publications | Gustavo A. Olivares

2022

Key challenges for tropospheric chemistry in the Southern Hemisphere

Clare Paton-Walsh, Kathryn M. Emmerson, Rebecca M. Garland, and 25 more authors

Elementa: Science of the Anthropocene, Jan 2022

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This commentary paper from the recently formed International Global Atmospheric Chemistry (IGAC) Southern Hemisphere Working Group outlines key issues in atmospheric composition research that particularly impact the Southern Hemisphere. In this article, we present a broad overview of many of the challenges for understanding atmospheric chemistry in the Southern Hemisphere, before focusing in on the most significant factors that differentiate it from the Northern Hemisphere. We present sections on the importance of biogenic emissions and fires in the Southern Hemisphere, showing that these emissions often dominate over anthropogenic emissions in many regions. We then describe how these and other factors influence air quality in different parts of the Southern Hemisphere. Finally, we describe the key role of the Southern Ocean in influencing atmospheric chemistry and conclude with a description of the aims and scope of the newly formed IGAC Southern Hemisphere Working Group.
Analyzing and repairing concept drift adaptation in data stream classification

Ben Halstead, Yun Sing Koh, Patricia Riddle, and 5 more authors

Machine Learning, Oct 2022

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Data collected over time often exhibit changes in distribution, or concept drift, caused by changes in factors relevant to the classification task, e.g. weather conditions. Incorporating all relevant factors into the model may be able to capture these changes, however, this is usually not practical. Data stream based methods, which instead explicitly detect concept drift, have been shown to retain performance under unknown changing conditions. These methods adapt to concept drift by training a model to classify each distinct data distribution. However, we hypothesize that existing methods do not robustly handle real-world tasks, leading to adaptation errors where context is misidentified. Adaptation errors may cause a system to use a model which does not fit the current data, reducing performance. We propose a novel repair algorithm to identify and correct errors in concept drift adaptation. Evaluation on synthetic data shows that our proposed AiRStream system has higher performance than baseline methods, while is also better at capturing the dynamics of the stream. Evaluation on an air quality inference task shows AiRStream provides increased real-world performance compared to eight baseline methods. A case study shows that AiRStream is able to build a robust model of environmental conditions over this task, allowing the adaptions made to concept drift to be analysed and related to changes in weather. We discovered a strong predictive link between the adaptions made by AiRStream and changes in meteorological conditions.
Online Air Pollution Inference using Concept Recurrence and Transfer Learning

Bowen Chen, Yun Sing Koh, Gillian Dobbie, and 3 more authors

In 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) , Oct 2022

2021

Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification

Ben Halstead, Yun Sing Koh, Patricia Riddle, and 5 more authors

In 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) , Oct 2021

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Data collected over time often exhibit changes in distribution, or concept drift, caused by changes in hidden context relevant to the classification task, e.g. weather conditions. Adaptive learning methods are able to retain performance in changing conditions by explicitly detecting concept drift and changing the classifier used to make predictions. However, in realworld conditions, existing methods often select classifiers which poorly represent current data due to adaptation errors, where change in context is misidentified. We propose the AiRStream system, which uses a novel repair algorithm to identify and correct adaptation errors. We identify errors by periodically testing the performance of inactive classifiers. If an error is identified, a backtracking procedure repairs training done under the misidentified context. AiRStream achieves higher accuracy compared to baseline methods and selects classifiers which better match changes in context. A case study on a real-world air quality inference task shows that AiRStream is able to build a robust model of environmental conditions, allowing the adaptions made to concept drift to be analysed and related to changes in weather.
Indoor Emission Sources Detection by Pollutants Interaction Analysis

Shaoning Pang, Lei Song, Abdolhossein Sarrafzadeh, and 3 more authors

Applied Sciences, Jan 2021

Number: 16 Publisher: Multidisciplinary Digital Publishing Institute

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This study employs the correlation coefficients technique to support emission sources detection for indoor environments. Unlike existing methods analyzing merely primary pollution, we consider alternatively the secondary pollution (i.e., chemical reactions between pollutants in addition to pollutant level), and calculate intra pollutants correlation coefficients for characterizing and distinguishing emission events. Extensive experiments show that seven major indoor emission sources are identified by the proposed method, including (1) frying canola oil on electric hob, (2) frying olive oil on an electric hob, (3) frying olive oil on a gas hob, (4) spray of household pesticide, (5) lighting a cigarette and allowing it to smoulder, (6) no activities, and (7) venting session. Furthermore, our method improves the detection accuracy by a support vector machine compared to without data filtering and applying typical feature extraction methods such as PCA and LDA.
O-Tū-Kapua (What Clouds See): A Mixed Reality Exploration of Atmospheric Science

Guy Coulson, Susan Jowsey, Marcus Williams, and 1 more author

Leonardo, Apr 2021

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The authors’ project O-Tū-Kapua (what clouds see) explored concepts related to air quality by creating a mixed reality, art/science, educationally focused exhibition for children, mixing participatory art, scientific concepts and technology. The young are directly affected by the social and environmental impacts of the changing world climate, making their voices particularly important in determining ongoing dialogue about Earth’s atmosphere. Through a nexus of the handmade, education, augmented technology, installation and aural soundscapes, O-Tū-Kapua engaged over 1,000 children. The project also combined real-time air quality and weather data, superimposing it as a virtual data layer on top of hand-drawn images of native flora and fauna. The magnitude of the data determined the visual and aural form of the virtual experience, creating environmentally responsive representations that enabled participants to readily see and interpret how the atmosphere was affecting the native forest in their neighborhood.
The MAPM (Mapping Air Pollution eMissions) method forinferring particulate matter emissions maps at city-scale from in situconcentration measurements: description and demonstration ofcapability

Brian Nathan, Stefanie Kremser, Sara Mikaloff-Fletcher, and 6 more authors

Jan 2021

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MAPM (Mapping Air Pollution eMissions) is a two-year project whose goal is to develop a method to infer particulate matter (PM) emissions maps from in situ PM concentration measurements. Central to the functionality of MAPM is an inverse model. The input of the inverse model includes a spatially-distributed prior emissions estimate and PM measurement time series from instruments distributed across the desired domain. Here we describe the construction of this inverse model, 5 the mathematics underlying the retrieval of the resultant posterior PM emissions maps, the way in which uncertainties are traced through the MAPM processing chain, and plans for future development of the processing chain. To demonstrate the capability of the inverse model developed for MAPM, we use the PM2.5 measurements obtained during a dedicated winter ﬁeld campaign in Christchurch, New Zealand, in 2019 to infer PM2.5 emissions maps on city scale. The results indicate a systematic overestimation in the prior emissions for Christchurch of at least 40–60%, which is consistent with some of the un10 derlying assumptions used in the composition of the bottom-up emissions map used as the prior, highlighting the uncertainties in bottom-up approaches for estimating PM2.5 emissions maps.

2020

Toward a Framework for Resilience Assessments: Working Across Cultures, Disciplines, and Scales in Aotearoa/New Zealand

Guy Coulson, Jonathan Moores, Andrew Waa, and 6 more authors

Frontiers in Sustainable Cities, Jan 2020

Publisher: Frontiers

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Resilience appears within diverse literatures across the physical and social sciences, pervades social and ecological systems models and has been mobilised in the quest to change environmental practices at local and international levels. Yet common language is needed to enable cross-disciplinary conversations. We discuss a novel interdisciplinary process identifying shared terminology and developing a framework to facilitate the integration of physical and social science understandings of urban infrastructure and resilience in urban systems. Drawing on bicultural knowledge traditions unique to Aotearoa/New Zealand, we reflect on resilience as a system property having ecological, social, economic and technical dimensions that influence wellbeing and sustainability outcomes. .
The winter 2019 air pollution (PM_\textrm2.5) measurement campaign in Christchurch, New Zealand

Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, and 11 more authors

Earth System Science Data Discussions, Oct 2020

Publisher: Copernicus GmbH

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\textlessp\textgreater\textlessstrong\textgreaterAbstract.\textless/strong\textgreater MAPM (Mapping Air Pollution eMissions) is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from in situ PM concentration measurements. In support of MAPM, a winter field campaign was conducted in New Zealand in 2019 (June to September) to obtain the measurements required to test and validate the MAPM methodology. Two different types of instruments measuring PM were deployed: ES-642 remote dust monitors (17 instruments) and Outdoor Dust Information Nodes (ODINs; 50 instruments). The measurement campaign was bracketed by two intercomparisons where all instruments were co-located, with a permanently installed Tapered Element Oscillating Membrane (TEOM) instrument, to determine any instrument biases. Changes in biases between the pre- and post-campaign intercomparisons were used to determine instrument drift over the campaign period. Once deployed, each ES-642 was co-located with an ODIN. In addition to the PM measurements, meteorological variables (temperature, pressure, wind speed and wind direction) were measured at three automatic weather station (AWS) sites established as part of the campaign, with additional data being sourced from 27 further AWSs operated by other agencies. Vertical profile measurements were made in two intensive radiosonde sub-campaigns and were supplemented with measurements made with a mini micropulse lidar and ceilometer. Here we present the data collected during the campaign and discuss the correction of the measurements made by various PM instruments. We find that for while for the ODINs a correction based on environmental conditions is beneficial, this results in over-fitting and increased uncertainties when applied to the measurements obtained using the more sophisticated ES-642s. We also compare PM_\textrm2.5 and PM_\textrm10 measured by ODINs which, in some cases, allows us to identify PM from natural and anthropogenic sources. The PM data collected during the campaign are publicly available from \textlessa href=" https://doi.org/10.5281/zenodo.4023402"target="_blank"\textgreaterhttps://doi.org/10.5281/zenodo.4023402\textless/a\textgreater (Dale et. al., 2020b), the data from other instruments are available from \textlessa href=" https://doi.org/10.5281/zenodo.4021685"target="_blank"\textgreaterhttps://doi.org/10.5281/zenodo.4021685\textless/a\textgreater (Dale et. al., 2020a).\textless/p\textgreater
Mapping Air Pollution eMissions (MAPM)

Stefanie Kremser, Sara Mikaloff-Fletcher, Brian Nathan, and 11 more authors

May 2020

Conference Name: EGU General Assembly Conference Abstracts

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The growth of megacities from global urbanization has degraded urban air quality sufficient to impede economic growth and create a public health hazard. Emissions of particulate matter, photochemically reactive gases, and long-lived greenhouse gases, contribute to the urban environmental footprint with concomitant economic and social costs. Mitigation actions rely critically on knowing where these emissions occur. In response to this challenge, our team has developed a new method, MAPM (Mapping Air Pollution eMissions), to generate near real-time surface emissions maps of particulate matter pollution. Surface particulate matter (PM 2.5) emission maps will be derived from atmospheric measurements of particulate matter using an inverse model in conjunction with a state-of-the-art mesoscale atmospheric model.The MAPM methodology is validated and refined using particulate matter measurements made during a field campaign that took place in Christchurch, New Zealand from June to September 2019. Key questions that MAPM aims to answer include:How do uncertainties on the PM 2.5 measurements affect the quality of the emissions maps we extract from our inverse model. How do uncertainties in the meteorological data affect the quality of the emissions maps we extract from our inverse model. How does the spatial and temporal resolution of the air pollution concentration measurements affect the uncertainties in the retrieved pollution emissions maps? Here we will not only present the measurements made during the winter field campaign but also present the first derived PM 2.5 emissions maps for the city of Christchurch.

2019

Predicting Air Quality from Low-Cost Sensor Measurements

Hamish Huggard, Yun Sing Koh, Patricia Riddle, and 1 more author

In Data Mining , May 2019

Citation Key Alias: huggardPredictingAirQuality2018

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Urban air pollution poses a significant global health risk, but due to the high expense of measuring air quality, the amount of available data on pollutant exposure has generally been wanting. In recent years this has motivated the development of several cheap, portable air quality monitoring instruments. However, these instruments also tend to be unreliable, and thus the raw measurements require preprocessing to make accurate predictions of actual air quality conditions, making them an apt target for machine learning techniques. In this paper we use a dataset of measurements from a low cost air-quality instrument—the ODIN-SD—to examine which techniques are most appropriate, and the limitations of such an approach. From theoretical and experimental considerations, we conclude that a robust linear regression over measurements of air quality metrics, as well as relative humidity and temperature measurements produces the model with greatest accuracy. We also discuss issues of concept drift which occur in this context, and quantify how much training data is required to strike the right balance between predictive accuracy and efficient data collection.
The use of portable HEPA air cleaners to improve residential indoor air quality during biomass burning events.

A Wheeler, I Longley, F Reisen, and 7 more authors

Environmental Epidemiology, May 2019
Separating spatial patterns in pollution attributable to woodsmoke and other sources, during daytime and nighttime hours, in Christchurch, New Zealand

Brett Tunno, Ian Longley, Elizabeth Somervell, and 8 more authors

Environmental Research, Apr 2019

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During winter nights, woodsmoke may be a predominant source of air pollution, even in cities with many sources. Since two major earthquakes resulted in major structural damage in 2010 and 2011, reliance on woodburning for home heating has increased substantially in Christchurch, New Zealand (NZ), along with intensive construction/demolition activities. Further, because NZ is a relatively isolated western country, it offers the unique opportunity to disentangle multiple source impacts in the absence of long-range transport pollution. Finally, although many spatial saturation studies have been published, and levoglucosan is an established tracer for woodburning emissions, few studies have monitored multiple sites simultaneously for this or other organic constituents, with the ability to distinguish spatial patterns for daytime vs. nighttime hours, in complex urban settings. We captured seven-day integrated samples of PM2.5, and elemental and organic tracers of woodsmoke and diesel emissions, during “daytime” (7 a.m. – 5:30 p.m.) and “nighttime” (7 p.m. – 5:30 a.m.) hours, at nine sites across commercial and residential areas, over three weeks in early winter (May 2014). At a subset of six sites, we also sampled during hypothesized “peak” woodburning hours (7 p.m. – 12 a.m.), to differentiate emissions during “active” residential woodburning, vs. overnight smouldering. Concentrations of PM2.5 were, on average, were twice as high during nighttime than daytime [µ = 18.4 (SD = 6.13) vs. 9.21 (SD = 6.13) µg/m3], with much greater differences in woodsmoke tracers (i.e., levoglucosan [µ = 1.83 (SD = 0.82) vs. 0.34 (SD = 0.17) µg/m3], potassium) and indicators of treated- or painted-wood burning (e.g., arsenic, lead). Only nitrogen dioxide, calcium, iron, and manganese (tracers of vehicular emissions) were higher during daytime. Levoglucosan and most PAHs were higher during “active” woodburning, vs. overnight smouldering. Our time-stratified spatial saturation detected strong spatial variability throughout the study area, which distinctly differed during daytime vs. night time hours, and quantified the substantial contribution of woodsmoke to overnight spatial variation in PM2.5 across Christchurch. Daytime vs. nighttime differences were greater than those observed across sites. Traffic, especially diesel, contributed substantially to daytime NO2 and spatial gradients in non-woodsmoke constituents.
Assessment of Spatial Variability across Multiple Pollutants in Auckland, New Zealand

Ian Longley, Brett Tunno, Elizabeth Somervell, and 8 more authors

International journal of environmental research and public health, Apr 2019
Evaluation of portable air cleaners to improve residential indoor air quality during biomass burns

Amanda Wheeler, Ian Longley, Fabienne Reisen, and 7 more authors

Air Quality and Climate Change, Dec 2019

Publisher: Clean Air Society of Australia and New Zealand

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Bushfires, prescribed burns and residential wood burning are a significant source of fine particles (PM2.5) affecting the health and well-being of many communities (Johnston et al, 2011; Dennekamp et al, 2011; Morgan et al, 2010). Despite the lack of evidence, homes are perceived as a critical frontline of defence against episodic outdoor air pollution from smoke emissions (Reisen et al, 2019). Typical guidance to the public provided by regulatory agencies recommends closing doors and windows and putting air conditioners on recirculation (Department of Health Tasmania, 2019).

2018

Deployment issues for integrated open-source—Based indoor air quality school Monitoring Box (SKOMOBO)

Yu Wang, Julian Jang-Jaccard, Mikael Boulic, and 7 more authors

In 2018 IEEE Sensors Applications Symposium (SAS) , Dec 2018
Vehicle emission prediction using remote sensing data and machine learning techniques

Jiazhen Chen, Gillian Dobbie, Yun Sing Koh, and 2 more authors

In Proceedings of the 33rd Annual ACM Symposium on Applied Computing , Dec 2018
Deployment Issues for Integrated Open-Source-ased Indoor Air Quality School Monitoring Box (SKOMOBO)

Yu Wang, Julian Jang-Jaccard, Mikael Boulic, and 7 more authors

In 2018 Ieee Sensors Applications Symposium (sas) , Dec 2018

WOS:000462064300045

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A low-cost, low power consumption indoor environment monitoring device, called SKOMOBO (SKOol MOnitoring Box), was developed. SKOMOBO includes the sensors to monitor temperature/relative humidity, carbon dioxide, particulate matter (PM) and motion (PIR). SKOMOBO was developed using the open source software on Arduino Pro Mini. 165 units of SKOMOBO were manufactured at Massey University (New Zealand) in September 2017. These units were then deployed across New Zealand to monitor the indoor air quality in primary school classrooms. This paper describes the practical deployment issues we faced and lessons learnt prior/during the field study aimed at understanding the connection between the air quality and student performance. We believe that the discussion in this paper is of importance and could potentially save a lot of money and effort for other similar sensor products.

2017

Ten years of woodburner research in New Zealand: A review

Guy Coulson, Elizabeth Somervell, Edward Mitchell, and 3 more authors

Air Quality and Climate Change, Dec 2017
Integrating Open-Source Technologies to Build a School Indoor Air Quality Monitoring Box (SKOMOBO)

Yu Wang, Mikael Boulic, Robyn Phipps, and 7 more authors

In 2017 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) , Dec 2017

2016

To combat air inequality, governments and researchers must open their data

C. A. Hasenkopf, D. C. Adukpo, M. Brauer, and 9 more authors

Clean Air Journal, Dec 2016

Publisher: National Association for Clean Air

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More about this open access article on DOAJ. DOAJ is an online directory that indexes and provides access to quality open access, peer-reviewed journals.

2015

The Outdoor Dust Information Node (ODIN) – development and performance assessment of a low cost ambient dust sensor

G. Olivares, and S. Edwards

Atmos. Meas. Tech. Discuss., Jul 2015

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The large gradients in air quality expected in urban areas present a significant challenge to standard measurement technologies. Small, low-cost devices have been developing rapidly in recent years and have the potential to improve the spatial coverage of traditional air quality measurements. Here we present the first version of the Outdoor Dust Information Node (ODIN) as well as the results of the first real-world measurements. The lab tests indicate that the Sharp dust sensor used in the ODIN presents a stable baseline response only slightly affected by ambient temperature. The field tests indicate that ODIN data can be used to estimate hourly and daily PM2.5 concentrations after appropriate temperature and baseline corrections are applied. The ODIN seems suitable for campaign deployments complementing more traditional measurements.

2014

Spatio-temporal PM 2.5 prediction by spatial data aided incremental support vector regression

Lei Song, Shaoning Pang, Ian Longley, and 2 more authors

In 2014 international joint conference on neural networks (ijcnn) , Jul 2014
Spatio-temporal PM lt;inf gt;2.5 lt;/inf gt; prediction by spatial data aided incremental support vector regression

L. Song, S. Pang, I. Longley, and 2 more authors

In 2014 International Joint Conference on Neural Networks (IJCNN) , Jul 2014

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Machine learning requires sufficient and reliable data to enhance the prediction performance. However, environmental data sometimes is short and/or contains missing data. Often existing prediction models built on machine learning fail to predict environmental problems accurately. We argue that spatial domain data can be used to facilitate the training of temporal prediction model. This paper formulates mathematically a spatial data aided incremental support vector regression (SalncSVR) for spatio-temporal PM_\textrm2.5 prediction. We conduct spatio-temporal PM_\textrm2.5 prediction over 13 monitoring stations in Auckland New Zealand, and compare the proposed SalncSVR with a pure temporal IncSVR prediction.
Personal Exposure to Noise and Air Pollution (PENAP) in the Queen Street Valley, Auckland

Ian Longely, Jennifer Salmond, Kim Dirks, and 7 more authors

Jul 2014

OCLC: 906699850

2013

What is sustainable air quality?

Ian Longley, and Gustavo Olivares

International Journal of Sustainable Development, Jan 2013

Publisher: Inderscience Publishers

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For 40 years or more, air quality policy has been based on the paradigm of the air quality standard as a uniform criterion of acceptable environmental degradation, built on the foundations of the precautionary principle. However, developments in health science have undermined some of the underlying assumptions of this paradigm whilst technological emission controls have been offset by growing economic activity. Current trends are towards increasingly demanding notions of what constitutes acceptable air quality. Proposed future air quality standards could require a revolution in urban form and infrastructure. We need a new paradigm – sustainable air quality. In this paper, we discuss the need for a new paradigm of sustainable air quality management, its basis and what it might hope to achieve, including how further downward pressure can be exerted on emissions through urban form, urban design, transport policy and projects, energy strategy, etc.
Marine aerosol hygroscopicity and volatility, measured on the Chatham Rise (New Zealand)

Luke Cravigan, Marc Mallet, Zoran Ristovski, and 5 more authors

AIP Conference Proceedings, May 2013

Publisher: American Institute of Physics

2011

Ultrafine Particles Inside Cars in Busy Traffic—Developing an Empirical Model

Ian Longley, Sharleen Harper, Gustavo Olivares, and 4 more authors

Epidemiology, Jan 2011

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An abstract is unavailable.
Street-to-street variations in PM, PNC and BC in a motorway-dominated urban neighbourhood

G. Coulson, I. Longley, W. Pattinson, and 3 more authors

Manchester, UK: European Aerosol Conference (EAC2011), Jan 2011

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2010

Healthy Urban Atmospheres (HUA) – Observational Studies from Year One of New Zealand’s Exposure Research Programme

Ian; NIWA; i longley@niwa co nz Longley, Guy; ; g coulson@niwa co nz Coulson, and Gustavo; ; g olivares@niwa co nz Olivares

In Air Pollution and Health. , Mar 2010

2008

Estimates of Black Carbon and Size-Resolved Particle Number Emission Factors from Residential Wood Burning Based on Ambient Monitoring and Model Simulations

G. Olivares, J. Ström, C. Johansson, and 1 more author

Journal of the Air & Waste Management Association, Mar 2008

2007

Microphysical and chemical characteristics of cloud droplet residuals and interstitial particles in continental stratocumulus clouds

Admir C. Targino, Kevin J. Noone, Frank Drewnick, and 5 more authors

Atmospheric Research, Dec 2007

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During June and July 2003 the Sources and Origins of Atmospheric Cloud Droplets experiment (SOACED) was carried out on a mountain-top site in central Sweden. The main objective of the experiment was to characterise the microphysical and chemical properties of cloud droplet residuals and interstitial aerosol particles in continental clouds and to understand the processes controlling cloud properties at this location. Interstitial and residual aerosol size distributions, cloud liquid water content and species- and size-resolved aerosol mass concentrations are the main variables employed to address questions pertaining to the cloud droplet number concentration and scavenging efficiency during a stratocumulus cloud event observed on July 28, 2003. In this cloud event, about 56% of the aerosol mass was associated with organic species, whilst SO4 accounted for 23% and NH4 for 14%. NO3 and Cl made up about 7% of the total mass. The partitioning of the aerosol particles between cloud droplets and interstitial air has been studied in terms of their microphysical properties. The scavenging efficiency, defined as the fraction of particles activated into cloud elements compared to the total amount of particles, was investigated as a function of size. The scavenging efficiency curves displayed different shapes during the cloud event, from an S-shaped curve, with low scavenging efficiency in the Aitken mode and larger scavenging efficiency in the accumulation mode, to more unusual shapes where Aitken-mode particles were either solely activated or activated in addition to accumulation-mode particles. This study suggests that alterations of the aerosol chemical composition occurred during the measurement period, changing the hygroscopic nature of the CCN and decreasing their activation diameter. It is also hypothesized that entrainment of drier air aloft may have introduced inhomogeneities in the supersaturation field and modified the S-shaped scavenging curves.
The role of ambient temperature for particle number concentrations in a street canyon

Gustavo Olivares, Christer Johansson, Johan Ström, and 1 more author

Atmospheric Environment, Mar 2007

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Two and a half years (June 2002 to September 2004) of air pollution and meteorological parameters in a street canyon in Stockholm were analyzed. A distinctive dependence of particle number concentration, normalized by NOx, with ambient temperature was found. By comparison with NOx, it is concluded that this variation is not related to variability in the emissions nor due to changes in atmospheric dilution. The observed ratio between total particle number and NOx increases from ca. [150±60] particles per picogram of NOx [] at to [380±50] [] at . The increase in particle number concentration with decreasing temperatures is different for different particle sizes. For particle sizes smaller than 40 nm the variation is more pronounced while for particle sizes larger than 100 nm the change is not statistically significant. This reflects the impact of temperature dependent processes that affect mainly particles smaller than 100 nm in diameter. Modeling results indicate that condensation of volatile compounds onto pre-existing aerosols gives similar changes in the particle size distribution as those observed. Coagulation is shown to have only minor effects on the particle size distribution. Even though, with the present data set is not possible to quantify the impact of an increased nucleation rate with low temperatures, it was shown that nucleation mode particles are largely influenced by relative humidity with high concentrations during high relative humidity periods and therefore it is expected that for cold periods, when the relative humidity is higher, nucleation is enhanced by the water content of the air.

2004

Simulation of NOx and ultrafine particles in a street canyon in Stockholm, Sweden

L. Gidhagen, C. Johansson, J. Langner, and 1 more author

Atmospheric Environment, May 2004

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A computational fluid dynamic (CFD) model has been used to assess the concentrations of NOx and particle number in a street canyon in Stockholm with a high traffic volume. Comparisons of a simulated 11-week long time series of NOx with measurements (both sides of the street, urban background excluded) show good agreement, especially if emissions are distributed to be three times higher along the side of the street where the traffic is uphill, as compared to the downhill side. The simulation of number concentrations of inert particles indicates a similar asymmetry in emissions. A month-long measurement of particle size distribution (7-450 nm) at street level indicates that the ratio of nucleation size mode particle (7-20 nm) to total particle number (7-450 nm) is decreasing for increased particle surface area. Given the strong dominance of the locally generated particles over the urban background, this is interpreted as a local change in the size distribution. The results of a monodisperse aerosol dynamic model, coupled to the CFD model that simulates also the turbulence generated by vehicle movements, show that coagulation and deposition may reduce total particle inside the canyon with approximately 30% during low wind speeds. Most of the removal occurs shortly after emission, before the particles reach the leeward curb-side. Losses between the leeward curb-side and other locations in the street, e.g. roof levels, is estimated to be smaller, less than 10%. Coagulation is the dominating removal process under low wind speed conditions and deposition for higher wind speeds, the summed removal being smaller for high wind velocities. Deposition is enhanced over the road surface due to the velocities generated by vehicle movements. Although coagulation and deposition removal is most effective on the smallest ultrafine particles, this effect is not sufficient to explain the observed change in size distribution. It is suggested that also the formation of particles in the exhaust plumes is influenced by a larger particle surface area in the ambient air.
Model simulations of NO x and ultrafine particles close to a Swedish highway

Lars Gidhagen, Christer Johansson, Gunnar Omstedt, and 2 more authors

Environmental science & technology, May 2004
Aerosols and their role in the Earth’s energy balance

KJ Noone, A Targino, G Olivares, and 2 more authors

Global Change Newsletter, May 2004

2002

Regional dispersion of oxidized sulfur in Central Chile

G. Olivares, L. Gallardo, J. Langner, and 1 more author

Atmospheric Environment, Aug 2002

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Chile has a long tradition of exploiting mineral resources, particularly copper (Cu). One of the largest Cu smelters, Caletones, located some 150 km south of the country’s capital, Santiago, in Central Chile, is responsible for about 0.4% of about 70 Tg S/yr oxidized sulfur (SOx) emitted by anthropogenic sources worldwide. Santiago, a megacity with 5 million inhabitants, stands for about 5 Gg S/yr. The average meteorological conditions are unfavorable for the dispersion of pollutants in this area. All this poses risks for human health and vegetation. Also, downwind from these polluted areas there may be large-scale impacts on cloud properties and on oxidative cycles. Here, we present the first attempt to assess the regional distribution of SOx in Central Chile using a dispersion model (MATCH) driven with data from a limited area weather forecast model (HIRLAM). Emphasis has been given to the impact of Cu smelters upon urban air quality, particularly that of Santiago. Six 1-month long periods were simulated for the years 1997, 1998 and 1999. These periods span over a broad range of typical meteorological conditions in the area including El Niño and La Niña years. Estimates of the regional dispersion and deposition patterns were calculated. The emissions from the large Cu smelters dominate the distribution of SOx. A budget of SOx over an area of 200×200 km2 around Santiago is presented. There is too low a number of monitoring stations to perform a detailed evaluation of MATCH. Nevertheless, the model reproduces consistently all the regional-scale characteristics that can be derived from the available observations.
Coastal lows and sulfur air pollution in Central Chile

L. Gallardo, G. Olivares, J. Langner, and 1 more author

Atmospheric Environment, Aug 2002

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Air pollutants in Santiago (33.5°S, 70.8°W, 500 m a.s.l.), a city with 5 million inhabitants, located in a basin in Central Chile surrounded by the high Andes, frequently exceed air quality standards. This affects human health and it stresses vegetation. The most extreme winter and fall pollution events occur when the subsident regime of the Pacific high is further enhanced by coastal lows (CLs), which bring down the base of the subsidence inversion. Under these conditions, the air quality worsens significantly giving rise to acute air pollution episodes. We assess the ability of a regional transport/chemistry/deposition model (MATCH) coupled to a meteorological model (High Resolution Limited Area Model–HIRLAM) to simulate the evolution of oxidized sulfur (SOx) in connection with intensive CLs. We focus on SOx since it is an environmental issue of concern, and the emissions and concentrations of SOx have been regularly monitored making it easier to bracket model outputs for SOx than for other pollutants. Furthermore, the SOx emissions in the area are very large, i.e., about 0.4% of the global anthropogenic sources. Comparisons with observations indicate that the combination of HIRLAM and MATCH is a suitable tool for describing the regional patterns of dispersion associated with CLs. However, the low number and the limited geographical coverage of reliable air quality data preclude a complete evaluation of the model. Nevertheless, we show evidence of an enhanced contribution of the largest copper smelter in the area, i.e., Caletones, to the burden of SOx in the Santiago basin, especially in the form of sulfate associated to fine particles (diameters \textless2.5 [mu]m), during CLs. Further, we speculate that the Caletones plume may trigger or promote secondary aerosol formation during CLs in the Santiago basin.

2000

An analysis of ozone measurements at Cerro Tololo (30°S, 70°W, 2200 m.a.s.l.) in Chile

LAURA GALLARDO, JORGE CARRASCO, and GUSTAVO OLIVARES

Tellus B, Aug 2000

Abs

Increases in tropospheric ozone (O3) abundance are likely to take place in the near future in the populous and rapidly developing countries in the tropics and subtropics. An accurate evaluation of the future impact of increasing industrial activities in tropical and subtropical areas requires knowledge of the background levels of ozone. New ozone monitoring stations have been installed at several sites by the World Meteorological Organization (WMO) since the mid201090s. We analyze ozone data collected during two years since April 1996 at Cerro Tololo (30°S, 70°W, 2200 m.a.s.l.) some 50 km east from the city of La Serena. In this paper, we describe some of the atmospheric chemistry and meteorology that characterizes the Tololo site. The data show a seasonal variation with maximum mixing ratios in late winter and spring and minimum mixing ratios in late summer and early fall. These variations are most likely associated with the large2010scale subsidence of the Hadley circulation and the location of the subtropical jet stream (STJ). Also, there is a diurnal variation that is probably partly associated with a mountain wind flow which is strongest in late spring and summer months. No significant mixing with marine boundary layer air perturbed by anthropogenic activities is apparent from the data. We find the Cerro Tololo site to be generally representative for background conditions of free2010tropospheric air in the subtropics of the Southern Hemisphere. This work is done within the framework of a larger effort recently started by several Chilean institutions in cooperation with research centers abroad.