter in Pollluted New Zealand Urban Environments: Sources, Patterns and Transport

2021 ◽  
Author(s):  
◽  
Travis Ancelet
Keyword(s):  
Particulate Matter ◽  
New Zealand ◽  
Biomass Burning ◽  
Time Scale ◽  
Ion Beam ◽  
Urban Environments ◽  
Marine Aerosol ◽  
Wood Combustion ◽  
Dominant Source ◽  
Katabatic Flows

<p>During the winters of 2010 and 2011, three intensive particulate matter (PM) monitoring campaigns were undertaken in Masterton, Alexandra and Nelson, New Zealand. The goal of these campaigns was, for the first time, to identify the sources and factors contributing to elevated PM concentrations on an hourly time-scale. In each location, hourly coarse (PM₁₀-₂.₅; particles with aerodynamic diameters 2.5 μm < d < 10 μm) and fine (PM₂.₅; particles with aerodynamic diameters < 2.5 μm) samples, PM₁₀ (particles with aerodynamic diameters < 10 μm, incorporating the coarse and fine fractions) concentrations and meteorological variables were collected from a number of sites. Using elemental concentrations determined from ion beam analysis and black carbon concentrations determined from light reflection for each hourly sample, PM sources and their contributions on an hourly time-scale were identified using positive matrix factorization (PMF). In Masterton, where two sampling sites were employed, PM₁₀ concentrations displayed distinct diurnal cycles, with peak concentrations occurring in the evening (7 pm–midnight) and in the morning (7–9 am). Four PM sources were identified (biomass burning, marine aerosol, crustal matter and vehicles) at each of the sites and biomass burning was identified as the most dominant source of PM₁₀ during both the evening and morning. One of the sites experienced consistently higher PM₁₀ concentrations and katabatic flows across Masterton were identified to be the main contributor to this phenomenon. In Alexandra and Nelson, three sampling sites on a horizontal transect (upwind, central and downwind of the general katabatic flow pathway) and a fourth site located centrally, but at a height of 26 m, were incorporated in a novel study design. Each of the sites in Alexandra and Nelson also showed diurnal patterns in PM₁₀ concentrations. The central site in Alexandra experienced consistently higher PM₁₀ concentrations and four PM₁₀ sources were identified at each of the sites (biomass burning, marine aerosol, vehicles and crustal matter). Biomass burning was identified as the main source of PM₁₀ throughout the day at each of the sites. The convergence of numerous katabatic flows was identified as the contributing factor to the elevated PM₁₀ concentrations measured at the central site. In Nelson, five PM sources were identified at each of the sites (biomass burning, vehicles, marine aerosol, shipping sulfate and crustal matter) and biomass burning was identified as the dominant source of PM₁₀ throughout the day. Katabatic flows were also identified to play an important role in PM₁₀ transport. Analyses of source-specific (wood combustion and vehicles) PM samples was also undertaken, and the results of these analyses are included in this thesis.</p>

scholarly journals Air Particulate Matter in Pollluted New Zealand Urban Environments: Sources, Patterns and Transport

2021 ◽  
Author(s):  
◽  
Travis Ancelet
Keyword(s):  
Particulate Matter ◽  
New Zealand ◽  
Biomass Burning ◽  
Time Scale ◽  
Ion Beam ◽  
Urban Environments ◽  
Marine Aerosol ◽  
Wood Combustion ◽  
Dominant Source ◽  
Katabatic Flows

<p>During the winters of 2010 and 2011, three intensive particulate matter (PM) monitoring campaigns were undertaken in Masterton, Alexandra and Nelson, New Zealand. The goal of these campaigns was, for the first time, to identify the sources and factors contributing to elevated PM concentrations on an hourly time-scale. In each location, hourly coarse (PM₁₀-₂.₅; particles with aerodynamic diameters 2.5 μm < d < 10 μm) and fine (PM₂.₅; particles with aerodynamic diameters < 2.5 μm) samples, PM₁₀ (particles with aerodynamic diameters < 10 μm, incorporating the coarse and fine fractions) concentrations and meteorological variables were collected from a number of sites. Using elemental concentrations determined from ion beam analysis and black carbon concentrations determined from light reflection for each hourly sample, PM sources and their contributions on an hourly time-scale were identified using positive matrix factorization (PMF). In Masterton, where two sampling sites were employed, PM₁₀ concentrations displayed distinct diurnal cycles, with peak concentrations occurring in the evening (7 pm–midnight) and in the morning (7–9 am). Four PM sources were identified (biomass burning, marine aerosol, crustal matter and vehicles) at each of the sites and biomass burning was identified as the most dominant source of PM₁₀ during both the evening and morning. One of the sites experienced consistently higher PM₁₀ concentrations and katabatic flows across Masterton were identified to be the main contributor to this phenomenon. In Alexandra and Nelson, three sampling sites on a horizontal transect (upwind, central and downwind of the general katabatic flow pathway) and a fourth site located centrally, but at a height of 26 m, were incorporated in a novel study design. Each of the sites in Alexandra and Nelson also showed diurnal patterns in PM₁₀ concentrations. The central site in Alexandra experienced consistently higher PM₁₀ concentrations and four PM₁₀ sources were identified at each of the sites (biomass burning, marine aerosol, vehicles and crustal matter). Biomass burning was identified as the main source of PM₁₀ throughout the day at each of the sites. The convergence of numerous katabatic flows was identified as the contributing factor to the elevated PM₁₀ concentrations measured at the central site. In Nelson, five PM sources were identified at each of the sites (biomass burning, vehicles, marine aerosol, shipping sulfate and crustal matter) and biomass burning was identified as the dominant source of PM₁₀ throughout the day. Katabatic flows were also identified to play an important role in PM₁₀ transport. Analyses of source-specific (wood combustion and vehicles) PM samples was also undertaken, and the results of these analyses are included in this thesis.</p>

AIR PARTICULATE RESEARCH CAPABILITY AT THE NEW ZEALAND ION BEAM ANALYSIS FACILITY USING PIXE AND IBA TECHNIQUES

2005 ◽  
Vol 15 (03n04) ◽  
pp. 249-255 ◽  
Author(s):  
W. J. TROMPETTER ◽  
A. MARKWITZ ◽  
P. DAVY
Keyword(s):  
Particulate Matter ◽  
New Zealand ◽  
Limit Of Detection ◽  
Ion Beam ◽  
Anthropogenic Sources ◽  
Ion Beam Analysis ◽  
Air Particulate Matter ◽  
X Ray ◽  
Air Particulate ◽  
Beam Analysis

PIXE and Ion Beam Analysis are one of the few techniques that can be used to identify the elemental composition of air particulates without destroying the filter sample. They are key tools for identifying the sources and determining the relative contribution of biogenic and anthropogenic sources of air particulate matter pollution in our environment. Over the last 8 years, specialised equipment has been designed and built at the New Zealand Ion Beam Analysis facility in Lower Hutt for semi automated analysis of air filters. The equipment and experimental techniques have been refined to improve sensitivities for many of the elements in the periodic table. At GNS, sensitivities have recently been further improved by using two X-ray detectors simultaneously with different amounts of X-ray filtering and collimation. The average limit of detection is improved from 66 ng/cm2 (typical for a setup using a single detector) to 35 ng/cm2 using two detectors simultaneously. The New Zealand Ion Beam Analysis facility now routinely analyses air particulate matter collected on filters from several locations around New Zealand. In this paper, results of air particulate studies from several locations in the Wellington region are presented.

scholarly journals Atmospheric Monitoring of PM₂.₅, PM₁₀₋₂.₅, PM₁₀, Arsenic and Carbonaceous Aerosol at Wainuiomata

2021 ◽  
Author(s):  
◽  
Chandar Singh
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Biomass Burning ◽  
Limit Of Detection ◽  
Ion Beam ◽  
Ambient Air ◽  
Guideline Value ◽  
Treated Timber ◽  
Gf Aas

<p>Air pollution is harming our health and that of our children and parents. Air pollution causes many harmful effects, ranging from premature death, to headaches, coughing and asthma attacks. Previous studies (2008-2009) of particulate matter at Wainuiomata, Lower Hutt showed that biomass burning was primarily responsible for peak PM₂.₅ and PM₁₀ concentrations and exceedances of the National Environmental Standard (NES) and the New Zealand Ambient Air Quality Guidelines (NZAAQG). Arsenic was also found to be associated with biomass burning sources during winter at Wainuiomata. The source of arsenic was considered to be due to the use of copper chromium arsenate (CCA) treated timber as solid fuel for fires for domestic heating. While particulate matter pollution from domestic fires itself presents a health risk for the exposed population, the addition of arsenic to the mix enhances the potential risk. The use of CCA treated timber was unlikely to be used on a regular basis hence the peak arsenic concentrations did not always coincide with peak contributions from domestic fires and that the use of CCA – treated timber is more intermittent and opportunistic.  This work compared several different analytical methodologies for the determination of arsenic in air particulate matter. The primary purpose was to use a standard analytical method as recommended by the NZAAQ guidelines and compare those results with the Ion Beam Analysis (IBA) and X-ray Fluorescence Spectroscopy (XRF) methods used to determine arsenic concentrations in previous studies.  Through this collaborative research with GNS Science and GWRC, it was found that annual PM₁₀ and PM₂.₅ averages were well within the NZAAQG values of; 20 μg m⁻³ and 10 μg m⁻³ respectively. There was a much correlated seasonal and temporal variations observed for black carbon (BC), PM₂.₅ and arsenic concentrations. The overall concentrations of BC, PM₂.₅ and PM₁₀ have decreased significantly in the Wainuiomata airshed compared to previous studies as reported in 2009 with fewer exceedances of the NES and NZAAQG on a 24 hour daily average.  The overall weighted mean arsenic concentration as measured by GF-AAS was 6.3 ± 0.8 ng m⁻³ and that measured by XRF and IBA was 3.8 ± 2.0 ng m⁻³ and 3.1 ± 5.9 ng m⁻³ respectively. The XRF and IBA arsenic concentrations were consistently lower than that of GF-AAS. The two annual arsenic averages (GF-AAS) were 6.5 ± 0.9 ng m⁻³ and 5.9 ± 0.7 ng m⁻³ respectively, for the entire sampling period. In both the cases the NZAAQG value of 5.5 ng m⁻³ were exceeded. The exceedance in the second year of sampling was not statistically significant as the guideline value 5.5 ngm⁻³ falls within the given uncertainty of the measured annual averages for arsenic.  However, it is definitely an area of concern as the overall arsenic concentrations during winter periods was 12.2 ± 1.0 ng m⁻³. Moreover, burning CCA treated timber is effectively banned through regional plan rules and the problem presents itself as one of enforcement and/or public education.  The inter-method comparison showed that IBA technique can be used for “screening” purposes due to high limit of detection (LOD) and analytical noise. While XRF can still be used interchangeably with GF-AAS but with Teflon or thinner filter membrane, for long term environmental monitoring of arsenic and other elemental compositions. Given the excellent recoveries of 99.2 ± 0.8% for duplicate spiked analysis and 102.7 ± 0.9% for lab blank filters spiked analysis, at 95% confidence intervals, GF-AAS method is highly reproducible and should be used in the determination of arsenic in ambient air for the purpose of comparing with the NZAAQG values.</p>

ELEMENTAL ANALYSIS AND SOURCE APPORTIONMENT OF AMBIENT PARTICULATE MATTER AT MASTERTON, NEW ZEALAND

2005 ◽  
Vol 15 (03n04) ◽  
pp. 225-231 ◽  
Author(s):  
P. DAVY ◽  
W. J. TROMPETTER ◽  
A. MARKWITZ ◽  
D. C. WEATHERBURN
Keyword(s):  
Particulate Matter ◽  
New Zealand ◽  
Elemental Composition ◽  
Ion Beam ◽  
Airborne Particulate Matter ◽  
Gravimetric Analysis ◽  
Air Particulate Matter ◽  
Air Particulate ◽  
Beam Analysis ◽  
Light Reflectance

At certain locations in the Wellington Region, pollution episodes due to air particulate matter are known to occur from time to time. Traditional gravimetric analysis of airborne particulate matter is unable to provide information on the sources contributing to air particulate concentrations. Ion Beam Analysis (IBA) is one of the few non-destructive techniques that can be used to identify the elemental composition of air particulate matter on a filter sample. In this work IBA was used to characterise air particulate matter in two size fractions, PM 20. and PM 10-2.0, collected at a monitoring station in Masterton, New Zealand. Elements with atomic mass above neon were measured by the PIXE technique. Elemental carbon was measured with a light reflectance device. Elemental 'fingerprints' of contributing sources were determined by performing factor analysis of the elemental composition. The results indicate that 'Sea Salt' and 'Soil' sources are major contributors to the coarse ( PM 10-2.0) fraction and 'Combustion' sources dominate the fine ( PM 2.0) fraction of air particulate matter. Analysis of seasonal differences was a useful tool in elucidating source profiles.

scholarly journals Carbonaceous Aerosols in Contrasting Atmospheric Environments in Greek Cities: Evaluation of the EC-tracer Methods for Secondary Organic Carbon Estimation

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 161 ◽  
Author(s):  
Dimitris G. Kaskaoutis ◽  
Georgios Grivas ◽  
Christina Theodosi ◽  
Maria Tsagkaraki ◽  
Despina Paraskevopoulou ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Biomass Burning ◽  
Urban Environments ◽  
Atmospheric Composition ◽  
Carbonaceous Aerosol ◽  
Carbonaceous Aerosols ◽  
Wood Combustion ◽  
Aerosol Mass ◽  
Secondary Organic Carbon ◽  
The Difference

This study examines the carbonaceous-aerosol characteristics at three contrasting urban environments in Greece (Ioannina, Athens, and Heraklion), on the basis of 12 h sampling during winter (January to February 2013), aiming to explore the inter-site differences in atmospheric composition and carbonaceous-aerosol characteristics and sources. The winter-average organic carbon (OC) and elemental carbon (EC) concentrations in Ioannina were found to be 28.50 and 4.33 µg m−3, respectively, much higher than those in Heraklion (3.86 µg m−3 for OC and 2.29 µg m−3 for EC) and Athens (7.63 µg m−3 for OC and 2.44 µg m−3 for EC). The winter OC/EC ratio in Ioannina (6.53) was found to be almost three times that in Heraklion (2.03), indicating a larger impact of wood combustion, especially during the night, whereas in Heraklion, emissions from biomass burning were found to be less intense. Estimations of primary and secondary organic carbon (POC and SOC) using the EC-tracer method, and specifically its minimum R-squared (MRS) variant, revealed large differences between the sites, with a prevalence of POC (67–80%) in Ioannina and Athens and with a larger SOC fraction (53%) in Heraklion. SOC estimates were also obtained using the 5% and 25% percentiles of the OC/EC data to determine the (OC/EC)pri, leading to results contrasting to the MRS approach in Ioannina (70–74% for SOC). Although the MRS method provides generally more robust results, it may significantly underestimate SOC levels in environments highly burdened by biomass burning, as the fast-oxidized semi-volatile OC associated with combustion sources is classified in POC. Further analysis in Athens revealed that the difference in SOC estimates between the 5% percentile and MRS methods coincided with the semi-volatile oxygenated organic aerosol as quantified by aerosol mass spectrometry. Finally, the OC/Kbb+ ratio was used as tracer for decomposition of the POC into fossil-fuel and biomass-burning components, indicating the prevalence of biomass-burning POC, especially in Ioannina (77%).

Sources and transport of particulate matter on an hourly time-scale during the winter in a New Zealand urban valley

Urban Climate ◽  
2014 ◽  
Vol 10 ◽  
pp. 644-655 ◽  
Author(s):  
Travis Ancelet ◽  
Perry K. Davy ◽  
William J. Trompetter ◽  
Andreas Markwitz ◽  
David C. Weatherburn
Keyword(s):  
Particulate Matter ◽  
New Zealand ◽  
Time Scale

scholarly journals Atmospheric Monitoring of PM₂.₅, PM₁₀₋₂.₅, PM₁₀, Arsenic and Carbonaceous Aerosol at Wainuiomata

2021 ◽  
Author(s):  
◽  
Chandar Singh
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Biomass Burning ◽  
Limit Of Detection ◽  
Ion Beam ◽  
Ambient Air ◽  
Guideline Value ◽  
Treated Timber ◽  
Gf Aas

<p>Air pollution is harming our health and that of our children and parents. Air pollution causes many harmful effects, ranging from premature death, to headaches, coughing and asthma attacks. Previous studies (2008-2009) of particulate matter at Wainuiomata, Lower Hutt showed that biomass burning was primarily responsible for peak PM₂.₅ and PM₁₀ concentrations and exceedances of the National Environmental Standard (NES) and the New Zealand Ambient Air Quality Guidelines (NZAAQG). Arsenic was also found to be associated with biomass burning sources during winter at Wainuiomata. The source of arsenic was considered to be due to the use of copper chromium arsenate (CCA) treated timber as solid fuel for fires for domestic heating. While particulate matter pollution from domestic fires itself presents a health risk for the exposed population, the addition of arsenic to the mix enhances the potential risk. The use of CCA treated timber was unlikely to be used on a regular basis hence the peak arsenic concentrations did not always coincide with peak contributions from domestic fires and that the use of CCA – treated timber is more intermittent and opportunistic.  This work compared several different analytical methodologies for the determination of arsenic in air particulate matter. The primary purpose was to use a standard analytical method as recommended by the NZAAQ guidelines and compare those results with the Ion Beam Analysis (IBA) and X-ray Fluorescence Spectroscopy (XRF) methods used to determine arsenic concentrations in previous studies.  Through this collaborative research with GNS Science and GWRC, it was found that annual PM₁₀ and PM₂.₅ averages were well within the NZAAQG values of; 20 μg m⁻³ and 10 μg m⁻³ respectively. There was a much correlated seasonal and temporal variations observed for black carbon (BC), PM₂.₅ and arsenic concentrations. The overall concentrations of BC, PM₂.₅ and PM₁₀ have decreased significantly in the Wainuiomata airshed compared to previous studies as reported in 2009 with fewer exceedances of the NES and NZAAQG on a 24 hour daily average.  The overall weighted mean arsenic concentration as measured by GF-AAS was 6.3 ± 0.8 ng m⁻³ and that measured by XRF and IBA was 3.8 ± 2.0 ng m⁻³ and 3.1 ± 5.9 ng m⁻³ respectively. The XRF and IBA arsenic concentrations were consistently lower than that of GF-AAS. The two annual arsenic averages (GF-AAS) were 6.5 ± 0.9 ng m⁻³ and 5.9 ± 0.7 ng m⁻³ respectively, for the entire sampling period. In both the cases the NZAAQG value of 5.5 ng m⁻³ were exceeded. The exceedance in the second year of sampling was not statistically significant as the guideline value 5.5 ngm⁻³ falls within the given uncertainty of the measured annual averages for arsenic.  However, it is definitely an area of concern as the overall arsenic concentrations during winter periods was 12.2 ± 1.0 ng m⁻³. Moreover, burning CCA treated timber is effectively banned through regional plan rules and the problem presents itself as one of enforcement and/or public education.  The inter-method comparison showed that IBA technique can be used for “screening” purposes due to high limit of detection (LOD) and analytical noise. While XRF can still be used interchangeably with GF-AAS but with Teflon or thinner filter membrane, for long term environmental monitoring of arsenic and other elemental compositions. Given the excellent recoveries of 99.2 ± 0.8% for duplicate spiked analysis and 102.7 ± 0.9% for lab blank filters spiked analysis, at 95% confidence intervals, GF-AAS method is highly reproducible and should be used in the determination of arsenic in ambient air for the purpose of comparing with the NZAAQG values.</p>

scholarly journals The Effect of Blue-Green Infrastructure on Habitat Connectivity and Biodiversity: A Case Study in the Ōtākaro/Avon River Catchment in Christchurch, New Zealand

2021 ◽  
Vol 13 (12) ◽  
pp. 6732
Author(s):  
Thuy Thi Nguyen ◽  
Colin Meurk ◽  
Rubianca Benavidez ◽  
Bethanna Jackson ◽  
Markus Pahlow
Keyword(s):  
New Zealand ◽  
Green Infrastructure ◽  
Natural Capital ◽  
Research Question ◽  
Urban Environments ◽  
Habitat Connectivity ◽  
Added Value ◽  
Environmental Evaluation ◽  
Representative Species ◽  
The Matrix

The natural capital components in cities (“blue-green infrastructure” BGI) are designed to address long-term sustainability and create multi-benefits for society, culture, business, and ecology. We investigated the added value of BGI through the research question “Can the implementation of blue-green infrastructure lead to an improvement of habitat connectivity and biodiversity in urban environments?” To answer this, the Biological and Environmental Evaluation Tools for Landscape Ecology (BEETLE) within the Land Utilisation and Capability Indicator (LUCI) framework was adopted and applied in Christchurch, New Zealand, for the first time. Three ecologically representative species were selected. The parameterisation was based on ecological theory and expert judgment. By implementation of BGI, the percentages of habitats of interest for kereru and paradise shelduck increased by 3.3% and 2.5%, respectively. This leads to improved habitat connectivity. We suggest several opportunities for regenerating more native patches around the catchment to achieve the recommended minimum 10% target of indigenous cover. However, BGI alone cannot return a full suite of threatened wildlife to the city without predator-fenced breeding sanctuaries and wider pest control across the matrix. The socio-eco-spatial connectivity analysed in this study was formalised in terms of four interacting dimensions.

scholarly journals Characterization of gas-phase organics using proton transfer reaction time-of-flight mass spectrometry: fresh and aged residential wood combustion emissions

2016 ◽  
Author(s):  
Emily A. Bruns ◽  
Jay G. Slowik ◽  
Imad El Haddad ◽  
Dogushan Kilic ◽  
Felix Klein ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Reaction Time ◽  
Biomass Burning ◽  
Transfer Reaction ◽  
Proton Transfer Reaction ◽  
Wood Combustion ◽  
Flight Mass Spectrometry ◽  
Combustion Emissions ◽  
Organic Gases

Abstract. Organic gases emitted during the flaming phase of residential wood combustion are characterized individually and by functionality using proton transfer reaction time-of-flight mass spectrometry. The evolution of the organic gases is monitored during photochemical aging. Primary gaseous emissions are dominated by oxygenated species (e.g., acetic acid, acetaldehyde, phenol and methanol), many of which have deleterious health effects and play an important role in atmospheric processes such as secondary organic aerosol formation and ozone production. Residential wood combustion emissions differ considerably from open biomass burning in both absolute magnitude and relative composition. Ratios of acetonitrile, a potential biomass burning marker, to CO are considerably lower (~ 0.09 pptv ppbv−1) than those observed in air masses influenced by open burning (~ 1–2 pptv ppbv−1), which may make differentiation from background levels difficult, even in regions heavily impacted by residential wood burning. Considerable formic acid forms during aging (~ 200–600 mg kg−1 at an OH exposure of (4.5–5.5) × 107 molec  cm−3 h), indicating residential wood combustion can be an important local source for this acid, the quantities of which are currently underestimated in models. Phthalic anhydride, a naphthalene oxidation product, is also formed in considerable quantities with aging (~ 55–75 mg kg−1 at an OH exposure of (4.5–5.5) × 107 molec  cm−3 h). Although total NMOG emissions vary by up to a factor of ~ 9 between burns, SOA formation potential does not scale with total NMOG emissions and is similar in all experiments. This study is the first thorough characterization of both primary and aged organic gases from residential wood combustion and provides a benchmark for comparison of emissions generated under different burn parameters.

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