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Impact of fugitive sources and meteorological parameters on vertical distribution of particulate matter over the industrial agglomeration
Journal of Environmental Management xxx (2017) 1e9
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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman
Research article
Impact of fugitive sources and meteorological parameters on vertical distribution of particulate matter over the industrial agglomeration a, b, *, Helena Raclavska a, c, Jirí Bílek d Kristína Strbov a a ENET e Energy Units for Utilization of Non-Traditional Energy Sources, V SB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, OstravaPoruba, Czech Republic b Department of Energy Engineering, Faculty of Mechanical Engineering, V SB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, OstravaPoruba, Czech Republic c Institute of Geological Engineering, Faculty of Mining and Geology, VSB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, Ostrava-Poruba, Czech Republic d 1487, Újezd nad Lesy, 190 16, Praha 9, Czech Republic ENVIRTA, s.r.o., Policanska
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 December 2016 Received in revised form 25 May 2017 Accepted 1 June 2017 Available online xxx
The aim of the study was to characterize vertical distribution of particulate matter, in an area well known by highest air pollution levels in Europe. A balloon filled with helium with measuring instrumentation was used for vertical observation of air pollution over the fugitive sources in Moravian-Silesian metropolitan area during spring and summer. Synchronously, selected meteorological parameters were recorded together with particulate matter for exploration its relationship with particulate matter. Concentrations of particulate matter in the vertical profile were significantly higher in the spring than in the summer. Significant effect of fugitive sources was observed up to the altitude ~255 m (~45 m above ground) in both seasons. The presence of inversion layer was observed at the altitude ~350 m (120 e135 m above ground) at locations with major source traffic load. Both particulate matter concentrations and number of particles for the selected particle sizes decreased with increasing height. Strong correlation of particulate matter with meteorological parameters was not observed. The study represents the first attempt to assess the vertical profile over the fugitive emission sources e old environmental burdens in industrial region. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Vertical profile Tethered balloon Particulate matter Meteorological factor Fugitive source Old environmental burden
1. Introduction Particulate matter (PM) in ambient air is of high concern due to its significant and adverse effects on climate change, air quality, human health, and ecosystems (Hu et al., 2015). Despite the implementation of regulations in air quality improvement, the increasing amount of cardiovascular and respiratory morbidity and mortality with a relationship to atmospheric particles has been observed e including European cities (Pascal et al., 2013). PM concentrations are rapidly increasing because of globally increasing urbanization and industrialization, thus industrialized cities e and their agglomerations e are facing serious air quality
* Corresponding author. Department of Energy Engineering, Faculty of Mechan e Technical University of Ostrava, 17. listopadu 15/2172, 708 ical Engineering, VSB 33, Ostrava-Poruba, Czech Republic. E-mail addresses: [email protected] (K. Strbov a), [email protected] ), [email protected] (J. Bílek). (H. Raclavska
problems caused by high levels of air pollutant concentrations related to environmental hazards (Elbayoumi et al., 2013). It is well known that air pollution is not only an environmental problem within the cities it originates in, it also has important regional and global environmental influence (Tiwari et al., 2015). Since the emissions from natural sources can be not controlled, monitoring and reduction of contribution from anthropogenic sources are crucial (Vicente et al., 2012). Therefore, it is important to study chemical and physical properties of particulate matter and its relationship with sources, as well as their spatial and temporal variations (Pakkanen et al., 2003), especially in such industrialized cities as Ostrava e where the human population is exposed to high pollution levels. High pollution concentration episodes in Ostrava are caused by several factors: its geographical position, weather e related temperature inversion and by the ongoing heavy industrialization of the region (Vossler et al., 2015). Particulate matter emissions escape into the atmosphere from ducted or fugitive sources. Ducted emissions are emitted from
http://dx.doi.org/10.1016/j.jenvman.2017.06.001 0301-4797/© 2017 Elsevier Ltd. All rights reserved.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
regulated processes via designed release point (e.g. smoke stack), in contrast to fugitive emissions which are not discharged into the air in a confined flow stream, but from a rather disperse area or volume. Except for the most mentioned fugitive sources such as leaks from the industrial plants, agricultural tilling, or construction, there are insufficiently explored fugitive sources including paved and unpaved roads, bare ground site (US Environmental Protection Agency, 2009), among the least studied fugitive sources, slag heaps or oil lagoons can be named: both are the subject of this study. Despite the fact that to date many studies concerning the physical and chemical characteristic of PM were performed, the particles behavior in the ambient air is still insufficiently described or at least not complexly. Moreover, majority of the studies were applied only at the ground level e the human breathing zone e in which the pollution influences the human health the most seriously and little is known about vertical variation of air pollutants in the lower troposphere (Li et al., 2015) especially in the case of fine particulate matter e which often constitutes up to ~ 90% of total particle number (Quang et al., 2012). According to the EPA, several methods can be used to perform fugitive emissions measurements (the methods are detailed described in the EPA document (Frankel, 1993). The most used methods available to measure PM from fugitive sources in the vertical profile are Exposure Profile Method and Balloon Method. In the Exposure Profile method, the number of ambient samplers (mostly 3 or 4) is used at several heights set at a tower to sample the fugitive PM plume isokinetically. The method is considerably restricted to sampling close to the source and may not be practical for sampling large area sources (US EPA, 1998). Also, tower-based measurements are limited by the tower height that is fixed e ranging from tens to hundreds of meters e and its immobility. Such measurements were performed at Canton Tower, a landmark building in Guangzhou (China), at heights of 121 and 454 m focused on PM (Deng et al., 2015). In comparison between measured heights, the vertical concentration distributions of PM10, PM2.5, and PM1 in the polluted seasons generally decreased with height, however, this study did not deal with detailed changes of PM with rising height and was performed only at one location. Similar measurements were performed on Eiffel Tower in Paris (Dupont et al., 1999) and on the Frohnau Tower in Berlin (Rappenglück et al., 2004).
Balloon measurement focused on black carbon was performed in Shanghai from height 150 m up to 1000 m (Li et al., 2015), where the strong gradient of BC concentrations with altitude was observed from the ground up to boundary layer. It was the first study on aerosol vertical distribution over Eastern China using a tethered balloon, however, observations were performed at only one location in a rural area. Balloon measurement with Grimm sampler to 400 m above ground was performed at an open urban location in Christchurch, New Zealand and was focused domestic burning of wood and coal. (McKendry et al., 2004). A tethered balloon sampling system was also used to measure vertical profiles of ozone, particles, and solar radiation while focused on the atmospheric boundary layer (400 me700 m) on the northern edge of Mexico City, where the particle number concentration (0.3, 0.5, 1.0 and 5.0 mm) showed just little variation with altitude. Generally, the most of the balloon studies were focused on ozone observation e especially in the mixing layer. PM measurements in the vertical profile of ambient air were also performed using aircrafts or kites (Li et al., 2015). Aircraftbased measurements were mainly focused to the mid and high troposphere, i.e. 1e10 km (Ding et al., 2009), the vertical range of such measurement is, however, relatively low, moreover it is the most expensive method. Kite-based measurement can be performed only below 100 m (Reiche et al., 2012), moreover, its use allows only light-weight payload. Although tethered balloon has a limited payload and can carry only light-weight instruments, it is more flexible than other methods and is applicable for open area fugitive sources e the main concern of this study. The object of this study was to observe the vertical distribution of air pollution within lower troposphere (up to 500 m above sea level) using the balloon method. The focus was to explore the space over the unique and generally unexplored fugitive sources e slag heap and oil lagoons e which represent old environmental burdens and the major environmental concern in the heavy industry affected Ostrava agglomeration (Czech Republic). Due to the fact that both sources are situated close to the residential buildings, the information about its influence on PM distribution in vertical profile is important and helpful for source identification. Simultaneously, the PM concentrations and meteorological parameters were recorded to assess their influence on the vertical distribution of PM. This research is believed to be the first vertical profile observation of ambient air within the 500 m a. s. l. troposphere over
Fig. 1. Location of the area of interest.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
3
burdens as well as high building density sites with significant influence of traffic load. Locations characteristics. Both Karolina (spring measurements) and Poruba (summer measurements) locations represent high building density residential areas with high traffic load. Locations are situated far from industrial plants and their direct influence. Both spring and summer measurements were performed at Laguny and Hermanice locations which represent the most significant old environmental burdens in Ostrava. Location Hermanice is a slug heap originating from piling up slug from Hermanice mine and it is still burning on the many places under the surface. The operations on the slag heap lead to high dustiness e all the surface is covered by dust which still raises a cloud of dust. Location Laguny represents former waste dump (known as the OSTRAMO lagoons) filled with 300 000 tons of waste resulting from chemical refinery and other chemical industries e containing used mineral oils, acid resins, lyesand sludge, oil sludge and waste whitening limewash, and also construction waste and dichloroethane with benzene or trichloroethylene and heavy metals e e.g. lead (Brenek et al., 2014). The Laguny location is also influenced by the emissions from nearby incineration plant, coke plant, chemical plant and waste water treatment plant as well. Laguny is a part of industrial complex e on the north and north-east from the location are a coke plant, chemical plant, waste water treatment plant and incineration plant; the Laguny location is also close to housing estate Fifejdy. The sampling was carried out with the aim of comparison of the distribution of air pollution in vertical profile over the old environmental burdens and over the residential sites in the period of the year influenced by frequent smog situation with a period without such influence. The balloon flights were performed during two seasons e spring (March, April) and summer (August) 2014 e according to the schedule in Table 1. Measured locations are situated at 200e230 m a. s. l., the balloon was able to fly up to 500 m a. s. l. All performed measurements characteristics are described in Table 2.
a metropolitan area in the Czech Republic.
2. Materials and methods 2.1. Study area The measurements were performed in the industrial agglomeration of Ostrava region (Fig. 1) of the Moravian-Silesian metropolitan area situated in the northeast part of the Czech Republic (49 482 - 49 502 N, 18 172 - 18 142 E). Ostrava is the third largest city in the Czech Republic with an area of 214 km2 and the current population of over 300 000 inhabitants (Vossler et al., 2015). The region is well known for the highest air pollution levels in the Czech Republic (remains the air pollution hotespot), as well as in central Europe in long-term observations (Hunova, 2001; Pokorna et al., 2015) e air pollution of particulate matter coming from the heavy industry (mainly metallurgy), and from concentrated transport infrastructure (Vossler et al., 2015). Since Ostrava agglomeration is situated close to the borders with Poland (north-northeast-east) and Slovakia (south), long-distance pollution transport has a sig€fstedt, 1998). The region nificant effect on the air quality as well (Lo is bordered by the Beskydy Mountains and the Jeseníky Mountains (southeast and northwest, respectively) (Dostal et al., 2013). The climate of the area is typical continental with four seasons with warm and dry summers and quite cold, damp and foggy winters with pollution, the coldest month is January and the warmest month is July. Table 1 shows meteorological data for the year 2014 obtained from Meteorological station Mosnov (Czech Hydrometeorological Institute) (49 694 Ne18 120 E, at height 252.8 a. s. l.). Annual mean minimum and maximum temperatures were 2.9 and 17.3 C, respectively (Table 1). Wind velocity varied from 2.49 to 4.70 ms 1 with an average of 3.48 ms-1. Prevailing wind directions at study area are southwest (especially in the winter) and north-east winds (Dostal et al., 2013). The measurements took place at 4 locations of the study area. PM were sampled during 2014 spring (period of the year influenced by frequent smog situation) and summer (no such influenced) seasons were compared e three sites were measured in spring and three in summer from which two were common for both seasons and two were different but having a similar character considering the major pollution sources. Sampling sites were strategically chosen in order to represent significant fugitive air pollution sources e old environmental
2.2. Experimental set-up The “Balloon method” was applied as a variation of the exposure profiling method according to the EPA in this study. Balloon method is especially suited for sampling of large area sources or sources which do not need to be closely approached (Woodard, 1998). Grimm Aerosol Laser Particle Spectrometer model 1.108 was
Table 1 Meteorological data of the study area (Data source: Czech Hydrometeorological Institute). Month
Mean wind velocity (ms1)
January February March April May June July August September October November December Annual average Total
4.25 3.97 3.74 3.09 3.95 2.79 2.49 3.13 3.26 3.16 3.25 4.70 3.48
Mean temperature ( C)
Relative humidity (%)
Min.
Max.
Min.
Max.
13.3 0.2 3.2 4.2 5.3 11.9 14.7 11.7 8.8 3.3 3.2 12.1 2.9
8.7 6.6 16.4 15.8 23.0 24.1 25.8 24.5 18.9 16.2 16.6 10.9 17.3
66 47 36 58 52 51 55 65 72 77 53 64 58
99 97 92 88 95 92 95 95 98 96 98 97 95.17
Pressure (hPa)
Total monthly precipitation (mm)
No. of precipitation days
Sunshine (hours)
983.40 983.30 986.79 984.03 984.97 986.82 984.19 984.90 988.12 989.31 987.22 988.54 985.96
23.5 26.8 13.0 49.9 108.9 74.1 107.0 140.5 109.9 41.3 31.0 27.6
11 8 7 12 15 8 15 19 16 10 7 20
45.7 117.4 169.9 166.0 189.3 240.2 258.2 174.2 152.1 112.6 64.2 45.9
753.5
148
1735.7
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
4 Table 2 Measurements schedule. Location
GPS
Location altitude (m a. s. l.)
0
00
0
00
Karolina Laguny
49 49 48 N, 18 17 20 E 49 500 26.8200 S, 18 150 8.5900 V
216 205
Hermanice
49 510 58.9500 S, 18 190 22.8500 V
210
Poruba
49 500 0.0200 N, 18 110 12.7200 E
225
Season
spring spring summer spring summer summer
Time (h)
11.00e14.30 10.50e14.00 10.00e17.00 10.00e12.30 10.00e17.00 9.40e13.30
Meteorological data Temp. ( C)
Wind sp. (km/h)
16e20 12e16 10e22 8e15 22 16e20
14 13 25 10 21 22
Fig. 2. a) Measurement at Poruba location, b) Measurement at Laguny location.
used for particulate matter sampling proved in several studies of the vertical profile before (McKendry et al., 2004). Small portable dust sampler works on Dual-Technology, which allows at the same rate the dust on the light diffusion principle and a gravimetric principle. The spectrometer detects the airborne aerosol particles in the size range 0.25e32 mm in 15 size channels in real time and represents the results in particle number concentration or particle mass. Dust sampler has been supplemented with the devices for the recording of the meteorological data ebarometer and thermohygrometer with an external probe, and also GPS and altimeter devices. Digital conception with microprocessor provides longterm stability of parameters, temperature compensation of the humidity and pressure sensors and malfunction indication. Meteorological parameters, geographic position, and altitude were recorded at the current time in each position of the balloon. A 20 m3 custom-made balloon filled with helium with a diameter of 4 m was used to lift measuring technique. The tethered balloon was made of polyurethane and nylon with UV inhibitors, certificated by ISO 9002, the volume of He used was 15e20 m3, capable of lifting a payload of 6 kg, maximum load was 15 kg with balloon rope. Balloon visibility was around 4 km and the maximum head wind was 12 m/sec. The balloon was attached by parachute cord to the winch e allowed fast balloon withdraw to the ground in case of adverse weather conditions. Balloon operations were subject to the rules of air traffic e all flights had to be reported to the dispatching of Mosnov Airport in Ostrava. Dust sampler with the supplementary devices was saved in a waterproof box and attached to the modified payload under the balloon device. The measurements were performed in heights up to maximum 500 m a. s. l., and the balloon was halted for 3e10 min every 15 m in spring and every 30 m in the summer. All the measurements were performed in clear weather without any precipitation. The wind occurred during the measurements
affected the balloon horizontal dislocation. Dislocation was calculated according to GPS coordinates, minimum dislocation was observed at Hermanice location (summer) by around 6.60 m, maximum dislocation was observed at Laguny location (spring) by around 185 m. Average horizontal dislocation was 80.35 m. Measuring process is shown in Fig. 2. 2.3. Data analysis The relationships between PM concentrations, height, and meteorological parameters were assessed by correlation analysis, performed in the R programme environment (R Core Team, 2015) using the Openair package (Carslaw and Ropkins, 2012) e the outputs were plotted to correlation matrices e so called CorPlots. 3. Results and discussion 3.1. PM distribution at various height levels From the observational data of PM, median values were calculated for each height level where the balloon was halted and all data points were taken in Fig. 3. In general, decreasing trend of PM concentrations (PM10, PM2.5, PM1) with increasing height was observed. However, a particular trend was not so clear in all cases. Measured values of PM concentrations were significantly higher in the spring season, thus decreasing trend of PM concentrations with increasing height was more obvious in that season. The highest PM concentrations were measured over the Hermanice location in spring. An approximately uniform trend of all PM (PM10, PM2.5, PM1) in whole vertical profile was observed, except the height between 240 and 255 m a. s. l. (30e45 m) e where the highest median of PM10 (96.1 mg/m3) and PM2.5 (71.3 mg/ m3) was observed, moreover, the median concentrations of PM10 were significantly distinct from both PM2.5 and PM1 (PM1
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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Fig. 3. Distribution of PM concentrations in vertical profile in the locations measured in spring and summer.
Fig. 4. Distribution of PM1 concentrations in vertical profile, the Karolina location, spring.
constituted only ~66% of PM10) which signifies strong influence of the fugitive source accumulated in this height interval e this effect could cause smog situation which led to formation of inversion layer in this height. From 255 m. a. s. l., PM1 particles constituted a major portion of PM10 (~94%). At the same location, significantly
lower PM concentrations were measured in summer, however, the similar effect of PM10 was observed e median of PM10 is significantly distinct from PM2.5 and PM1 between 210 and 255 m a. s. l. (0e45 m) e which, again, signifies strong influence of the fugitive source in this height interval, PM1 particles constituted only ~55% of PM10. Decreasing trend of PM concentrations with increasing height was more obvious at Hermanice location in summer, however, PM1 particles constituted only ~77% between 255 and 360 m a. s. l. (45e150 m) and ~83% between 390 and 480 m a. s. l. (180e270 m). At Laguny location in spring, a large decrease of PM with increasing height was observed (~38% between the start and the end height); the largest decrease was observed between 204 and 300 m a. s. l. (5e100 m). PM1 constituted ~81% of PM10 up to 219 m a. s. l. (15 m) e which signifies influence of the fugitive source, and ~90% of PM1 constituted PM10 from 240 m a. s. l. (40 m). At the same location measured in summer, very low PM concentration (10 mg/m3) were measured and approximately uniform trend of PM concentration in all vertical profile was observed. PM1 particles constituted ~92% of PM10. The influence of fugitive source was not observed at the Laguny location in the summer. At Karolina location measured in spring, an uniform trend of PM concentration (median of PM10 was 60e55 mg/m3) up to 350 m a. s. l. (up to 135 m) was observed. Then the decrease about 10 mg/m3 (to 42 mg/m3) between 350 and 365 m a. s. l. (135e150 m) was observed, followed
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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Fig. 5. Distribution of number of particles/litre in the selected particle size classes in the vertical profile at location measured in spring.
by the uniform or only slightly increasing trend of PM concentration with increasing height e this effect could be caused by the presence of inversion layers in the height interval 350 m a. s. l. and 365 m a. s. l. (Fig. 4) PM1 constituted ~87% of PM10, between 365 and 396 m a. s. l. (150e180 m) PM1 constituted 90% of PM10. The effect of the fugitive source was not so obvious at this location. At Poruba location measured in summer very low PM concentrations were measured, however, decrease of PM with increasing height was clearly observed (median of PM10 was 16 mg/m3 at starting height and 6.5 mg/m3 ending height). The largest decrease was observed between 230 and 285 m a. s. l. (0e60 m). At height level 230e255 m a. s. l. (up to 30 m) PM1 constituted 68% of PM10 e which signifies strong influence of fugitive source, then the portion of PM1 in PM10 increased to 80% up to 315 m a. s. l. (up to 90 m) and between 315 and 345 m a. s. l. (90e120 m) the portion of PM1 in PM10 decreased to constituted 70%, finally, the portion of PM1 in PM10 increased with increasing height up to ~ 90%. 3.2. Number of particles at various height levels Measured values of a number of particles in different size classes per litre were calculated and resulting medians were associated with the altitudes. Measured data set in the number of particles per litre mode for different size classes was statistically processed only for spring season because the dataset obtained from measurements in the summer season was insufficient. The outcomes were plotted in form of line graphs shown in Fig. 5. The highest values of the number of particles per litre were measured at Hermanice location, a uniform trend with increasing height was observed at this location. The most significant descending trend of a number of particles with increasing height
was observed at Laguny location. The presence of inversion layer was observed from measured values of particle mass too. In the case of all monitored locations, the highest number of particles was observed at the particle size of 0.265 mm. Overlapping trends were observed between particles of the size 0.290 mm and 0.325 mm in all measured locations. 3.3. Correlation analysis Data from the balloon measurement campaign were subjected to correlation analysis. Outputs were plotted to correlation matrices which show correlations between variables in three ways. Shape indicates positive, negative or zero correlation (right-oriented ellipses signify positive correlation, left-oriented indicate negative correlation, and the circle shape signifies zero correlation). Colour indicates statistical significance of the correlation, the numeric value is described in percentage and represents Pearson correlation coefficient. Moreover, the CorPlots are supplemented with dendrograms (hierarchical clustering) to group similar variables (David and Karl, 2016). Correlation plots (Fig. 6) were created for each location divided to spring and summer season. The aim of this was to observe a correlation of PM concentrations (PM10, PM2.5,and PM1) with the elevation of the measurement and selected meteorological variables e temperature, humidity, pressure and dew point. Fig. 6 shows that in most cases concentrations of PM1 particles are significantly strongly negatively correlated only with elevation (r ¼ - 0.72 and more). Significant strong correlation of concentrations of particles size PM10 and PM2.5 with elevation was observed at location Laguny and Karolina measured in spring (though in both cases the correlation was weaker than in the case of PM1). No
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
Fig. 6. CorPlots with dendrograms for locations measured in spring and summer.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
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Table 3 Linear regression analysis, p e significance level, R2 e coefficient of determination. Season
Location
Factors
p
R2
Spring
Hermanice Laguny Hermanice
PM1 e pressure PM1 e elevation PM1 e elevation
<2.1016 <2.1016 <2.1016
0.7261 0.7845 0.7242
Summer
Fig. 7. The trend of PM concentration and precipitation during the year 2014 in Ostrava.
Table 4 Correlation matrix of monthly average PM concentration and monthly total precipitation.
PM10 PM2.5 PM1 Precipitation
PM10
PM2.5
PM1
Precipitation
1.00 0.99 0.99 0.81
0.99 1.00 1.00 0.82
0.99 1.00 1.00 0.83
0.81 0.82 0.83 1.00
correlation of PM concentrations (PM10, PM2.5, and PM1) with elevation was observed at Laguny location (summer), this could be caused by the fact that measured concentrations at this location were, overall, very low. PM1 (and also PM2.5 and PM10) concentration was significantly strongly positively correlated with air pressure at Karolina location measured in spring. For measurements in the summer, PM1 is significant strong negative correlated with temperature, dew point, pressure and significant positive correlated with humidity at Poruba location. For all pairs of the correlation matrix, several clusters appeared, the character of which differed at particular locations. The linear regression analysis was performed for PM concentrations and both the meteorological variables and height whenever the significance level (p < 0.05) was reached by the correlation analyses, Table 3 presents the outcomes of the linear regression analysis, whenever the result proved to be significant. It is apparent that the only linear relationships were found between the concentration of the finest fraction (PM1) and elevation (and related air pressure) during three measurements in two locations. 3.4. Possible effect of precipitation on PM concentrations The effect of precipitation on particulate matter depends on such factors as the intensity of precipitation, raindrop size, and particle size. According to the previous studies (Feng and Wang, 2012), coarse particles (PM > 10 mm and PM2.510) can be washed
out from the air more efficiently than fine particles (PM2.5 and PM1.0). Feng and Wang (2012) also found that even the most intense precipitation reduced coarse particles by around 60% and fine particles were reduced by around 30%. In the Ostrava agglomeration in 2014 (according to Czech Hydrometeorological Institute), total year precipitation was 753.5 mm (Table 1), season-wise, total precipitation was 171.8 mm in spring with peak in May (108.9 mm) and trough in March (13 mm), 321.6 mm in summer with peak in August (140.5) and trough in June (74.1. mm), 182.2 mm in autumn with peak in September (109.9 mm) and trough in November (31 mm), and 77.9 mm in winter with peak in February (27.6 mm) and trough in December (23.5 mm). Fig. 7 shows the trend of the local monthly average mass concentrations of PM particles (PM10, PM2.5, and PM1) combined with monthly precipitation in 2014 from January to December. The trend is consistent and takes concave parabolic form approximately opposite to the trend of precipitation. The peak values of monthly average mass concentration of PM10, PM2.5 and PM1 appeared in December, reaching 77.84 mg/m3, 71.10 mg/m3and 61.90 mg/m3, respectively, while the lowest values were recorded in August, reaching 26.48 mg/m3, 18.71 mg/m3 and 16.97 mg/m3, respectively. On the contrary, the monthly total precipitation in May, July, August, September was over the 100 mm, while from October to March was less than 50 mm. Thus, the concave parabolic trend of the PM distribution can be explained by the abundant precipitation in summer and the cumulative effects of pollution in winter due to worsened dispersion conditions. The results of correlation analysis (Table 4) showed that monthly average concentrations of PM particles are strongly negatively correlated with total monthly precipitation. However, daily average concentrations of PM particles are not correlated with total daily precipitation whatsoever. As it is obvious from the figures and our analysis, the relations of PM concentrations and precipitation are not as clear and they required more complex and sophisticated analysis for more accurate interpretation. 4. Conclusion A pilot study with the tethered balloon was conducted in the metropolitan area in the Czech Republic and provides first insight of the PM distribution in vertical profile over the fugitive sources in the study area. The measurements carried out in spring showed significantly higher concentrations of PM in the vertical profile compared to summer measurements. In general, decreasing trend of PM concentration with increasing height was observed (more apparent in spring). A significant effect of the fugitive source was observed at Hermanice location up to the same height ~255 m a. s l. (~45 m) in both seasons e PM1 constituted only ~55e66% of PM10, moreover, the trend of PM concentrations was uniform with increasing height (up to 400 m a. s. l.) in spring e between starting and ending height the difference was only 10 mg/m3. The influence of fugitive source was not so clear at Laguny (spring) location. Of all the locations measured, the largest decrease with increasing height was observed at this location ~47% (up to 300 m a. s. l.) Karolina and Poruba locations were chosen as a location with similar character e influenced mainly by the traffic load. The presence of inversion layer was observed at both locations at height ~350 m a. s. l. (120e135 m) despite the fact that the measurements at both locations were performed in different seasons. The finest particulate matter had the highest contribution in the vertical profile. Generally speaking, the monitored meteorological parameters did not
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
influence the PM concentrations at measured height levels. Fugitive emissions are commonly assessed by balance calculations using the emission factors, this is, however not suited for vertical observations. Tethered balloon method was chosen for presented study because it possesses advantages over another PM profiling techniques devices. Balloon device is flexible, costeffective, portable, and can be used to measure in different places in a short period of time without any extra costs for transport, furthermore, is able to measure at higher altitude levels. These benefits, in combination with used small compact dust sampler, make it well-suited for PM profiling in any place without heavy air traffic. The disadvantage of this method is mainly its high sensibility to meteorological conditions e rainfall or strong wind. Also, it is not possible to change the filters during one measurement and the method does not allow performance of continual measurements. Despite that, it is the cheapest alternative e compared to other measurement methods in vertical profile e the costs involved in sampling process are still high (balloon needs to be refilled with helium for each measurement). The applied method may lead to future modifications of vertical air pollution emissions monitoring. Acknowledgements This paper was supported by research projects of the Ministry of Education, Youth and Sport of the Czech Republic: The National Programme for Sustainability LO1404 e TUCENET, SP2016/173 Research on the behavior of carbon during thermal processes. References Brenek, R., Santarius, A., Hude cek, V., 2014. Decontamination of a waste dumpside of s. p. DIAMO 19, 15e21. Carslaw, D.C., Ropkins, K., 2012. Openair d an R package for air quality data analysis. Environ. Model. Softw. 27e28, 52e61. http://dx.doi.org/10.1016/ j.envsoft.2011.09.008. David, C., Karl, R., 2016. Tools for the Analysis of Air Pollution Data: Package “ openair.”. Deng, X., Li, F., Li, Y., Li, J., Huang, H., Liu, X., 2015. Vertical distribution characteristics of PM in the surface layer of Guangzhou. Particuology 20, 3e9. http:// dx.doi.org/10.1016/j.partic.2014.02.009. Ding, A., Wang, T., Xue, L., Gao, J., Stohl, A., Lei, H., Jin, D., Ren, Y., Wang, X., Wei, X., Qi, Y., Liu, J., Zhang, X., 2009. Transport of north China air pollution by midlatitude cyclones: case study of aircraft measurements in summer 2007. J. Geophys. Res. 114, D08304. http://dx.doi.org/10.1029/2008JD011023. Dostal, M., Pastorkova, A., Rychlik, S., Rychlikova, E., Svecova, V., Schallerova, E., Sram, R.J., 2013. Comparison of child morbidity in regions of Ostrava, Czech Republic, with different degrees of pollution: a retrospective cohort study. Environ. Health 12, 74. http://dx.doi.org/10.1186/1476-069X-12-74. Dupont, E., Menut, L., Carissimo, B., Pelon, J., Flamant, P., 1999. Comparison between the atmospheric boundary layer in Paris and its rural suburbs during the ECLAP experiment. Atmos. Environ. 33, 979e994. http://dx.doi.org/10.1016/S13522310(98)00216-7. Elbayoumi, M., Ramli, N.A., Md Yusof, N.F.F., Al Madhoun, W., 2013. Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms. Atmos. Environ. 80, 389e397. http://dx.doi.org/10.1016/ j.atmosenv.2013.07.067. Feng, X., Wang, S., 2012. Influence of different weather events on concentrations of
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particulate matter with different sizes in Lanzhou, China. J. Environ. Sci. 24, 665e674. http://dx.doi.org/10.1016/S1001-0742(11)60807-3. Frankel, R., 1993. Review of Methods for Measuring Fugitive PM-10 Emission Rates. North Carolina Univ., Chapel Hill, NC (United States) (Dept. of Environmental Sciences and Engineering). Hu, J., Wu, L., Zheng, B., Zhang, Q., He, K., Chang, Q., Li, X., Yang, F., Ying, Q., Zhang, H., 2015. Source contributions and regional transport of primary particulate matter in China. Environ. Pollut. 207, 31e42. http://dx.doi.org/10.1016/ j.envpol.2015.08.037. Hunova, I., 2001. Spatial interpretation of ambient air quality for the territory of the Czech Republic. Environ. Pollut. 112, 107e119. Li, J., Fu, Q., Huo, J., Wang, D., Yang, W., Bian, Q., Duan, Y., Zhang, Y., Pan, J., Lin, Y., Huang, K., Bai, Z., Wang, S., Fu, J.S., Louie, P.K.K., 2015. Tethered balloon-based black carbon pro fi les within the lower troposphere of Shanghai in the 2013 East China smog. Atmos. Environ. 123, 327e338. http://dx.doi.org/10.1016/ j.atmosenv.2015.08.096. €fstedt, R.E., 1998. Transboundary environmental problems: the case of the Lo burning of coal in Poland for heating and electricity purposes. Glob. Environ. Chang. 8, 329e340. http://dx.doi.org/10.1016/S0959-3780(98)80001-0. McKendry, I.G., Sturman, A.P., Vergeiner, J., 2004. Vertical profiles of particulate matter size distributions during winter domestic burning in Christchurch, New Zealand. Atmos. Environ 38, 4805e4813. http://dx.doi.org/10.1016/ j.atmosenv.2004.06.029. Pakkanen, T.A., Kerminen, V.M., Loukkola, K., Hillamo, R.E., Aarnio, P., Koskentalo, T., Maenhaut, W., 2003. Size distributions of mass and chemical components in street-level and rooftop PM1 particles in Helsinki. Atmos. Environ. 37, 1673e1690. http://dx.doi.org/10.1016/S1352-2310(03)00011-6. Pascal, M., Corso, M., Chanel, O., Declercq, C., Badaloni, C., Cesaroni, G., Henschel, S., Meister, K., Haluza, D., Martin-Olmedo, P., Medina, S., 2013. Assessing the public health impacts of urban air pollution in 25 European cities: results of the Aphekom project. Sci. Total Environ. 449, 390e400. http://dx.doi.org/10.1016/ j.scitotenv.2013.01.077. Pokorna, P., Hovorka, J., Klan, M., Hopke, P.K., 2015. Source apportionment of size resolved particulate matter at a European air pollution hot spot. Sci. Total Env. 502, 172e183. http://dx.doi.org/10.1016/j.scitotenv.2014.09.021. Quang, T.N., He, C., Morawska, L., Knibbs, L.D., Falk, M., 2012. Vertical particle concentration profiles around urban office buildings. Atmos. Chem. Phys. 12, 5017e5030. http://dx.doi.org/10.5194/acp-12-5017-2012. R Core Team, 2015. R development Core Team. R a lang. Environ. Stat. Comput. 55, 275e286. Rappenglück, B., Forster, C., Jakobi, G., Pesch, M., 2004. Unusually high levels of PAN and ozone over Berlin, Germany, during nighttime on August 7, 1998. Atmos. Environ. 38, 6125e6134. http://dx.doi.org/10.1016/j.atmosenv.2004.08.009. Reiche, M., Funk, R., Zhang, Z., Hoffmann, C., 2012. Using a parafoil kite for measurement of variations in particulate matterda kite-based dust profiling approach. Atmos. Clim. Sci. 2, 41e51. http://dx.doi.org/10.4236/acs.2012.21006. Tiwari, S., Hopke, P.K., Pipal, A.S., Srivastava, A.K., Bisht, D.S., Tiwari, S., Singh, A.K., Soni, V.K., Attri, S.D., 2015. Intra-urban variability of particulate matter ( PM 2. 5 and PM 10 ) and its relationship with optical properties of aerosols over Delhi, India. Atmos. Res. 166, 223e232. http://dx.doi.org/10.1016/ j.atmosres.2015.07.007. US Environmental Protection Agency, 2009. Stationary Point and Area Sources, in: AP 42, Compilation of Air Pollutant Emissions Factors, vol. 1, p. 13.5-1-13.5-5. US EPA, 1998. Stationary Source Control Techniques Document for Fine Particulate Matter doi:EPA CONTRACT NO. 68-D-98e026. WORK ASSIGNMENT NO. 0-08. Vicente, A.B., Sanfeliu, T., Jordan, M.M., 2012. Assesment of PM10 pollution episodes in a ceramic cluster (NE Spain): proposal of a new quality index for PM10, As, Cd, Ni and Pb. J. Environ. Manag. 108, 92e101. http://dx.doi.org/10.1016/ j.jenvman.2012.04.032. Vossler, T., Cernikovsky, L., Novak, J., Placha, H., Krejci, B., Nikolova, I., Chalupnickova, E., Williams, R., 2015. An investigation of local and regional sources of fine particulate matter in Ostrava, the Czech Republic. Atmos. Pollut. Res. 6, 454e463. http://dx.doi.org/10.5094/APR.2015.050. Woodard, K., 1998. Stationary Source Control Techniques Document for Fine Particulate Matter, p. 286.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman
Research article
Impact of fugitive sources and meteorological parameters on vertical distribution of particulate matter over the industrial agglomeration a, b, *, Helena Raclavska a, c, Jirí Bílek d Kristína Strbov a a ENET e Energy Units for Utilization of Non-Traditional Energy Sources, V SB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, OstravaPoruba, Czech Republic b Department of Energy Engineering, Faculty of Mechanical Engineering, V SB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, OstravaPoruba, Czech Republic c Institute of Geological Engineering, Faculty of Mining and Geology, VSB e Technical University of Ostrava, 17. listopadu 15/2172, 708 33, Ostrava-Poruba, Czech Republic d 1487, Újezd nad Lesy, 190 16, Praha 9, Czech Republic ENVIRTA, s.r.o., Policanska
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 December 2016 Received in revised form 25 May 2017 Accepted 1 June 2017 Available online xxx
The aim of the study was to characterize vertical distribution of particulate matter, in an area well known by highest air pollution levels in Europe. A balloon filled with helium with measuring instrumentation was used for vertical observation of air pollution over the fugitive sources in Moravian-Silesian metropolitan area during spring and summer. Synchronously, selected meteorological parameters were recorded together with particulate matter for exploration its relationship with particulate matter. Concentrations of particulate matter in the vertical profile were significantly higher in the spring than in the summer. Significant effect of fugitive sources was observed up to the altitude ~255 m (~45 m above ground) in both seasons. The presence of inversion layer was observed at the altitude ~350 m (120 e135 m above ground) at locations with major source traffic load. Both particulate matter concentrations and number of particles for the selected particle sizes decreased with increasing height. Strong correlation of particulate matter with meteorological parameters was not observed. The study represents the first attempt to assess the vertical profile over the fugitive emission sources e old environmental burdens in industrial region. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Vertical profile Tethered balloon Particulate matter Meteorological factor Fugitive source Old environmental burden
1. Introduction Particulate matter (PM) in ambient air is of high concern due to its significant and adverse effects on climate change, air quality, human health, and ecosystems (Hu et al., 2015). Despite the implementation of regulations in air quality improvement, the increasing amount of cardiovascular and respiratory morbidity and mortality with a relationship to atmospheric particles has been observed e including European cities (Pascal et al., 2013). PM concentrations are rapidly increasing because of globally increasing urbanization and industrialization, thus industrialized cities e and their agglomerations e are facing serious air quality
* Corresponding author. Department of Energy Engineering, Faculty of Mechan e Technical University of Ostrava, 17. listopadu 15/2172, 708 ical Engineering, VSB 33, Ostrava-Poruba, Czech Republic. E-mail addresses: [email protected] (K. Strbov a), [email protected] ), [email protected] (J. Bílek). (H. Raclavska
problems caused by high levels of air pollutant concentrations related to environmental hazards (Elbayoumi et al., 2013). It is well known that air pollution is not only an environmental problem within the cities it originates in, it also has important regional and global environmental influence (Tiwari et al., 2015). Since the emissions from natural sources can be not controlled, monitoring and reduction of contribution from anthropogenic sources are crucial (Vicente et al., 2012). Therefore, it is important to study chemical and physical properties of particulate matter and its relationship with sources, as well as their spatial and temporal variations (Pakkanen et al., 2003), especially in such industrialized cities as Ostrava e where the human population is exposed to high pollution levels. High pollution concentration episodes in Ostrava are caused by several factors: its geographical position, weather e related temperature inversion and by the ongoing heavy industrialization of the region (Vossler et al., 2015). Particulate matter emissions escape into the atmosphere from ducted or fugitive sources. Ducted emissions are emitted from
http://dx.doi.org/10.1016/j.jenvman.2017.06.001 0301-4797/© 2017 Elsevier Ltd. All rights reserved.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
regulated processes via designed release point (e.g. smoke stack), in contrast to fugitive emissions which are not discharged into the air in a confined flow stream, but from a rather disperse area or volume. Except for the most mentioned fugitive sources such as leaks from the industrial plants, agricultural tilling, or construction, there are insufficiently explored fugitive sources including paved and unpaved roads, bare ground site (US Environmental Protection Agency, 2009), among the least studied fugitive sources, slag heaps or oil lagoons can be named: both are the subject of this study. Despite the fact that to date many studies concerning the physical and chemical characteristic of PM were performed, the particles behavior in the ambient air is still insufficiently described or at least not complexly. Moreover, majority of the studies were applied only at the ground level e the human breathing zone e in which the pollution influences the human health the most seriously and little is known about vertical variation of air pollutants in the lower troposphere (Li et al., 2015) especially in the case of fine particulate matter e which often constitutes up to ~ 90% of total particle number (Quang et al., 2012). According to the EPA, several methods can be used to perform fugitive emissions measurements (the methods are detailed described in the EPA document (Frankel, 1993). The most used methods available to measure PM from fugitive sources in the vertical profile are Exposure Profile Method and Balloon Method. In the Exposure Profile method, the number of ambient samplers (mostly 3 or 4) is used at several heights set at a tower to sample the fugitive PM plume isokinetically. The method is considerably restricted to sampling close to the source and may not be practical for sampling large area sources (US EPA, 1998). Also, tower-based measurements are limited by the tower height that is fixed e ranging from tens to hundreds of meters e and its immobility. Such measurements were performed at Canton Tower, a landmark building in Guangzhou (China), at heights of 121 and 454 m focused on PM (Deng et al., 2015). In comparison between measured heights, the vertical concentration distributions of PM10, PM2.5, and PM1 in the polluted seasons generally decreased with height, however, this study did not deal with detailed changes of PM with rising height and was performed only at one location. Similar measurements were performed on Eiffel Tower in Paris (Dupont et al., 1999) and on the Frohnau Tower in Berlin (Rappenglück et al., 2004).
Balloon measurement focused on black carbon was performed in Shanghai from height 150 m up to 1000 m (Li et al., 2015), where the strong gradient of BC concentrations with altitude was observed from the ground up to boundary layer. It was the first study on aerosol vertical distribution over Eastern China using a tethered balloon, however, observations were performed at only one location in a rural area. Balloon measurement with Grimm sampler to 400 m above ground was performed at an open urban location in Christchurch, New Zealand and was focused domestic burning of wood and coal. (McKendry et al., 2004). A tethered balloon sampling system was also used to measure vertical profiles of ozone, particles, and solar radiation while focused on the atmospheric boundary layer (400 me700 m) on the northern edge of Mexico City, where the particle number concentration (0.3, 0.5, 1.0 and 5.0 mm) showed just little variation with altitude. Generally, the most of the balloon studies were focused on ozone observation e especially in the mixing layer. PM measurements in the vertical profile of ambient air were also performed using aircrafts or kites (Li et al., 2015). Aircraftbased measurements were mainly focused to the mid and high troposphere, i.e. 1e10 km (Ding et al., 2009), the vertical range of such measurement is, however, relatively low, moreover it is the most expensive method. Kite-based measurement can be performed only below 100 m (Reiche et al., 2012), moreover, its use allows only light-weight payload. Although tethered balloon has a limited payload and can carry only light-weight instruments, it is more flexible than other methods and is applicable for open area fugitive sources e the main concern of this study. The object of this study was to observe the vertical distribution of air pollution within lower troposphere (up to 500 m above sea level) using the balloon method. The focus was to explore the space over the unique and generally unexplored fugitive sources e slag heap and oil lagoons e which represent old environmental burdens and the major environmental concern in the heavy industry affected Ostrava agglomeration (Czech Republic). Due to the fact that both sources are situated close to the residential buildings, the information about its influence on PM distribution in vertical profile is important and helpful for source identification. Simultaneously, the PM concentrations and meteorological parameters were recorded to assess their influence on the vertical distribution of PM. This research is believed to be the first vertical profile observation of ambient air within the 500 m a. s. l. troposphere over
Fig. 1. Location of the area of interest.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
3
burdens as well as high building density sites with significant influence of traffic load. Locations characteristics. Both Karolina (spring measurements) and Poruba (summer measurements) locations represent high building density residential areas with high traffic load. Locations are situated far from industrial plants and their direct influence. Both spring and summer measurements were performed at Laguny and Hermanice locations which represent the most significant old environmental burdens in Ostrava. Location Hermanice is a slug heap originating from piling up slug from Hermanice mine and it is still burning on the many places under the surface. The operations on the slag heap lead to high dustiness e all the surface is covered by dust which still raises a cloud of dust. Location Laguny represents former waste dump (known as the OSTRAMO lagoons) filled with 300 000 tons of waste resulting from chemical refinery and other chemical industries e containing used mineral oils, acid resins, lyesand sludge, oil sludge and waste whitening limewash, and also construction waste and dichloroethane with benzene or trichloroethylene and heavy metals e e.g. lead (Brenek et al., 2014). The Laguny location is also influenced by the emissions from nearby incineration plant, coke plant, chemical plant and waste water treatment plant as well. Laguny is a part of industrial complex e on the north and north-east from the location are a coke plant, chemical plant, waste water treatment plant and incineration plant; the Laguny location is also close to housing estate Fifejdy. The sampling was carried out with the aim of comparison of the distribution of air pollution in vertical profile over the old environmental burdens and over the residential sites in the period of the year influenced by frequent smog situation with a period without such influence. The balloon flights were performed during two seasons e spring (March, April) and summer (August) 2014 e according to the schedule in Table 1. Measured locations are situated at 200e230 m a. s. l., the balloon was able to fly up to 500 m a. s. l. All performed measurements characteristics are described in Table 2.
a metropolitan area in the Czech Republic.
2. Materials and methods 2.1. Study area The measurements were performed in the industrial agglomeration of Ostrava region (Fig. 1) of the Moravian-Silesian metropolitan area situated in the northeast part of the Czech Republic (49 482 - 49 502 N, 18 172 - 18 142 E). Ostrava is the third largest city in the Czech Republic with an area of 214 km2 and the current population of over 300 000 inhabitants (Vossler et al., 2015). The region is well known for the highest air pollution levels in the Czech Republic (remains the air pollution hotespot), as well as in central Europe in long-term observations (Hunova, 2001; Pokorna et al., 2015) e air pollution of particulate matter coming from the heavy industry (mainly metallurgy), and from concentrated transport infrastructure (Vossler et al., 2015). Since Ostrava agglomeration is situated close to the borders with Poland (north-northeast-east) and Slovakia (south), long-distance pollution transport has a sig€fstedt, 1998). The region nificant effect on the air quality as well (Lo is bordered by the Beskydy Mountains and the Jeseníky Mountains (southeast and northwest, respectively) (Dostal et al., 2013). The climate of the area is typical continental with four seasons with warm and dry summers and quite cold, damp and foggy winters with pollution, the coldest month is January and the warmest month is July. Table 1 shows meteorological data for the year 2014 obtained from Meteorological station Mosnov (Czech Hydrometeorological Institute) (49 694 Ne18 120 E, at height 252.8 a. s. l.). Annual mean minimum and maximum temperatures were 2.9 and 17.3 C, respectively (Table 1). Wind velocity varied from 2.49 to 4.70 ms 1 with an average of 3.48 ms-1. Prevailing wind directions at study area are southwest (especially in the winter) and north-east winds (Dostal et al., 2013). The measurements took place at 4 locations of the study area. PM were sampled during 2014 spring (period of the year influenced by frequent smog situation) and summer (no such influenced) seasons were compared e three sites were measured in spring and three in summer from which two were common for both seasons and two were different but having a similar character considering the major pollution sources. Sampling sites were strategically chosen in order to represent significant fugitive air pollution sources e old environmental
2.2. Experimental set-up The “Balloon method” was applied as a variation of the exposure profiling method according to the EPA in this study. Balloon method is especially suited for sampling of large area sources or sources which do not need to be closely approached (Woodard, 1998). Grimm Aerosol Laser Particle Spectrometer model 1.108 was
Table 1 Meteorological data of the study area (Data source: Czech Hydrometeorological Institute). Month
Mean wind velocity (ms1)
January February March April May June July August September October November December Annual average Total
4.25 3.97 3.74 3.09 3.95 2.79 2.49 3.13 3.26 3.16 3.25 4.70 3.48
Mean temperature ( C)
Relative humidity (%)
Min.
Max.
Min.
Max.
13.3 0.2 3.2 4.2 5.3 11.9 14.7 11.7 8.8 3.3 3.2 12.1 2.9
8.7 6.6 16.4 15.8 23.0 24.1 25.8 24.5 18.9 16.2 16.6 10.9 17.3
66 47 36 58 52 51 55 65 72 77 53 64 58
99 97 92 88 95 92 95 95 98 96 98 97 95.17
Pressure (hPa)
Total monthly precipitation (mm)
No. of precipitation days
Sunshine (hours)
983.40 983.30 986.79 984.03 984.97 986.82 984.19 984.90 988.12 989.31 987.22 988.54 985.96
23.5 26.8 13.0 49.9 108.9 74.1 107.0 140.5 109.9 41.3 31.0 27.6
11 8 7 12 15 8 15 19 16 10 7 20
45.7 117.4 169.9 166.0 189.3 240.2 258.2 174.2 152.1 112.6 64.2 45.9
753.5
148
1735.7
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
4 Table 2 Measurements schedule. Location
GPS
Location altitude (m a. s. l.)
0
00
0
00
Karolina Laguny
49 49 48 N, 18 17 20 E 49 500 26.8200 S, 18 150 8.5900 V
216 205
Hermanice
49 510 58.9500 S, 18 190 22.8500 V
210
Poruba
49 500 0.0200 N, 18 110 12.7200 E
225
Season
spring spring summer spring summer summer
Time (h)
11.00e14.30 10.50e14.00 10.00e17.00 10.00e12.30 10.00e17.00 9.40e13.30
Meteorological data Temp. ( C)
Wind sp. (km/h)
16e20 12e16 10e22 8e15 22 16e20
14 13 25 10 21 22
Fig. 2. a) Measurement at Poruba location, b) Measurement at Laguny location.
used for particulate matter sampling proved in several studies of the vertical profile before (McKendry et al., 2004). Small portable dust sampler works on Dual-Technology, which allows at the same rate the dust on the light diffusion principle and a gravimetric principle. The spectrometer detects the airborne aerosol particles in the size range 0.25e32 mm in 15 size channels in real time and represents the results in particle number concentration or particle mass. Dust sampler has been supplemented with the devices for the recording of the meteorological data ebarometer and thermohygrometer with an external probe, and also GPS and altimeter devices. Digital conception with microprocessor provides longterm stability of parameters, temperature compensation of the humidity and pressure sensors and malfunction indication. Meteorological parameters, geographic position, and altitude were recorded at the current time in each position of the balloon. A 20 m3 custom-made balloon filled with helium with a diameter of 4 m was used to lift measuring technique. The tethered balloon was made of polyurethane and nylon with UV inhibitors, certificated by ISO 9002, the volume of He used was 15e20 m3, capable of lifting a payload of 6 kg, maximum load was 15 kg with balloon rope. Balloon visibility was around 4 km and the maximum head wind was 12 m/sec. The balloon was attached by parachute cord to the winch e allowed fast balloon withdraw to the ground in case of adverse weather conditions. Balloon operations were subject to the rules of air traffic e all flights had to be reported to the dispatching of Mosnov Airport in Ostrava. Dust sampler with the supplementary devices was saved in a waterproof box and attached to the modified payload under the balloon device. The measurements were performed in heights up to maximum 500 m a. s. l., and the balloon was halted for 3e10 min every 15 m in spring and every 30 m in the summer. All the measurements were performed in clear weather without any precipitation. The wind occurred during the measurements
affected the balloon horizontal dislocation. Dislocation was calculated according to GPS coordinates, minimum dislocation was observed at Hermanice location (summer) by around 6.60 m, maximum dislocation was observed at Laguny location (spring) by around 185 m. Average horizontal dislocation was 80.35 m. Measuring process is shown in Fig. 2. 2.3. Data analysis The relationships between PM concentrations, height, and meteorological parameters were assessed by correlation analysis, performed in the R programme environment (R Core Team, 2015) using the Openair package (Carslaw and Ropkins, 2012) e the outputs were plotted to correlation matrices e so called CorPlots. 3. Results and discussion 3.1. PM distribution at various height levels From the observational data of PM, median values were calculated for each height level where the balloon was halted and all data points were taken in Fig. 3. In general, decreasing trend of PM concentrations (PM10, PM2.5, PM1) with increasing height was observed. However, a particular trend was not so clear in all cases. Measured values of PM concentrations were significantly higher in the spring season, thus decreasing trend of PM concentrations with increasing height was more obvious in that season. The highest PM concentrations were measured over the Hermanice location in spring. An approximately uniform trend of all PM (PM10, PM2.5, PM1) in whole vertical profile was observed, except the height between 240 and 255 m a. s. l. (30e45 m) e where the highest median of PM10 (96.1 mg/m3) and PM2.5 (71.3 mg/ m3) was observed, moreover, the median concentrations of PM10 were significantly distinct from both PM2.5 and PM1 (PM1
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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5
Fig. 3. Distribution of PM concentrations in vertical profile in the locations measured in spring and summer.
Fig. 4. Distribution of PM1 concentrations in vertical profile, the Karolina location, spring.
constituted only ~66% of PM10) which signifies strong influence of the fugitive source accumulated in this height interval e this effect could cause smog situation which led to formation of inversion layer in this height. From 255 m. a. s. l., PM1 particles constituted a major portion of PM10 (~94%). At the same location, significantly
lower PM concentrations were measured in summer, however, the similar effect of PM10 was observed e median of PM10 is significantly distinct from PM2.5 and PM1 between 210 and 255 m a. s. l. (0e45 m) e which, again, signifies strong influence of the fugitive source in this height interval, PM1 particles constituted only ~55% of PM10. Decreasing trend of PM concentrations with increasing height was more obvious at Hermanice location in summer, however, PM1 particles constituted only ~77% between 255 and 360 m a. s. l. (45e150 m) and ~83% between 390 and 480 m a. s. l. (180e270 m). At Laguny location in spring, a large decrease of PM with increasing height was observed (~38% between the start and the end height); the largest decrease was observed between 204 and 300 m a. s. l. (5e100 m). PM1 constituted ~81% of PM10 up to 219 m a. s. l. (15 m) e which signifies influence of the fugitive source, and ~90% of PM1 constituted PM10 from 240 m a. s. l. (40 m). At the same location measured in summer, very low PM concentration (10 mg/m3) were measured and approximately uniform trend of PM concentration in all vertical profile was observed. PM1 particles constituted ~92% of PM10. The influence of fugitive source was not observed at the Laguny location in the summer. At Karolina location measured in spring, an uniform trend of PM concentration (median of PM10 was 60e55 mg/m3) up to 350 m a. s. l. (up to 135 m) was observed. Then the decrease about 10 mg/m3 (to 42 mg/m3) between 350 and 365 m a. s. l. (135e150 m) was observed, followed
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
Fig. 5. Distribution of number of particles/litre in the selected particle size classes in the vertical profile at location measured in spring.
by the uniform or only slightly increasing trend of PM concentration with increasing height e this effect could be caused by the presence of inversion layers in the height interval 350 m a. s. l. and 365 m a. s. l. (Fig. 4) PM1 constituted ~87% of PM10, between 365 and 396 m a. s. l. (150e180 m) PM1 constituted 90% of PM10. The effect of the fugitive source was not so obvious at this location. At Poruba location measured in summer very low PM concentrations were measured, however, decrease of PM with increasing height was clearly observed (median of PM10 was 16 mg/m3 at starting height and 6.5 mg/m3 ending height). The largest decrease was observed between 230 and 285 m a. s. l. (0e60 m). At height level 230e255 m a. s. l. (up to 30 m) PM1 constituted 68% of PM10 e which signifies strong influence of fugitive source, then the portion of PM1 in PM10 increased to 80% up to 315 m a. s. l. (up to 90 m) and between 315 and 345 m a. s. l. (90e120 m) the portion of PM1 in PM10 decreased to constituted 70%, finally, the portion of PM1 in PM10 increased with increasing height up to ~ 90%. 3.2. Number of particles at various height levels Measured values of a number of particles in different size classes per litre were calculated and resulting medians were associated with the altitudes. Measured data set in the number of particles per litre mode for different size classes was statistically processed only for spring season because the dataset obtained from measurements in the summer season was insufficient. The outcomes were plotted in form of line graphs shown in Fig. 5. The highest values of the number of particles per litre were measured at Hermanice location, a uniform trend with increasing height was observed at this location. The most significant descending trend of a number of particles with increasing height
was observed at Laguny location. The presence of inversion layer was observed from measured values of particle mass too. In the case of all monitored locations, the highest number of particles was observed at the particle size of 0.265 mm. Overlapping trends were observed between particles of the size 0.290 mm and 0.325 mm in all measured locations. 3.3. Correlation analysis Data from the balloon measurement campaign were subjected to correlation analysis. Outputs were plotted to correlation matrices which show correlations between variables in three ways. Shape indicates positive, negative or zero correlation (right-oriented ellipses signify positive correlation, left-oriented indicate negative correlation, and the circle shape signifies zero correlation). Colour indicates statistical significance of the correlation, the numeric value is described in percentage and represents Pearson correlation coefficient. Moreover, the CorPlots are supplemented with dendrograms (hierarchical clustering) to group similar variables (David and Karl, 2016). Correlation plots (Fig. 6) were created for each location divided to spring and summer season. The aim of this was to observe a correlation of PM concentrations (PM10, PM2.5,and PM1) with the elevation of the measurement and selected meteorological variables e temperature, humidity, pressure and dew point. Fig. 6 shows that in most cases concentrations of PM1 particles are significantly strongly negatively correlated only with elevation (r ¼ - 0.72 and more). Significant strong correlation of concentrations of particles size PM10 and PM2.5 with elevation was observed at location Laguny and Karolina measured in spring (though in both cases the correlation was weaker than in the case of PM1). No
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
Fig. 6. CorPlots with dendrograms for locations measured in spring and summer.
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
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et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
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Table 3 Linear regression analysis, p e significance level, R2 e coefficient of determination. Season
Location
Factors
p
R2
Spring
Hermanice Laguny Hermanice
PM1 e pressure PM1 e elevation PM1 e elevation
<2.1016 <2.1016 <2.1016
0.7261 0.7845 0.7242
Summer
Fig. 7. The trend of PM concentration and precipitation during the year 2014 in Ostrava.
Table 4 Correlation matrix of monthly average PM concentration and monthly total precipitation.
PM10 PM2.5 PM1 Precipitation
PM10
PM2.5
PM1
Precipitation
1.00 0.99 0.99 0.81
0.99 1.00 1.00 0.82
0.99 1.00 1.00 0.83
0.81 0.82 0.83 1.00
correlation of PM concentrations (PM10, PM2.5, and PM1) with elevation was observed at Laguny location (summer), this could be caused by the fact that measured concentrations at this location were, overall, very low. PM1 (and also PM2.5 and PM10) concentration was significantly strongly positively correlated with air pressure at Karolina location measured in spring. For measurements in the summer, PM1 is significant strong negative correlated with temperature, dew point, pressure and significant positive correlated with humidity at Poruba location. For all pairs of the correlation matrix, several clusters appeared, the character of which differed at particular locations. The linear regression analysis was performed for PM concentrations and both the meteorological variables and height whenever the significance level (p < 0.05) was reached by the correlation analyses, Table 3 presents the outcomes of the linear regression analysis, whenever the result proved to be significant. It is apparent that the only linear relationships were found between the concentration of the finest fraction (PM1) and elevation (and related air pressure) during three measurements in two locations. 3.4. Possible effect of precipitation on PM concentrations The effect of precipitation on particulate matter depends on such factors as the intensity of precipitation, raindrop size, and particle size. According to the previous studies (Feng and Wang, 2012), coarse particles (PM > 10 mm and PM2.510) can be washed
out from the air more efficiently than fine particles (PM2.5 and PM1.0). Feng and Wang (2012) also found that even the most intense precipitation reduced coarse particles by around 60% and fine particles were reduced by around 30%. In the Ostrava agglomeration in 2014 (according to Czech Hydrometeorological Institute), total year precipitation was 753.5 mm (Table 1), season-wise, total precipitation was 171.8 mm in spring with peak in May (108.9 mm) and trough in March (13 mm), 321.6 mm in summer with peak in August (140.5) and trough in June (74.1. mm), 182.2 mm in autumn with peak in September (109.9 mm) and trough in November (31 mm), and 77.9 mm in winter with peak in February (27.6 mm) and trough in December (23.5 mm). Fig. 7 shows the trend of the local monthly average mass concentrations of PM particles (PM10, PM2.5, and PM1) combined with monthly precipitation in 2014 from January to December. The trend is consistent and takes concave parabolic form approximately opposite to the trend of precipitation. The peak values of monthly average mass concentration of PM10, PM2.5 and PM1 appeared in December, reaching 77.84 mg/m3, 71.10 mg/m3and 61.90 mg/m3, respectively, while the lowest values were recorded in August, reaching 26.48 mg/m3, 18.71 mg/m3 and 16.97 mg/m3, respectively. On the contrary, the monthly total precipitation in May, July, August, September was over the 100 mm, while from October to March was less than 50 mm. Thus, the concave parabolic trend of the PM distribution can be explained by the abundant precipitation in summer and the cumulative effects of pollution in winter due to worsened dispersion conditions. The results of correlation analysis (Table 4) showed that monthly average concentrations of PM particles are strongly negatively correlated with total monthly precipitation. However, daily average concentrations of PM particles are not correlated with total daily precipitation whatsoever. As it is obvious from the figures and our analysis, the relations of PM concentrations and precipitation are not as clear and they required more complex and sophisticated analysis for more accurate interpretation. 4. Conclusion A pilot study with the tethered balloon was conducted in the metropolitan area in the Czech Republic and provides first insight of the PM distribution in vertical profile over the fugitive sources in the study area. The measurements carried out in spring showed significantly higher concentrations of PM in the vertical profile compared to summer measurements. In general, decreasing trend of PM concentration with increasing height was observed (more apparent in spring). A significant effect of the fugitive source was observed at Hermanice location up to the same height ~255 m a. s l. (~45 m) in both seasons e PM1 constituted only ~55e66% of PM10, moreover, the trend of PM concentrations was uniform with increasing height (up to 400 m a. s. l.) in spring e between starting and ending height the difference was only 10 mg/m3. The influence of fugitive source was not so clear at Laguny (spring) location. Of all the locations measured, the largest decrease with increasing height was observed at this location ~47% (up to 300 m a. s. l.) Karolina and Poruba locations were chosen as a location with similar character e influenced mainly by the traffic load. The presence of inversion layer was observed at both locations at height ~350 m a. s. l. (120e135 m) despite the fact that the measurements at both locations were performed in different seasons. The finest particulate matter had the highest contribution in the vertical profile. Generally speaking, the monitored meteorological parameters did not
, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001
et al. / Journal of Environmental Management xxx (2017) 1e9 K. Strbova
influence the PM concentrations at measured height levels. Fugitive emissions are commonly assessed by balance calculations using the emission factors, this is, however not suited for vertical observations. Tethered balloon method was chosen for presented study because it possesses advantages over another PM profiling techniques devices. Balloon device is flexible, costeffective, portable, and can be used to measure in different places in a short period of time without any extra costs for transport, furthermore, is able to measure at higher altitude levels. These benefits, in combination with used small compact dust sampler, make it well-suited for PM profiling in any place without heavy air traffic. The disadvantage of this method is mainly its high sensibility to meteorological conditions e rainfall or strong wind. Also, it is not possible to change the filters during one measurement and the method does not allow performance of continual measurements. Despite that, it is the cheapest alternative e compared to other measurement methods in vertical profile e the costs involved in sampling process are still high (balloon needs to be refilled with helium for each measurement). The applied method may lead to future modifications of vertical air pollution emissions monitoring. Acknowledgements This paper was supported by research projects of the Ministry of Education, Youth and Sport of the Czech Republic: The National Programme for Sustainability LO1404 e TUCENET, SP2016/173 Research on the behavior of carbon during thermal processes. References Brenek, R., Santarius, A., Hude cek, V., 2014. Decontamination of a waste dumpside of s. p. DIAMO 19, 15e21. Carslaw, D.C., Ropkins, K., 2012. Openair d an R package for air quality data analysis. Environ. Model. Softw. 27e28, 52e61. http://dx.doi.org/10.1016/ j.envsoft.2011.09.008. David, C., Karl, R., 2016. Tools for the Analysis of Air Pollution Data: Package “ openair.”. Deng, X., Li, F., Li, Y., Li, J., Huang, H., Liu, X., 2015. Vertical distribution characteristics of PM in the surface layer of Guangzhou. Particuology 20, 3e9. http:// dx.doi.org/10.1016/j.partic.2014.02.009. Ding, A., Wang, T., Xue, L., Gao, J., Stohl, A., Lei, H., Jin, D., Ren, Y., Wang, X., Wei, X., Qi, Y., Liu, J., Zhang, X., 2009. Transport of north China air pollution by midlatitude cyclones: case study of aircraft measurements in summer 2007. J. Geophys. Res. 114, D08304. http://dx.doi.org/10.1029/2008JD011023. Dostal, M., Pastorkova, A., Rychlik, S., Rychlikova, E., Svecova, V., Schallerova, E., Sram, R.J., 2013. Comparison of child morbidity in regions of Ostrava, Czech Republic, with different degrees of pollution: a retrospective cohort study. Environ. Health 12, 74. http://dx.doi.org/10.1186/1476-069X-12-74. Dupont, E., Menut, L., Carissimo, B., Pelon, J., Flamant, P., 1999. Comparison between the atmospheric boundary layer in Paris and its rural suburbs during the ECLAP experiment. Atmos. Environ. 33, 979e994. http://dx.doi.org/10.1016/S13522310(98)00216-7. Elbayoumi, M., Ramli, N.A., Md Yusof, N.F.F., Al Madhoun, W., 2013. Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms. Atmos. Environ. 80, 389e397. http://dx.doi.org/10.1016/ j.atmosenv.2013.07.067. Feng, X., Wang, S., 2012. Influence of different weather events on concentrations of
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, K., et al., Impact of fugitive sources and meteorological parameters on vertical distribution of Please cite this article in press as: Strbov a particulate matter over the industrial agglomeration, Journal of Environmental Management (2017), http://dx.doi.org/10.1016/ j.jenvman.2017.06.001