Many studies have shown that the increased atmospheric concentration of pollutants has an intensified health risk on lung-, heart- and cardiovascular disease sufferers, as well as the increasing willingness of morbidity and mortality. Therefore, the monitoring of the air pollutants is particularly important. The goal of the recent study was to show a complex picture about Veszprém county’s air quality situation and to discover the relationships between the selected air pollutants (PM10, CO, NO2, SO2, O3) concentration and the picked health diseases (cardiovascular diseases, respiratory diseases, gastrointestinal disorders, ischemic heart disease, cerebrovascular disease, and chronic lower respiratory diseases). Ambient air pollution and hospital admission data for the research were obtained for 2005–2013. According to the calculations; it was found that there was a moderate relation between the air pollutants concentrations and the health diseases.
L. Ippoliti, 30 Novembre - 1 Dicembre 2021 -
Webinar: La domanda europea e nazionale di informazioni statistiche "green"
Titolo: Statistical models for environmental studies: air pollution and its adverse health effects
L’aria è elemento essenziale per la vita dell’uomo.La “mission” di questo blog è quello di soddisfare le esigenze di ricerca e di conoscenza delle tecnologie che possono permettere alle persone di respirare ogni giorno un’aria più pulita e sana, migliorando la qualità e la durata della loro vita.
Many studies have shown that the increased atmospheric concentration of pollutants has an intensified health risk on lung-, heart- and cardiovascular disease sufferers, as well as the increasing willingness of morbidity and mortality. Therefore, the monitoring of the air pollutants is particularly important. The goal of the recent study was to show a complex picture about Veszprém county’s air quality situation and to discover the relationships between the selected air pollutants (PM10, CO, NO2, SO2, O3) concentration and the picked health diseases (cardiovascular diseases, respiratory diseases, gastrointestinal disorders, ischemic heart disease, cerebrovascular disease, and chronic lower respiratory diseases). Ambient air pollution and hospital admission data for the research were obtained for 2005–2013. According to the calculations; it was found that there was a moderate relation between the air pollutants concentrations and the health diseases.
L. Ippoliti, 30 Novembre - 1 Dicembre 2021 -
Webinar: La domanda europea e nazionale di informazioni statistiche "green"
Titolo: Statistical models for environmental studies: air pollution and its adverse health effects
L’aria è elemento essenziale per la vita dell’uomo.La “mission” di questo blog è quello di soddisfare le esigenze di ricerca e di conoscenza delle tecnologie che possono permettere alle persone di respirare ogni giorno un’aria più pulita e sana, migliorando la qualità e la durata della loro vita.
Towards an accurate Ground-Level Ozone PredictionIJECEIAES
This paper motivation is to find the most accurate technique to predict the ground level ozone at Al Jahra station, Kuwait. The data on the meteorological variables (air temperature, relative humidity, solar radiation, direction and speed of wind) and concentration of seven pollutants of environment (SO2, NO2, NO, CO2, CO, NMHC, and CH4) were applied to forecast the ozone concentration in atmosphere. In this report, three methods (PLS regression, support vector machine (SVM), and multiple least-square regression) were used to predict ground-level ozone. We used Fifteen parameters to evaluate the performance of methods. Multiple least-square regression, partial least square regression (PLS regression), and SVM using linear and radial kernels were the best performers with MAE (mean absolute error) of 9.17x 10-03, 9.72 x 10-03, 9.64 x 10-03, and 9.12 x 10-03, respectively. SVM with polynomial kernel had MAE of 5.46 x 10-02. These results show that these methods could be used to predict ground-level ozone concentrations at Al Jahra station in Kuwait.
ORIGINAL PAPERRisk assessment of atmospheric heavy metals .docxgerardkortney
ORIGINAL PAPER
Risk assessment of atmospheric heavy metals exposure
in Baotou, a typical industrial city in northern China
Kexin Li . Tao Liang . Lingqing Wang
Received: 11 March 2015 / Accepted: 1 September 2015 / Published online: 8 September 2015
! Springer Science+Business Media Dordrecht 2015
Abstract Industrial activities have led to serious air
pollution and the potentially toxic elements in atmo-
spheric particles can cause various health problems to
humans. In this study, inhalable particulate matter
(PM10) and fine particles (PM2.5) were collected from
four typical sites in Baotou, an industrial city in
northern China. We investigated both the mass
concentrations of particulate matter and the concen-
trations of heavy metals (Cr, Ni, Pb, Cd, Cu, Mn, Co,
and Zn) in the collected samples. We assessed the
public health risks associated with atmospheric heavy
metal exposure. The results showed that the mass
concentrations of PM2.5 and PM10 as well as these
heavy metal concentrations varied notably influenced
by the prevailing wind directions. Among the studied
metals, Zn, Mn, Pb, and Cr were the main metal
pollutants in both PM10 and PM2.5. The results of the
health assessment showed that the eight heavy metals
studied pose significant non-carcinogenic risks and Cr,
Cd, and Co pose lifetime lung cancer risks to local
residents, especially to children.
Keywords PM10 ! PM2.5 ! Heavy metals !
Health risk ! Baotou
Introduction
Mining activities are notorious for adverse environ-
mental impacts, including pollution, habitat loss, soil
erosion, and geological disasters (Salomons 1995;
Klukanová and Rapant 1999; Aguilar et al. 2004; Luı́s
et al. 2011). Among these environmental problems
caused by mining activities, the production and
dispersion of atmospheric particles has become a
great concern in recent years (Kaonga and Kgabi
2011; Chen et al. 2013; Serbula et al. 2014). Atmo-
spheric particulates are generated from numerous
sources, both natural and anthropogenic, but in areas
near mining, mining operations are considered the
largest contributor. The processes of mining, such as
crushing, grinding, excavating, smelting, and refining,
can produce large quantities of particulate matter
(PM), containing dangerously high levels of heavy
metals (Csavina et al. 2012).
Inhalable particulate matter (PM10), particularly
fine particles (PM2.5), have been shown to cause
adverse effects on human health, including asthma,
lung cancer, and cardiovascular diseases (Pope et al.
2002; Sanchez et al. 2009). Lung and other organ
injuries from atmospheric heavy metal exposure have
also been well-documented (Espinosa et al. 2001;
Cancio et al. 2008; Leili et al. 2008).
K. Li ! T. Liang (&) ! L. Wang (&)
Key Laboratory of Land Surface Pattern and Simulation,
Institute of Geographical Sciences and Natural Resources
Research, Chinese Academy of Sciences, Beijing 100101,
China
e-mail: [email protected]
L. Wang
e-mail: [email p.
Big data and remote sensing: A new software of ingestion IJECEIAES
Currently, remote sensing is widely used in environmental monitoring applications, mostly air quality mapping and climate change supervision. However, satellite sensors occur massive volumes of data in near-real-time, stored in multiple formats and are provided with high velocity and variety. Besides, the processing of satellite big data is challenging. Thus, this study aims to approve that satellite data are big data and proposes a new big data architecture for satellite data processing. The developed software is enabling an efficient remote sensing big data ingestion and preprocessing. As a result, the experiment results show that 86 percent of the unnecessary daily files are discarded with a data cleansing of 20 percent of the erroneous and inaccurate plots. The final output is integrated into the Hadoop system, especially the HDFS, HBase, and Hive, for extra calculation and processing.
A lo largo de estas jornadas, expertos nacionales e internacionales en el tema analizarán la situación actual, tendencias futuras y principales retos que plantean los esquemas de reducción de emisiones y los mercados de carbono como herramientas en la lucha contra el calentamiento global, especialmente después de la cumbre de Copenhague.
Este documento es el informe del proyecto PESETA.
A - I QUADERNI DELL'ISEA - LINEE GUIDA SULL'IMPATTO ACUSTICO - COMPLETO.pdfISEA ODV
Il rumore è un importante problema di salute pubblica. Ha impatti negativi sulla salute e sul benessere umano ed è una preoccupazione crescente. L'Ufficio regionale dell'OMS per l'Europa ha sviluppato linee guida, basate sulla crescente comprensione di questi impatti sulla salute dell'esposizione al rumore ambientale.
Norwegian Report on Low-level Radiofrequency Electromagnetic FieldsThe Radiation Doctor
Check out the report from the Expert Committee appointed by the Norwegian Institute of Health, commissioned by the Ministry of Health and Care Services and the Ministry of Transport and Communications English, on Low-level radiofrequency electromagnetic fields – an assessment of health risks and evaluation of regulatory practice.
Towards an accurate Ground-Level Ozone PredictionIJECEIAES
This paper motivation is to find the most accurate technique to predict the ground level ozone at Al Jahra station, Kuwait. The data on the meteorological variables (air temperature, relative humidity, solar radiation, direction and speed of wind) and concentration of seven pollutants of environment (SO2, NO2, NO, CO2, CO, NMHC, and CH4) were applied to forecast the ozone concentration in atmosphere. In this report, three methods (PLS regression, support vector machine (SVM), and multiple least-square regression) were used to predict ground-level ozone. We used Fifteen parameters to evaluate the performance of methods. Multiple least-square regression, partial least square regression (PLS regression), and SVM using linear and radial kernels were the best performers with MAE (mean absolute error) of 9.17x 10-03, 9.72 x 10-03, 9.64 x 10-03, and 9.12 x 10-03, respectively. SVM with polynomial kernel had MAE of 5.46 x 10-02. These results show that these methods could be used to predict ground-level ozone concentrations at Al Jahra station in Kuwait.
ORIGINAL PAPERRisk assessment of atmospheric heavy metals .docxgerardkortney
ORIGINAL PAPER
Risk assessment of atmospheric heavy metals exposure
in Baotou, a typical industrial city in northern China
Kexin Li . Tao Liang . Lingqing Wang
Received: 11 March 2015 / Accepted: 1 September 2015 / Published online: 8 September 2015
! Springer Science+Business Media Dordrecht 2015
Abstract Industrial activities have led to serious air
pollution and the potentially toxic elements in atmo-
spheric particles can cause various health problems to
humans. In this study, inhalable particulate matter
(PM10) and fine particles (PM2.5) were collected from
four typical sites in Baotou, an industrial city in
northern China. We investigated both the mass
concentrations of particulate matter and the concen-
trations of heavy metals (Cr, Ni, Pb, Cd, Cu, Mn, Co,
and Zn) in the collected samples. We assessed the
public health risks associated with atmospheric heavy
metal exposure. The results showed that the mass
concentrations of PM2.5 and PM10 as well as these
heavy metal concentrations varied notably influenced
by the prevailing wind directions. Among the studied
metals, Zn, Mn, Pb, and Cr were the main metal
pollutants in both PM10 and PM2.5. The results of the
health assessment showed that the eight heavy metals
studied pose significant non-carcinogenic risks and Cr,
Cd, and Co pose lifetime lung cancer risks to local
residents, especially to children.
Keywords PM10 ! PM2.5 ! Heavy metals !
Health risk ! Baotou
Introduction
Mining activities are notorious for adverse environ-
mental impacts, including pollution, habitat loss, soil
erosion, and geological disasters (Salomons 1995;
Klukanová and Rapant 1999; Aguilar et al. 2004; Luı́s
et al. 2011). Among these environmental problems
caused by mining activities, the production and
dispersion of atmospheric particles has become a
great concern in recent years (Kaonga and Kgabi
2011; Chen et al. 2013; Serbula et al. 2014). Atmo-
spheric particulates are generated from numerous
sources, both natural and anthropogenic, but in areas
near mining, mining operations are considered the
largest contributor. The processes of mining, such as
crushing, grinding, excavating, smelting, and refining,
can produce large quantities of particulate matter
(PM), containing dangerously high levels of heavy
metals (Csavina et al. 2012).
Inhalable particulate matter (PM10), particularly
fine particles (PM2.5), have been shown to cause
adverse effects on human health, including asthma,
lung cancer, and cardiovascular diseases (Pope et al.
2002; Sanchez et al. 2009). Lung and other organ
injuries from atmospheric heavy metal exposure have
also been well-documented (Espinosa et al. 2001;
Cancio et al. 2008; Leili et al. 2008).
K. Li ! T. Liang (&) ! L. Wang (&)
Key Laboratory of Land Surface Pattern and Simulation,
Institute of Geographical Sciences and Natural Resources
Research, Chinese Academy of Sciences, Beijing 100101,
China
e-mail: [email protected]
L. Wang
e-mail: [email p.
Big data and remote sensing: A new software of ingestion IJECEIAES
Currently, remote sensing is widely used in environmental monitoring applications, mostly air quality mapping and climate change supervision. However, satellite sensors occur massive volumes of data in near-real-time, stored in multiple formats and are provided with high velocity and variety. Besides, the processing of satellite big data is challenging. Thus, this study aims to approve that satellite data are big data and proposes a new big data architecture for satellite data processing. The developed software is enabling an efficient remote sensing big data ingestion and preprocessing. As a result, the experiment results show that 86 percent of the unnecessary daily files are discarded with a data cleansing of 20 percent of the erroneous and inaccurate plots. The final output is integrated into the Hadoop system, especially the HDFS, HBase, and Hive, for extra calculation and processing.
A lo largo de estas jornadas, expertos nacionales e internacionales en el tema analizarán la situación actual, tendencias futuras y principales retos que plantean los esquemas de reducción de emisiones y los mercados de carbono como herramientas en la lucha contra el calentamiento global, especialmente después de la cumbre de Copenhague.
Este documento es el informe del proyecto PESETA.
A - I QUADERNI DELL'ISEA - LINEE GUIDA SULL'IMPATTO ACUSTICO - COMPLETO.pdfISEA ODV
Il rumore è un importante problema di salute pubblica. Ha impatti negativi sulla salute e sul benessere umano ed è una preoccupazione crescente. L'Ufficio regionale dell'OMS per l'Europa ha sviluppato linee guida, basate sulla crescente comprensione di questi impatti sulla salute dell'esposizione al rumore ambientale.
Norwegian Report on Low-level Radiofrequency Electromagnetic FieldsThe Radiation Doctor
Check out the report from the Expert Committee appointed by the Norwegian Institute of Health, commissioned by the Ministry of Health and Care Services and the Ministry of Transport and Communications English, on Low-level radiofrequency electromagnetic fields – an assessment of health risks and evaluation of regulatory practice.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2024.06.01 Introducing a competency framework for languag learning materials ...
AUPHEP Austrian Project on Health Effects of Particulates general overview.pdf
1. Atmospheric Environment 38 (2004) 3905–3915
AUPHEP—Austrian Project on Health Effects of
Particulates—general overview
H. Haucka,c,
*, A. Bernerb
, T. Frischerd
, B. Gomisceka
, M. Kundic
, M. Neubergerc
,
H. Puxbaume
, O. Preininga
, AUPHEP-Team1
a
Austrian Academy of Sciences—Clean Air Commission, Postgasse 7-9, Vienna, Austria
b
Institute for Experimental Physics, University of Vienna, Vienna, Austria
c
Institute of Environmental Health, Medical University of Vienna, Vienna, Austria
d
University Children’s Hospital, Medical University of Vienna, Vienna, Austria
e
Institute for Chemical Technologies and Analytics, Vienna University of Technology, Vienna, Austria
Received 28 July 2003; received in revised form 26 August 2003; accepted 15 September 2003
Abstract
AUPHEP was started in 1999 as a 5 years program to investigate the situation of the atmospheric aerosol with
respect to effects on human health. At four different sites in Austria (3 urban and one rural site) an extended monitoring
program was conducted for PM1, PM2.5 and PM10 as well as particle number concentration for 12 months each. Beside
continuous measurements using TEOM and beta attenuation high-volume sampling of PM2.5 and PM10 provided
samples for chemical analyses of various ions, heavy metals and organic compounds. Furthermore, carbonaceous
material (TC, EC, OC) year round and PAHs on selected days were analyzed. From collocated public monitoring
stations also pollutant gases (SO2, NO, NO2, O3, CO) and meteorological components are available. In winter and
summer campaigns aerosol size spectra including chemical components were measured for at least one week each. All
data are collected in a project data base (CD-ROM).
While extensive data analysis will be presented in following papers, some general results are presented within this
paper: annual averages for PM1 are between 10 and 20 mg m3
, for PM2.5 between 15 and 26 mg m3
and for PM10
between 20 and 38 mg m3
. Number concentrations are between 10,000 and 30,000 cm3
. Urban concentrations are
usually higher in winter, rural concentrations in summer. PM2.5 is in average around 70% of PM10, for PM1 this
fraction is about 57%.
Several studies on health effects are included in this project: a cross-sectional study on preschool and school children
regarding lung function measurements and questionnaires about respiratory impairment in the surrounding area of the
ARTICLE IN PRESS
*Corresponding author. Clean Air Commission, Austrian Academy of Sciences, Post gasse 7-9, 1010 Wien, Austria. Tel.: +43-1-
51581-3519; fax: +43-1-51581-3518.
E-mail address: helger.hauck@assoc.oeaw.acat (H. Hauck).
1
AUPHEP Team: T. Amoako-Mensah, H. Bauer, A. Berner, S. Broer, P. Ctyroky, E. Danninger, T. Eiwegger, T. Frischer, P.
Frühauf, Z. Galambos, C. Gartner, B. Gomiscek, H. Hauck (Codirector), W. Hann, F. Horak jr., H. Horvath, A. Iro, M. Kalina, J.
Klocker, P. Kreiner, W. Krejci, H. Kromp-Kolb, B. Krüger, M. Kundi, T. Lavric, A. Limbeck, W. Matzke, H. Moshammer, M.
Neuberger, B. Piegler, P. Pouresmaeil, O. Preining (Codirector), W. Pühringer, B. Putschögl, H. Puxbaum, W. Raber, P. Riess, A.
Salam, M. G. Schimek, H. Schmid, B. Schuster, G. Semmelrock, B. Syeda, S. Stopper, M. Studnicka, V. Tarmann, E. Wartlik, A.
Zarkada. International Advisory Board: Heinz Fissan, Duisburg, Germany; Nino Künzli, Basel, Switzerland; Anton van der Meulen,
Bilthoven, The Netherlands.
1352-2310/$ - see front matter r 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2003.09.080
2. monitoring sites as well as time series studies on mortality and respiratory morbidity on the general population.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Atmospheric aerosol; PM-fractions; Particle mass concentration; Particle number concentration; Chemical composition;
Urban; Rural; Health effects
1. Introduction
The atmospheric aerosol is a complex disperse system
of solid and liquid particles of different size, shape,
chemical composition and reactivity. There are possible
effects on climate, visibility, soil and water. Last but not
least effects on human health have gained considerable
interest. Epidemiologic studies in the past (e.g. Dockery
et al., 1993; Pope et al., 1992; Schwartz et al., 1996) gave
a strong hint on extended morbidity and mortality even
due to relatively low burdens of particulate matter (PM).
Although a lot of research efforts have been put in
within the last years and more recent epidemiological
findings basically confirm the earlier results (Pope, 2000;
Samet et al., 2000), the understanding of the causal
chains between the various parameters describing PM
exposure and the corresponding health effects are still
lacking. Up to now it is not possible to answer the
question which of the parameters PM mass, particle
number concentration, aerosol surface area or any other
parameter is the key to describe health impacts most
adequately.
The extrapolation of at least initially mostly American
studies to European or Austrian situations seems to be
questionable. Emission, composition, and kinetics of
aerosols are regionally very different; particularly the
results from arid or maritime areas, for instance in the
US, cannot be transferred to the European situation.
Therefore, the investigation of typical local or regional
situations is very important in order to understand and
interpret the exposure situation in various regions of
Europe. Exact comprehensive exposure data in combi-
nation with accurate analyses of health effects especially
in high risk groups can yield an essential contribution in
understanding the health effects of PM exposure.
Meanwhile several European studies contributed to this
question APHEA: (Katsouyanni et al., 1997), SAPAL-
DIA (Zemp et al., 1999), PEACE (Roemer et al., 1999),
Erfurt-Study (Pitz et al., 2001; Wichmann et al., 2000).
Several data bases have been assembled recently
(Jantunen et al., 1998; Putaud et al., 2002). Other
activities are still going on (AIRNET, COST-633).
A concerted research program was started in 1999 in
Austria (AUPHEP—Austrian Project on Health Effects
of Particulates) to provide an extensive data set of PM
related parameters and to use these data for special
epidemiological health studies. Many facilities from
universities and public ambient air monitoring institu-
tions were pulled together under the umbrella of the
Clean Air Commission of the Austrian Academy of
Sciences.
2. Methods
2.1. Monitoring sites
Four monitoring sites representative for a good part
of the country were chosen. The sites do not show the
highest concentrations and based on the data of the
ambient air quality public monitoring network are
considered to be representative for the general pollutant
burden of the population living in these areas. In order
to take advantage from the existing infrastructure as
well as to use preexisting ambient air quality data most
efficiently, monitoring stations already being operated
within the public monitoring networks were chosen
preferably. The position of the four monitoring sites is
laid out in Fig. 1.
AUPHEP-1: Vienna, area of the General Hospital,
16
200
5200
E/48
130
1500
N, 185 m above sea level.
AUPHEP-2: Streithofen, rural area 30 km west of
Vienna, 15
550
4700
E/48
160
1200
N, 220 m above sea level.
AUPHEP-3: Linz, ORF Zentrum, 14
180
0500
E/
48
170
5100
N, 263 m above sea level.
AUPHEP-4: Graz, commercial/suburban area in the
southern part of the city, 15
260
0900
E/47
020
4000
N, 345 m
above sea level.
The city of Vienna is placed on the river Danube in
the border region between the Alps and the Pannonian
plane. It represents the largest Austrian conurbation
(population about 2 millions). The most important
pollution sources are traffic and in winter time local
heating. Industrial emissions play a minor role and are
limited to local power plants, high-tech incineration
plants and minor production facilities. The main wind
direction is W–NW transporting Atlantic air across
Western Europe and is often associated with bad
weather phases and frontal passages. Second frequent
are winds from E–SE during stable continental weather
conditions in connection with high temperatures in
summer and low temperatures in winter. The site chosen
lies in an inner district of the city and is not influenced
by one dominating emitter. A nearby situated main
traffic artery (distance about 200 m) in typical for many
living areas of Vienna. The annual means for TSP at this
ARTICLE IN PRESS
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915
3906
3. site are somewhat above the overall mean in the Vienna
area of about 30 mg m3
.
Streithofen is considered to be representative for the
background aerosol of the prealpine area (Alpenvor-
land). In addition the site acts as indicator for the
preburden of Vienna, at least as far as the main wind
direction (W, NW) is concerned. Local emission is
mostly caused by a state road (distance about 200 m)
where the traffic is higher during the morning and late
afternoon hours, and during distinct events of agricul-
tural work (harvesting, etc.) on the surrounding fields.
For the second period of the project two sites have
been chosen which still could be considered representa-
tive for a big part of the Austrian population. Linz and
Graz are second and third in population in Austria. On
the other side special ambient stress situations should be
considered.
Linz, located north of the Alps on the Danube, is one
of Austria’s largest heavy industry conglomerates and
therefore predominantly affected by industrial emissions
(iron and steel plants, chemical industry) which can
build up rather high concentrations during stagnant
conditions. Furthermore, for this location epidemiologic
investigations on air quality related health effects had
been conducted before (Neuberger et al., 1995). The
particular monitoring site is situated within a big living
area. The PM concentration reflects about the typical
PM-burden in Linz and lies within the upper third of all
sites in the city.
Graz is situated south of the Alps in a semi-alpine
basin and shows a completely different ambient air
quality structure. The area is not exposed to heavy
industrial emissions but has only weak natural ventila-
tion. Because of long lasting inversion situations in
winter Graz should be also typical for a locally aged
aerosol under stagnant weather conditions. The project
site is in the southern part of Graz, directly influenced by
a medium traffic road. The vicinity is covered with single
family houses and other low buildings. Again the
average PM-concentration is in the upper third of all
data from Graz.
All monitoring stations were operated for 1 year. In
order to reduce the costs for the measuring equipment
Vienna (AUPHEP-1) and Streithofen (AUPHEP-2)
were operative during the first year (May 1999 to April
2000) and Linz (AUPHEP-3) and Graz (AUPHEP-4) in
the following year (October 2000 to September 2001).
2.2. Monitoring program
As part of the public monitoring network TSP, SO2,
NO, NO2, and O3 as well as the main meteorological
components had already been measured for many years.
PM10, PM2.5, PM1, and particle number concentration
were monitored continuously as part of the project.
Since automated and gravimetric methods show some
discrepancies several methods were used in parallel
(Hauck et al., 2004). For continuous monitoring on a
half-hour basis TEOMs
and beta attenuation were
applied. For filter-based gravimetry following the
European reference method (EN 12341) and chemical
evaluation PM10 and PM2.5 were sampled using high-
volume devices with quartz fiber filters on a daily basis.
More detailed information is given in Table 1.
The measuring equipment was placed into air condi-
tioned containers except the high-volume samplers,
which were situated outdoors on the shady side and in
addition shielded with reflecting aluminum foils. Each
ARTICLE IN PRESS
Fig. 1. Monitoring sites within AUPHEP (Vienna—AUPHEP-1, Streithofen—AUPHEP-2, Linz—AUPHEP-3, Graz—AUPHEP-4).
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915 3907
4. monitoring instrument had a separate sampling inlet on
the top of the container. The distance between those
inlets was roughly a minimum of 1 m, the height above
ground about 4.2 m. TEOMs
monitors were operated
at 40
C sensor temperature. The sensor flow of the
TEOMs
s was set to 2 l min1
. To maintain comparable
conditions the beta-attenuation instruments had a
heated inlet tube (stainless steel) so that the probe also
reached a temperature of about 40
C.
The condensation particle counter (TSIs
) sampled via
a separate TSP-sampling inlet made of stainless steel to
minimize losses (static electricity, settling, coagulation)
with a flow of 20 l min1
. The tubing between the
instrument and inlet was about 5 cm long. Despite the
TSP inlet the particle number refers mainly to
small particles, the contribution of larger particles is
negligible.
Furthermore, detailed information on the chemical
composition and the size distribution of the main
aerosol components could be achieved. PM-samples
from PM2.5 and partly PM10 filters have been analyzed
for the most common ions (Na+
, NH4
+
, K+
, Ca2+
,
Mg2+
, Cl
, NO3
, SO4
2
, NO2
, Oxalate2
), selected
organic compounds of strong and weak polarity,
carbonaceous material (TC, EC, OC) and heavy metals
(As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, Zn). While
monthly averages were prepared for all sites and the
whole period, daily analyses were provided particularly
for those days interesting for the health studies.
Analytical details can be found in Puxbaum et al. (2004).
To strengthen the information on the size distribution
of atmospheric particles also two field campaigns during
summer and winter for at least 1 week each were carried
out using cascade impactors (Berner et al., 1979). A
corresponding program of chemical analyzes like for the
filters was conducted for the impactor samples.
Benzene and ammonia concentrations were deter-
mined as monthly averages by passive sampling
(Kasper and Puxbaum, 1994). On the days of the
impactor measurements also PAH samples were
taken and analyzed for naphthalene, acenaphthylene,
acenaphthene, fluorene, phenanthrene, anthracene,
fluoranthene, pyrene, benzo(b)naphthothiophene, cychlo-
pentapyrene, benz(a)anthracene, chrysene, benzo(b)
fluoranthene, benzo(k)fluoranthene, benzo(e)pyrene,
benzo(a)pyrene, indeno(1,2,3-c,d)pyrene, dibenzo(a,h)
anthracene, benzo(g,h,i)perylene, coronene.
In general, the analyzing program was more extensive
for the first part covering Vienna and Streithofen.
Nevertheless, this project provides a unique data set of
continuous data for numerous physical and chemical
PM-parameters over 1 year for four locations with a
time resolution of 24 h, for PM mass and number
concentration even of 30 min.
2.3. Database
All environmental data collected within AUPHEP are
stored in a central project data bank also used as link
between the different working groups. The data are
stored as Microsoft Excel files related to the four
monitoring sites. Furthermore, the data are grouped
into continuously sampled concentrations (PM mass-
fractions, particle number concentration, pollutant
gases) generally as half-hour means, the filter data
comprising mass concentration and results of the
chemical analyses generally as daily and monthly
averages, meteorological data (wind, precipitation,
temperature, humidity at the monitoring sites), and
results of the impactor campaigns. An information file
about the measuring sites completes the set.
All data are stored on a CD and shall be available for
scientific purposes on request.
2.4. Data quality assurance
To insure comparability and consistence of all data a
standardized calibration procedure and quality assur-
ance is essential. A QA/QC plan was designed and
implemented during the project considering probe/
ARTICLE IN PRESS
Table 1
Measured PM parameters and used instrumentation
Parameter Sampling system Size-selective inlet
TSP X-attenuation (FH 62 I-N, Eberline) TSP
PM10 TEOMs
(1400a, RP) FRM-PM10 Inlet (RP)
X-attenuation (FH 62 I-N and FH 62 I–R, Eberline) FRM-PM10 Inlet (RP, Eberline)
PM2.5 TEOMs
(1400a, RP) SCC PM2.5 Inlet (RP)
X-attenuation (FH 62 I-R, Eberline) WINS PM2.5 Inlet (Eberline)
PM1 TEOMs
(1400a, RP) PM1.0 Cyclone Inlet (RP)
X-attenuation (FH 62 I-R, Eberline) PM1.0 Cyclone Inlet (RP)
PM10–HiVol DPM10/30 (Digital), PALLFLEX quartz-fiber filter PM 10/30 10 mm (Digital)
PM2.5–HiVol DPM2,5/30 (Digital), PALLFLEX quartz-fiber filter PM 2,5/30 2.5 mm (Digital)
Particle number concentration CPC-TSIs
3022A (lower size detection limit 7 nm) TSP
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915
3908
5. sampling inlets, transfer lines, operating conditions of
the monitors, sampling, calibration, and conditioning of
the filters. The three continuously operating monitors
(TEOMs
s as well as beta attenuation monitors) at each
site were compared once a month for about 6 h using
equal size-selective inlets. The mean ratios of all half-
hour means between all three instruments and their
standard deviations are summarized in Table 2. The
relatively big deviation for beta attenuation at AU-
PHEP-1 can be traced back to single malfunctions of
one instrument. One example of these signals for the
monitoring site AUPHEP-3 is given in Fig. 2. Though
the mean ratios look quite satisfying singular deviations
as also shown in Fig. 2 affect the standard deviation
considerably. The particle counters were run in parallel
around every third month to ensure differences of a few
percent only. The Digital high-volume samplers were
operated with PM10 sampling heads in parallel before
the start and at the end of each measuring period
showing deviations of o72%. Since all comparisons
were made with atmospheric aerosol the spatial varia-
bility of the aerosol concentration is included.
ARTICLE IN PRESS
Table 2
Mean ratios and standard deviations of all corresponding half-
hour means during the periodical monitor comparisons
TEOM Beta-attenuation
Mean SD Mean SD
AUPHEP-1 1.05 0.37 1.85 4.22
AUPHEP-2 1.18 0.95 1.10 0.50
AUPHEP-3 1.05 0.67 1.04 0.58
AUPHEP-4 0.91 0.84 1.07 0.93
beta attenuation
-20
0
20
40
60
80
100
46
HHM
concentration
(µg
m
-3
)
concentration
(µg
m
-3
)
ß-A
ß-B
ß-C
Teom
-20
0
20
40
60
80
100
45 49
HHM
Teom-A
Teom-B
Teom-C
Fig. 2. Typical results of parallel runs of all continuously measuring instruments equipped with equal sampling inlets (PM10 or TSP
respectively) at one site (AUPHEP-2). The comparisons lasted about 6 h evenly distributed over the whole 1 year period. The
differences are due to instrument errors and spatial variability of PM-sampling.
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915 3909
6. The routines included daily, weekly and monthly
checks and maintenance procedures. Actual measure-
ment data of continuous measuring instruments as well
as status signals of discontinuous samplers were avail-
able on-line via internet.
The yield of the data, on a half-hour basis for
TEOMs
and X-attenuation systems and particle number
concentration as well as on daily basis for filter systems
usually was well above 90% and is shown in detail in
Table 3.
Average parameters from half-hour-means were
compiled corresponding with ÖNORM M 5866, i.e.
for a daily mean at least 40 half-hour means had to be
available. Long term (seasonal) parameters have to be
based on at least 75% of the half-hour-means.
3. Results and discussion
According to the intention of the project, the ambient
air quality data should give an overview on the PM
situation typical for Austria and similar Central
European conditions. PM10 up to now has not been
monitored continuously for a long period of time in
Austria, the smaller fractions (PM2.5 and PM1) had not
been measured at all. The same situation applies for the
particle number concentration. The following examples
shall give a brief survey on the data gathered within the
project. Detailed information can be found in separate
contributions (Gomiscek et al., 2004; Puxbaum et al.,
2004; Berner et al., 2004).
The annual averages together with the corresponding
maximum daily mean based on TEOM-measurements
(for TSP only beta attenuation data are available) are
summarized in Table 4. Generally, the concentrations of
all PM fractions were higher in the urban areas. The
seasonal variation of the PM fractions showed at all sites
no clear trend (Fig. 3), whereas the winter averages were
slightly higher than the summer values except for the
rural site. Also the highest daily concentrations occurred
during wintertime except for the rural site. In Vienna the
highest daily mean was found on New Year’s Eve
because of fireworks.
The monthly averages of the particle number con-
centration at the rural site AUPHEP-2 showed no
strong variability during the seasons of the year.
Moreover, it turned out that during the spring months
the concentrations were higher than during the winter
months (October–January) when the concentration
remained almost unchanged between 10,000 and
11,000 particles cm3
. On contrary, the seasonal varia-
tion in the urban atmosphere was clearly governed by
the local emissions from traffic and heating facility
sources during the winter months. Considerably lower
concentrations were observed during the warmer
months of the year. The difference in the particle
number concentrations between the urban and rural
station was relatively high throughout the whole year
with its maximum during the winter time, when the
ARTICLE IN PRESS
Table 3
Data availability (half-hour means) within AUPHEP system in %
Component PM1 PM2.5 PM10 Number-concentr.
Site X-atten. TEOM X-atten. TEOM HiVol X-atten. TEOM HiVol
AUPHEP-1 86.6 94 91.9 93.8 94.8 90.8 94.6 96.4 92.5
AUPHEP-2 94.8 91.9 95.5 94.4 98.9 80.6 94.3 90.2 89.6
AUPHEP-3 96.3 91 96 95.5 95.1 95.9 96.6 84.9 99.2
AUPHEP-4 96 97.1 96.6 97.1 91.5 97.8 95.5 84.7 94.8
Table 4
Long term averages and maximum daily means
Site PM1 PM2.5 PM10 TSP Number-concentr.
(mg m3
) (mg m3
) (mg m3
) (mg m3
) (cm3
)
Mean Max Mean Max Mean Max Mean Max Mean Max
AUPHEP-1 14.9 75.1 18.6 96.4 26.5 104.6 36.1 153.5 26.234 62.835
AUPHEP-2 12.4 35.4 15.0 47.7 21.1 52.5 24.1 78.7 10.320 50.938
AUPHEP-3 14.7 48.3 18.8 76.4 29.9 127.4 42.9 193.8 23.387 82.520
AUPHEP-4 17.5 70.4 21.1 81.2 31.0 114.1 38.4 142.1 22.540 54.075
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915
3910
7. urban/rural concentration ratio (Vienna/Streithofen)
exceeded a value of 3.5.
The ratios between the various fractions of PM based
on daily means are lined out in Table 5. The standard
deviations reflect the day-to-day variability of the size
spectra as well as variability of the measurement
systems. Since TSP monitoring was not part of the
project, the same QA/QC measures used for the smaller
fractions did not apply. Furthermore, the TSP data are
based on beta attenuation while all other PM concen-
ARTICLE IN PRESS
PM1 PM2.5 PM10 Part PM1 PM2.5 PM10 Part
PM1 PM2.5 PM10 Part PM1 PM2.5 PM10 Part
0
10
20
30
40
50
0
10
20
30
40
50
AUPHEP-1 AUPHEP-2
June 1999 to May 2000
mass
concentration
(µg
m
-3
)
mass
concentration
(µg
m
-3
)
number
concentration
(1000
cm
-3
)
number
concentration
(1000
cm
-3
)
0
10
20
30
40
50
0
10
20
30
40
50
AUPHEP-3 AUPHEP-4
Oct 2000 to Sept 2001
Fig. 3. Monthly average mass concentrations of PM10, PM2.5, PM1 and particle number concentrations for all project sites. AUPHEP
1/2 from June 1999 to May 2000, AUPHEP 3/4 from October 2000 to September 2001. Number concentrations refer to TSP.
Table 5
Mean ratios between the various mass-fractions of PM
Site PM10/TSP PM2.5/TSP PM1/TSP PM2.5/PM10 PM1/PM10 PM1/PM2.5
AUPHEP-1 0.74 0.52 0.42 0.70 0.57 0.82
AUPHEP-2 0.91 0.64 0.54 0.70 0.60 0.84
AUPHEP-3 0.71 0.45 0.37 0.64 0.50 0.81
AUPHEP-4 0.81 0.54 0.46 0.67 0.57 0.86
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915 3911
8. tration data shown are based on TEOM measurements.
The average percentage of TSP (which actually is
somewhat like PM40) for PM10 is around 80% while
the fine fraction (PM2.5) comes to roughly 50%. As the
average ratio PM1 to PM2.5 is 0.85, the differences
between PM1 and PM2.5 concerning mass concentration
are small. Chemical composition, however, and conse-
quently health effects may be substantial. These results
do not differ substantially from other European results
if remote areas are excluded (Monn et al., 1995;
Harrison et al., 1999, 2000; Ruuskanen et al., 2001;
Wiedensohler et al., 2002).
The beta attenuation data have not been addressed in
particular within this paper since for a general overview
they do not provide additional information. A compar-
ison of corresponding TEOM, beta, and filter based data
is given in Hauck et al. (2004).
Filters of PM2.5 and PM10 collected with HiVol
Digital samplers were analyzed for ions, heavy metals,
carbonaceous and organic substances. In Figs. 4 and 5
the results for the PM2.5 and the PM10 fraction as
monthly averages are presented. For all main substances
the concentrations were higher at the urban sites and,
generally, higher during the winter time, resulting in the
typical annual cycle of PM concentrations. In case of
sulfate the average PM2.5 concentrations were higher
during the warmer months of the year than during the
winter months (October–March), however sometimes
contrary for PM10. For all other substances (nitrate,
ammonium, black carbon and organic carbon) the
concentrations were evidently elevated during the winter
time. Similar concentration proportions were observed
for sulfate and ammonium at all sites, but absolute
values were higher in the urban atmosphere. Nitrate
concentrations showed high values in winter and
disappeared almost completely during the summer
months—such behavior was observed at all sites and
the results may be due to the artifacts of the measure-
ment techniques (continuous and gravimetric) for the
determination of semi-volatile and volatile substances of
PM (Hauck et al., 2004). Namely secondary particles
which are more pronounced in the fine fraction and
usually form over several hours or even days are semi-
volatile or volatile—notably those containing ammo-
nium nitrate. This volatility has large impact on
measurements of gas as well as particle concentrations
in the ambient air.
The carbon data focusing predominantly on PM2.5
show higher concentrations in winter than in summer.
Black carbon generally is slightly higher than OC for all
urban sites, for the rural site partly OC exceeds BC. TC
concentrations are in the range between 6 and
ARTICLE IN PRESS
Fig. 4. Monthly average concentrations of chemical composition of PM2.5.
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915
3912
9. 7.5 mg m3
(annual mean) for the urban sites, for the
rural site the corresponding value is 4.5 mg m3
.
4. Health effects studies
Several studies on health effects related to PM were
conducted within the AUPHEP project, investigating
short term health effects of PM (and subfractions) on
risk groups in the general population. In particular, the
lung function of pre-school children (age 3–6 years) in
Vienna and of elementary school children (age 6–11
years) in Vienna, Streithofen and Linz was examined in
cross-sectional and time series approaches. At pre-
school age lung function tests by means of induction
plethysmography over the winter period 1999/2000 were
correlated with the air quality data of AUPHEP-1 and
indicators of indoor pollution such as cotinine. All PM
fractions as well as particle number concentration
showed a negative trend with lung function parameters.
In particular the organic carbon fraction showed a
significant negative association (Horak et al., 2001). In
elementary school children lung function was tested by
spirometry including flow-volume loops and by oscillo-
resistometry. From earlier cross-sectional and long-
itudinal studies on Austrian school children showing
improvements of pulmonary functions with reduction of
urban air pollution (Neuberger et al., 2002) only
remnant lung function deficits had been expected to be
air pollution related, however, in 2000/2001 short term
increases in fine particles were still followed by acute
decreases of lung function in healthy children and by
increases in pulmonary symptoms in a risk group
(Moshammer and Neuberger, 2003).
A further investigation will be comprised in the area
characterized by the AUPHEP exposure data as a
questionnaire based study with school children (primary
and secondary schools, pupils up to age 14). Symptoms
of respiratory and associated diseases are covered in
four cycles in such a pattern that data for all seasons will
be available (Kundi et al., 2004).
In a last approach time-series analyses of official
health statistics data from the whole AUPHEP-area
including exposure and weather data from these areas
are performed. Time-series data of morbidity (admission
data and final diagnosis from hospital records of
patients from these areas) as well as mortality due to
respiratory and cardiovascular causes in children and
elderly persons are linked with exposure and meteor-
ological data.
Most of these studies are still going on. A complete
overview including first results of time-series studies on
ARTICLE IN PRESS
Fig. 5. Monthly average concentrations of chemical composition of PM10.
H. Hauck et al. / Atmospheric Environment 38 (2004) 3905–3915 3913
10. respiratory diseases and symptoms is given in Neuberger
et al. (2004). Details will be given later in separate
special papers.
Acknowledgements
The project has been funded by the Ministry for the
Environment, Youth and Family Affairs and the
Ministry for Science and Traffic (contract No 14 4440/
45-I/4/98), and the Austrian Academy of Sciences.
Additional contributions have been made by the
ambient air monitoring networks of the Austrian
Provinces, the Federal Environmental Agency and
several companies.
We appreciate the substantial input from the project
advisory board. The cooperation of the schools, parents
and children participating in the health studies is also
warmly recognized.
Mention of the trade names or commercial products
does not institute endorsement or recommendation
for use.
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