Traffic emissions and tobacco smoke are considered two main sources of polycyclic aromatic
hydrocarbons (PAHs) in indoor and outdoor air. In this study, the impact of these sources on
the level of fine particulate matter (PM2.5) and on the distribution of 15 PAHs regarded as
priority pollutants by the US-EPA on PM2.5 were evaluated and compared.
Outdoor and indoor PM2.5 samples were collected during winter 2008 in Oporto city in
Portugal, for sampling periods of 12 and 24 hours, respectively. The outdoor PM2.5 were
sampled at one site directly influenced by traffic emissions and the indoor PM2.5 samples were
collected at one home directly influenced by tobacco smoke and another one without smoke.
A methodology based on microwave-assisted extraction and liquid chromatography with
fluorescence detection was applied for the efficient PAHs determination in indoor and outdoor
PAHs in indoor PM2.5 concentrations were significantly influenced by the presence of traffic
and tobacco smoking emissions. The mean of ΣPAHs in the outdoor traffic PM2.5 was not
significantly different from the value attained in the indoor without smoking site.
The tobacco smoke increased significantly PAHs concentrations on average about 1000
times more, when compared with the outdoor profile samples suggesting that tobacco
smoking may be the most important source of indoor PAHs pollution.
The aim of the present work was to characterize particulate matter (PM) and elemental
carbon (EC) indoor and outdoor concentration levels in the Athens area and to examine the
contribution of ambient air to the observed indoor levels.
24-hr simultaneous indoor and outdoor PM10 and PM2.5 measurements were conducted at a
central (CR) and a suburban (SR) residence, and at an office in the commercial centre of
Athens (CO), during cold and warm period of 2006. The absorption coefficient (α) was
measured on the collected filters, as a surrogate for EC concentration levels.
Ambient PM levels were very high at both central sites and significant at SR (mean 24-hr
PM10: 87.4, 50.3 and 87.3 μg m-3 and PM2.5: 50.7, 20.2 and 42.8 μg m-3 at CR, SR and CO).
The measured absorption coefficient values were very high at CR and CO for both size
Indoor PM concentration and absorption coefficient values were lower than the respective
outdoor ones, but still significant at the two central sites.
Very good correlations were observed between indoor and outdoor data (especially for
absorption coefficient values), indicating a large contribution of the ambient atmosphere to the
indoor levels, more pronounced in finer particles.
Particulate matter is one of the most important indoor air pollutants involved in a number of
adverse health effects, such as premature deaths and increased mortality of infants and other
parts of sensitive population.
This paper focuses on investigation of metal substances of suspended as well as settled
particulate matter in indoor environment. The monitoring of particulate matter concentration
was carried out in three rooms of a selected flat building in the city of Košice, Slovakia. The
sampling of settled particulate matter was carried out by passive methods during the period of
28 days. The investigation of suspended particulate matter investigation focused on total
suspended particles (TSP) and thoracic fraction called PM10. The presence of selected metals
in the samples was detected by atomic absorption spectrometry.
The surface concentrations of settled particulate matter were detected in the range from
276.43 μg cm-2 to 570.70 μg cm-2, mass concentrations of total suspended particulate matter
from 59.028 to 114.583 μg m-3. PM10 concentration values reached about half of the TSP
concentration values (PM10/TSP ratio was from 0.48 to 0.6). Higher percentage of metals
was detected in suspended particulate matter in comparison to the settled particles. Higher
values were detected for all metals (except iron and zinc) in each measured room.
In this study, the Bayesian approach is proposed to estimate the noise variances of Kalman
filter based statistical models for predicting the daily averaged PM10 concentrations of a typical
coastal city, Macau, with Latitude 22°10’N and Longitude 113°34’E. By using the
measurements in 2001 and 2002, the Bayesian approach is capable to estimate the most
probable values of the noise variances in the Kalman filter based prediction models. It turns
out that the estimated process noise variance of the time-varying autoregressive model with
exogenous inputs, TVAREX, is significantly (~76%) less than that of the time-varying
autoregressive model of order 1, TVAR(1), since the TVAREX model incorporates important
mechanisms which govern the daily averaged PM10 concentrations in Macau. By further using
data between 2003 and 2005, the choice of the noise variances is shown to affect the model
performance, measured by the root-mean-squared error, of the TVAR(p) model and the
TVAREX model. In addition, the optimal estimates of noise variances obtained by Bayesian
approach for both models are located in the region where the model performance is
insensitive to the choice of noise variances. Furthermore, the Bayesian approach will be
demonstrated to provide more reasonable estimates of noise variances compared to the
noise variances found by simply minimizing the root-mean-squared prediction error of the
model. By comparing the optimized TVAREX model and the TVAR(p) models in predicting the
daily averaged PM10 concentrations between 2003 and 2005, it is found that the TVAREX
model outperforms the TVAR(p) models in terms of the general performance and the episode
In this paper, three-dimensional numerical simulations are used to simulate the wind flow
structure over coal stockpiles of a real configuration of a power plant. Two configurations are
tested for various wind directions: the first one without representing the buildings and the
second one with the surrounding buildings in the calculation domain. The wind flow properties
over the full site and near the stockpile surfaces are analyzed in order to understand the dust
emission mechanisms over the various tested configurations. The emission factor formulation,
proposed by the EPA to quantify fugitive dust emissions from a stockpile, is used to check the
particle emission rate for each considered configuration using the velocity fields given by the
The analysis of the results from the two tested configurations shows by evidence that the
topography of the industrial site exerts large perturbations on the flow structure over the site.
This work shows that previous studies carried out without taking into consideration the
topography of the site probably lead to an inaccurate estimation of the fugitive dust emissions.
This study highlights the necessity to take into account the presence of surrounding buildings
to estimate and quantify the particle emission rate on stockpiles.
The study reported in this paper improves the understanding of fugitive dust emissions on
industrial sites and in mining zones. These results will allow a more accurate and relevant
evaluation of fugitive dust emissions from open storage systems on industrial sites and a
better evaluation of its environmental impacts.
One of the main environmental impacts of pig farms are the swine odours emitted from the
various stages of the process. The main cause of odour emissions from pig farms are the
anaerobic processes in manure. Numerous factors affect odour emissions such as diet,
manure management and manure age. The majority of the odorous compounds emitted from
pig farms are sulfurous organic compounds, hydrogen sulfide, phenols and indoles, ammonia,
volatile amines and volatile fatty acids (VFA’s) whose presence in the atmosphere causes
annoyance at relatively low concentrations. However, the detection and quantification of these
compounds at a daily basis is difficult because of their chemical instability and the fact that
they can be tracked only using techniques of gas chromatography. For the needs of the
present study many instantaneous measurements performed during the day in order to
estimate the daily variation of their emissions. This is the reason why the compounds studied
were hydrogen sulfide and ammonia. Both compounds have low odour threshold (0.47 ppb
for hydrogen sulfide and 130 ppb for ammonia). In the present study, the results of odour
concentration measurements sampled from a pig production unit placed close to the city of
Rethymno (Crete, Greece) are presented. These measurements are used to estimate the
emissions of hydrogen sulfide and ammonia from the various chambers of the pig farm. The
emission data were used as input data for the dispersion model AERMOD for an area of 10
km2 surrounding the odour source in order to determine the maximum allowed emissions in
order not to cause complaints from nearby residents. Modifications were performed in the
model based on the “peak to mean” ratio in order to predict the maximum odour
concentrations with few seconds time-scale. Also, relations between odour annoyance and
odour exposure concentrations have been used in order to express the odour impacts in
terms of probability of detection, probability of discrimination and degree of annoyance. These
parameters were embedded into the AERMOD model in order to be able to use this program
as an odour dispersion model. The results are provided as probability of detection and
probability of annoyance instead of hourly mean concentrations. Several scenarios were
examined using the modified AERMOD program taking into account the complex terrain
around the pig farm. Finally, the effect of raising the height of the stacks to the concentrations
around the facility was examined as a possible solution to the situation.
Particulate matter measurements were performed at the Akrotiri research station on the island
of Crete (Greece) using an 8-stages Andersen non-viable impactor. The main purpose of the
current work was to measure the ambient levels of PM10 particulate matter as well as the
concentrations of metals and ions in 8 different PM size fractions with aerodynamic diameter
cutoff at 9, 5.8, 4.7, 3.3, 2.1, 1.1, 0.7, 0.4 and a back-up filter for particles below 0.4 μm.
The mean PM10 concentration during the first sampling period of August 2007 was equal to
28.2 ± 14.0 μg m-3 (10/08/2007 – 26/08/2007), whereas during the second sampling period
(09/07/2008 – 16/07/2008) was 40.2 ± 16.9 μg m-3. Moreover, mean concentrations of PM2.1
particulate matter were measured on the average equal to a 41.0 % and 37.2 % of PM10,
respectively for the two corresponding sampling periods. The measurements showed high
concentration of fine particles (with aerodynamic diameter less than 0.9 μm), whereas the
mass concentration peak was located at an aerodynamic diameter close to 4 - 5 μm. Sulphate
was the most abundant anion PM10, whereas sea production ions, such as chlorine, sodium
and nitrate, were also in elevated concentrations presented. In addition, the crustal element
Fe was in higher concentrations in comparison to the measured heavy metals.
About 140 samplings of fine and coarse particles were gathered during the year 2006 in
Kozani that represent an urban area surrounded by opencast coal mining.
A low volume dichotomus sampler has been used to trap suspended particles. The filters
used were teflon, which are ideal for analysis in the determination of PAHs. The determination
of Polycyclic Aromatic Hydrocarbons (PAHs) has been carried out by the use of the analytic
technique of large volume injection and gas chromatography – mass spectrometry (LVI -
GC/MS). The extraction of substances has been made in a two stage procedure, firstly with
agitation in a magnetic shaker and secondly by the use of ultrasonic bath. This technique has
given high recoveries of PAHs, in short time intervals. The mean daily concentrations of fine
particles varied from 4 to 48 μg m-3 and annual mean was 16 μg m-3. The mean daily
concentrations of coarse particles respectively varied from 2 to 67 μg m-3 with 23 μg m-3
annual mean concentration.
The ΣPAH concentrations for fine samples were 4.80 ± 7.06 ng m-3 and for coarse samples
were 1.36 ± 1.59 ng m-3. The mean B[a]Py concentration for fine particles was 0.38 ng m-3.
Finally, diagnostic ratios were used to characterize and identify PAHs emission source in this
The analysis of the PM10 particle measurements at the two major urban areas of Greece,
Athens and Thessaloniki, showed that the mean monthly PM10 concentrations at the central
urban stations, are on the average about twice as high than the corresponding ones at the
examined peripheral stations. The distribution of the daily PM10 values shows significant
violations of the EU air quality standards, especially in the central urban stations. At the
peripheral stations comparable distributions of PM10 concentration values are found. The
highest PM10 hourly values are recorded at the central urban stations during the cold
semester of the year and during the morning hours. The scatter-plot diagrams of the central
urban daily PM10 mean values versus the peripheral stations show important influence of the
regional aerosol episodes on the measured PM10 concentrations in the urban areas of Athens
and Thessaloniki, which is stronger in Athens and during the warm semester of the year. The
PM10 diurnal variation pattern are quite similar with the corresponding variations observed for
primary urban pollutants, like the morning and the evening peaks, but also at the peripheral
stations exhibit a broad mid-day peak indicating elevated rural background PM10 levels.
Additional daily measurements at the rural station of Aliartos in Central Greece give PM10
average values around 30 μg m-3, comparable to the corresponding average PM10 values of
the peripheral stations in Athens and Thessaloniki. Such high rural background PM10 daily
mean values could lead to average annual values higher than the corresponding EU PM10
standard (40 μg m-3) and should be taken into account in the formulation of the local pollution
abatement strategies as they represent about the half of the average PM10 levels measured at
the central urban stations of both examined urban areas.
The relationship between the viable airborne bacterial and fungal concentrations and the
respirable particulate matter with aerodynamic diameter less than 10 μm (PM10), 2.5 μm
(PM2.5), and 1 μm (PM1) in the ambient air was studied. An Andersen six stage viable particle
sampler and a MAS 100 sampler were used for microbial measurements. Duplicates of
samples were collected at each sampling period (20 campaigns in total) at a residential site in
the city of Chania (Crete, Greece) during April, May and June 2008.
Mean concentration of the total sum of the six size fractions was 79 + 41 CFU m-3 for
mesophilic heterotrophic bacteria, whereas for mesophilic fungi it was five times higher (395 +
338 CFU m-3). Particulate matter measurements at the same time period at the same site
revealed that the mean concentrations of PM10, PM2.5, and PM1 were 46 + 14, 35 + 14, and 28
+ 12 μg m-3, respectively, whereas the mean cumulate counts of PM1 particles was 5,059 +
1,973 particles cm-3. The mean arithmetic concentration of the size distribution of the airborne
fungi had a maximum at aerodynamic diameters between 2.1 and 3.3 μm. However, a
maximum was not observed for the mean arithmetic concentration of the size distribution of
the airborne heterotrophic bacteria. It was also observed that concentrations of airborne
bacteria and fungi outdoors were highly variable and do not correlate with the particle number
(PM1) or mass concentration of PM10, PM2.5 and PM1. Thereby, the R2-values in all
correlations were less than 0.3. However, the concentrations of airborne bacteria and fungi
were decreased with increasing mass concentrations of PM10, PM2.5, or PM1 while were
increased with increasing number concentration of PM1. In addition, the concentrations of
airborne bacteria were increased with increasing concentrations of airborne fungi. Finally, the
microbial or the particulate matter data did not correlate with meteorological parameters, such
as temperature, relative humidity, wind speed and UV radiation in ambient conditions.