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Citation: Kravchenko, M.; Trach, Y.;
Trach, R.; Tkachenko, T.; Mileikovskyi,
V. Behaviour and Peculiarities of Oil
Hydrocarbon Removal from Rain
Garden Structures. Water 2024,16,
1802. https://doi.org/10.3390/
w16131802
Academic Editor: Zhenyao Shen
Received: 11 June 2024
Revised: 20 June 2024
Accepted: 23 June 2024
Published: 26 June 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
water
Article
Behaviour and Peculiarities of Oil Hydrocarbon Removal from
Rain Garden Structures
Maryna Kravchenko 1, Yuliia Trach 2,3 ,*, Roman Trach 2,4 , Tetiana Tkachenko 1and Viktor Mileikovskyi 1
1Institute of Engineering Systems and Ecology, Kyiv National University of Construction and Architecture,
Povitrianykh Syl pr., 31, 03037 Kyiv, Ukraine; kravchenko.mv@knuba.edu.ua (M.K.);
tkachenko.tm@knuba.edu.ua (T.T.); mileikovskyi.vo@knuba.edu.ua (V.M.)
2Institute of Civil Engineering, Warsaw University of Life Sciences, 02-776 Warsaw, Poland
3Institute of Agroecology and Land Management, National University of Water and Environmental Engineering,
33028 Rivne, Ukraine
4
Institute of Civil Engineering and Architecture, National University of Water and Environmental Engineering,
33028 Rivne, Ukraine
*Correspondence: yuliia_trach@sggw.edu
Abstract: The expansion of impervious areas in the context of climate change leads to an increase
in stormwater runoff. Runoff from roads, petrol stations, and service stations is the most common
form of unintentional release of petroleum hydrocarbons (PHs). Rain gardens are an important
practice for removing PHs from stormwater runoff, but little data exist on the removal efficiency and
behaviour of these substances within the system. The main objective of the study is to investigate
the effectiveness of rain gardens in removing pollutants such as diesel fuel (DF) and used engine
oil (UEO) in a laboratory setting, as well as to study the behaviours of these pollutants within the
system. Eight experimental columns (7.164 dm
3
) were packed with soil (bulk density 1.48 kg/dm
3
),
river sand (1.6 kg/dm
3
), and gravel. Plants of the Physocarpus opulifolia Diabolo species were planted
in the topsoil to study their resistance to PHs. For 6 months, the columns were watered with
model PHs followed by simulated rain events. The concentrations of PHs in the leachate and soil
media of the columns were determined by reverse-phase high-performance liquid chromatography
(
RP-HPLC
). The results of HPLC indicated the absence of UEO and DF components in the leachates
of all experimental columns, which suggested 100% removal of these substances from stormwater.
The chromatography results showed that 95% of the modelled PHs were retained in the surface layer
of the soil medium due to the sorption process, which led to a change in hydraulic conductivity over
time. Recommendations are proposed to increase the service life of rain gardens designed to filter
PHs from stormwater.
Keywords: rain garden; stormwater; petroleum hydrocarbons; removal efficiency; hydraulic
conductivity
;
plant resistance
1. Introduction
Increasing urban populations, expanding urban areas, and increasing building density
and impervious soil cover play key roles in the deterioration of water resources, affecting
both their quantity and quality in urbanised water basins [
1
]. At the same time, global
climate change is altering the spatial and temporal distributions of precipitation, leading to
an increase in the frequency and intensity of precipitation [
2
]. The interaction of imperme-
able areas with extreme and intense precipitation leads to the formation of local floods and
an increase in stormwater runoff [3,4].
Stormwater runoff is the flow of water that results from rainfall or snowmelt and flows
over a surface without penetrating the ground. In rural areas, the volume of stormwater
runoff is less than 20% of the average annual rainfall, but in urban areas, this figure reaches
60–70% [5].
Water 2024,16, 1802. https://doi.org/10.3390/w16131802 https://www.mdpi.com/journal/water
Water 2024,16, 1802 2 of 29
Urbanisation of cities leads to changes in the characteristics of urban transport due to
an increase in traffic and the spread of congestion. Urban transport is a source of a large
number of organic pollutants due to exhaust emissions, tire and brake wear, and the spillage
and leakage of fuels and lubricants that contaminate stormwater as a result of petroleum
hydrocarbons (PHs) from diesel fuel, petrol, and used engine oil [
6
]. Such water flows from
roads, petrol stations, service stations, etc. The concentration of petroleum hydrocarbons
in rainwater usually ranges from 0.2 to 277 mg/dm
3
[
7
]. It should be emphasised that
impervious surfaces themselves can also be sources of PHs, as coal tar pavement is believed
to be a significant source of surfactants in the environment [8].
The most common organic pollutants (OPs) are diesel fuel (DF) and used engine oil
(UEO), which is the main source of energy worldwide. It is a complex chemical mixture
of intermediate distillates of crude oil that has been separated by fractional distillation.
The carbon number of diesel fuel ranges from 11 to 25, and the distillation range is from
180 to 380
◦
C. Diesel fuel contains between 2000 and 4000 hydrocarbons that cannot be
completely separated by gas chromatography [
9
]. Diesel fuel contains approximately
64% aliphatic hydrocarbons, 1–2% olefinic hydrocarbons, and 35% aromatic hydrocarbons
and consists of four main structural classes: n-alkanes or n-paraffins (linear saturated
hydrocarbons); isoalkanes or isoparaffins (branched saturated hydrocarbons); cycloalkanes
or naphthenes (saturated cyclic alkanes); and polycyclic aromatic hydrocarbons [
10
]. UEO
contains polyaromatic hydrocarbons derived from petroleum, such as phenol, toluene,
benzene and other compounds, as well as the metals V, Pb, Al, Ni, and Fe [
11
]. Thus, UEO
is considered one of the most dangerous environmental pollutants [12].
Due to the harmful effects of OPs on humans and the environment, in particular
the combination of genotoxicity, bioaccumulation, and their resistance to degradation,
stormwater treatment is becoming increasingly important in the field of urban stormwater
management [
13
]. Solving this problem requires modern research and development on
innovative and effective stormwater quality management technologies that can prevent
further transport and spread of OPs into the environment, where they can bioaccumu-
late/biodegrade.
The choice of a stormwater treatment method and its application requires taking into
account the fact that many OPs (benzene, toluene, ethylbenzene, xylene, and light aromatic
hydrocarbons) are volatile and weakly hydrophilic, and are difficult to detect in stormwater
in the particulate phase [
14
]. Some types of OPs (PHs, phthalates, and polycyclic aro-
matic hydrocarbons (PAHs)) are hydrophobic, which allows them to be removed from
the aqueous phase by simple methods, such as particle sedimentation [
15
]. There are also
hydrophilic–hydrophobic compounds, such as diesel hydrocarbons, alkylphenols (APs)
and their ethoxylates (APEOs), diesel fuel with APs and APEOs, phthalates, and used
engine oil components, which can form nano- and micro-dispersed emulsions in rainwa-
ter [
16
]. Therefore, when choosing a stormwater treatment method, it is also advisable
to take into account that such waters contain colloids, truly dissolved components, and
emulsions of OPs.
Over the past decades, urban stormwater management paradigms have gained popu-
larity, focusing on controlling stormwater directly near the source of its generation rather
than on rapid drainage [
17
]. One of the practices often used in these cases is rain gardens,
which are implemented in residential areas for local stormwater management and con-
tribute to slowing the rate of peak runoff, reducing its volume, recharging groundwater
through infiltration, and removing pollutants from water before it reaches local streams.
The study of the quality of urban stormwater runoff, which is an important aspect of
managing the quality of surface and groundwater sources, began in the mid-20th century,
and the authors of [
18
] were among the first to draw attention to this problem. The main
problem was the presence of elevated concentrations of toxic pollutants in such waters. It
was found that, in addition to organic contaminants, these waters contain total suspended
solids (TSSs) [
19
], metals (Cd, Cr, Cu, Ni, Pb, and Zn) [
20
], pathogenic microorganisms [
21
],
Water 2024,16, 1802 3 of 29
and nutrients (N and P) [
22
]. In addition, modern scientific studies often confirm the
presence of pesticides [23], microplastics [24], and others.
One of the most effective ways to solve this problem is to organise rain gardens
of various types and designs. Various scientific studies have shown that the efficiency
of removing total phosphorus (TP) by rain gardens is 90% [
25
], total nitrogen (TN) is
60–97% [26]
, suspended solids (TSSs) is 53–60% [
27
], zinc (Zn) is 80–95%, copper (Cu) is
72–95%, lead (Pb) is 95%, cadmium (Cd) is 81–99% [
28
], mercury is 37%, methylmercury
is 49% [
29
], microplastics is 70–99% [
30
], pesticides is 99.7% [
31
], faecal coliform counts is
69% [32], and E. coli is 71–83% [33].
The authors of [
34
] experimentally determined a reduction of more than 96% of
oil and grease in laboratory-scale rain gardens and almost 100% in full-scale systems.
Hong et al. [
35
] observed an approximately 90% reduction in petroleum hydrocarbons in
laboratory columns. DiBlasi et al. [
36
] investigated the removal of PAHs by a rain garden
design and reported an average reduction in the total load of 87%. The efficiency of removal
of PHs and other organic pollutants in urban stormwater runoff by rain gardens was about
80–95% [
37
]. In real-world conditions, rain gardens demonstrated high efficiency in the
treatment of PHs and PAHs in stormwater, with a concentration reduction of 60–90% and
an average annual reduction of 87%.
Recent studies have highlighted the effectiveness of supplementing traditional rain
garden soil media with sorption materials to improve pollutant removal and hydrological
performance. The authors of [
30
] showed that petroleum hydrocarbons and PAHs were
effectively removed by bioretention systems using sphagnum peat, biochar, and ash from
municipal solid waste incineration with compost as sorption materials. In recent years,
the use of biochar as a soil amendment has attracted much attention around the world.
In [
38
], the authors investigated the biochar production processes, the impacts of pyrolysis
parameters on its properties, and the subsequent physicochemical impact of biochar on soil
and water characteristics, noting the effective effects. Organic pollutants are removed by
several different processes, the main ones being sedimentation on the surface of filters due
to the sorption of larger particles, evaporation from the surface, sorption in solid materials,
and biodegradation and/or phytoremediation by plants. In [
39
], the sorption response of
the two most common metals derived from PHs, hexavalent chromium (Cr
+6
) and mercury
(Hg
+2
), was studied using two semi-arid soils from Saudi Arabia. Based on the empirical
models (Langmuir and Freundlich), the nature of sorption (single-layer or heterogeneous)
and its features were clarified. In addition, kinetic models were used to verify the type and
nature of the sorption that occurs (pseudo-first or second order).
In [
40
], laboratory experimental studies were conducted on the behaviour of PHs in
three pilot rain gardens and the impact of vegetation on their removal. As a result of the
experiment, the authors concluded that soil adsorption was the most effective mechanism
for PH removal (>50%), although plant uptake was also significant. Weerasundara and
Vithanage [
41
] noted that when using a combination of phytoremediation and bioremedia-
tion systems, the rate of PH removal could be increased by 18–115%. Some studies confirm
that microorganisms (Pseudomonas,Arthrobacter,Rhodococcus,Acinetobacter,Flavobacterium,
Corynebacterium,Xanthomonas,Alcaligenes,Nocardia,Brevibacterium,Candida,Mycobacterium,
Beijerinkia,Bacillus,Enterobacteriaceae,Klebsiella, and Micrococcus) in rain gardens play im-
portant roles in the removal of oil pollutants [42].
Since the process of PH removal is mainly based on adsorption by soil media, it can
be assumed that these pollutants are not completely degraded within the system, which
can lead to their accumulation over time. When it comes to the accumulation of PHs
in the soil environment, the problem is complicated by the fact that these compounds
can migrate by diffusion and capillary forces through saturated or unsaturated flow [
43
].
Prolonged exposure to PHs can lead to a decrease in the affinity of the soil surface for
water molecules, which disrupts its water-holding properties. Possible mechanisms that
contribute to changes in soil moisture retention include the formation of a surface film at
the «solid–air» interface and direct contamination of soil macro- and microchannels by
Water 2024,16, 1802 4 of 29
PHs [
44
]. Thus, it can be assumed that over time, the accumulation of PHs in the layers
of the rain garden structure can directly affect the hydraulic characteristics of the entire
system, with a violation of its functionality and efficiency.
The choice of plants for rain gardens is an important component, especially in solving
the problem of petroleum hydrocarbon removal. Adaptation to new environmental con-
ditions, high resistance to pollutants, and the ability to selectively adsorb pollutants are
the main criteria for selecting vegetation for such systems. In addition, plants should have
characteristics such as ease of maintenance, availability of planting materials, a fast growth
rate, and a developed root system [41].
There are a small number of studies on the possible consequences of plant resistance
to PHs for the effective functioning of rain gardens. On the other hand, the phytotoxicity of
petroleum hydrocarbons, in particular diesel fuel, has been widely studied by the authors
of [
45
]. Barrutia et al. [
46
] studied the impact of DF on the physiological state of plants
(Trifolium repens and Lolium perenne) and the characteristics of the soil microbial community
in the context of the rhizoremediation of contaminated soils. For this purpose, a DF spill
on soil was simulated in pot conditions. The authors assessed the germination of new
sprouts, plant growth, and the condition of the root system. According to the results of
the experiment, L. perenne plants showed high resistance to diesel contamination of the
soil; shoot and root growth, as well as physiological productivity, were almost unaffected.
On the contrary, the fibrous root system of L. perenne showed a greater potential for the
rhizoremediation of diesel contaminated soil than T. repens. It was concluded that plant
tolerance is the main characteristic for the restoration of the physicochemical properties of
soil contaminated with petroleum hydrocarbons. Another study [47] indicates that plants
of the Fabaceae and Poaceae species are draining and can contribute to the phytoremediation
of soils contaminated with oil products. The use of herbs in this process is associated with
their well-developed fibrous root system, which creates a high rhizosphere effect that is
extremely important for the decomposition of organic contaminants.
The main objectives of the work are as follows:
1.
Determine the effectiveness of rain garden designs in removing petroleum hydrocar-
bons, such as diesel fuel and used engine oil, from rainwater;
2.
Study the temporal and spatial characteristics of the distribution and accumulation of
petroleum hydrocarbons in experimental rain gardens;
3.
Study the impact of petroleum hydrocarbons on plants of the species Physocarpus
opulifolia Diabolo;
4.
Provide recommendations for the implementation and maintenance of rain gardens in
real environmental conditions, in particular in areas with high levels of oil pollution,
such as petrol stations, car parks, and car washes.
The object of the study is experimental filter columns that simulate rain gardens in
the laboratory. The subject of the study is to determine the effectiveness of rain gardens in
removing PHs from rainwater. The scientific novelty of the work is to establish the peculiar-
ities of the temporal and spatial characteristics of the distribution and accumulation of PHs
in rain gardens. The practical significance of the research is to study the impact of PHs on
plants of the Physocarpus opulifolia Diabolo species, as well as to develop recommendations
for the implementation and maintenance of rain gardens in real environmental conditions.
2. Materials and Methods
2.1. Experimental Filter Columns (Cylinders)
In this work, a set of three experiments in one was carried out based on the objectives.
The experiment was carried out in the laboratory of environmental parameters control
of the Department of Environmental Protection Technologies and Labour Protection of
the Kyiv National University of Construction and Architecture (Ukraine) for 6 months
(22 weeks).
For the experimental studies, cylindrical columns (Figure 1) were used, made of
polyvinyl chloride materials, 100 mm in diameter, 900 mm in height and 2 mm in wall
Water 2024,16, 1802 5 of 29
thickness, to create an economical and compact installation with dimensions that minimised
the wall (edge) effect and dispersion in the columns. The wall effect is the phenomenon
of increased hydraulic flow at the interface between the column walls and its holding
surface [
48
]. To reduce this effect, the inner surfaces of the columns were lightly ground to
slow the fluid flow, and the distribution of solutions took place in the upper layer in the
centre of the column. In addition, large-diameter columns increase the risk of dispersion,
which can cause erosion of the filter media due to the formation of various channels for
liquid flow, which are then eroded vertically [
49
]. A total of eight experimental filter
columns (cylinders) were used, which were studied depending on the type of PHs that
penetrated the layers. A scale was installed on each column to measure the level of liquid
seepage. Special holes were made in the bottom of each column to collect the filtrate.
Water 2024, 16, x FOR PEER REVIEW 5 of 29
the Department of Environmental Protection Technologies and Labour Protection of the
Kyiv National University of Construction and Architecture (Ukraine) for 6 months (22
weeks).
For the experimental studies, cylindrical columns (Figure 1) were used, made of pol-
yvinyl chloride materials, 100 mm in diameter, 900 mm in height and 2 mm in wall thick-
ness, to create an economical and compact installation with dimensions that minimised
the wall (edge) effect and dispersion in the columns. The wall effect is the phenomenon of
increased hydraulic flow at the interface between the column walls and its holding surface
[48]. To reduce this effect, the inner surfaces of the columns were lightly ground to slow
the fluid flow, and the distribution of solutions took place in the upper layer in the centre
of the column. In addition, large-diameter columns increase the risk of dispersion, which
can cause erosion of the filter media due to the formation of various channels for liquid
flow, which are then eroded vertically [49]. A total of eight experimental filter columns
(cylinders) were used, which were studied depending on the type of PHs that penetrated
the layers. A scale was installed on each column to measure the level of liquid seepage.
Special holes were made in the boom of each column to collect the filtrate.
Figure 1. Experimental filter columns and a schematic diagram: 1—Physocarpus opulifolia Diabolo;
2—soil layer; 3—sand layer; and 4—gravel layer.
In the vertical section of the experimental filtration columns, the layers were laid as
follows (starting from the top): 330 mm of soil, 330 mm of sand, and 200 mm of gravel.
The total volume of soil and sand in each column was approximately 2.6 dm3, and the
volume of gravel was 1.57 dm3. The total height of the three different media layers in the
column was 860 mm, with 40 mm of depth left for the water level. Since the main functions
of the mulch layer in rain garden designs are to suppress weed growth, maintain the nec-
essary moisture level for plants, and reduce the risk of waterlogging of the soil environ-
ment, it was decided to neglect this layer in the laboratory. In addition, according to the
conclusions of a report [50], the degree of PH removal in rain gardens with and without
mulch did not differ significantly in terms of efficiency.
2.2. Characteristics of Experimental Samples
Soils. The soil for planting was collected from the surface layer at a depth of 50–100
mm from an uncontaminated area in one of the districts of Kyiv in September 2023. To
avoid the presence of contaminants, the soil sampling site was chosen to be away from
active road traffic or industrial facilities. The collected soil sample was rinsed with dis-
tilled water, air-dried, and sieved through a 2 × 2 mm sieve to ensure a homogeneous
material and remove particles with a nominal size > 2 mm and long plant fibres. The tex-
ture of the soil was sandy loam, which is typical of Ukrainian soils. Natural river sand was
used for the intermediate infiltration layer of the experimental columns [51]. The drainage
(gravel) layer is the lower part of a typical rain garden structure, which consists of fine,
Figure 1. Experimental filter columns and a schematic diagram: 1—Physocarpus opulifolia Diabolo;
2—soil layer; 3—sand layer; and 4—gravel layer.
In the vertical section of the experimental filtration columns, the layers were laid as
follows (starting from the top): 330 mm of soil, 330 mm of sand, and 200 mm of gravel. The
total volume of soil and sand in each column was approximately 2.6 dm
3
, and the volume
of gravel was 1.57 dm
3
. The total height of the three different media layers in the column
was 860 mm, with 40 mm of depth left for the water level. Since the main functions of the
mulch layer in rain garden designs are to suppress weed growth, maintain the necessary
moisture level for plants, and reduce the risk of waterlogging of the soil environment, it
was decided to neglect this layer in the laboratory. In addition, according to the conclusions
of a report [
50
], the degree of PH removal in rain gardens with and without mulch did not
differ significantly in terms of efficiency.
2.2. Characteristics of Experimental Samples
Soils. The soil for planting was collected from the surface layer at a depth of
50–100 mm
from an uncontaminated area in one of the districts of Kyiv in September 2023. To avoid
the presence of contaminants, the soil sampling site was chosen to be away from active
road traffic or industrial facilities. The collected soil sample was rinsed with distilled water,
air-dried, and sieved through a 2
×
2 mm sieve to ensure a homogeneous material and
remove particles with a nominal size > 2 mm and long plant fibres. The texture of the
soil was sandy loam, which is typical of Ukrainian soils. Natural river sand was used for
the intermediate infiltration layer of the experimental columns [
51
]. The drainage (gravel)
layer is the lower part of a typical rain garden structure, which consists of fine, medium, or
coarse gravel. This layer is more porous and is responsible for retaining and transporting
treated water to the drainage system or surrounding soil, and prevents leaching of the
engineered soil [
52
]. For the drainage layer of the experimental columns, gravel with sizes
of the main fractions of 5–7 mm and the accompanying fractions of 1–3 mm was selected.
The geotechnical analysis of soils was performed by the following methods. The
hydraulic conductivity (filtration coefficient)
k
, mm/h, was determined at a given pressure
Water 2024,16, 1802 6 of 29
on the soil and a variable pressure gradient when water was passed from top to bottom
after pre-saturating the soil sample with water [
53
]. The moisture content of the soil and
sand was determined by drying in an oven at 105
◦
Cfor3h[
54
], after which the samples
were left in the oven for 30 min before weighing. The moisture content was calculated as
the ratio between the mass, kg, of water in the sample (
mw
) and the mass of the dry sample
(
md
). The mass of water in the sample was determined as the difference between the mass
of the wet and dry samples. The water-holding capacity of the materials was determined
using the method validated by Nelson [
55
] with a funnel and filter paper after two hours
of gravity drainage from a saturated sample. The particle size analysis of soil and sand was
performed using the sieving method [
56
]. The particle size of the soil was less than 0.5 mm,
while the grain size of the sand pores ranged from 0.06 mm to 0.5 mm and had an average
size of 0.3 m. The physical and chemical properties of the soil filter materials are shown in
Table 1.
Table 1. Physical and chemical properties of soil mixtures used in laboratory experiments.
Soil Type Density (kg/dm3)Porosity, % Hydraulic Conductivity
(m/s) Moisture Content, % Water-Holding
Capacity, m3/m3
Natural soil 1.48 52.1 0.018 ×10−33.7 0.41
River sand 1.6 39.3 0.127 ×10−36.0 0.35
Gravel - - >5.0 ×10−2- 0.1
The soil was compacted in the columns by the methodology [
57
]. The bulk density
of the soil in the columns was 1.48 kg/dm
3
, which is considered the optimal value for
plant growth [
57
]. The value of hydraulic conductivity for all experimental columns at the
beginning of the experiment was 5.1
×
10
−5
m/s or 185 mm/h, which corresponds to the
recommended range of 50 to 200 mm/h specified in the recommendations for a temperate
climate [58].
Plants. Resistance to petroleum hydrocarbons is a prerequisite for rain garden plants.
This study focuses on plants with a well-developed fibrous root system, in particular on the
widespread species Physocarpus opulifolia Diabolo in Ukraine. It is a deciduous spreading
shrub with branches that form a dense, hemispherical crown up to 3 m high and wide. This
species is frost-resistant and light-tolerant, as it can grow in light and shade, undemanding
to soil conditions, and resistant to urban environments. Plants of the Physocarpus opulifolia
Diabolo species are known for their effectiveness in the phytoremediation of air and removal
of various organic substances and heavy metals [
59
]. However, there are no data in the
scientific literature on the impact of this plant species on the soil environment and water.
Model petroleum hydrocarbons. Rain gardens, whose main function is to clean PHs from
stormwater, are installed along motorways, petrol stations, and parking areas where motor
vehicles are the main source of diesel fuel, petrol, and used engine oil. The fractional
composition of petroleum products is divided into light hydrocarbons (petrol and DF) and
heavy hydrocarbons (fuel oil and UEO). To achieve the research objectives, representatives
of each of these classes were selected as model oils. Due to the content of lighter and
more volatile components, petrol has a higher degree of evaporation compared to DF,
which makes it less suitable for long-term studies. Therefore, DF was chosen as the model
fuel. Since UEO contains almost all types of hydrocarbons, this oil product was chosen
as another model PH. The diesel fuel used in this study was purchased at a petrol station
in Kyiv. The density of the diesel fuel was 0.83 g/cm
3
, and its viscosity at 20
◦
C was
5.8 mm
2
/s. The used engine oil was obtained from a car service station in Kyiv. Before
starting the experiment, the degree of extraction of diesel components and UEO into water
was checked. The degree of extraction was determined by intensively mixing 3 cm
3
of
distilled water with 0.15 cm
3
of DF or UEO, followed by water-phase chromatography.
Shaking was performed for 2 h.
Water 2024,16, 1802 7 of 29
2.3. Calculation of Model Solution Volumes
To simulate rain events, the volumes of model solutions were calculated by taking into
account the typical drying and wetting regime in the city of Kyiv, which is characterised
by a temperate climate. For this purpose, a rain event was simulated twice a week. The
volume of water supplied to the experimental columns was calculated based on statistical
data on the amount of precipitation for 2023, when 673 mm of precipitation fell [
60
]. Most
of the precipitation falls from April to October (400 mm), with a maximum of 85 mm
in July and a minimum of 35 mm in March. In the period from November to March,
respectively, just over 200 mm of precipitation falls. During the year, the average number of
days with precipitation is about 160. Therefore, it can be assumed that it rains on average
every 2.2 days, and the volume of water per rain event should be assumed to be 4.05 mm.
The volume of rainwater supplied to the experimental columns was calculated by taking
into account the runoff coefficient, typical rain events in the region, and the area of the
experimental column, which was 0.00785 m2.
It was assumed that the area of impermeable surfaces was 85% (the runoff coefficient
was 0.85), and the area of the experimental column simulating the rain garden design was
7% of the catchment area (one column was designed for 0.112 m2of catchment) [61].
The required volume of model rainwater (
V
) was calculated by the volumetric
method [62] using Equation (1):
V=F·ψ·H, (1)
where
F
is the catchment area of the runoff (m
2
);
ψ
is the runoff coefficient; and
H
is the
calculated rainfall depth (dm3/m2).
Based on these assumptions, it was calculated that each column should be irrigated
with approximately 0.385 dm
3
of rainwater per event (4.05 dm
3
/m
2×
0.112 m
2×
0.85
= 0.385 dm
3
). In this way, a typical wetting and drying pattern was reproduced in the
laboratory according to the regional climate with a regular dosing regime. This approach
allowed the columns to dry naturally between dosing events, which helped to avoid
introducing artifacts in the time trends of hydraulic conductivity.
The volume of model petroleum hydrocarbons injected into the experimental columns
was calculated from the typical volume of PHs that can be released during emergencies or
gradually accumulate in the environment, for example, from car washing [
63
]. We injected
5 cm
3
of diesel fuel and used engine oil twice a week into each experimental column with
an area of 0.00785 m
2
. This volume was chosen to simulate a moderate level of pollution,
since the volume of each pollutant per 1 m2of area is 637.58 cm3/m2.
2.4. Reverse-Phase High-Performance Liquid Chromatography
Quantitative measurements of the concentrations of model PHs involve regular sam-
pling of soil materials at different depths in the vertical direction of the experimental
columns [
64
]. In order not to violate the conditions of the processes taking place inside
the experimental columns and to avoid affecting the functional development of Physocar-
pus opulifolia Diabolo plants, the experiment did not involve interference with the system.
Reverse-phase high-performance liquid chromatography (RP-HPLC) was used to analyse
the original DF and UEO samples. Petroleum hydrocarbons are typically analysed using
gas chromatography (GC)-based methods due to their non-polar and thermally stable
nature. However, the analysis of samples containing aqueous extracts of contaminated
soil or aqueous leachates is mainly carried out by the HPLC method. An advantage of
HPLC is its compatibility with aqueous samples (or extracts), which minimises sample
pretreatment steps. However, a disadvantage of HPLC is that analytes are only identified
by their retention times. Identification should be performed when samples are complex
and multiple peaks are detected, which can be achieved by ultraviolet (UV) detection
that provides a match to specific UV spectra for the components of the PHs [
65
]. Widely
used HPLC detectors are based on the UV spectrum and the interaction of UV (absorption
or fluorescence) with compounds. For this reason, PHs can be easily detected in soil or
water samples by HPLC analysis, and the detection limit is higher than that of GC [
66
].
Water 2024,16, 1802 8 of 29
The method under consideration was used by researchers to determine the concentration
of benzo(a)pyrene in oil-contaminated soil [
67
]. In this study, the individual and total
concentrations of PHs present in contaminated soil samples were studied using HPLC with
detection limits ranging from 0.2 to 12 ppm, with an average PH recovery of 85% to 105%.
Samples of aqueous filtrates were extracted with dichloromethane, filtered and analysed
by reverse-phase HPLC, as reported by the authors of [
68
]. Therefore, the chosen HPLC
method is suitable for the analysis of compounds with high molecular weights and boiling
points and provides a high level of detail in the analysis of the PH components, which
allows for a better assessment of their behaviours in the soil phase and water leaching.
The study was carried out on an Agilent 1100 system (Agilent Technologies, Inc., Santa
Clara, CA, USA) with a four-channel pump and a diode array detector after pre-filtering
through iPure filters with a nylon membrane with a pore diameter of 0.22
µ
m. A Zorbax
SB C-18 4.6
×
250 mm chromatographic column with a 5
µ
m grain diameter was used
to separate the substances in the samples. The sample volume was 5 mm
3
. The mobile
phase consisted of a mixture of an aqueous solution of orthophosphoric acid (0.050 M) and
acetonitrile. The elution was started with a proportion of acetonitrile of 5%, which was
increased to 100% after 10 min. The flow rate was 0.6 cm
3
/min, and the total analysis time
was 16 min. The column separation temperature was 20
◦
C. Detection was performed at
a wavelength of 206 nm. Blank chromatograms were also recorded with 5 mm
3
of pure
hexane and water separately.
2.5. Experimental Procedure with Filter Columns
Taking into account the above, the following experimental procedure was adopted.
Plants of the Physocarpus opulifolia Diabolo species were planted on 12 October 2023 in
experimental filter columns I to VI. Columns VII and VIII were left without vegetation.
To support the physiological development of plants, red–blue artificial LED lighting was
used, which was calculated according to the method described by the authors of [
69
].
After planting, the plants were regularly watered with tap water without any additional
nutrients to accelerate their adaptation period, which lasted 10 to 20 days after planting
and was controlled by measuring the height of each sample and recording the appearance
of new leaves.
The experiment to study the process of PH retention by filter columns was started on
13 November 2023 and completed on 13 April 2024 (22 weeks). Experimental columns I and
II, in which plants of the Physocarpus opulifolia Diabolo species were planted, were watered
with 5 cm
3
of used engine oil, and after 30 min, with 385 cm
3
of tap water, as provided
for by the methodology. Columns III and IV with plants of the same species were watered
with only 385 cm
3
of tap water without adding model PHs to the system to have control
variants for observing plant development. Experimental columns V and VI with plants of
the Physocarpus opulifolia Diabolo species were watered with 5 cm
3
of diesel fuel, and after
30 min, with 385 cm
3
of tap water. Columns VII and VIII, which had identical soil layers to
the other columns but no vegetation, were watered with 5 cm
3
of UEO and DF, respectively,
and after 30 min, with 385 cm
3
of tap water. Watering of the experimental models was
carried out according to the calculated volumes of pollutants and water with the same
time interval—every 3 days. It was accompanied by recording the signs of development
of the studied plant species. The purpose of the chosen methodology was to assess the
efficiency of the filter layers of the experimental plants to remove significant loads of PHs
in a short period.
A study by Zhang et al. [
70
] showed that dry periods of at least 10 h are required
for the biodegradation of pollutants to occur. Decomposition of petroleum hydrocarbon
compounds with low degradation rates may take several days or weeks. Thus, in the
experimental columns with uniform water flow, sorption processes prevail; so, the study of
the biodegradation process was not the target of our work.
The quality of the leachate was monitored by taking samples at the outlet of the
experimental columns at intervals of three months. The total volume of each sample taken
Water 2024,16, 1802 9 of 29
for analysis was 100 cm
3
. The samples were collected in glass flasks and stored in a cooling
bag until transported to the laboratory, where they were placed in refrigerators until further
analysis. The content of PHs in the leachate samples was determined by the HPLC method
at the Institute of High Molecular Weight Chemistry of the National Academy of Sciences of
Ukraine. The first leachate samples were collected from columns I and II (with vegetation)
and analysed on 13 January 2024 to determine the presence of UEO, from columns V and
VI (with vegetation) to detect DF, and from columns VII and VIII (without vegetation) to
determine the presence of both UEO and DF, respectively. Samples were not taken from
columns III and IV (with vegetation), as these sites were not irrigated with model PHs and
were used as controls to observe plant development.
To evaluate the efficiency of PH removal by the experimental columns imitating rain
gardens, the concentrations of PH components in the leachate at the outlet of the columns
was analysed and compared with the samples of the original model pollutants. To analyse
the vertical accumulation of pollutants, samples of the topsoil and intermediate sand layer
were taken after 6 months of operation of the experimental columns. The general samples
of the sand and soil layers were obtained by quarting according to the following method:
each layer of about 2.7 dm
3
was scattered on a clean surface and formed a cone, which
was divided into four equal parts. The first and third quarters were then removed and the
remaining quarters were combined. This procedure was repeated until a 5 cm
3
sample
was obtained.
The resulting sand and soil samples were prepared by adding hexane at a ratio of
2 cm
3
of hexane per 1 cm
3
of sand/soil and then stirring the mixture for 2 h. The hexane
phase was separated, while the residual aqueous phase was further extracted with 20 cm
3
of hexane. Both hexane extracts were combined and then concentrated to approximately
1 cm
3
by purging with nitrogen gas. The samples were then left to stand for one hour,
after which a 1 cm
3
aliquot was taken and passed through iPure filters with a 0.22
µ
m
PTFE membrane. The filtered extract was weighed, transferred to a separatory funnel, and
shaken for one hour. The filtered samples were analysed by HPLC using an Agilent 1100
system according to the same procedure as the original model samples. The total analysis
time was 20 min. The analysis time was extended compared to the analysis of DF and UEO
samples due to the presence of substances with longer retention times in the sand and
soil extracts.
2.6. Study of Plant Resistance
This experiment, conducted with Physocarpus opulifolia Diabolo, was not aimed at
studying the degradation of petroleum hydrocarbons in the process of bioremediation
by plants and bacteria but allowed a study of the reaction of plants to pollutants and
determination of the degree of their suitability for use in rain gardens.
The susceptibility of each plant sample to phytotoxicity was assessed by comparing
the biomass of control and treated plants. A comparative susceptibility scale was used to
assess the response of plants to the stress of PH-contaminated soil [
71
]. Plants weighing
less than 25% of the weight of control plants were considered highly sensitive. Plants
weighing between 25% and 50% of the weight of the control plants were considered
moderately sensitive. Plants weighing more than 50% of the weight of the control plants
were considered resistant to stress caused by model petroleum hydrocarbon contamination.
The number of shoots and plant height (from the base of the shoot to the top) were
measured weekly, starting from the first week after planting until the 22nd week of the
experiment. At the end of the experiment, the plants were harvested to determine the
dry and wet weights. Uprooted plants were washed with distilled water to remove any
adhering deposits and separated into shoots (the part above the soil level) and roots. All
samples were dried at 80
◦
C for 48 h in a forced-air oven. The dried shoots and roots were
weighed separately to determine the masses of shoots and roots, and together to calculate
the total biomass of the plant.
Water 2024,16, 1802 10 of 29
Growth analysis is a widely used analytical tool for characterising plant growth. One
of the most important parameters commonly calculated is the relative growth rate (RGR),
which is defined as the parameter r in Equation (2) [72]:
W2=W1·er(t2−t1), (2)
where W1and W2are the plant dry weights at time t1and t2.
Relative growth rates (RGRs) of shoots and roots were calculated based on Equation (3):
RGR =ln(W2)−ln (W1)
t2−t1, (3)
where
W1
is the dry weight of the shoot or root at the 4th week after planting;
W2
is the dry
weight of the shoot or root at 22 weeks after planting;
t1
is the initial value of the time after
planting and the end of the adaptation period of plants (4 weeks);
t2
is the last value of the
time after planting (22 weeks).
The tolerance index (TI) was calculated as the ratio between the dry aboveground
biomass of a plant in the PH-contaminated soil to the dry aboveground biomass of plants
in the control soil [73]:
TI =[Biomass]treated∨cont aminated
[Biomass]control∨non−contaminated
, (4)
where
[Biomass]treated∨contaminated
is the biomass of the whole plant in the treated or contam-
inated soil;
[Biomass]control∨non−contaminated
is the biomass of the whole plant in the control
or non-contaminated soil.
The tolerance of the studied plants is expressed on a scale where 1 and above mean full
tolerance and from 0.5 to 1 means partial tolerance. These values will allow the development
of recommendations for the use of this plant species in rain gardens in urban environments
contaminated with PHs. If TI is in the range from 0 to 0.5, plants are considered not tolerant,
and so they are not recommended for use in rain gardens.
3. Results and Discussion
3.1. Analysis of the Leachate from the Experimental Columns
Figure 2shows the chromatograms of samples of source diesel (Figure 2a) and used
engine oil (Figure 2b) dissolved in hexane in a ratio of 1:40.
Water 2024, 16, x FOR PEER REVIEW 10 of 29
weighing between 25% and 50% of the weight of the control plants were considered mod-
erately sensitive. Plants weighing more than 50% of the weight of the control plants were
considered resistant to stress caused by model petroleum hydrocarbon contamination.
The number of shoots and plant height (from the base of the shoot to the top) were
measured weekly, starting from the first week after planting until the 22nd week of the
experiment. At the end of the experiment, the plants were harvested to determine the dry
and wet weights. Uprooted plants were washed with distilled water to remove any adher-
ing deposits and separated into shoots (the part above the soil level) and roots. All samples
were dried at 80 °C for 48 h in a forced-air oven. The dried shoots and roots were weighed
separately to determine the masses of shoots and roots, and together to calculate the total
biomass of the plant.
Growth analysis is a widely used analytical tool for characterising plant growth. One
of the most important parameters commonly calculated is the relative growth rate (RGR),
which is defined as the parameter r in Equation (2) [72]:
𝑊
=𝑊
∙𝑒
(), (2)
where 𝑊
and 𝑊
are the plant dry weights at time 𝑡 and 𝑡.
Relative growth rates (RGRs) of shoots and roots were calculated based on Equation
(3):
𝑅𝐺𝑅 = 𝑙𝑛(𝑊
)−𝑙𝑛 (
)
, (3)
where 𝑊
is the dry weight of the shoot or root at the 4th week after planting; 𝑊
is the
dry weight of the shoot or root at 22 weeks after planting; 𝑡 is the initial value of the time
after planting and the end of the adaptation period of plants (4 weeks); 𝑡 is the last value
of the time after planting (22 weeks).
The tolerance index (TI) was calculated as the ratio between the dry aboveground
biomass of a plant in the PH-contaminated soil to the dry aboveground biomass of plants
in the control soil [73]:
𝑇𝐼 = ∨
∨, (4)
where 𝐵𝑖𝑜𝑚𝑎𝑠𝑠∨ is the biomass of the whole plant in the treated or
contaminated soil; 𝐵𝑖𝑜𝑚𝑎𝑠𝑠∨ is the biomass of the whole plant in
the control or non-contaminated soil.
The tolerance of the studied plants is expressed on a scale where 1 and above mean
full tolerance and from 0.5 to 1 means partial tolerance. These values will allow the devel-
opment of recommendations for the use of this plant species in rain gardens in urban en-
vironments contaminated with PHs. If TI is in the range from 0 to 0.5, plants are consid-
ered not tolerant, and so they are not recommended for use in rain gardens.
3. Results and Discussion
3.1. Analysis of the Leachate from the Experimental Columns
Figure 2 shows the chromatograms of samples of source diesel (Figure 2a) and used
engine oil (Figure 2b) dissolved in hexane in a ratio of 1:40.
Figure 2. Chromatogram of the original diesel fuel (a) and the original used engine oil (b).
Figure 2. Chromatogram of the original diesel fuel (a) and the original used engine oil (b).
In addition, Table 2shows the mass percentages of substances in the initial DF and
UEO and their retention times.
Water 2024,16, 1802 11 of 29
Table 2. Mass percentages of components of the initial model petroleum hydrocarbons.
No.
Diesel Fuel Used Engine Oil
Retention Time,
min
Content, % by
Weight
Retention Time,
min
Content, % by
Weight
1 11.4 19% 11.4 3%
2 11.8 0% 11.9 4%
3 12.1 22% 12.1 3%
4 12.4 1% 12.4 6%
5 12.6 11% 12.6 2%
6 12.7 18% 12.7 2%
7 13.1 4% 12.9 2%
8 13.2 8% 13.1 9%
9 13.4 7% 13.7 4%
10 13.7 1% 14.0 12%
11 13.8 2% 14.1 4%
12 14.0 3% 14.4 8%
13 14.6 3% 14.6 20%
14 - - 15.2 8%
15 - - 15.6 15%
For each peak in the chromatogram of the original DF, the corresponding UV spectra
were analysed to determine the nature of the constituents based on their UV absorption
(Figure A1). According to the spectral profiles, it was determined that the peaks of the
chromatogram correspond to substances from the class of alkyl benzene and alkenes. Many
of the PHs have very specific UV spectra. Despite the fact that most of the PHs are absorbed
at 254 nm, this is not the only UV wavelength for all their components. The highest
sensitivity and lowest detection limit can only be achieved by measuring at a specific UV
wavelength. In this study, saturated PHs, which are the main component of DF and UEO,
do not absorb UV radiation below 190 nm. This makes it difficult to detect them with
the available detector. Therefore, the scan was carried out from 190 to 400 nm, which
indicates a change in the absorption capacity of the DF at different UV wavelengths. By
analysing the UV spectra, it is possible to detect the presence of diesel fuel components by
correlating them with the peaks of alkyl benzene and alkenes on the chromatogram. Such
spectral analysis helps to identify diesel components and determine their amounts, which
is important for fuel quality control and detection of possible impurities or contaminants in
leachate samples from the experimental columns.
The UV-vis spectra of the peaks in the chromatogram of the original used engine oil
(Figure A1) indicate the presence of various unsaturated derivatives with both linear and
cyclic structures. The available spectra do not allow for an accurate determination of the
structure of specific components, but, as in the case of DF, they can serve for a general
analysis of the composition of the original UEO. The detected peaks of the respective
components can be used to track the presence of these components in the samples, which
allows for quality control of the filtrate from the experimental columns and the detection of
possible impurities or contaminants.
At the end of 18 irrigation cycles, 63 days (9 weeks) after the start of the experiment,
samples of water that passed through the experimental columns contaminated with PHs
were analysed. Sample 1 (Figure 3a) and sample 2 (Figure 3b) correspond to leachates from
cylinders I and VII, which were irrigated with UEO and were with and without vegetation,
respectively. Sample 3 (Figure 3c) and sample 4 (Figure 3d) correspond to leachates from
cylinders V and VIII, which were watered with DF and were with and without vegetation,
Water 2024,16, 1802 12 of 29
respectively. The results of the chromatographic analysis of leachates from cylinders II and
VI, which contained vegetation and were irrigated with UEO and DF, showed a complete
correspondence to the chromatograms of samples 1 and 3, respectively. Therefore, these
results were not included in the report.
Water 2024, 16, x FOR PEER REVIEW 12 of 29
etation, respectively. Sample 3 (Figure 3c) and sample 4 (Figure 3d) correspond to leacha-
tes from cylinders V and VIII, which were watered with DF and were with and without
vegetation, respectively. The results of the chromatographic analysis of leachates from
cylinders II and VI, which contained vegetation and were irrigated with UEO and DF,
showed a complete correspondence to the chromatograms of samples 1 and 3, respec-
tively. Therefore, these results were not included in the report.
Figure 3. Chromatograms of the filtrate from the experimental columns: (a) sample 1 (cylinder I); (b)
sample 2 (cylinder VII); (c) sample 3 (cylinder V); and (d) sample 4 (cylinder VIII).
After 44 irrigation cycles, 154 days (22 weeks) from the start of the experiment, leach-
ate 5 (Figure 4a) from column I and leachate 6 (Figure 4b) from column VI were analysed
to analyse how the removal of model petroleum hydrocarbons changed over time.
Figure 4. Chromatograms of the filtrate from the experimental columns: (a) sample 5 (cylinder I)
and (b) sample 6 (cylinder VI).
The results of HPLC indicate the absence of UEO and DF components in the filtrates
of all experimental columns. However, an intense peak with a retention time of 4.22 min
was observed in each sample. The UV-vis spectrum (Figure A2) of this peak does not cor-
respond to any of the components of the model petroleum hydrocarbons. It can be as-
sumed that the peak belongs to a substance released by the roots of the Physocarpus opuli-
folia Diabolo plant into the soil, which requires further study of the bioremediation process.
It should also be noted that at certain wavelengths (240 and 290 nm), PHs can affect other
compounds absorbing UV light, such as fulvic and humic acids of the soil matrix, and
these effects were not properly assessed. The soil used in this experiment was fertile sandy
loam soil with a high organic maer content, and so humic compounds can be extracted
together and detected in defined fractions on chromatograms.
By analysing the UV-vis spectrum of the peaks in the chromatogram of the leachate
samples (Figure A2), the retention time in the chromatographic column, and peak areas
Figure 3. Chromatograms of the filtrate from the experimental columns: (a) sample 1 (cylinder I);
(b) sample 2 (cylinder VII); (c) sample 3 (cylinder V); and (d) sample 4 (cylinder VIII).
After 44 irrigation cycles, 154 days (22 weeks) from the start of the experiment, leachate
5 (Figure 4a) from column I and leachate 6 (Figure 4b) from column VI were analysed to
analyse how the removal of model petroleum hydrocarbons changed over time.
Water 2024, 16, x FOR PEER REVIEW 12 of 29
etation, respectively. Sample 3 (Figure 3c) and sample 4 (Figure 3d) correspond to leacha-
tes from cylinders V and VIII, which were watered with DF and were with and without
vegetation, respectively. The results of the chromatographic analysis of leachates from
cylinders II and VI, which contained vegetation and were irrigated with UEO and DF,
showed a complete correspondence to the chromatograms of samples 1 and 3, respec-
tively. Therefore, these results were not included in the report.
Figure 3. Chromatograms of the filtrate from the experimental columns: (a) sample 1 (cylinder I); (b)
sample 2 (cylinder VII); (c) sample 3 (cylinder V); and (d) sample 4 (cylinder VIII).
After 44 irrigation cycles, 154 days (22 weeks) from the start of the experiment, leach-
ate 5 (Figure 4a) from column I and leachate 6 (Figure 4b) from column VI were analysed
to analyse how the removal of model petroleum hydrocarbons changed over time.
Figure 4. Chromatograms of the filtrate from the experimental columns: (a) sample 5 (cylinder I)
and (b) sample 6 (cylinder VI).
The results of HPLC indicate the absence of UEO and DF components in the filtrates
of all experimental columns. However, an intense peak with a retention time of 4.22 min
was observed in each sample. The UV-vis spectrum (Figure A2) of this peak does not cor-
respond to any of the components of the model petroleum hydrocarbons. It can be as-
sumed that the peak belongs to a substance released by the roots of the Physocarpus opuli-
folia Diabolo plant into the soil, which requires further study of the bioremediation process.
It should also be noted that at certain wavelengths (240 and 290 nm), PHs can affect other
compounds absorbing UV light, such as fulvic and humic acids of the soil matrix, and
these effects were not properly assessed. The soil used in this experiment was fertile sandy
loam soil with a high organic maer content, and so humic compounds can be extracted
together and detected in defined fractions on chromatograms.
By analysing the UV-vis spectrum of the peaks in the chromatogram of the leachate
samples (Figure A2), the retention time in the chromatographic column, and peak areas
Figure 4. Chromatograms of the filtrate from the experimental columns: (a) sample 5 (cylinder I) and
(b) sample 6 (cylinder VI).
The results of HPLC indicate the absence of UEO and DF components in the filtrates
of all experimental columns. However, an intense peak with a retention time of 4.22 min
was observed in each sample. The UV-vis spectrum (Figure A2) of this peak does not
correspond to any of the components of the model petroleum hydrocarbons. It can be
assumed that the peak belongs to a substance released by the roots of the Physocarpus
opulifolia Diabolo plant into the soil, which requires further study of the bioremediation
process. It should also be noted that at certain wavelengths (240 and 290 nm), PHs can
affect other compounds absorbing UV light, such as fulvic and humic acids of the soil
matrix, and these effects were not properly assessed. The soil used in this experiment was
fertile sandy loam soil with a high organic matter content, and so humic compounds can
be extracted together and detected in defined fractions on chromatograms.
By analysing the UV-vis spectrum of the peaks in the chromatogram of the leachate
samples (Figure A2), the retention time in the chromatographic column, and peak areas
Water 2024,16, 1802 13 of 29
(Table 3), it can be stated that this is a hydrophilic compound with a low molecular weight
that contains a carbonyl or carboxyl group conjugated to a separate double bond.
Table 3. Peak areas in the chromatograms of water samples (the peak area is proportional to the
concentration of the corresponding substance).
No. Sampling Date Cylinder
Number
Peak Area
4.22 min
Peak Area
3.92 min
Peak Area
12–13 min
1 13 January 2024 I 34,522 - 162
2 13 January 2024 V 3711 - 235
3 13 January 2024 VIII 2038 62 177
4 13 April 2024 I 2745 - 243
5 13 April 2024 VI 1110 1596 210
According to the chromatographic analysis, the highest concentration of the identified
hydrophilic compound was observed in sample 1 obtained from experimental column I
(with vegetation), which was subjected to UEO irrigation. There was also a significant
tendency for the concentrations of certain substances with a retention time of 12–13 min
to increase in samples 4 and 5. It should be noted that these substances, although present
in low concentrations (<10 mg/cm3), do not correspond to DF or UEO components in the
UV spectrum and the retention times. The substances are the result of the transformation
of petroleum hydrocarbons and are characterised by the presence of a long carbon chain,
which determines their hydrophobicity.
Based on the results of chromatographic analysis of the filtrate from the experimental
columns, which were subjected to regular irrigation with model petroleum hydrocarbons
during all 62 cycles for the 154 days (22 weeks) of the experiment, no diesel fuel or used
engine oil components were detected in the samples. These data allow us to conclude
that with the given parameters of the experimental columns, properties of soil mixtures,
dosages of pollutants and stormwater, the removal efficiency of both model PHs by the
columns was 100%.
A similar laboratory study to evaluate the efficiency of PH removal by rain gardens
under controlled laboratory conditions was conducted by the authors of [
16
]. The ex-
periment was carried out on two prototypes of modified rain garden structures with a
soil substrate based on a specially developed mineral–organic mixture and a drainage
channel. By analysing the results of the research, it was found that the pilot structures
are characterised by a very high efficiency of PH removal from rainwater, close to 100%.
Similar laboratory tests were conducted on two prototype rain gardens in Poland [
74
].
The results showed that the bioretention structure is characterised by a high efficiency of
removal of PHs from rainwater, and the efficiency of the reduction in these pollutants for
both prototypes is close to 100%. The effectiveness of removing petroleum hydrocarbons
by rain gardens was also tested in real conditions [
75
]. Rain gardens in Vancouver (Canada)
were tested on 18 soil environments of different compositions. Based on the results, all
soil media showed a degree of PH removal that exceeded 99%, similar to the results of our
laboratory study.
Despite the limited amount of available data on the performance of rain gardens in
removing PHs from stormwater, existing studies and the results of our experiment show
that these systems are highly effective at removing hydrophobic compounds. They can
achieve a 90% to 100% reduction in the input load.
As noted above, sorption is the main kinetic process during stormwater infiltration,
which depends on the duration of contact between the medium and the pollutant, i.e., the
infiltration rate. Hydraulic conductivity (infiltration rate) and filter media properties are
the main rain garden design configurations that need to be considered in the design. High
Water 2024,16, 1802 14 of 29
infiltration can lead to increased hydraulic performance of the system, but at the same time,
it can negatively affect pollutant removal efficiency.
In our experimental study, soil mixtures representing typical soils found in most of
Ukraine (sandy loam and sandy loam soils) demonstrated a 100% efficiency in removing
petroleum hydrocarbons. However, the relationship between the infiltration rate of other
soil types (e.g., loams and clay soils) and their abilities to remove pollutants requires further
investigation. This is necessary to obtain a more accurate understanding and improve the
bioremediation process aimed at cleaning pollutants from the environment [76].
3.2. Analysis of Soil Media
The chromatographic profiles of petroleum hydrocarbons in soil media were inves-
tigated in experimental columns II and V to study the ability of soil and sand to retain
and/or remove PHs from rainwater in space and time, as well as the impact of long-term
accumulation of pollutants.
The chromatograms of samples of extracts from the sand (Figure 5a) and soil layers
(Figure 5b) of experimental column II, which was exposed to UEO irrigation for 6 months
(22 weeks) of the experiment, were obtained. For each peak on the chromatogram, the
corresponding UV-vis spectra were obtained (Figures A3 and A4).
Water 2024, 16, x FOR PEER REVIEW 14 of 29
In our experimental study, soil mixtures representing typical soils found in most of
Ukraine (sandy loam and sandy loam soils) demonstrated a 100% efficiency in removing
petroleum hydrocarbons. However, the relationship between the infiltration rate of other
soil types (e.g., loams and clay soils) and their abilities to remove pollutants requires fur-
ther investigation. This is necessary to obtain a more accurate understanding and improve
the bioremediation process aimed at cleaning pollutants from the environment [76].
3.2. Analysis of Soil Media
The chromatographic profiles of petroleum hydrocarbons in soil media were investi-
gated in experimental columns II and V to study the ability of soil and sand to retain
and/or remove PHs from rainwater in space and time, as well as the impact of long-term
accumulation of pollutants.
The chromatograms of samples of extracts from the sand (Figure 5a) and soil layers
(Figure 5b) of experimental column II, which was exposed to UEO irrigation for 6 months
(22 weeks) of the experiment, were obtained. For each peak on the chromatogram, the
corresponding UV-vis spectra were obtained (Figures A3 and A4).
Figure 5. Chromatogram of extracts from the sand (a) and soil layers (b) of cylinder II (UEO irriga-
tion).
The UV-vis spectra show that the peaks in the chromatogram of the sand layer ex-
tracts (Figure A3), obtained by scanning in the wavelength range from 200 to 400 nm, usu-
ally appear between 12 and 18 min. All the spectra have a large peak at 210–230 nm and a
weak peak at 250–270 nm, which corresponds to the two maximum UV absorption levels
for PHs.
According to the UV-vis spectra (Figure A4), the peaks in the chromatogram of the
soil extract obtained by scanning in the wavelength range from 200 to 400 nm are observed
between 4 and 18 min. The spectra have maximum peaks at 210–220 nm and weak peaks
at 300–320 nm, indicating that most of the extracted petroleum hydrocarbon compounds
tend to interact with the mobile phase.
A comparison of the results of chromatographic analysis of the sand and soil layers
of experimental column II showed that approximately 95% of the UEO substances re-
mained in the soil layer and only 5% reached the sand layer. The UV-vis spectra of the
peaks in the chromatograms of the sand and soil layers differ significantly from the UV-
vis spectra of the peaks in the chromatogram of the original UEO. This indicates that the
oil components underwent a series of chemical transformations after entering the soil. The
increase in absorbance in the wavelength range of 250–300 nm is due to the formation of
new conjugated systems, possibly aromatic. The chemical transformations of the compo-
nents also led to an increase in their hydrophobicity, which was confirmed by higher re-
tention times.
Figure 6 shows the chromatograms of samples of extracts from the sand (a) and soil
layers (b) of experimental column V, which was watered with DF. The corresponding UV-
vis spectrum was obtained for each peak on the chromatogram (Figures A5 and A6).
Figure 5. Chromatogram of extracts from the sand (a) and soil layers (b) of cylinder II (UEO irrigation).
The UV-vis spectra show that the peaks in the chromatogram of the sand layer extracts
(Figure A3), obtained by scanning in the wavelength range from 200 to 400 nm, usually
appear between 12 and 18 min. All the spectra have a large peak at 210–230 nm and a weak
peak at 250–270 nm, which corresponds to the two maximum UV absorption levels for PHs.
According to the UV-vis spectra (Figure A4), the peaks in the chromatogram of the
soil extract obtained by scanning in the wavelength range from 200 to 400 nm are observed
between 4 and 18 min. The spectra have maximum peaks at 210–220 nm and weak peaks at
300–320 nm, indicating that most of the extracted petroleum hydrocarbon compounds tend
to interact with the mobile phase.
A comparison of the results of chromatographic analysis of the sand and soil layers of
experimental column II showed that approximately 95% of the UEO substances remained
in the soil layer and only 5% reached the sand layer. The UV-vis spectra of the peaks in the
chromatograms of the sand and soil layers differ significantly from the UV-vis spectra of
the peaks in the chromatogram of the original UEO. This indicates that the oil components
underwent a series of chemical transformations after entering the soil. The increase in ab-
sorbance in the wavelength range of 250–300 nm is due to the formation of new conjugated
systems, possibly aromatic. The chemical transformations of the components also led to an
increase in their hydrophobicity, which was confirmed by higher retention times.
Figure 6shows the chromatograms of samples of extracts from the sand (a) and soil
layers (b) of experimental column V, which was watered with DF. The corresponding
UV-vis spectrum was obtained for each peak on the chromatogram (Figures A5 and A6).
Water 2024,16, 1802 15 of 29
Water 2024, 16, x FOR PEER REVIEW 15 of 29
Figure 6. Chromatogram of an extract from the sand (a) and soil layers (b) of cylinder V (DF irriga-
tion).
The UV-vis spectra (Figure A5) show that the peaks in the chromatogram of the sand
layer extracts obtained by scanning in the wavelength range from 200 to 400 nm usually
appear between 12 and 13 min. In total, two spectra were detected with maximum peaks
at 200–210 nm and minimum peaks at 260–320 nm, which correspond to the two maxi-
mum UV absorption levels for the PHs.
According to the UV-vis spectra (Figure A6), the peaks in the chromatogram of the
soil extract obtained by scanning in the wavelength range from 200 to 400 nm are observed
between 13 and 18 min. The spectra have maximum peaks at 210–240 nm and weak peaks
at 270–300 nm.
The total peak areas in the chromatograms of the sand and soil samples in experi-
mental columns II and V are shown in Table 4. The results of chromatographic analysis
showed that almost all DF components were absorbed by 95% in the upper soil layer.
According to the UV-vis spectra, it can be concluded that the DF components underwent
a chemical transformation in the soil, which led to the appearance of an absorption band
with a maximum around 225 nm. This can be explained by the formation of conjugated
double-bond systems, which caused changes in the UV-vis spectra. In addition, there was
an increase in peak retention time, which may be due to the formation of larger molecules
from the original DF components. Similar to the chromatographic analysis of the original
DF, four components with more than 50% of the total were observed, but all of them dif-
fered in their UV spectra and retention times.
Table 4. Total peak areas in the chromatograms of sand and soil samples in experimental columns
II and V.
No. Sampling Date Cylinder Number Layer Total Peak Area
1 13 January 2024 II soil 10,464
2 13 January 2024 II sand 586
3 13 January 2024 V soil 100,037
4 13 April 2024 V sand 553
As can be seen from the results of the experimental study, the retention of most (95%)
of the model petroleum hydrocarbons occurs in the surface layer of the soil medium for
planted plants due to the sorption process. During the experimental study, the DF and
UEO components introduced into the soil environment underwent a biochemical trans-
formation. This was confirmed by changes in UV-visible spectra. Oxidation processes may
be responsible for the formation of oxygen-containing functional groups, such as hy-
droxyl, carbonyl, epoxy, and carboxyl groups, as well as for the possible reduction of the
carbon skeleton. However, the retention time of the new substances increased compared
to the original components, indicating the absence of polar groups and an increase in mo-
lecular size. As a rule, the increase in the size of the molecules of the PHs leads to simul-
taneous increases in hydrophobicity, electrochemical stability, high sorption capacity, and
stability in the soil.
Figure 6. Chromatogram of an extract from the sand (a) and soil layers (b) of cylinder V (DF
irrigation).
The UV-vis spectra (Figure A5) show that the peaks in the chromatogram of the sand
layer extracts obtained by scanning in the wavelength range from 200 to 400 nm usually
appear between 12 and 13 min. In total, two spectra were detected with maximum peaks at
200–210 nm and minimum peaks at 260–320 nm, which correspond to the two maximum
UV absorption levels for the PHs.
According to the UV-vis spectra (Figure A6), the peaks in the chromatogram of the
soil extract obtained by scanning in the wavelength range from 200 to 400 nm are observed
between 13 and 18 min. The spectra have maximum peaks at 210–240 nm and weak peaks
at 270–300 nm.
The total peak areas in the chromatograms of the sand and soil samples in experimental
columns II and V are shown in Table 4. The results of chromatographic analysis showed
that almost all DF components were absorbed by 95% in the upper soil layer. According
to the UV-vis spectra, it can be concluded that the DF components underwent a chemical
transformation in the soil, which led to the appearance of an absorption band with a
maximum around 225 nm. This can be explained by the formation of conjugated double-
bond systems, which caused changes in the UV-vis spectra. In addition, there was an
increase in peak retention time, which may be due to the formation of larger molecules
from the original DF components. Similar to the chromatographic analysis of the original
DF, four components with more than 50% of the total were observed, but all of them
differed in their UV spectra and retention times.
Table 4. Total peak areas in the chromatograms of sand and soil samples in experimental columns II
and V.
No. Sampling Date Cylinder Number Layer Total Peak Area
1 13 January 2024 II soil 10,464
2 13 January 2024 II sand 586
3 13 January 2024 V soil 100,037
4 13 April 2024 V sand 553
As can be seen from the results of the experimental study, the retention of most (95%)
of the model petroleum hydrocarbons occurs in the surface layer of the soil medium
for planted plants due to the sorption process. During the experimental study, the DF
and UEO components introduced into the soil environment underwent a biochemical
transformation. This was confirmed by changes in UV-visible spectra. Oxidation processes
may be responsible for the formation of oxygen-containing functional groups, such as
hydroxyl, carbonyl, epoxy, and carboxyl groups, as well as for the possible reduction of the
carbon skeleton. However, the retention time of the new substances increased compared
to the original components, indicating the absence of polar groups and an increase in
molecular size. As a rule, the increase in the size of the molecules of the PHs leads to
Water 2024,16, 1802 16 of 29
simultaneous increases in hydrophobicity, electrochemical stability, high sorption capacity,
and stability in the soil.
The results obtained correlate with the conclusions drawn in [
77
]. Three laboratory-
scale columns were packed with soil. Activated carbon (0.5% by weight) was added to two
columns. For 28 days, synthetically modelled stormwater saturated with petroleum hydro-
carbons was passed through the column layers. The desorbed amounts of contaminants
from the soils were determined by gas chromatography and mass spectrometry, which
showed that the contaminants were strongly sorbed in the upper soil layer to a depth of
about a centimetre.
3.3. Changes in Hydraulic Conductivity
The hydrological processes in a rain garden design include surface infiltration, percola-
tion through the soil medium, and drainage through the gravel layer. Surface infiltration is
the key process in these systems, as it determines the rate at which stormwater can reach the
underlying layers for infiltration and drainage. The rate of surface infiltration is determined
by the saturated hydraulic conductivity of the soil media, the height of the water column at
the soil surface, and the moisture content of the soil. In practice, the saturated hydraulic
conductivity is usually used to control the infiltration capacity of rain gardens. However,
over time, the deposition of pollutants, which are transported within the system by water
flows, can cause clogging and changes in saturated hydraulic conductivity. In long-term
studies, the change in the saturated hydraulic conductivity of soil media is used as an
indicator of clogging development.
The effect of fouling on the efficiency of PH removal by the experimental columns was
not specifically investigated in this work. However, during the experimental study, which
lasted 22 weeks, a change in hydraulic conductivity
k
(mm/h) was detected over time,
especially for the experimental columns that were subjected to irrigation with used engine
oil (Table 5). This indicates a clogging of the experimental rain gardens, which manifested
itself in the delayed infiltration of water inside the columns.
Table 5. The average value of hydraulic conductivity
k
(mm/h) of the experimental columns after 10
and 22 weeks of their operation under different conditions.
Number of Experimental
Columns (Presence of
Vegetation/Type of
Model PH)
Value of kafter 10 Weeks,
mm/h
Percentage of Decrease
in kafter 10 Weeks, %
Value of kafter 22 Weeks,
mm/h
Percentage of Decrease in
kafter 22 Weeks, %
I and II
(with vegetation/UEO) 137 26 47 75
III and IV
(with vegetation/without
irrigation with PHs)
180 2.7 157 15.1
V and VI
(with vegetation/DF) 163 12 112 40
VII
(without vegetation/UEO) 124 33 42 78
VIII
(without vegetation/DF) 158 15 98 47
The value of hydraulic conductivity for all experimental columns at the beginning
of the experiment was 185 mm/h. After 10 weeks of research (20 irrigation cycles), the
k
value decreased by 26 and 12% for columns I, II, V, and VI with vegetation and the
corresponding type of PHs. For columns without vegetation, VII and VIII, the decrease in
k
was 33 and 15%, respectively. As can be seen from the results in Table 5, the hydraulic
conductivity decreased with time for all configurations of the experimental columns (with
and without vegetation). For the systems with vegetation (I, II, V, and VI), the hydraulic
conductivity was higher, although not significantly, but remained below the initial value of
Water 2024,16, 1802 17 of 29
185 mm/h. By the end of the experiment (22 weeks and 62 irrigation cycles), the k value
had significantly decreased for columns I, II, and VII, which were irrigated with UEO, in
contrast to columns V, VI, and VIII, which were irrigated with DF. Moreover, the percentage
of reduction in
k
depending on the presence of plants did not differ significantly, since at
this stage, the development of the outer part of the plant and its root system was already
inhibited. This result is similar to the results of Hatt et al. [
78
], who showed a decrease in
the hydrological conductivity of the system after 40 weeks of operation.
The results obtained can be explained by the ability of UEO, unlike DF, to change the
hydrophilic properties of the air-dispersed soil medium to hydrophobic ones. Used engine
oil contains alkyl sulfonates, which can change the interfacial properties of the soil. When
water penetrates the oil-filled soil pores, it does not wet the mineral particles and does
not displace the oil, as is required by physical laws [
79
]. Thus, water seepage through the
UEO adsorbed on hydrophobic mineral surfaces is slower, which leads to a decrease in the
hydraulic performance of the system as a whole.
The change in hydraulic conductivity of experimental columns III and IV, which were
planted with vegetation and were not subjected to watering with any of the model PHs,
but only with tap water, should be separately justified. This allows us to draw a conclusion
and compare it with the results available in the literature regarding the change in the
hydrological parameters of the system during its operation in the absence of the pollutant
factor. As can be seen from the results presented in Table 5, the percentage of reduction
in k for columns III and IV after 10 and 22 weeks was 2.7 and 15.1%, respectively. That
is, the modelled flow in the columns showed a slight decrease in k values at the end of
the experiment, which correlates with the results obtained in studies [
80
,
81
]. Rain garden
systems «clog up» over time and the hydraulic conductivity decreases by an average of
3.6 times during 72 weeks of testing due to the top layer. Other authors [
82
] studied
an infiltration basin built on sandy loam soils. They found that hydraulic conductivity
increased from 20% to 40% (of its original value) after replacing the top 5 cm of soil.
Removal of 15 cm of soil was required to restore the hydraulic conductivity of the system
to its original value (68%). High concentrations of contaminants, especially of petroleum
origin, in the filter material can pose a risk to humans or wildlife through acute or chronic
toxicity [80].
The results of some studies of hydrological parameters in the field differ significantly
from laboratory experiments. From a hydrological point of view, rain garden systems
function well in real conditions over time, based on the results of a study of 22 non-novel
rain garden designs in Ontario that had been in operation for up to 10 years [
83
]. The hy-
draulic conductivity of 20/22 systems was 25 mm/h, which is the recommended minimum
according to local standards. Similar values have been observed in other studies [
84
,
85
].
For example, in North Carolina, 98% of the studied designs had medium to high permeabil-
ity [
85
]. Additionally, studies with rain gardens aged 10–22 years showed that hydraulic
conductivity values in most systems exceeded local minimum recommendations [84].
A comparison of the results obtained in the field and laboratory shows uncertainty
about whether hydraulic conductivity improves or deteriorates with time and age of rain
garden structures if no contamination factors are present. Laboratory experiments are
typically conducted over short time scales, such as weeks or months, and do not reproduce
the same dry periods between wet periods that are typical of field systems. Modelling
experiments do not allow sufficient time for slow biological, soil formation, or flow path
formation processes to become apparent and possibly affect the ability of systems to
maintain infiltration rates. Furthermore, hydraulic conductivity is not only a function of
the permeability of the soil media in rain gardens but also of the density and viscosity of
the water. Therefore, as the temperature decreases,
k
will decrease [
86
]. The relationship
between water permeability and hydraulic conductivity
k
, together with the tabulated
values of water density and viscosity at different temperatures, suggest that the value of
k
measured at 22.5
◦
C will be reduced by 25% at 12
◦
C and by another 50% at 0
◦
C. Therefore,
kvalues in the field can be much lower than those measured at room temperature.
Water 2024,16, 1802 18 of 29
3.4. Plant Resistance
All plant samples survived in the control (C) and DF- and UEO-contaminated soil
throughout the study period (22 weeks). However, not all plant samples grew equally,
demonstrating different sensitivities to a particular type of pollutant, which led to signifi-
cant differences in growth rates (Figure 7, Table 6).
Water 2024, 16, x FOR PEER REVIEW 18 of 29
3.4. Plant Resistance
All plant samples survived in the control (C) and DF-