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Research Article
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A Comparison of the Langmuir, Freundlich and Temkin Equations to Describe Phosphate Sorption Characteristics of Some Representative Soils of Bangladesh |
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Mohammad Z. Afsar,
Sirajul Hoque
and
K.T. Osman
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ABSTRACT
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To study the phosphate sorption potential of soils, an experiment was conducted with eight different soil series of Bangladesh. The soils were equilibrated with 0.01 M calcium chloride solution containing 0, 1, 2, 4, 8, 16, 25, 50, 100 and 150 μg phosphorus mL-1 and the amount of phosphate sorbed was determined. Calcareous soils sorbed more phosphorus than non-calcareous soils. The sorption curves showed more or less similar pattern of changes. Langmuir model showed better fit to sorption data at higher P concentrations. Phosphate sorption was highly correlated with Fe oxide and clay content of the soils. Freundlich constant kf and n, Phosphorus Sorption Maximum (Smax) and EPC0 values were positively correlated with both the above soil properties. On the contrary, phosphate binding strength (b) was negatively correlated. It is suggested that Langmuir equation might be more suitable for commercial soil-testing laboratories for routine determination of phosphate sorption characteristics of soils.
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How
to cite this article:
Mohammad Z. Afsar, Sirajul Hoque and K.T. Osman, 2012. A Comparison of the Langmuir, Freundlich and Temkin Equations to Describe Phosphate Sorption Characteristics of Some Representative Soils of Bangladesh. International Journal of Soil Science, 7: 91-99. DOI: 10.3923/ijss.2012.91.99 URL: https://scialert.net/abstract/?doi=ijss.2012.91.99
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Received: December 16, 2011;
Accepted: April 17, 2012;
Published: May 28, 2012
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INTRODUCTION
Phosphorus (P) is one of the essential elements for plant growth. Phosphorus
fertilization management is a means of improving soil P for crop production
in the cropping system. In Bangladesh, most of the farmers usually apply phosphorus
fertilizers without judging the P status of the soils. This practice may cause
either depletion of the soil quality or deterioration of various environmental
niches. The dual goals of soil-P management are to maintain the concentration
of biologically available soil-P at a value adequate for plant growth while
minimizing the movement of dissolved and particulate-P to surface waters and
shallow groundwater (Hossain et al., 2011).
Better management of phosphorus fertilizer can be achieved by studying the
P sorption-desorption behavior of the soil that reflects the partitioning of
P between soil solid phase and soil solution. The principal processes involved
in the retention and release of P are sorption and desorption reactions (Pierzynski
et al., 2005). Various modeling approaches have been used to describe
P sorption reactions in soils. Under specific set of conditions (e.g., the solution
to soil ratio, reaction time and temperature), any soil possesses a characteristic
sorption curve. Phosphorus sorption curve can be used for predicting the fertilizer
P needed to replenish the soil solution P to a level optimum for a particular
crop. Quantitative descriptions of P sorption by soils have often been made
with the Linear, Langmuir, Freundlich and Temkin equations (Villapando
and Greatz, 2001):
The Linear Eq.: S = KC-S0
The Freundlich Eq.: S = KfCn
The logarithmic form of the Freundlich Eq.: Log S = log Kf +nxlogC
The Langmuir Eq.:
The Temkin Eq.: S = axlogC+k. where, S = Total sorbed P (μg g-1), C = the amount of P in the solution after equilibration (μg mL-1), K is the P-sorption coefficient (slope), S0, Kf and n are empirical constants, with n<1. Kf represents the amount of P sorbed (in mmol kg-1) when C is 1 mmol L-1, Smax = phosphate sorption maximum and b = P binding strength, a and k´ of Temkin equation are constants. On this background, the present study was aimed at (1) finding out the phosphate sorption potential of some representative soils of Bangladesh, (2) developing model sorption behavior using Linear, Freundlich, Langmuir and Temkin models, (3) observing the effects of some soil properties on phosphate sorption and (4) evaluating the relationships among P sorption parameters and selected soil properties. MATERIALS AND METHODS Soil series and soil sampling: With a view to study phosphate sorption characteristics of soils, this experiment was conducted in the laboratory of the department of soil, water and environment, University of Dhaka with eight different bench-mark soil series. Among these, Baliadangi series (eutric cambisol) of old Himalayan Piedmont plain; Gongachara series (eutric fluvisol) of Tista Meander floodplain; Lockdeo (eutric fluvisol), Silmondi (eutric fluvisol) and Ghatail series (eutric fluvisol) of old Brahmaputra floodplain were noncalcareous. On the other hand, Gopalpur (calcaric fluvisol), Ishurdi (calcaric fluvisol) and Ghior (calcaric fluvisol) series of low Ganges river floodplain were calcareous. The three calcareous soil series comprised a catena, where Gopalpur and Ghior soil series located at the highest and the lowest elevation, respectively. Soil samples at a depth of 0-15 cm were collected from 20 spots from an area of ~1 km2 under a soil series. Equal proportions of theses samples were mixed to form a composite sample. The soils were then air dried, ground and sieved through a 2 mm sieve.
Phosphorus sorption studies: Triplicate 1 g soil samples were equilibrated
in a 50 mL centrifuge tube with 20 mL 0.01 M CaCl2 solution containing
0, 1, 2, 4, 8, 16, 25, 50, 100 and 150 μg phosphorus mL-1 (equivalent
to 0, 20, 40, 80, 160, 320, 500, 1000, 2000 and 3000 μg phosphorus g-1
soil) as KH2PO4. The soil samples were then incubated
at room temperature for 3 days prior to the sorption study. This incubation
time was chosen in accordance with a previous experiment by Sharpley
et al. (1981). Yaseen et al. (1999)
and Hernandez et al. (2005) showed that the amount
of adsorbed P was increased with increasing incubation period from 1-15 days.
However, Akhtar and Alam (2001) observed that the P
availability in soil was gradually decreased with increasing the incubation
time for both organic and inorganic sources of P. After centrifugation at 3000
rpm for 15 min, the supernatant was collected. The amount of P sorbed by the
soil was calculated from the difference in P concentration between the initial
P and equilibrium P concentrations in the solution. The P in the filtered solutions
was measured colorimetrically by a Shimadzu model UV-120-02 spectrophotometer.
Chemical analysis: Soil samples were analyzed for textural classes,
total P and available N, P, K, organic carbon, free carbonate, fractions of
iron, etc. Particle size analysis was done by hydrometer method (Bouyoucos,
1927). Soil organic matter was determined by wet oxidation method (Walkley
and Black, 1934). Cation Exchange Capacity (CEC) was estimated by NH4OAc
saturation (Jackson, 1973). Available P was extracted
by 0.5 M NaHCO3 at pH 8.5 (Olsen et al.,
1954) and P in the extract was determined by ascorbic acid blue color method
(Murphy and Riley, 1962). Free carbonate content was
measured by rapid titration method (Allison and Moodie, 1965).
Among the three iron fractions, free iron oxides were estimated according to
Holmgren (1967). Active or Amorphous
iron oxides were determined by using a modified procedure of Schwertmann
(1964) and McKeague and Day (1966) as reported by
Loeppert and Inskeep (1996). Sodium pyrophosphate extractant
(pH 10) was used for the estimation of organically bound Fe (Bascomb,
1968). Subsequent iron determinations were carried out by the process described
by Olson and Ellis (1982).
Statistical analysis: Microsoft Office Excel and SPSS-12 computer programs
were used to estimate relationships between phosphate sorption and different
soil properties. Correlation coefficients were calculated between phosphate
sorption parameters like P-sorption capacities (kf), Freundlich constant
(n), P-sorption maximum (Smax) and Equilibrium Phosphate Concentration
(EPC0) values with soil properties like percent clay, organic matter
content and CDB-extractable iron content. Correlation coefficients among various
P-sorption parameters were also calculated. Suitability of different adsorption
equations were studied by calculating the R2 values of the respective
equations. Regression curves were drawn by the Microsoft Office Excel program.
RESULTS AND DISCUSSION Properties of the soils: Soils of the present study varied widely in physical and chemical properties. Some important soil properties are presented in Table 1. Among the soil properties, percent clay and free iron oxide content of calcareous soils were higher than non-calcareous soils. Ghior soil had the highest 59% clay and 15,241 μg g-1 free iron oxide. Whereas, Lokdeo soil had the lowest 20% clay and 3,524 μg g-1 free iron oxide. Phosphorus sorption behavior: In all the soils, P-sorption occurred due to application of P at different rates. On the other hand, there was some desorption in the 0 μg phosphorus mL-1 treatment (i.e., control). The highest proportion of sorption was found where phosphorus was applied at the rate of 1-2 μg mL-1 of P and the value was found to decrease with increasing rates of P application.
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Fig. 1: |
Trend of phosphate sorption in different soils with different
rates of P application |
Figure 1 shows the trend of P-sorption with different rates of P application. Among the non-calcareous soils, Baliadangi soil was more retentive than the other four non-calcareous soils in terms of phosphate sorption potential at 150 μg P mL-1 concentration. Among the calcareous soils, Ghior series, located at the lower elevation in the catena of Lower Ganges Floodplain, was more retentive than the other two calcareous soils. Gopalpur series, located at the highest elevation among the three soils, sorbed the lowest amount of phosphate.
Phosphate sorption was positively correlated with both the CDB-extractable
iron (0.728*, p>0.05) and percent clay content (0.745*, p>0.05) of the
soils when phosphate was applied at the rate of 100 μg phosphorus mL-1.
Solis and Torrent (1989) also found that P-sorption capacity
is highly correlated with Fe oxide and clay content of the soil.
Phosphate sorption was also positively correlated with both amorphous iron
oxide and organically bound iron content of the soils. Having possessed the
highest amount of free iron oxide and clay content, Ghior soil exhibited tremendous
potential for sorbing phosphate from the applied phosphorus. However, the amount
of P sorption did not show any trend of change in relation to the amounts of
CaCO3 present in soils. These findings corroborate with those of
Holford and Mattingly (1975) who indicated that hydrous
oxides are important for adsorption of P even in calcareous soils.
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Fig. 2(a-h): |
Phosphate sorption equations for the soils fitted with the
Linear equation, (a) Baliadangi, (b) Gangachara, (c) Lokdeo, (d) Silmandi,
(e) Ghatail, (f) Gopalpur, (g) Ishurdi and (h) Ghior soil series |
Figure 2-5 describes the phosphate sorption
characteristics of soils with respect to different adsorption equations. The
phosphate sorption characteristics in these soils were best fitted to the linear
equation only at very low equilibrium solution P concentrations (R2
= 0.83-0.99) while higher P concentration showed some evidence of deviation
from linearity. The linear relationship at lower P concentrations was probably
due to the large intermolecular distance between P molecules which resulted
in negligible mutual repulsion. Deviation from the straight line indicated that
the bonding energy is a decreasing function of increasing surface-saturation
(Emadi et al., 2009). The P sorption data of
the presently studied soils were also plotted according to the Langmuir, Freundlich
and Temkin equations. Among these three equations, the linear form of Langmuir
equation was best fitted to phosphate sorption studies, as indicated by the
R2 values that ranged from 0.94-0.99. The Freundlich equations also
gave a better fit to the equilibrium phosphate concentration in solution as
described by the R2 values (0.88-0.99).
Linear equation: The P-sorption coefficients, k (Fig. 2) of calcareous soils were much lower than that of non-calcareous soil. The Ghior soil had the lowest (89.0 L kg-1) and the Silmandi soil had the highest (329.15 L kg-1) P-sorption coefficient. Higher K values of non-calcareous soils indicate that the change in the amount of sorbed-P with per unit change in equilibrium phosphorus concentration in solution was higher for non-calcareous soils than for calcareous soils.
Freundlich equation: By using the Freundlich equation model, the phosphate
sorption capacities (kf) and Freundlich constant, k, n values were
measured (Fig. 3). Calcareous soils had lower Kf
values than non-calcareous soils which indicated lower P-retention capacity
of calcareous soils than non-calcareous soils at low P concentration, even though
calcareous soils can retain larger amounts of P at higher P concentrations.
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Fig. 3(a-h): |
Phosphate sorption equation for the soils fitted by the Freundlich
equation, (a) Baliadangi, (b) Gangachara, (c) Lokdeo, (d) Silmandi, (e)
Ghatail, (f) Gopalpur, (g) Ishurdi and (h) Ghior soil series |
Langmuir equation: Phosphorus Sorption Maximum (Smax) and Langmuir constant, b values were measured (Fig. 4) by using the Langmuir equation. The range of maximum P sorption observed in this study was in between 416.67-1000.00 μg g-1, where Lokdeo and Ghior soils showed the respective lowest and highest sorption maximum values. Temkin equation: The Equilibrium Phosphorus Concentration (EPC) at which net P adsorption is 0 (adsorption equals desorption) is defined as EPC0. The EPC0 values were determined by using Temkin equation (Fig. 5).
The EPC0 values were higher for calcareous soils (0.19-0.26) than
the non-calcareous soils (0.05-0.11). The EPC0 value can be defined
as an estimation of the intensity factor of the soils (Hartikainen,
1991). High EPC0 values suggested much higher P intensity in
calcareous soils than non-calcareous soils.
Correlation of phosphate sorption parameters with soil properties: There
were good agreement between phosphate sorption parameters and soil properties.
Among the sorption parameters, P-sorption Capacities (kf), Freundlich
constant n, Phosphorus Sorption Maximum (Smax) and EPC0
values were positively correlated with both the percent clay and CDB-extractable
iron content of the soil. The relationships were significant at 1-5% level.
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Fig. 4(a-h): |
Phosphate sorption equation for the soils fitted by the Langmuir
equation, (a) Baliadangi, (b) Gangachara, (c) Lokdeo, (d) Silmandi, (e)
Ghatail, (f) Gopalpur, (g) Ishurdi and (h) Ghior soil series |
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Fig. 5(a-h): |
Phosphate sorption equation for the soils fitted by the Temkin
equation, (a) Baliadangi, (b) Gangachara, (c) Lokdeo, (d) Silmandi, (e)
Ghatail, (f) Gopalpur, (g) Ishurdi sand (h) Ghior soil series |
On the contrary, phosphate binding strength (b) was negatively correlated with
both the above soil parameters, though in case of clay, the relationship was
non-significant. Zhou and Li (2001) reported a positive
correlation of Kf with total clay and non-carbonate clay (such as
Fe oxide, Al oxide and Si clays) in Southern Florida calcareous soils.
Phosphate sorption coefficient (K) values determined from Linear equation were found to be positively correlated with Kf values (0.676*, p>0.05) but negatively correlated with EPC0 values (-0.679*, p>0.05). Freundlich constant, n values were positively correlated with both Smax (0.641*, p>0.05) and EPC0 (0.949**, p>0.01) values. CONCLUSION The soils differed considerably in their capacity to sorb the added P and in the estimated labile pool of native soil P. Soils with the lower clay and iron oxide content showed the lowest retentive capacity. Except b, other phosphate sorption parameters like kf, Smax and EPC0 values were positively correlated with both the soil parameters. In general, calcareous soils sorbed more phosphorus in their labile pool than non-calcareous soils when provided with same concentrations of P in solution.
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