Advances in Meteorology
Volume 2018 (2018), Article ID 7529043, 11 pages
https://doi.org/10.1155/2018/7529043

Research Article

Overview of Air Pollution Assessment in Northern Europe (Lithuania) by Passive Diffusion Sampling

Steigvilė Byčenkienė,¹ Dalia Jasinevičienė,¹ and Donatas Perkauskas²

¹Center for Physical Sciences and Technology, Savanorių 231, 02300 Vilnius, Lithuania
²Environmental Protection Agency, Juozapavičiaus St. 9, 09311 Vilnius, Lithuania

Correspondence should be addressed to Steigvilė Byčenkienė; steigvile.bycenkiene@ftmc.lt

Received 28 June 2018; Accepted 5 November 2018; Published 27 November 2018

Academic Editor: Enrico Ferrero

Copyright © 2018 Steigvilė Byčenkienė et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The regional air pollution study in Lithuania provided a comprehensive overview of air quality in Lithuania (in Vilnius (capital) and rest of territory) when 375 monitoring sites at different representative locations (urban, suburban, and residential) were equipped with diffusion samplers. The samples were analyzed for sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) concentration. The measurement results show that the mean concentrations of SO₂ in all investigation sites during the study period did not exceed the annual limit value of 20.0 μg·m⁻³ and were below the lower assessment threshold value of 8.0 μg·m⁻³. The mean concentrations of NO₂ in Vilnius agglomeration exceeded the annual limit value of 40 μg·m⁻³ at seven sites and in zone–at three sites with the intensive traffic flow, located near to highway. Comparison of SO₂ and NO₂ concentration levels was performed for 2004-2005 and 2010-2011. The level of nitrogen dioxide concentrations has decreased by 34, 26, 24, and 49% during the next six years in the city of Vilnius, and the concentration of SO₂ in the air environment decreased by 40–60%.

1. Introduction

During the past 20 years, there has been a marked improvement of the air in Europe [1]. As SO₂ produced by burning of fossil fuels significantly contributes to acid deposition, it affects ecosystems and is harmful for human health. Nitrogen oxides are mostly produced during combustion by industrial facilities and the road transport sector.

Nowadays, the main goals of monitoring lie in providing useful up-to-date information to the public on pollutant concentrations in ambient air, as well as supporting economical stakeholders and decision makers in air-quality assessment and management. Instruments for air quality may change in complexity and cost. While air pollution is highest in urban zones, the monitoring efforts are typically concentrated in cities, and little sites represent the background level. The financial resources are not equal in different countries, and there are no possibilities to extend monitoring network or upgrade of equipment. The use of passive samplers greatly reduces the cost and the need of long-term measurement programs [2–4]. Personal passive air samplers have been developed and widely used to measure gaseous air pollutants since their introduction in the late 1970s [5, 6].

Monitoring of air pollution in Lithuania is organized by the Environmental Protection Agency. Currently, Lithuanian national air-monitoring network consists of one mobile, fourteen continuously operating urban stations, and three integrated monitoring (IM) stations. European Union (EU) environment law acts and legislation were applied and implemented by the National Environmental Monitoring Program (NEMP).

In this paper, within the framework of “Lithuanian Air Monitoring System Modernization Using Diffusive Samplers” (LAQMO) project for the first time were evaluated the concentrations of SO₂ and NO₂ by determining the ambient concentration using the passive sampling method at 375 sites in Lithuania. The spatial maps of compounds using geographical information systems (GIS) were evaluated on one year measurements with diffusive air samplers.

2. Methodology

The analysis of concentration for SO₂ and NO₂ using diffusive samplers were set up in the urban background (residential), semiurban (mixed residential and commercial), and roadside (busy street/road and crossing) sites in order to get spatial variation in pollutants concentrations. The obtained data were compared with the acceptable levels of air pollutants that are adopted in the EU as the limit values (Table 1).

Table 1: Atmospheric air quality (μg/m³) guidelines for selected air pollutants aiming to protect human health adopted by the European Union Council Directive 2008/50/EB.

SO₂
NO₂

Annual limit value (LV)
20 (vegetation)
40 (human health)

Upper assessment threshold (UAT)
12
32

Lower assessment threshold (LAT)
8
26

2.1. Campaigns

The most appropriate sites for placement were determined. For purposes of taking into account the influence of weather conditions, a network of 375 passive samplers was deployed for all four seasons: autumn (September–November) 2010, winter (December–February), spring (March–May), and summer (June–August) of 2011 and were covered in 8 measurement periods (Table 2).

Table 2: The measurement periods.

Season
Period
From
To

I autumn
1
5.11.2010
17.11.2010

2
17.11.2010
1.12.2010

II winter
3
6.1.2011
20.1.2011

4
20.1.2011
3.2.2011

III spring
5
25.2.2011
8.4.2011

6
8.4.2011
22.4.2011

IV summer
7
6.6.2011
20.6.2011

8
20.6.2011
4.7.2011

10% of the sampler was in duplicates, i.e., some colocated passive samplers were deployed at the sampling sites with available continuous monitors for cross correlation and calibration purposes [7]. This information was used for uncertainty calculation in the framework of GUM (Guide to the expression of Uncertainty in Measurement), applied in the laboratory of Passam Ltd., Switzerland (Table 3).

Table 3: Uncertainty in measurements.

Analyte

Limit value (μg/m³)
Standard deviation

NO₂
Annual mean
40
3.9

UAT
32
4.8

LAT
26
5.9

SO₂
Annual mean
20
5.4

UAT
12
8.9

LAT
8
13.4

Eight sampling campaigns of 14 days were carried out in Vilnius agglomeration and zone (the rest part of Lithuania). The locations of the monitoring sites in Vilnius and zone selected for the passive sampling is shown in Figure 1.

Figure 1: Location of diffusive samplers.

2.2. Description of Samplers and Measurement Uncertainty

Passive samplers deployed in different city sites were collected after 14 days of exposure time intervals. The passive samplers were provided and analyzed by PASSAM AG (Switzerland). As supplied by the firm, the tubes are protected from sunlight by an opaque cylindrical box. These samples have been exposed to sites with different sources of atmospheric emission and environments (Section 2.1).

Although several approaches to uncertainty evaluation exist, the indirect approach of GUM published by the ISO was used (Table 4). The permanent verification of the sampling rate, based on weight losses of permeation tubes, is an independent way of checking the overall performance of diffusive sampling systems. The output information is important for assessing measurement uncertainty. With this procedure, the requirements of ISO 9001 (process control) was fulfilled as well. Furthermore, with this procedure, long-term stability of results was guaranteed, and measurement results were comparable over time. The calculation of uncertainty started on the basis of the following measurement equation:

where is the ambient concentration, μg·m⁻³; is the mass of desorbed analyte, μg; is the blank of analyte, μg; is the diffusive uptake rate, ml/min; and is the exposure time. The input quantities and their uncertainties are defined as follows:

 : uncertainty of the mass of absorbed analyte. The standard uncertainty can be characterized by the standard deviation of the calibration function. : blank values. The variation of the blank value has to be added to in absolute terms uSR—uncertainty of sampling rate. The variation of this term is given by the standard deviation of repeated verification experiments in standard atmospheres. : exposure time. This term is in general negligible at exposure times of more than one week. At shorter times, this term has been taken into account.

Table 4: Uncertainty estimation according to GUM.

Component

Limit value (μg m⁻³)
Uncertainty combined
Uncertainty expanded
Umean

NO₂
Annual mean
40
10.8
21.6
7.7

UAT
32
10.2
9.9
7.3

LAT
26
20.5
19.7
7

SO₂
Annual mean
20
11
22.1
7.8

UAT
12
13.1
26.2
9.3

LAT
8
16.7
33.5
11.9

C₆H₆
Annual mean
5
14.1
28.2
10

UAT
3.5
17.3
34.6
14.1

LAT
2
26.6
53.3
18.9

An additional term has been introduced, which covers the uncertainties budgets of repeated measurements, microenvironmental factors, variations in the geometry of samplers, etc.

 : variation of multiple samples at the same site. The size of this term is estimated by the median of triplicate samplers in the field. : external influences such as temperature, wind speed, and humidity. This term has to be taken into account, if the samplers are used in extreme conditions.

The combined uncertainty is calculated as follows:

The expanded uncertainty is calculated by using a coverage factor of 2:

The uncertainty of the mean of the 8 periods is calculated as follows:

2.3. Spatial Interpolation

Maps of the pollutant concentrations over the area were obtained by interpolation of the passive sampler measurements. By using custom-made automated scripts on open source GRASS GIS software (version 6.4), the following geostatistical methods commonly used for surface interpolation from randomly sampled points: inverse distance squared weighting (IDW; GRASS function v.surf.idw), bicubic spline interpolation (BCS; GRASS function v.surf.bspline), and kriging interpolation with automated calibration of parameters (AK; GRASS function v.krige) were tested [8].

By comparing statistical variability of the interpolated datasets, it became obvious that with increasing search radius (N of neighboring points used in interpolation), the IDW method produced rather unstable results, the BCS method under similar conditions (increasing length of splines) produced clearly predictable results with a slight tendency of statistical “smoothing” of the interpolated grid, while AK indicated the most stable statistical results due to its ability to autocorrelate all measurements in the sample [8].

In order to streamline the process of geostatistical data analysis and operational mapping, a customized Linux shell script was developed. It uses geostatistical and mapping functions of the open source GRASS GIS software (v.surf.bspline), as well as some of the Linux OS libraries (libgdal, libgeotiff, libpng, etc.) to automatically generate geostatistical grids and operational maps by iterating over each of the polygon objects (urban areas, etc.) by using standard samples of coordinated measurement points as an input. Geostatistical grids will be created in GRASS GIS environment with 10 m pixel size in the standard LKS94 CRS and masked with boundaries of the urban areas. They will be exported from GRASS database as Float64 data type rasters in GeoTIF file format without any associated color table [8].

3. Results

3.1. Vilnius Agglomeration

3.1.1. Sulfur Dioxide

The SO₂ passive samplers were exposed for periods of 2 weeks each at a time over the study period (120 samples). The values of passive samplers for SO₂ ranged between approximately 0.7 and 1.8 μg·m⁻³. The exceedance above the annual limit value (20.0 μg·m⁻³) for the ecosystems was not observed. The examination of seasonal variation patterns revealed valuable information. As expected, SO₂ values show seasonal variation. The period of measurement was analyzed corresponding to the four seasons: winter, spring, summer, and fall. The temporal variation for all of the 14 sampling sites is presented in Figures 2 and 3. SO₂ concentration during the entire period of observation ranged from a minimum (0.15 μg·m⁻³) in summer to a maximum (3.05 μg·m⁻³) level in winter.

Figure 2: Seasonal variation of mean SO₂ concentrations for the entire study period from 3 November 2010 to 4 July 2011 (bar lines show ±22.1% expanded uncertainty).

Figure 3: Seasonal variation of mean SO₂ concentrations for the entire study period.

During fall, the mean SO₂ concentration had the highest level (up to 1.80 μg·m⁻³) at sites located in the residential and recreation areas with a mean concentrations ranging from 0.5 to 1.3 μg·m⁻³. In wintertime, SO₂ concentrations ranged from 0.5 to 4.1 μg·m⁻³. The highest mean values for this study period were found to be between 3.1 and 2.3 μg·m⁻³. The results indicate that in springtime, SO₂ concentrations ranged from 0.2 to 4.1 μg·m⁻³. The minimum mean value (0.4 μg·m⁻³) of SO₂ concentration was measured at a site in a residential area and the maximum (3.0 μg·m⁻³) in traffic-influenced area. During the summer study period, SO₂ concentrations ranged between 0.2 and 2.1 μg·m⁻³.

Data indicate that at sites in the residential and recreation areas, the higher SO₂ levels were recorded in autumn, winter, and spring, when the emissions from energy production are at their highest level (Figure 4).

Figure 4: Annual mean concentrations of SO₂ in Vilnius.

Conversely, the lowest SO₂ levels were measured in the summer period. Therefore, the seasonal variability of concentrations should be interpreted using existing knowledge on emission and meteorological patterns. In summary, the mean sulfur dioxide concentration in Vilnius ranged from 0.2 to 3.1 μg·m⁻³ with an annual mean of 1.1 μg·m⁻³.

3.1.2. Nitrogen Dioxide

The obtained data (35 sites) during all the study period revealed that NO₂ concentrations varied considerably, which coincides with the other study depending on the distance of the measurement site from main roads caused by the large numbers of vehicles releasing NO₂ [9]. For the entire study period, the mean concentration for the NO₂ ranged between 9.1 and 55.6 μg·m⁻³ (Figures 5 and 6). The NO₂ concentrations demonstrate a large spatial gradient (up to factor of 5), which indicate that road traffic is an important contributor to the NO₂ concentration in urban environment with a mean concentration above the NO₂ limit value of 40 μg·m⁻³. However, the mean concentrations of NO₂ at sites with the minor traffic density were close to the upper assessment value of 32 μg·m⁻³ (Figure 6). At sites in the most visited areas with high density of motor vehicles, the mean concentration of NO₂ ranged between 26.0 and 42.1 μg·m⁻³. Thus, an exposure to NO₂ concentrations represents a serious risk to human health. The data analysis indicates (Figure 5) that the mean NO₂ concentration during 3 November–1 December 2010 ranged from 9.6 to 53.8 μg·m⁻³ depending on the site environment. The NO₂ concentrations measured at almost all traffic sites were higher than those at the residential or urban background sites and ranged between 18.6 and 53.8 μg·m⁻³. The limit value of 40 μg·m⁻³ as annual mean concentration of NO₂ was exceeded at 5 sites with intensive traffic flow: Vilnius 13, 18, 20, 27, and 31. The mean concentration of NO₂ reached a value of 46.9 μg·m⁻³. The exceedances above the NO₂ limit value (40 μg·m⁻³) were not observed at sites in the residential area, and they ranged from 13.0 to 29.9 μg·m⁻³. The NO₂ concentrations at sites in the recreation and suburban background areas were in the range 9.6–36.6 μg·m⁻³ and were below the lower assessment threshold (26 μg·m⁻³). In wintertime (6 January–3 February 2011), mean NO₂ levels ranged from 9.6 to 57.4 μg·m⁻³ (not shown). The highest mean values of NO₂ for this study period achieved or exceeded the limit value of 40 μg·m⁻³ at 7 sites in traffic sites. The upper assessment threshold value of 32.0 μg·m⁻³ was exceeded at 3 sites in a high traffic area. In spring, mean values of NO₂ varied from 7.8 to 60.1 μg·m⁻³ differing from site to site. Remarkably higher NO₂ concentrations with values of 42.8, 43.0, 54.0, 56.5, and 59.3 μg·m⁻³ were observed, respectively, at the traffic-exposed sites. As can be seen from Figure 5, higher levels of NO₂ were measured during summer at some sites in the residential and recreation areas (20.8–28.3 and 22.7–40.2 μg·m⁻³, respectively). As expected, NO₂ concentration was significantly higher in the residential and recreation areas at the sites influenced by transport emissions. Seasonally averaged concentrations of NO₂ were generally higher during winter and spring nearly at all sites. The lowest NO₂ levels were measured in summer (Figure 5).

(a)

(b)

(c)

Figure 5: Seasonal variation of mean nitrogen dioxide concentrations at site-specific areas for the entire study period from 3 November 2010 to 4 July 2011 (bar lines show ±21.6% expanded uncertainty). (a) Vilnius, transport. (b) Vilnius, residential. (c) Vilnius, suburban.

Figure 6: Annual mean concentrations of NO₂ in Vilnius agglomeration for the period from 3 November 2010 to 4 July 2011.

3.1.3. The Seasonal Variation of Atmospheric Sulfur Dioxide and Nitrogen Dioxide Concentrations in Zone

The mean concentrations of NO₂ in 40 zones’ territory sites, during the study period did not exceed the annual limit value of 40.0 μg·m⁻³. The spatial distribution of NO₂ concentrations indicates the tendency to be the higher concentrations in the west part of Lithuania. The principal sources of nitrogen dioxide are traffic and to a lesser extent industry and households. High NO₂ levels, combined with other oxidants, have become one of the major air pollution problems in urban areas. For the entire study period (from 6 November 2010 to 4 July 2011), the mean annual concentrations of NO₂ at different sites in the zone were in the range from 3.6 μg·m⁻³ to 59.6 μg·m⁻³ (Figure 7). Regarding the annual limit value of 40 μg·m⁻³, it was exceeded at three sites with high traffic flow in Klaipeda04 (44.6 μg·m⁻³), Klaipeda09 (44.7 μg·m⁻³), and Klaipeda11 (51.7 μg·m⁻³). At the sites, which were in an area with the relatively intensive traffic flow (Panevezys01 and Siauliai02), annual mean NO₂ concentrations were found to be 27.3 and 33.9 μg·m⁻³, respectively. The exceedances above the NO₂ limit values were not observed at sites in the residential or the suburb areas. Data indicate that the influence of heavy traffic flows reflected on the annual average NO₂ concentrations at sites located near to the highway A1 (Grigiskes01 and Vievis). Annual average NO₂ concentrations were 40.3 μg·m⁻³ and 33.5 μg·m⁻³. Annual average NO₂ concentrations were between the lower and the upper assessment threshold values at sites exposed to traffic in urban environment Mazeikiai (27.4 μg·m⁻³), Kedainiai (31.7 μg·m⁻³), Telsiai (28.1 μg·m⁻³), and Taurage (34.4 μg·m⁻³). At sites Jonava01 (μg·m⁻³), Trakai01 (26.8 μg·m⁻³), Utena01 (26.7 μg·m⁻³), and Plunge01 (26.7 μg·m⁻³), annual average NO₂ concentrations were close or slightly exceeded the lower assessment threshold value. The annual average NO₂ concentrations at major sites in the other towns of zone were in the range from 3.6 to 20.0 μg·m⁻³.

Figure 7: Annual mean concentrations of NO₂ in the zone (58 cities) for the period from 3 November 2010 to 4 July 2011.

The mean concentrations of SO₂ in 40 zones’ territory sites during the study period did not exceed the annual limit value of 20.0 μg·m⁻³ and were below the lower assessment threshold value of 8.0 μg·m⁻³. The spatial distribution of SO₂ concentrations indicates the tendency to be the higher concentrations in west and southwest parts of Lithuania. As can be seen (Figure 8), during autumn (3 November–1 December 2010), the averaged SO₂ concentration had the highest value of 5.0 μg·m⁻³ at site with crossing of streets. In a residential area, the highest values of SO₂ were 5.0 μg·m⁻³ and 4.3 μg·m⁻³. At the rest sites in zone, average concentrations of SO₂ ranged from 0.20 to 3.5 μg·m⁻³. In winter (6 January–3 February 2011), SO₂ concentrations ranged from 0.30 to 5.40 μg·m⁻³, from 0.10 to 2.10 μg·m⁻³, and from 0.60 to 2.60 μg·m⁻³, respectively. Overall, the SO₂ concentration ranged from 0.2 to 4.8 μg·m⁻³ at the rest sites in the zone. The results indicate that in the springtime (25 March–22 April 2011), SO₂ mean concentrations ranged from 0.20 to 1.50 μg·m⁻³ and from 0.30 to 2.50 μg·m⁻³.

Figure 8: Annual mean concentrations of SO₂ in the zone (58 cities) for the period from 3 November 2010 to 4 July 2011.

During the summer (6 June–4 July 2011), SO₂ concentrations ranged between 0.20 and 2.10 μg·m⁻³. Data indicated that higher SO₂ levels were measured during autumn, winter, and spring at sites in the residential and recreation areas when the emissions from energy production and heating are at their highest level. Conversely, the lowest SO₂ levels were measured in summer.

3.2. Comparison of SO₂ and NO₂ Concentration Levels for 2004-2005 and 2010-2011

The results of the 2004-2005 and 2010-2011 campaign in Figure 9 show that in Vilnius, the level of sulfur dioxide concentrations in the five years has not changed significantly. Significant decrease in SO₂ concentrations was observed at 03 and 05 in Klaipėda sites located in residential areas, while in the cities of Kedainiai and Palanga, the concentration of SO₂ in the air environment decreased by 40–60%.

Figure 9: Time series of mean SO₂ concentration.

The level of nitrogen dioxide concentrations has decreased by 34, 26, 24, and 49% during five years in the city of Vilnius at the sites next to traffic. Also the increase of NO₂ concentration was observed at Žirnių street and at the crossroads of V. Kudirkos Street near Pamenkalnis (Figure 10).

(a)

(b)

Figure 10: Time series of mean NO₂ concentration.

4. Conclusion

Concentrations of SO₂ and NO₂ were determined over a year using the passive sampling method. For the entire study period (from 3 November 2010 to 4 July 2011), the annual mean concentrations of SO₂ ranged between 0.20 and 3.40 μg·m⁻³ in 40 zones territory sites. The SO₂ annual averages were below the value of 1.50 μg·m⁻³ at all sampling sites (except two). These values demonstrate rather small differences and the even regional pollution by SO₂ and its strong connection to the long-range transport of SO₂ on the regional scale. The emission of SO₂ from the local sources more or less formed the level of pollution at those sites. Mean concentrations of NO₂ ranged between 2.3 and 9.4 μg·m⁻³ in 40 zones territory sites. The annual mean concentrations of NO₂ were in the range 3.0–5.0 μg·m⁻³ at the sites in major part of the territory and were significantly below the lower assessment threshold limit value of 26.0 μg·m⁻³ for the annual NO₂ concentration. The highest annual average concentrations of NO₂ were measured at sites close to road with intensive traffic.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the paper.

Acknowledgments

This research was supported by EPA of Lithuania (Contract No. 4F10-1010).

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