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Citation: Hasan, M.S.; Trapp, J.; Geza,
M. Improvement of Onsite
Wastewater Systems Performance:
Experimental and Numerical
Investigation. Clean Technol. 2022,4,
824–840. https://doi.org/10.3390/
cleantechnol4030051
Academic Editor: Bin Gao
Received: 29 May 2022
Accepted: 9 August 2022
Published: 24 August 2022
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clean
technologies
Article
Improvement of Onsite Wastewater Systems Performance:
Experimental and Numerical Investigation
Md Sazadul Hasan , Joshua Trapp and Mengistu Geza *
Department of Civil and Environmental Engineering, South Dakota School of Mines and Technology,
501 E St. Joseph St., Rapid City, SD 57701, USA
*Correspondence: stu.geza@sdsmt.edu; Tel.: +1-720-982-5359
Abstract:
Population growth and the associated increase in the use of Onsite Wastewater Treatment
Systems (OWTS) in the Black Hills have been a reason for interest in nitrate contamination within the
public water supply over the past few years. The main concern for the Black Hills is the presence
of karst formation that all OWTS for wastewater travel faster, limiting the natural attenuation of
wastewater contaminants. The treatment performance of common soils in the Black Hills and wood-
based media was evaluated using soil column experiments and a numerical model, HYDRUS 2D.
Nitrate treatment performances were evaluated using alluvial and cedar soils collected from the
Black Hills, sand, woodchips (loose and dense), and biochar. This research investigated hydraulic
and reaction parameters through a combination of experimental and inverse modeling approaches.
A good agreement was obtained between the measured and model-predicted soil moisture content,
with R
2
values ranging from 0.57 to 0.99. The model was calibrated using flow data and nitrate
concentration data measured from leachate collected at the bottom of the experimental columns.
Nitrate removal rates varied from 32.3% to 70%, with the highest removal rate in loose woodchips,
followed by dense woodchip and biochar, and the lowest removal rate in alluvial materials. The
biochar and loose woodchips removed an additional 20% compared to common soils, attributable
to the enhanced denitrification rate due to higher water content and organic content. The use of
woodchips and biochar should be implemented in OWTS, where there are known karst formations.
Keywords: on-site treatment system; biochar; woodchips; nitrate removal; contaminant transport
1. Introduction
Wastewater management throughout the U.S. incorporates a variety of centralized
and decentralized approaches for the protection of public health and the environment [
1
].
Nearly 21% of the US population is served by decentralized wastewater systems, with a
substantial portion of all new development being supported by these systems [
2
]. Onsite
wastewater treatment systems (OWTS) have become a popular form of dealing with
household wastewater in rural and suburban homes. The average home produces about
180 gallons of wastewater per week. The wastewater containing several pollutants is
collected in a septic tank, dispersed onto a leach field, and eventually ends up in the surface
or groundwater. These contaminants will naturally be treated while flowing through the
soil [
3
]. While OWTS vary widely in their design and implementation, conventional OWTS
rely on septic tanks for retention and digestion of solids in raw wastewater, followed
by discharge of wastewater effluent to the soil treatment unit for eventual recharge to
underlying groundwater [4–6].
In conventional systems, where local conditions permit, septic tank effluent (or higher-
quality effluent if additional treatment is employed) may still contain high concentrations of
pollutants that are further treated by discharging the effluent to the soil treatment units [
7
].
A soil treatment unit may be comprised of a series of subsurface trenches or beds for
infiltration and percolation through an underlying unsaturated zone (vadose zone) with
Clean Technol. 2022,4, 824–840. https://doi.org/10.3390/cleantechnol4030051 https://www.mdpi.com/journal/cleantechnol
Clean Technol. 2022,4825
ultimate recharge to groundwater [
8
]. An unsaturated flow regime may result in longer
travel times and more extensive contact between the percolating effluent and the soil [
9
,
10
].
In an unsaturated system, water is retained first in the finer pore spaces adjacent to soil
grains and not in large pores. An understanding of flow, transport, and chemical reactions
in unsaturated soil is very important for the optimal design of OWTS and for predicting
the performance of a soil treatment unit [11].
Traditionally, OWTS design and regulation have been based primarily on ensuring
that wastewater can be successfully infiltrated into the soil, preventing the backup of the
effluent to the soil surface or into the associated dwelling or business [
12
]. However, this
approach does not consider potential nutrient or pollutant treatment and mass loading to a
receiving environment (soil, groundwater, surface water, including stormwater) in specific
areas (single lot, subdivision, watershed) [
13
]. Problems are typically highlighted only
after a gross failure is observed (e.g., surfacing effluent, detection of bacteria, nutrients,
or other pollutants in nearby drinking water wells or surface waters) [
14
,
15
]. In both
low- and high-density development scenarios, OWTS should be required to achieve a
specified treatment performance, with the assurance that the performance objectives can be
reliably met.
The risk of nitrate contamination in humans includes vomiting, diarrhea, abdominal
pain, cancer, thyroid disease, birth defects, and blue baby syndrome [
16
]. The purpose
of implementing OWTS is to remove common contaminants from wastewater before
entering ecosystems [
17
]. The most common contaminant is nitrogen in the form of
ammonia/nitrate/nitrous gas. The main processes for removing nitrogen are mineraliza-
tion, nitrification, and denitrification [
18
]. A previous study found that once wastewater
reaches the soil, the main form of nitrogen is nitrate [
19
]. Nitrate is an anion repelled by
negatively charged soil particles [
20
]. The carbon-based media was an electron donor with
which the negatively charged nitrate particles could react. The need for future studies was
to study the specific effects of different carbon-based media on nitrogen treatment.
The use of OWTS in South Dakota (SD) has been on the rise over the last few years.
Currently, 27% of SD homeowners rely on OWTS; this number is estimated to be on the
rise, as it is estimated that 30–35% of new homes will be using OWTS [
21
,
22
]. OWTS can be
an excellent option for dealing with wastewater when living in a country or suburban area
where there are no conventional sewer systems. OWTS can be implemented on a site if the
native soil in the area can leach out the waste and remove the contaminants that come with it.
Nitrate is the most common groundwater contaminant across the country [
23
]. It originally
came just from the natural processes of decomposition of organic matter and agriculture,
contaminating both surface water and groundwater. The contribution from anthropogenic
sources increases with time. The risk of groundwater contamination will increase as more
and more OWTS are installed. The Black Hills hydrogeology is composed of alluvial
deposits as well as karst limestones (including the Madison aquifer) [
24
]. These formations
allow water to move freely through previous soils or underground flow paths. Previous
investigations of monitoring well observations have indicated concerns about groundwater
contamination in karst limestone and shallow alluvial aquifers in the
Black Hills [25].
In the
Black Hills, there have been several documented cases of OWTS polluting groundwater and
nearby wells. Contamination was found to be the result of cracks within geology, allowing
contaminants to travel faster and farther than they could travel in natural soils [
26
]. This
has caused concerns about how OWTS are to be installed and what treatments are to be
used in the leach field to prevent future problems.
This research aimed to determine the treatment performance of new treatment media,
such as wood chips and biochar, relative to the native soils in the Black Hills. This study
conducted numerical modeling for the parameterization of hydraulic and solute reaction
processes based on small-scale laboratory tests. Important hydraulic and water quality
coefficients/parameters such as residual water content (
θr
), saturated water content (
θs
),
bubbling pressure (
α
), pore size distribution index (
n
), and first-order reaction rate were
estimated using inverse modeling in the absence of measured data. The effects of various
Clean Technol. 2022,4826
scenarios of loading rate and effluent quality on effluent concentration were evaluated. This
research includes both experimental and numerical investigations using
HYDRUS 2D,
a
numerical model for unsaturated flow and contaminant transport with an inverse modeling
feature to allow for the determination of hydraulic and reaction parameters. It was hypoth-
esized that the presence of organic carbon and high-water holding capacity in geomedia,
such as biochar and woodchips, relative to local soils would improve nitrate removal
efficiency through enhanced denitrification.
2. Materials and Methods
2.1. Experimental Setup
Six different treatment media combinations were used in the experiment, as shown
in Figure 1. The treatment media included sand, native alluvium, native cedar canyon,
dense woodchips, loose woodchips, and biochar. The media were compacted to the bulk
densities presented in Table S1 in the Supplementary File. The sand column was used
as a control. Two of the columns represent native soils of the Black Hills, including an
alluvial soil collected just upstream of Canyon Lake along rapid creek. The second soil
was a cedar soil collected from a cedar canyon and is classified as a silty sand (80% sand
20% silt) by a web soil survey. Duplicate columns were used for each media type. Other
geomedia, namely loose woodchips, compacted woodchips, and biochar, were placed as
a layer between the cedar canyon soil layers. The sand was sieved using 40–50 mesh.
The biochar was obtained from Biochar Now, LLC. The native soils were collected from
sites on the west side of Rapid City above Canyon Lake. A clear acrylic pipe was used
to build the 12 soil columns. The bottom of the columns was capped with 6 in quick
caps
(FERNCO Quick Cap)
with
1/2holes
drilled in the center and sealed with porous filter
material to prevent sands from escaping the column during the experiment. A PVC pipe
was used at the bottom of the cap to collect the outflow. The columns were 60 cm long
and 15 cm in diameter, with a single outlet located at the bottom of the column where the
nitrate samples were collected.
Clean Technol. 2022, 4, FOR PEER REVIEW 3
rate were estimated using inverse modeling in the absence of measured data. The effects
of various scenarios of loading rate and effluent quality on effluent concentration were
evaluated. This research includes both experimental and numerical investigations using
HYDRUS 2D, a numerical model for unsaturated flow and contaminant transport with an
inverse modeling feature to allow for the determination of hydraulic and reaction param-
eters. It was hypothesized that the presence of organic carbon and high-water holding
capacity in geomedia, such as biochar and woodchips, relative to local soils would im-
prove nitrate removal efficiency through enhanced denitrification.
2. Materials and Methods
2.1. Experimental Setup
Six different treatment media combinations were used in the experiment, as shown
in Figure 1. The treatment media included sand, native alluvium, native cedar canyon,
dense woodchips, loose woodchips, and biochar. The media were compacted to the bulk
densities presented in Table S1 in the Supplementary File. The sand column was used as
a control. Two of the columns represent native soils of the Black Hills, including an allu-
vial soil collected just upstream of Canyon Lake along rapid creek. The second soil was a
cedar soil collected from a cedar canyon and is classified as a silty sand (80% sand 20%
silt) by a web soil survey. Duplicate columns were used for each media type. Other geo-
media, namely loose woodchips, compacted woodchips, and biochar, were placed as a
layer between the cedar canyon soil layers. The sand was sieved using 40–50 mesh. The
biochar was obtained from Biochar Now, LLC. The native soils were collected from sites
on the west side of Rapid City above Canyon Lake. A clear acrylic pipe was used to build
the 12 soil columns. The bottom of the columns was capped with 6 in quick caps (FERNCO
Quick Cap) with ½” holes drilled in the center and sealed with porous filter material to
prevent sands from escaping the column during the experiment. A PVC pipe was used at
the bottom of the cap to collect the outflow. The columns were 60 cm long and 15 cm in
diameter, with a single outlet located at the bottom of the column where the nitrate sam-
ples were collected.
Figure 1. Experimental Column Setup.
Wastewater effluent collected from a primary clarifier at the Rapid City Wastewater
Treatment plant was applied to the columns at a constant rate of 2 cm/day using a 12-
channel peristaltic pump (Golander, BT100S-1, Pump head DG10-12). The flow was
drained into beakers to collect samples for nitrate concentration measurement. Soil
Figure 1. Experimental Column Setup.
Wastewater effluent collected from a primary clarifier at the Rapid City Wastewa-
ter Treatment plant was applied to the columns at a constant rate of 2 cm/day using a
12-channel
peristaltic pump (Golander, BT100S-1, Pump head DG10-12). The flow was
drained into beakers to collect samples for nitrate concentration measurement. Soil mois-
ture sensors were placed at the mid-point of the column as well as the mid-point point of
the bottom third layer. Water content data were collected hourly, while the nitrate concen-
tration was measured daily using an HACH meter (DR 2400) by the NitraVer
®
5 cadmium
Clean Technol. 2022,4827
reduction method. The columns were allowed to run for 15 months (10/2019–1/2021).
Hydraulic loading is described in Section S1 in the Supplementary File. All lab experiments
were conducted in the Civil and Environmental Engineering Lab at South Dakota Mines.
2.2. Numerical Modeling
HYDRUS 2D [
27
] was used to simulate the long-term (steady-state) vertical flow and
soil moisture distribution in the experimental columns described above. HYDRUS 2D
is a software package for simulating water, solute, and heat movement in two- or three-
dimensional variably saturated porous media. HYDRUS 2D has been used by several re-
searchers to model water movement and pollutant transport in unsaturated
zones [28–30].
The program produces a finite element model utilizing Richards’ equation for unsatu-
rated/saturated flow, with the Fickian-based convection dispersion equation for solute
transport. Both are solved using the Galerkin finite element method. For hydraulic trans-
port, Richards’ equation is coupled with the Van Genuchten equation to simulate water
movement. The solute transport equations consider convection–dispersion transport in
the liquid phase and diffusion in the gaseous phase. Within the transport equations, there
is an option for zero-order, first-order, and second-order reactions. The software program
can be used to analyze the movement of water and solutes through variably saturated
porous media.
2.2.1. Subsubsection
The governing equation for variably saturated flow in HYDRUS 2D is Richards’
equation. The Richards equation is derived based on Darcy’s law and the conservation of
mass. The two-dimensional form of Richards’ equation (Equation (1)) is shown below.
δθ
δt=δ
δxi0"K KA
ij
δh
δxj
+KA
ij !#−S(1)
where,
θ
is the volumetric water content (L
3
/L
3
); his the pressure head (L); Sis a sink
term (T
−1
); x
i
is the spatial coordinates (L); tis time (T);
KA
ij
are components of a dimension-
less anisotropy tensor K
A
;K(h) is a function of water content,
θ
.K(h) is the unsaturated
hydraulic conductivity function (LT−1), which is given by the Equation (2):
K(h,x,y)=Ks(x,y)Kr(h,x,y)(2)
where, K
r
is the relative hydraulic conductivity dependent on soil moisture (LT
−1
) given by
Equation (3):
Kr(h) = KsSl
eh1−1−S1/m
emi2(3)
where, K
s
is the saturated hydraulic conductivity (LT
−1
); nis the pore size distribution
index; mis a dimensionless parameter expressed as
m=
1
−1
n
;lis the pore connectivity
parameter; S
e
is the effective saturation given as
Se=θ(h)−θr
θs−θr
;
θr
is the residual water
content (L3/L3); θsis the saturated water content (L3/L3).
Richard’s equation has too many unknowns: K
ij
,
θ
, and
ψ
. Additional equations
are needed to solve the equation. Thus, other hydraulic relationships must be used to
help solve Richards’ equation. The Van Genuchten relation Equations (4)–(6) are used to
relate the suction head and water content, while the flux equation relates the hydraulic
conductivity and suction head.
θ(h) = θr+θs−θr
1+|αh|nmwhen h <0 (4)
θ(h) = θswhen h >0 (5)
m=1−1
n(6)
Clean Technol. 2022,4828
where,
θr
is the residual water content (L
3
/L
3
);
θs
is the saturated water content (L
3
/L
3
);
α
is
the inverse of the air-entry value (bubbling pressure) (cm
−1
); nis a pore size
distribution index.
q(z) = Kδh
δxi
+1(7)
where qis the flux (L
2
/t); Kis the hydraulic conductivity (L/t); his the suction head (L);
xiis the spatial coordinates (L).
For water movement in the unsaturated zone, HYDRUS 2D numerically solves
Richards’ equation using the Galerkin finite element method. The parameters
α
and nare of-
ten considered to be simply empirical coefficients that affect the shape of
hydraulic functions.
2.2.2. Governing Equations for Solute Transport
The first-order reaction approach was used as the governing equation for transport.
A first-order reaction was used to represent the loss of nitrate through the denitrification
process into nitrogen gas. The denitrification reaction was assumed to be conducted entirely
through the liquid state.
δθc1
δt=δ
δxi θDw
ij,1
δc1
δxj!−δqic1
δxi
−Scr,1 −µ0w,1θc1(8)
where cis the liquid concentration (ML
−3
);
θ
is the volumetric water content (cm
3
/cm
3
);
q
i
is the i-th component of the volumetric flux density (LT
−1
);
µ0w
is the first-order rate
constant providing connections to individual chain species; Sis the sink term; c
r
is the
concentration of the sink term; Dijwis the dispersion coefficient tensor (L2T−1).
The second governing equation deals with solute transport; the key aspects working
here are diffusion and dispersion due to the tortuosity of the soil.
θDw
ij =Dr|q|δij +(DL−DT)qjqi
|q|+θDwτwδw(9)
where, D
w
is the molecular diffusion coefficient in free water (L
2
T
−1
);
τw
is the tortuosity
factor in the liquid phase; |q| is the absolute value of the Darcian flux
density (LT−1);
δij
is the Kronecker delta function (
δij
= 1 if I=j, and
δij
= 0 if i
6=
j); D
L
is the lon-
gitudinal dispersive (L); D
T
is the transverse dispersive (L);
θ
is the volumetric water
content (cm3/cm3).
It is well recognized that soil water content expressed as water-filled pore space (WFPS)
is a major controlling factor, and nitrification is a source of N
2
O until WFPS values reach
about 70% [
31
], after which denitrification dominates the water content dependence of
degradation coefficients is implemented using the modified equation of Walker [32]:
µ(θ) = µr(θr)min"1, θ
θrβ#(10)
where,
µr
is the first-order reaction rate constant at the reference water content (
θr
);
µ
is the
first-order reaction rate constant at the actual water content (
θ
);
β
is a solute-dependent
parameter (0.7 for nitrate).
The implementation of Walker’s equation suggests increased removal with increasing
water content.
2.2.3. Model Setup
The HYDRUS 2D model was set up to match the experimental columns as closely as
possible. Observation nodes in HYDRUS 2D were placed at locations corresponding to the
experimental water content measurement points in the column. The finite element mesh
for the HYDRUS 2D setup is shown in Figure S1 in the Supplementary File. The mesh size
and distribution of nodes were chosen to result in a numerical solution that converged and
Clean Technol. 2022,4829
maintained a small error in water balance. The initial pressure head distribution was set
such that the soil profile was hydrostatic with a pressure head of
−
100 cm at the bottom
boundary. Because our analyses were based on steady-state flow conditions, the short-term
transient initial conditions were not expected to influence the results.
For the boundary condition, wastewater was applied at 2 cm/day. A seepage face
boundary condition was used for the bottom boundary. This type of boundary condition is
often applied to laboratory soil columns when the base of the soil column is exposed to
the atmosphere (gravity drainage of a finite soil column). The condition assumes that the
boundary flux will remain zero as long as the pressure head is negative. However, when
the lower end of the soil profile becomes saturated, a zero-pressure head is imposed at the
lower boundary, and the outflow is calculated accordingly [
33
]. This saturated boundary
condition is consistent with observations from actual experiments [9].
2.2.4. Parameter Sensitivity Analysis
A manual sensitivity analysis was performed to assess how each of the water flow
parameters and reaction rates influenced the effluent nitrate concentration. The calibrated
values served as a starting point to increase and decrease each of the parameter values by
25% and to determine the change in nitrate concentration. Three homogeneous columns
were used, including the sand column, a full loose woodchip column, and a full biochar
column, for the analysis.
2.3. Scenario Analysis
The calibrated models for both hydraulics and nitrate transport were used to conduct a
scenario analysis to answer several “what if” questions, including higher flow rates, higher
influent concentrations, and a combination of increased flow and concentrations. Lastly,
the effect of increasing the treatment depth was assessed. Increasing the treatment depth
allowed us to evaluate the effect of depth on groundwater or compare shallow aquifers
versus deep aquifers. The analysis was conducted for the media with the best nitrate
treatment performance (loosely compacted woodchips) and sand as a control.
3. Results and Discussion
Both experimental and modeling approaches were used to determine hydraulic and
solute transport parameters. When possible, the parameters were determined using an
experimental approach. The parameters that could not be determined through experimental
approaches were determined using an inverse modeling approach. Table 1shows the
methods used to determine the hydraulic parameters for each soil medium.
Table 1. Methods used to determine parameter values.
Parameter Sand Alluvial Cedar
Canyon
Dense
Woodchips
Loose
Woodchips Biochar Mixed
θr
(cm
3
/cm
3)
Study by
Hasan et al. [13]
Inverse
modeling Inverse
Modeling Study by
Ghane et al. [34]Study by
Ghane et al. [34]
Study by
Hasan et al. [30]
Homogenous
Cedar
Canyon
θs
(cm
3
/cm
3) Inverse
Modeling Study by R.C.
Heath [35]Saturated Water
Content Test Saturated Water
Content Test
Homogenous
Cedar
Canyon
α
(1/cm)
Soil Moisture
Characteristic
Curve
Inverse
Modeling Inverse
Modeling Inverse
Modeling Inverse
Modeling
n
Soil Moisture
Characteristic
Curve
Inverse
Modeling Inverse
Modeling Inverse
Modeling Inverse
Modeling
Ks
(cm/day) Inverse
Modeling Study by R.C.
Heath [35]Inverse
Modeling Inverse
Modeling Inverse
Modeling
Clean Technol. 2022,4830
3.1. Parameterization of Hydraulic Parameters
HYDRUS 2D has several hydraulic parameters, including the residual water content
(
θr
), saturated water content (
θs
), bubbling pressure (
α
), pore size distribution index (
n
),
saturated hydraulic conductivity (
Ks
), and the pore connectivity parameter (
l
) that influence
water movement and solute transport in the unsaturated zone. For each column, some
of these parameter values were determined using inverse modeling, while others were
determined using laboratory experiments.
Hydraulic parameters were determined using soil characteristic curves and satu-
rated water content by laboratory experiments (described in Sections S2 and S3 in the
Supplementary File), which eventually served as inputs for parameterization/calibration
of the unsaturated zone model. The goal is to specify parameter values to improve the
model prediction of soil moisture and solute transport.
The calibrated hydraulic parameters for each of the soils are shown in Table 2, along
with the corresponding R
2
. This is followed by time series figures for each experimentally
observed water content vs. the modeled water content.
Table 2. Calibrated Hydraulic Parameters.
Parameters C1 C2 C3 C4 C5 C6
Sand Alluvial Cedar Canyon Dense Woodchips Loose Woodchips Biochar Mix
θr
(cm3/cm3)0.002 0.02 0.001 0.21 0.21 0.001 0.001
θs
(cm3/cm3)0.24 0.47 0.34 0.44 0.66 0.64 0.34
α
(cm−1)0.070 0.17 0.16 0.046 0.121 0.00001 0.11
n4.45 1.34 5.97 4.33 4.47 3.07 1.35
Ks
(cm/day) 720 750 689 746 114 554 25
R20.98 0.57 0.57 0.97 0.98 0.99
Based on the parameter values presented in Table 2above, a good agreement was
obtained between the observed and modeled values, with R
2
ranging from 0.567 to 0.996.
The time series of the observed and modeled outputs are shown in Figure 2a–f. The
R
2
values were either very high or roughly 0.6. This was due to the variation from the
experimental data and the fact that the calibrated models were only able to model the
steady-state conditions. Many of the columns reached a steady state and did not deviate
from the mean by more than
±
5%. While the Alluvial and Cedar Canyon soils observed
water contents did not reach steady-state and slowly increased in water content over time.
The HYDRUS 2D graphical display for changes in water content with depth for each
of the calibrated columns is shown in Figure 3.
Clean Technol. 2022,4831
Clean Technol. 2022, 4, FOR PEER REVIEW 8
Figure 2. Calibrated Water Content for (a) Sand, (b) Alluvial, (c) Cedar Canyon, (d) Woodchips
(dense), (e) Woodchips (Loose), and (f) Biochar.
The HYDRUS 2D graphical display for changes in water content with depth for each
of the calibrated columns is shown in Figure 3.
Figure 2.
Calibrated Water Content for (
a
) Sand, (
b
) Alluvial, (
c
) Cedar Canyon, (
d
) Woodchips
(dense), (e) Woodchips (Loose), and (f) Biochar.
Clean Technol. 2022,4832
Clean Technol. 2022, 4, FOR PEER REVIEW 9
Figure 3. Calibrated Water Content HYDRUS Graphical Outputs (a) Sand, (b) Cedar Canyon, (c)
Alluvial, (d) Dense Woodchips, (e) Loose Woodchips, and (f) Biochar.
3.2. Nitrate Parameter Calibration Using Observed Nitrate Concentration
A constant flux of wastewater was applied to the soil columns. The wastewater was
collected from the Rapid City Wastewater Treatment Plant. The wastewater had a known
concentration of 28.0 mg/L of nitrate. The denitrification reaction from nitrate to nitrogen
gas is considered a first-order anaerobic reaction with no sorption [20]. Leachate samples
were collected and compared to the modeled output concentration. Measured nitrate con-
centration data were limited compared to the data used to determine soil hydraulic pa-
rameters. Thus, manual calibration was used. Calibration was performed based on the
average nitrate effluent concentrations. This was compared to the effluent nitrate concen-
tration at a steady state in the model. The first-order reaction rates were adjusted until the
modeled effluent concentration matched the average experimental concentration.
The layered columns include carbon-based media with cedar canyon soil both on the
top and bottom of the column. Each layer is of equal thickness of 16.6 cm. The calibrated
solute parameters from the homogenous cedar canyon column were used for the cedar
canyon layers. The carbon-based layers were then calibrated by changing the middle
layer’s first-order reaction rate constant for the middle layer only. For the biochar column,
the top and bottom cedar canyon layers were assumed to have the same reaction rate as
the homogenous cedar canyon column.
Figure 3.
Calibrated Water Content HYDRUS Graphical Outputs (
a
) Sand, (
b
) Cedar Canyon,
(c) Alluvial, (d) Dense Woodchips, (e) Loose Woodchips, and (f) Biochar.
3.2. Nitrate Parameter Calibration Using Observed Nitrate Concentration
A constant flux of wastewater was applied to the soil columns. The wastewater was
collected from the Rapid City Wastewater Treatment Plant. The wastewater had a known
concentration of 28.0 mg/L of nitrate. The denitrification reaction from nitrate to nitrogen
gas is considered a first-order anaerobic reaction with no sorption [
20
]. Leachate samples
were collected and compared to the modeled output concentration. Measured nitrate
concentration data were limited compared to the data used to determine soil hydraulic
parameters. Thus, manual calibration was used. Calibration was performed based on
the average nitrate effluent concentrations. This was compared to the effluent nitrate
concentration at a steady state in the model. The first-order reaction rates were adjusted
until the modeled effluent concentration matched the average experimental concentration.
The layered columns include carbon-based media with cedar canyon soil both on the
top and bottom of the column. Each layer is of equal thickness of 16.6 cm. The calibrated
solute parameters from the homogenous cedar canyon column were used for the cedar
canyon layers. The carbon-based layers were then calibrated by changing the middle
layer’s first-order reaction rate constant for the middle layer only. For the biochar column,
the top and bottom cedar canyon layers were assumed to have the same reaction rate as
the homogenous cedar canyon column.
Clean Technol. 2022,4833
The first-order denitrification rate was determined by changing the 1st order reaction
rate constant until the modeled effluent concentration matched the average observed
experimental concentration. Table 3shows the average effluent nitrate concentration from
the experimental models, as well as the calibrated denitrification reaction rate constant.
Table 3. Observed/Modeled Nitrate Solute Transport.
Parameters
C1 C2 C3 C4 C5 C6
Sand Alluvial Cedar
Canyon
Dense
Woodchips
Loose
Woodchips Biochar Mix
Observed/Modeled
Concentration (mg/L)
14.22/
14.25
18.71/
18.69
15.54/
15.55
10.14/
10.14
8.28/
8.26
10.25/
10.26
First Order Reaction
Constant (1/day) 0.26 0.045 0.28 0.17 0.24 0.032 0.28
The experimental results show that nitrate removal is observed to dramatically increase
with the use of carbon-based media. The first-order reaction rate constant did not change
much from the soil media to the carbon-based media. This is because the model has a
water content function (Walker’s equation, Equation (10)) that increases the reaction rate as
the water content increases. Thus, with identical reaction rates, the carbon-based material
has a higher removal attributable to higher content. In Section 3.1, it was observed that
the woodchip and biochar layers had a major effect on increasing the water content in the
woodchip and biochar layers. Equations (8)–(10) give the reasoning as to why the water
content increased nitrate removal. It is seen in each equation that the water content affected
removal (Equation (8)), dispersion of nitrate (Equation (9)), and the filled pore space in
Walker’s Equation (10). One of the limitations of the model in distinguishing between the
various factors that influence nitrate removal (e.g., water content versus carbon content).
The results of the nitrate treatment calibration are shown in Figure 4a–f. This is followed
by Figure 5a,b, which shows the vertical nitrate concentration distribution produced by
HYDRUS 2D.
Higher nitrate removal efficiencies were observed in woodchips and biochar. There-
fore, the removal efficiencies compared with previous studies are shown in Table 4. The
comparison showed that initial nitrate concentrations play an important role in removal
efficiency. The removal performances of the media decreased with increasing initial con-
centrations. This is because of the faster saturation of the available removal sites in the case
of a higher initial concentration. The removal performance of the media also depends on
the input wastewater components. However, the media we used performed relatively well
in nitrate removal compared to other studies.
Clean Technol. 2022,4834
Clean Technol. 2022, 4, FOR PEER REVIEW 12
Figure 4. Calibrated Nitrate Concentration for (a) Sand, (b) Alluvial, (c) Cedar Canyon, (d) Wood-
chips (dense), (e) Woodchips (Loose), and (f) Biochar.
Higher nitrate removal efficiencies were observed in woodchips and biochar. There-
fore, the removal efficiencies compared with previous studies are shown in Table 4. The
comparison showed that initial nitrate concentrations play an important role in removal
efficiency. The removal performances of the media decreased with increasing initial con-
centrations. This is because of the faster saturation of the available removal sites in the
case of a higher initial concentration. The removal performance of the media also depends
on the input wastewater components. However, the media we used performed relatively
well in nitrate removal compared to other studies.
Figure 4.
Calibrated Nitrate Concentration for (
a
) Sand, (
b
) Alluvial, (
c
) Cedar Canyon, (
d
) Woodchips
(dense), (e) Woodchips (Loose), and (f) Biochar.
Clean Technol. 2022,4835
Clean Technol. 2022, 4, FOR PEER REVIEW 13
Table 4. Nitrate removal efficiencies of Woodchips and Biochar.
Media Initial Concentration Nitrate Removal Efficiency Reference
(mg/L) (%)
Woodchips
10 98.7 [36]
30 39 ± 9 [37]
10 79 ± 14 [37]
50 29 ± 12 [37]
41.2 35 to 43 [38]
28 70.46 Our Study
Biochar
20 15 to 20 [39]
10 20 to 40 [40]
10 57.1 ± 2.1 [41]
100 20.63 [42]
28 63.39 Our Study
Figure 5. Vertical Nitrate Distribution in (a) homogeneous columns (Sand, Alluvial, and Cedar Can-
yon) and (b) layered columns (Woodchips (dense), Woodchips (Loose), and Biochar).
The HYDRUS 2D graphical output for nitrate concentration compared to the depth
for each of the calibrated columns is shown in Figure 6a–f.
Figure 5.
Vertical Nitrate Distribution in (
a
) homogeneous columns (Sand, Alluvial, and Cedar
Canyon) and (b) layered columns (Woodchips (dense), Woodchips (Loose), and Biochar).
Table 4. Nitrate removal efficiencies of Woodchips and Biochar.
Media Initial Concentration Nitrate Removal Efficiency Reference
(mg/L) (%)
Woodchips
10 98.7 [36]
30 39 ±9 [37]
10 79 ±14 [37]
50 29 ±12 [37]
41.2 35 to 43 [38]
28 70.46 Our Study
Biochar
20 15 to 20 [39]
10 20 to 40 [40]
10 57.1 ±2.1 [41]
100 20.63 [42]
28 63.39 Our Study
The HYDRUS 2D graphical output for nitrate concentration compared to the depth for
each of the calibrated columns is shown in Figure 6a–f.
The difference from the homogenous soil columns was minimal, and there was only
an observed difference in the nitrate treatment once an increased water content was ob-
served. For both the dense and loose woodchip layers, a sharp increase in nitrate treatment
was observed, while in the biochar layer, no changes were seen in the nitrate treatment
performance until the mixed layer where the observed water content was much higher
compared to the homogenous cedar canyon column.
Clean Technol. 2022,4836
Clean Technol. 2022, 4, FOR PEER REVIEW 14
Figure 6. Calibrated Nitrate Concentrations HYDRUS Graphical Outputs: (a) Sand, (b) Cedar Can-
yon, (c) Alluvial, (d) Dense Woodchips, (e) Loose Woodchips, and (f) Biochar.
The difference from the homogenous soil columns was minimal, and there was only
an observed difference in the nitrate treatment once an increased water content was ob-
served. For both the dense and loose woodchip layers, a sharp increase in nitrate treat-
ment was observed, while in the biochar layer, no changes were seen in the nitrate treat-
ment performance until the mixed layer where the observed water content was much
higher compared to the homogenous cedar canyon column.
3.3. Sensitivity Analysis
The parameter inputs and results for the sensitivity analysis are shown in Section S5
and Tables S6–S11 in the Supplementary File. The values displayed are the percent differ-
ence from the original effluent nitrate concentration. The average experimental effluent
nitrate concentration for the sand, loose woodchips, and biochar columns was found to
be 14.22, 9.49, and 16.6 mg/L in the corresponding order.
Through sensitivity analysis, it was found that three major parameters affected ni-
trate treatment performance. The major factors were the saturated water content, Van
Genuchten parameter α, and the first-order reaction constant. The saturated water content
and α were parameters that had a major impact on the overall water content of the col-
umn. Meanwhile, k, the first-order reaction constant, had a direct impact on the solute
Figure 6.
Calibrated Nitrate Concentrations HYDRUS Graphical Outputs: (
a
) Sand, (
b
) Cedar Canyon,
(c) Alluvial, (d) Dense Woodchips, (e) Loose Woodchips, and (f) Biochar.
3.3. Sensitivity Analysis
The parameter inputs and results for the sensitivity analysis are shown in
Section S5
and Tables S6–S11 in the Supplementary File. The values displayed are the percent differ-
ence from the original effluent nitrate concentration. The average experimental effluent
nitrate concentration for the sand, loose woodchips, and biochar columns was found to be
14.22, 9.49, and 16.6 mg/L in the corresponding order.
Through sensitivity analysis, it was found that three major parameters affected nitrate
treatment performance. The major factors were the saturated water content, Van Genuchten
parameter
α
, and the first-order reaction constant. The saturated water content and
α
were
parameters that had a major impact on the overall water content of the column. Mean-
while, k, the first-order reaction constant, had a direct impact on the solute concentration.
Figure S6a–c in the Supplementary File shows a summary of the effect on the effluent
nitrate concentration by changing the respective parameters.
It was unexpected that the water content of the soil would have such a large impact
on nitrate transport and reaction through the column. Looking at Equations (6)–(8), in
Section 2.2.2, it is seen that the water content is a direct modifier to the first-order reaction
rate and the dispersion/diffusion within the column. This is the reason that the biochar
column was able to remove more nitrate than the cedar canyon column, even if the Biochar
first-order reaction rate constant was 0.032 compared to Cedar Canyons reaction rate of
Clean Technol. 2022,4837
0.278. The biochar column was much more efficient in retaining water in the column,
increasing the denitrification reaction rate. The effect of water content would also explain
the 6% difference between the compacted and uncompacted woodchip columns. This is
explained by the fact that denitrification is an anaerobic reaction and will occur faster with
a lack of oxygen. This means that soils that are capable of retaining water longer while still
allowing for adequate flow will be the most effective in nitrate removal.
3.4. Scenario Analysis Modeling
Six different scenarios based on flux rate, influx concentration, and flow depth are
shown in Table 5, which provides a summary of each of the analyzed scenarios.
Table 5. Scenario analysis summary.
Scenario Flux Rate (cm/Day) Influx Concentration (mg/L) Flow Depth (cm)
Scenario 1 2 60 50
Scenario 2 5 60 50
Scenario 3 5 30 50
Scenario 4 2 60 100
Scenario 5 5 60 100
Scenario 6 5 30 100
Figure 7shows the scenario analysis results of the sand column. It was observed that
by increasing the hydraulic loading rate by 250%, the nitrate effluent only increased by
50%. The results of doubling the column depth had minimal impact, as the average nitrate
effluent concentration was reduced by less than 20% for each of the loading rates and water
quality scenarios.
Clean Technol. 2022, 4, FOR PEER REVIEW 15
concentration. Figure S12a–c in the Supplementary File shows a summary of the effect on
the effluent nitrate concentration by changing the respective parameters.
It was unexpected that the water content of the soil would have such a large impact
on nitrate transport and reaction through the column. Looking at Equations (6)–(8), in
Section 2.2.2, it is seen that the water content is a direct modifier to the first-order reaction
rate and the dispersion/diffusion within the column. This is the reason that the biochar
column was able to remove more nitrate than the cedar canyon column, even if the Biochar
first-order reaction rate constant was 0.032 compared to Cedar Canyons reaction rate of
0.278. The biochar column was much more efficient in retaining water in the column, in-
creasing the denitrification reaction rate. The effect of water content would also explain
the 6% difference between the compacted and uncompacted woodchip columns. This is
explained by the fact that denitrification is an anaerobic reaction and will occur faster with
a lack of oxygen. This means that soils that are capable of retaining water longer while
still allowing for adequate flow will be the most effective in nitrate removal.
3.4. Scenario Analysis Modeling
Six different scenarios based on flux rate, influx concentration, and flow depth are
shown in Table 5, which provides a summary of each of the analyzed scenarios.
Table 5. Scenario analysis summary.
Scenario Flux Rate (cm
/
Day) Influx Concentration (mg/L) Flow Depth (cm)
Scenario 1 2 60 50
Scenario 2 5 60 50
Scenario 3 5 30 50
Scenario 4 2 60 100
Scenario 5 5 60 100
Scenario 6 5 30 100
Figure 7 shows the scenario analysis results of the sand column. It was observed that
by increasing the hydraulic loading rate by 250%, the nitrate effluent only increased by
50%. The results of doubling the column depth had minimal impact, as the average nitrate
effluent concentration was reduced by less than 20% for each of the loading rates and
water quality scenarios.
Figure 7. Scenario analysis results.
Figure 7. Scenario analysis results.
Figure 7shows the results of the loose woodchip column scenario analysis. As
the depth of the soil column doubled, the effluent nitrate concentration was reduced by
roughly 40% for both hydraulic loading rates of 5 cm/day. For the hydraulic loading rate of
2 cm/day there was a reduction of 60%. When the hydraulic loading rate was increased by
250% with the same water quality, the nitrate effluent increased by 200% for the original
column depth. At the doubled depth, there was an increase in nitrate effluent of
over 300%.
The loose woodchips operate under a low hydraulic loading rate, the best with thick
soil columns.
Clean Technol. 2022,4838
Some important factors should be considered when implementing the study findings
in the field design. As seen in this study, the effect of a higher water content had a major ef-
fect on the denitrification reaction rate. For all OWTS, the leeching field should be designed
to create highly saturated soil below. This will help increase the denitrification reaction rate,
reducing the amount of nitrate leaching into groundwater. Lastly, the implementation of
loosely compacted woodchips below the leeching field should be used in areas where karst
formations are known to occur. The use of woodchips will increase the level of saturation,
and the presence of carbon will increase the denitrification rate.
4. Conclusions
The increased usage of onsite wastewater systems in the Black Hills poses a threat to
the water supply. With the increased number of OWTS in use, nitrate concentrations have
been on the rise in the Black Hills. The nitrate treatment performance of soils will become
increasingly important as septic tank density increases. The work in this study focused on
analyzing the treatment performance of common soils from Black Hills and other carbon-
based soil media. The soil media included two soils from the Black Hills (alluvium and
silty sand), sand, compacted woodchips, loose woodchips, and biochar. Experimental soil
columns were made with each of the soil media, with the carbon-based media included
as a layered component. The numerical model was instrumental in understanding water
movement and nitrate treatment performance through various media. The hydraulic
calibration reached good agreement between the measured and model-predicted soil
moisture content, with R
2
values ranging from 0.57 to 0.99. The lower R
2
values were due
to the steady increase in the observed water content over time. A high R
2
was achieved
because the soil columns reached a constant steady state. All carbon-based soil media
showed increased nitrate treatment performance from wastewater filtration. The most
effective nitrate treatment media were found to be loosely compacted woodchips. This
is thought to be the result of the increased water content that enhanced the anaerobic
denitrification reaction. The total effect of replacing the middle third layer soil with carbon-
based media increased the nitrate treatment performance from 34% to 65%. The sensitivity
analysis showed that the major factors for improving nitrate removal efficiency included
the saturated water content and the denitrification rate. This is to be expected, as the
denitrification rate has a direct effect on removal efficiency. The saturated water content
is due to denitrification being an anaerobic reaction requiring a lack of oxygen. This was
achieved using Walker’s equation, which implemented the effect of increased saturations
having a higher denitrification reaction rate.
Supplementary Materials:
The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/cleantechnol4030051/s1, File: Supplementary File-S1.
Author Contributions:
Conceptualization, M.S.H. and M.G.; methodology, M.S.H. and M.G.; soft-
ware, J.T., M.S.H. and M.G.; validation, J.T., M.S.H. and M.G.; formal analysis, J.T. and M.S.H.;
investigation, J.T., M.S.H. and M.G.; resources, M.G.; data curation, J.T. and M.S.H.; writing—original
draft preparation, J.T., M.S.H. and M.G.; writing—review and editing, J.T., M.S.H. and M.G.; visu-
alization, M.S.H. and M.G.; supervision, M.S.H. and M.G.; project administration, M.G.; funding
acquisition, M.G. All authors have read and agreed to the published version of the manuscript.
Funding:
This research was funded by the USGS 104b Grant Program (3TQ861) and the Civil and
Environmental Engineering Department, South Dakota School of Mines and Technology.
Institutional Review Board Statement: Not Applicable.
Informed Consent Statement: Not Applicable.
Data Availability Statement: Not Applicable.
Acknowledgments:
The authors would like to acknowledge Forest Cooper for his support in setting
up the column frame and acquiring materials.
Conflicts of Interest: The authors declare no conflict of interest.
Clean Technol. 2022,4839
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