- Email: [email protected]
Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst
Accepted Manuscript Title: Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst Author: Chao Liu Jinhui Peng Aiyuan Ma Libo Zhang Jing Li PII: DOI: Reference:
S0304-3894(16)30885-8 http://dx.doi.org/doi:10.1016/j.jhazmat.2016.09.063 HAZMAT 18069
To appear in:
Journal of Hazardous Materials
Received date: Revised date: Accepted date:
17-6-2016 26-8-2016 27-9-2016
Please cite this article as: Chao Liu, Jinhui Peng, Aiyuan Ma, Libo Zhang, Jing Li, Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst, Journal of Hazardous Materials http://dx.doi.org/10.1016/j.jhazmat.2016.09.063 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst Chao Liu a, b, c, d, Jinhui Peng a, b, c, d, Aiyuan Ma a, b, c, d Libo Zhang a, b, c, d,*, Jing Li a, b, c, d
a
State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization, Kunming
University of Science and Technology, Kunming, Yunnan 650093, China b
Yunnan Provincial Key Laboratory of Intensification Metallurgy, Kunming, Yunnan 650093,
China c
National Local Joint Laboratory of Engineering Application of Microwave Energy and
Equipment Technology, Kunming, Yunnan 650093, China d
Faculty of Metallurgical and Energy Engineering, Kunming University of Science and
Technology, Kunming, Yunnan 650093, China
* Corresponding author. E-mail address: [email protected] (L. Zhang) 1
Highlights
Thermal desorption of mercury from spent HgCl2 catalyst is investigated.
Apparent activation energy is revealed as a function of conversion.
Diffusion mechanisms are found to govern the whole process.
A complex process related to mercury release is validated.
2
ABSTRACT Kinetics of the thermal desorption of mercury from spent mercury chloride catalysts were investigated using non-isothermal thermal analysis technique. Complex mercury species absorbed on waste catalysts were revealed by sequential extraction procedure. A scheme of six reactions was applied to elucidate mercury desorption kinetics. Activation energy estimated by model-free isoconversional methods is a slightly increasing function of conversion, implying a variation in the mechanism controlling mercury desorption. Average value of apparent activation energy (116.32 kJ/mol) calculated by isoconversional Starink method was used to determine reaction mechanism using model-fitting and 𝑧(𝛼) master method. One dimensional diffusion appears to govern mercury desorption process in the conversion range of 10%-40%, and then the reaction kinetic is controlled by two and three dimensional diffusion at greater conversion. Key words: Mercury chloride catalysts Mercury desorption Non-isothermal kinetics
1. Introduction
All forms of mercury have been considered as toxic [1]. Mercury containing wastes can constitute a potential threat to the human survival environment as mercury tends to bio-accumulate and cause damage to kidney and central nervous system of 3
living organisms [2-4]. Anthropogenic emissions of mercury should be largely responsible for the mercury contamination. Mercuric chloride supported on activated carbon (HgCl2/AC) used as catalyst for the production of vinyl chloride monomer (VCM) is considered as one of the three largest secondary sources of mercury anthropogenic emissions [5,6]. VCM is an indispensible material for the synthesis of polyvinyl chloride (PVC), which functioned as the second largest general plastic in the fields of industry, agriculture and national defense [7]. The industrial routes for manufacturing VCM are either through oxychlorination process using ethylene made from petroleum as raw material or through hydrochlorination process using acetylene made from coal as raw material with the assistant of HgCl2/AC catalyst [8,9]. In the early 1960s, hydrochlorination process is replaced by oxychlorination process in most developed countries due to the widely exploitation and utilization of inexpensive oil resource. However, hydrochlorination process for manufacture of PVC still prevails in developing countries with abundant coal reserves to date [10]. In order to fundamentally eliminate the harmful and scarce mercury, many efforts have been made to explore non-mercury catalysts to replace the HgCl2/AC catalyst [11-13]. Nevertheless, the development of substitutable catalysts remains at the stage in laboratory [14]. China served as the largest PVC producing country in the world, more than 13 Mt PVC are synthesized based on the acetylene hydrochlorination method per year, which occupies over 70% of the PVC production in China [15,16]. After using for a 4
certain time, HgCl2/AC catalysts will deactivate, yielding waste HgCl2/AC catalysts, which are classified as “high mercury waste” (total Hg content > 260 mg/kg) according to the US Land Disposal Restrictions [6]. Thermal treatment process is recommended by US EPA for “high mercury waste” [17,18]. In fact, chemical preprocessing followed by thermal treatment at a elevated temperature to desorb mercury and retorting process operating in controlled atmosphere were two main methods for handling waste HgCl2/AC catalysts. However, a complete recovery for mercury is actually difficult to be achieved as nearly all the researchers have focused on optimizing process parameters and few studies with regard to thermal desorption mechanisms of mercury species from deactivated HgCl2/AC catalysts are reported. In order to reduce processing costs and enhance mercury recovery to meet the increasing environmental requirement, a deep understanding for desorption kinetics of mercury is indispensable. Model-free and model-fitting methods are commonly used to study thermal decomposition kinetics [19]. Several researchers used these methods to study thermal decomposition of mercury containing wastes. Decomposition of HgCl2 supported on pure activated carbon as well as activated carbon treated with FeCl3 or NaCl has been developed, and it was proved that FeCl3 or NaCl were suitable catalysts for HgCl2 decomposition by decreasing activation energy [20]. Model-free and reaction order methods were used to understand the kinetic parameters and reaction mechanism of the thermal decomposition for mercury waste generated by chlor-alkali plants, and it was found that at 250 oC the process was controlled by D1-diffusion mechanism 5
whereas a combination of the diffusion mechanism (D1) and the third order reaction mechanism (F3) seemed to fit the decomposition kinetics at 450 oC [6]. For studying the thermal desorption of mercury from a contaminated soil, a combination of model-free and model-fitting method was performed to evaluate the activation energy and reaction mechanism respectively using non-isothermal experimental approach [21]. This research aims to elucidate the thermal desorption kinetics of mercury species from the spent HgCl2/AC catalysts using non-isothermal experimental data. A scheme of six reactions with regard to mercury compounds absorbed on waste catalysts was proposed. Apparent activation energy was obtained by model-free methods and served as a useful evaluation for subsequent analysis. Model-fitting method combined with 𝑧(𝛼) master plots method was employed to determine reaction mechanisms. This study intends to obtain kinetic parameters of mercury thermal
desorption
and
a
preliminary
understanding
to
the
complex
multiple-component system of spent catalyst. If possible, further investigations will be done to explore new process and develop novel equipment for disposing of deactivated HgCl2/AC catalysts based on the results obtained from this work. In addition, more work is required to study the complex system of spent catalysts further.
2. Experimental
2.1. Sample and chemical analysis
The spent mercuric chloride catalyst sample used for this study was collected 6
from a chemical plant for producing polyvinyl chloride in China. The catalyst support activated carbon (AC) is derived from coal. In the laboratory, samples were dried at 60 oC to constant weight, followed by ground in an agate mortar to pass through a 75 μm sieve. Deactivated catalyst sample was subject to Toxicity Characteristic Leaching Procedure (TCLP) test for evaluating mercury toxicity levels according to US EPA [22]. A standardized procedure designed for analyzing Hg in coal was used to analyze Hg in spent HgCl2/AC catalyst [23,24]. Inductively coupled plasma optical emission spectrometry (ICP-OES, Leeman labs, America) was used to determine mercury in the solution. The metals content in waste catalyst was quantified using 0.5 g of sample by digestion for 2 h at 150 oC with aqua regia [18], and then, employing ICP-OES. All reagents used were analytical grade. All experiments were carried out in triplicate. Mean value and standard deviations were represented. ICP-OES measurements were performed in triplicate for each solution and averages were reported. The standard solutions were achieved by diluting the 1000 mg/l stock solution to different concentrations. The calibration curve was obtained using 5 points including the blank. Only the calibration curve with correlation coefficient larger than 0.995 was used. The precision expressed as relative standard deviation (RSD) was less than 2%.
2.2. Fractionation of mercury
Sequential extraction procedure is considered as an effective method to identify various species of an element and to determine its gross content in each class. A lot of 7
methods for mercury sequential extraction from soil, sludge and sediment samples have been proposed [25-27]. However, no methods are applied to the sequential extraction of mercury species absorbed on activated carbon or carbon based catalysts. Hall and Pelchat [28] designed a six-step sequential extraction scheme to extract different mercury species from geological samples, which can especially separate HgS from other forms of Hg using 40% HNO3. This method has been used by researchers [24, 29] for fractionating mercury absorbed on chemically modified activated carbons. The extraction experiment in this study was modified by using only 0.1g of sample instead of 1g while maintaining the concentration of extraction reagents. This change aims to increase liquid-solid ratio and then minimize the mercury readsorption onto the sample for its high mercury contents. The extraciton test for 1g of sample was also performed for comparison. Mercury concentration in the extracted solutions was determined using ICP-OES. Tests were carried out in triplicate. Averages and standard deviations were calculated. Standard deviations were represented by error bars.
2.3. Thermal analysis experiments
A Mettler Toledo Star SW 13.00 thermogravimetric analyzer operated in dry nitrogen atmosphere with a flow rate of 20 ml/min, was used for thermal analysis experiments. The sample was heated from room temperature to 1200 oC at four different heating rates of 5, 10, 15 and 20 oC/min. About 20 mg sample passed through a 75 μm sieve was placed in alumina crucible for each experiment.
8
2.4. Thermodynamic analysis
Thermodynamic analysis was carried out by using thermodynamic software FactSage. Thermodynamic parameters, i.e. standard Gibbs free energy change (ΔGo ), standard enthalpy change (ΔH o ) and standard entropy change (ΔS o ) of the reactions proposed based on the sequential extraction results and thermogravimetric analysis were calculated. ΔH o and ΔGo are used to estimate the heat of reactions and probability of occurrence of reactions, respectively.
2.5. Theoretical background of thermal analysis kinetics
The scheme for reactions involved a single solid reactant (e.g. sublimation or decomposition) can be generally described by 𝐴(𝑠) → 𝐵(𝑠) + 𝐶(𝑔)
(1)
Thermal analysis methods are commonly used to study kinetics of thermal decomposition for solid materials. For isothermal experimental data, the reaction rate follows the general law below, 𝑑𝛼 = 𝑘(𝑇)𝑓(𝛼) 𝑑𝑡
（2）
with 𝑇(𝐾) being the absolute temperature, 𝑓(𝛼) being the differential expression of reaction model, the reacted fraction 𝛼 at time 𝑡(𝑚𝑖𝑛) is defined as, 𝛼=
𝑚0 − 𝑚𝑡 𝑚0 − 𝑚∞
（3）
where, 𝑚0 is the initial sample weight, 𝑚𝑡 is the remaining sample weight at time 𝑡, 𝑚∞ is the final sample weight. Substituting 𝑘 (𝑇) according to Arrhenius equation, Eq. (2) can be rewritten as, 9
𝐸𝛼 𝑑𝛼 = 𝐴 𝑒 −𝑅𝑇 𝑓(𝛼) 𝑑𝑡
where,
𝐴(𝑚𝑖𝑛−1 )
represents
the
(4)
pre-exponential
factor,
𝐸𝛼 (kJ/mol)
represents the activation energy, 𝑅(8.314 kJ/mol K) represents gas constant. For evaluating non-isothermal kinetic, heating rate 𝛽 is introduced into Eq. (2) to form the non-isothermal reaction rate expression as follows, 𝑑𝛼 𝐴 − 𝐸𝛼 = 𝑒 𝑅𝑇 𝑓(𝛼) 𝑑𝑇 𝛽
(5)
Integrating both the left and right sides of Eq. (5) in interval 𝑇0 − 𝑇 and 0 − 𝛼 respectively gives the integral reaction model 𝑔(𝛼), 𝛼
1 𝐴 𝑇 − 𝐸𝛼 𝑔(𝛼) = ∫ 𝑑𝛼 = ∫ 𝑒 𝑅𝑇 𝑑𝑇 𝑓(𝛼) 𝛽 𝑇0 0
(6)
Differential Eqs. (4) and (5) and integral Eq. (6) are the basic formulas for studying thermal decomposition kinetics based on the thermal analysis data. Approximations with different precision were proposed for solving the famous 𝑇
temperature integral ∫𝑇 𝑒 −
𝐸𝛼
𝑑𝑇 in Eq. (6) with no analytical solution, leading to the
various integral methods.
2.5.1. Model-free method
Model-free method has attractive characteristics that as can be used to analyze either isothermal or nonisothermal data and the results from isothermal and nonisothermal experiments are internally consistent [29]. It is considered as a reliable approach to obtain kinetic parameters as it can actually reveal thermal decomposition mechanisms at different conversion for system with complex and multiple reactions [30-32]. Model-free methods usually refer to isoconversional methods which evaluate 10
the activation energy at a fixed conversion using multi-curves. It is worth noting that not all model-free methods are isoconversional such as Kissinger method discussed below. The information of the model-free methods used in this paper and corresponding linear equations derived from the general reaction rate formulas with separation of 𝐸𝛼 and other kinetic parameters are listed in Table 1. Plots of the left side of linear equations versus 1/𝑇 at fixed conversion value allow determinating the activation energy from the slope of the fitting line. Note that 𝐸𝛼 obtained by model-free methods is a function of conversion except Kissinger method as it is not isoconversional method.
2.5.2. Evaluation of reaction mechanism
2.5.2.1. Model-fitting method
Only the activation energy values can be obtained by model-free methods whereas model-fitting methods give “kinetic triplet” (𝐸𝛼 , 𝐴 and 𝑓(𝛼)) simutaneously. For non-isothermal data, many model-fitting methods allow evaluation for kinetic parameters wherein Coats–Redfern equation [40] was used in this paper, which shows as follows, 𝑙𝑛[
𝑔(𝛼) 𝐴𝑅 𝐸𝛼 ] = 𝑙𝑛 [ ] − 𝑇2 𝛽𝐸𝛼 𝑅𝑇
(12)
the kinetic mechanism function with good correlation coefficient for the fitting straight line obtained by plotting 𝑙𝑛 *
𝑔(𝛼) 𝑇2
+ vs.
1
at fixed conversion under different
𝑇
heating rate 𝛽 was selected as the reaction model. 11
2.5.2.2. 𝒛(𝜶) master plots method
The use of 𝑧(𝛼) master plots method [40] mainly adopts the following expressions of theoretical and experimental 𝑧(𝛼), 𝑧(𝛼) = 𝑓(𝛼) 𝑔(𝛼) 𝑧(𝛼) = 𝜋(𝑢) =
𝑑𝛼 )𝑇 𝑑𝑡 𝛽
𝜋(𝑢) (
(13) (14)
𝑢3 + 18𝑢2 + 86𝑢 + 96 𝑢4 + 20𝑢3 + 120𝑢2 + 240𝑢 + 120
(15)
Where 𝑢 is 𝐸𝛼 /𝑅𝑇, 𝜋(𝑢) is taken from the forth Senum-Yang approximations of the temperature integral. The plots of 𝑧(𝛼) vs. 𝛼 can be obtained by substituting model expressions considered and experimental data from TG/DTG to Eq. (13) and Eq. (14), respectively. Comparing the experimental curves with theoretical curves allow determination of the best fit model.
3. Results and discussion
3.1. Characteristics of sample
The waste catalyst is considered as hazardous materials with mercury concentration leached by TCLP test being 64.18 mg/L, which is highly greater than the TCLP reference value 0.2 mg/L [20]. Spent HgCl2/AC catalyst is characterized as “high mercury waste” as its total mercury concentration of 3.31 wt% (33100 mg/kg) (Table 2) far exceeds 260 mg/kg according to the US Land Disposal Restrictions [6]. High levels of Ca, Fe, Mg, Al, K and Cl were found in the spent catalyst (Table 2). These are expected as some alkaline and alkaline earth metal chlorides are added to 12
the HgCl2/AC catalyst during the process of catalyst preparation, enhancing catalytic activity and the stability of HgCl2. Ca, Fe, Mg and Al may exist in activated carbon in the oxides forms [22]. Traces of Ce and Ba are also attributed to addition of corresponding metal chlorides to catalyst acting as catalytic additives.
3.2. Sequential extraction procedure
Fig. 1 shows the sequential extraction results for both 0.1g and 1g of sample. It can be seen from Fig. 1 that there is an obvious difference in the extraction ratio at each step between the samples of 0.1g and 1g, especilly in the first two steps. For the sample of 0.1g, 56.35% and 16.62% of mercury were leached in step 1 and step 2, respectively. While there was an opposite tendency for the sample of 1g, only 6.48% of mercury was extracted in step 1, but step 2 extracted 45.56% of mercury. This is likely due to the readsorption of mercury extracted in the leachate onto AC for the sample of 1g and the high mercury content (3.31%, table 2) in the spent catalyst sample, which is much larger than those of literatures [24, 28, 29]. According to Fig. 1, it was proved to be useful to minimize the mercury readsorption by reducing the sample mass from 1g to 0.1g. Therefore the extraction results for the sample of 0.1g were considered as more reliable and were used for subsequent analysis. For sample of 0.1g (Fig. 1), mercury was extracted in each step, indicating the presence of various mercury compounds in the spent catalyst. This reminded us that mercury species absorbed on spent catalyst is not just HgCl2 but the mercury in other forms. About 94% of mercury was leached in the first four steps under weak 13
conditions, indicating highly instability of mercury absorbed on the waste catalyst. Therefore, it is necessary to conduct strict management and storage for spent HgCl2/AC catalyst. The total amount of mercury extracted in all the six steps as a percentage of the mercury determined by the standardized procedure mentioned in section 2.1 was 88.9%. This mass unbalance may be likely due to the testing error of mercury content and volatility of mercury involved in the six-step extraction procedure. However, this result is still acceptable for sequential extraction [29]. The first step was able to extract a majority (56.35%) of the mercury that was in the “easily soluble” forms, attributing to the main component, HgCl2, supported on the catalyst. 16.62% of mercury was extracted by the second step, showing the presence of mercury associated with labile organic phases, possibly carbon deposition. Formation of the carbon deposition on the surface of catalysts used for acetylene hydrochlorination has been observed by researchers [43, 44]. 21.06% of mercury was extracted by the third and fourth step, indicating that a large proportion of mercury was absorbed to Fe/Al oxides, which existed in the catalyst support AC derived from coal [24]. The fifth step extracted only 3.25% of mercury using 40% HNO3, however, it suggested the possibility of presence of elemental mercury, Hg2Cl2 or mercury combined with nonlabile organic phases containing carbon deposits and oxygen functionality in the AC [24]. In general, the existence of Hgo and Hg2Cl2 is derived from the reduction of HgCl2 at the reductive reaction atmosphere during the utilization of HgCl2/AC catalysts. Moreover, HgCl2 tends to form Hg2Cl2 after 14
absorbing on the AC, which is validated by Adams [45] using potentiometric analysis. The presence of hydroquinonic, phenolic and hydrosulphide groups on the surface of the activated carbon can also reduce Hg (II) to Hg (I) [46]. The mercury extracted by the last step proved that a minor fraction of mercury formed HgS, which was likely the deactivation product of HgCl2. Recently, many researchers [47-50] reported that the presence of H2S derived from feed gas can easily lead to the deactivation of catalysts, yielding metal sulfides covered on the surface of reactive metal. This is obvious under the reductive atmosphere such as acetylene for hydrochlorination reaction process [51].
3.3. Thermogravimetric analysis
The thermogravimetry (TG) and differential thermogravimetry (DTG) curves of thermal decomposition of waste catalysts in N2 at different heating rates are shown in Figs. 2a and 2b, respectively. It can be observed that heating rates affect the positions of thermogravimetric curves, and therefore the peak temperatures. When the heating rates increase, initial, maximum and end temperatures of peaks also increase. Take the heating rate 10 oC/min for analysis. The first stage till 150 oC mainly relates to the evaporation of moisture, trace of weak absorbed mercury and some highly volatile impurities may release at this temperature region. These impurities mainly are products derived from the side reaction during the acetylene hydrochlorination process. The second stage corresponding to the temperature range of 150 oC to 380 oC is the major devolatilization zone with weight loss of 11.3%, 15
which can be largely attributed to the thermal desorption of mercury species i.e. Hg2Cl2, HgCl2 and HgS according to the results of sequential extraction procedure. In addition, the desorption temperatures of these mercury species are below 400 oC regardless of matrix according to accessible literature data (Table 3). Carbon deposition and trace of remaining mercury wrapped in AC is possibly responsible for the third region (380-776 oC). The last stage corresponding to the weak peak 3 at the temperatures ranging from 776 oC to 1120 oC is due to the volatilization of metal chlorides e.g. CaCl2, KCl, BaCl2 and CeCl3 [56]. Note that the release of carbon deposition from deactivated HgCl2/AC catalyst may occur throughout the whole heating process either by thermal decomposition or by taking away along with the desorption of mercury. This is explained by the complexity of carbon deposition, which may include crushed carbon dust and various organics with different volatility. Further study is required to recognize the carbon containing species. In this study, kinetic analysis is conducted at the temperature interval 150-400 o
C representing the main thermal decomposition region of mercury species [21,
52-55].
3.4. Thermodynamic analysis of the potential reactions
A scheme of six reactions with regard to mercury species is proposed to elucidate mercury desorption kinetics (Table 4). Note that R(1) and R(2) may occur in series. Thermodynamic parameters were calculated at the temperature of 400 oC representing the end temperature of reactions for kinetic analysis. The positive values of ΔH o
16
imply that all the reactions are endothermic. Generally, the negative value of ΔGo indicates the reaction can proceed spontaneously. According to Table 4, only the two phase change reactions R(4) and R(6) presented negative ΔGo . However, this cannot indicate that other reactions do not have the potential to occur below 400 oC as the partial pressures of the gaseous products related to the calculation of ΔGo were assumed as one bar pressure. Actually, the reactions proceeded in a 20 ml/min N2 flow in this study. The actual pressure of gas products is far less than one bar. Thus, the ΔG value will reduce if the actual partial pressure is taken into account. In addition, according to the experimental data from literature available (Table 3), the reactions proposed in table 4 actually were proved to occur below 400 oC.
3.5. Determination of activation energy
All the isoconversional methods mentioned above i.e. Friedman, KAS, FWO and Starink methods were used for kinetic studies to obtain the isoconversion plot of activation energy 𝐸𝛼 with conversion 𝛼 under conversion range of 0.1-0.9 with an increment of 0.05. All methods used show a nice fit to the experimental data with the correlation coefficients greater than 0.99. Plots of the activation energy versus conversion for the considered kinetic methods are shown in Fig. 3. It can be seen from Fig. 3 that the shape of the curves derived from different methods are similar and the activation energy values estimated by Friedman, KAS and Starink methods are almost the same except
FWO method. Similar phenomenon was
observed by
Lopez-Gonzalez [46], who studied the decomposition activation energy of mercury 17
species in contaminated soil and found that the activation values obtained with the FWO method were higher than those obtained by the Friedman method. This may be ascribed to a systematic error associated with the simplified approximation of temperature integral when using FWO method. The activation energy values obtained by Friedman method are slightly greater than KAS and Starink methods. Friedman method is a differential method which is susceptible to experimental noise and thus gives scattered activation energy values. This also has been confirmed in the estimation of decomposition activation energy of rice straw [57]. KAS and Starink methods yield nearly overlapping activation energy values. Average activation energy of 116.3 kJ/mol derived from Starink method with employment of a more precise approximation of temperature integral is used as a global estimation for subsequent analysis. In addition, Kissinger method also gives a good fit to experimental data with linear correlation coefficient being 0.98 and a single activation energy value of 114.9 kJ/mol was obtained, which is very close to the value estimated by Starink method. Fig. 3 visually shows that the activation energy values practically fluctuate as the conversion with a slightly rising trend as a whole, revealing occurrence of complex mechanism during the thermal decomposition process of mercury species. It should be reminded that spent HgCl2/AC catalyst is also a multi-component and poly-disperse system similar to mercury polluted sludge [6], the activation energy values determined cannot represent any individual step, and therefore, the term “apparent” activation energy is used in this study. Nevertheless, the average value of apparent activation energy obtained in this work is slightly greater than that of the 18
decomposition of HgCl2-AC, HgCl2–FeCl3–AC and HgCl2–NaCl–AC with 𝐸𝛼 being 97.5, 95.1 and 99.1 kJ/mol, respectively [20]. This may be possibly ascribed to the more complex system of spent HgCl2/AC catalyst. It is of importance to further study the thermal decomposition of different mercury species supported on waste AC.
3.6. Evaluation of reaction mechanism
3.6.1. Model-fitting methods
Forty-one kinetic models are developed by researchers [58], nevertheless all can be reduced to three major types: accelerating, decelerating, and sigmoidal [42]. Common kinetic models are shown in Table 5. In this study, only decelerating models were considered based on the shape of isothermal experimental conversion curve. Decelerating kinetic model functions (Table 5) and the original data 𝛼, 𝑑𝛼/𝑑𝑇, 𝑇𝛼 from TG–DTG curves under various linear heating rates were substituted into Eq. (7) for calculation. The average value and standard deviation of activation energy, logarithm of pre-exponential factor and correlation coefficient determined from four heating rates using deceleratory models are given in Table 6. It can be seen that the experimental data shows a good fitting to nearly all the models considered whereas only the four diffusion models have 𝐸𝛼 closest to the average value of apparent activation energy (116.32 kJ/mol) estimated by model-free Starink model. Although models D1 and D2 reveal themselves as potential ones by showing good fit to the experimental data, the achieved activation energy seems inferior to that of D4. Because the activation energy (117.8 kJ/mol) determined by D4 is closest to 19
the value (116.32 kJ/mol) obtained by model-free Starink model. In addition, the correlation coefficients of D3 (0.9977) and D4 (0.9946) are also superior to those of D1 (0.9817) and D2 (0.9916). Therefore, D1 and D2 model among all the diffusion models cannot be considered as the best fitting model with combined consideration of correlation coefficient and 𝐸𝛼 . Generally, D3 model with highest correlation efficient should be considered as the optimum fitting model. But further taking into account activation energy, D4 model is superior to D3. Thus there is an ambiguity in selecting a proper model to describe the overall process, suggesting the whole mechanism cannot be predicted by a single rate equation, which may meet distinct mechanism model at different extent of conversion. However, diffusion models with the 𝐸𝛼 closest to that of model-free Starink model show their distinct fitting potential to experimental data than other models evaluated. This may be helpful to determine the most probable model using 𝑧(𝛼) master plots method discussed in the section below.
3.6.2. 𝒛(𝜶) master plots method
Fig. 4 (a) and (b) shows the experimental and theoretical 𝑧(𝛼) curves. The experimental curves for four different heating rates are nearly overlapping whereas they are not in accord with any single model curve estimated. The experimental curves practically conform to different model functions with change of conversion. It is close to the curve of D1 at conversion 0.1-0.4, and then transfers to the curve of D2 and D4. At the conversion greater than 0.6 the decomposition mechanism roughly follows D3 model. D1 model also showed robust fitting to the decomposition of 20
HgCl2 absorbed on AC [20]. The whole reaction course is oriented by diffusion mechanism. These are expected as the mercury species i.e. Hg, HgCl2, Hg2Cl2 and HgS are prone to sublimate or decompose at the temperature interval of peak two in the DTG pattern while diffusion is blocked by gas products, pores of AC and carbon deposition. The temperature corresponds to conversion 0.4 is 282-297 oC for different heating curves, which is on the verge of the peak temperature 285-316 oC. When conversion less than 0.4 the decomposition rate of mercury compounds is slow so that the process only refers to one dimensional diffusion. At higher conversions (>0.4) corresponding to higher temperatures, the decomposition reactions rate increased, with greater release of gaseous products. The reaction process was controlled by two and then three dimensional diffusion, showing increasing diffusion resistance. The best fitting kinetic model cannot be determined by model-fitting method as more than one kinetic model can fit the experimental data well. The utilization of 𝑧(𝛼) master plots can visually reveal the variation of reaction mechanism with conversion, which is especially useful for the complex system of this study. As model-free method involves no hypothesis with regard to any mechanism of the process, it can give the activation energy a precise prediction and assist to determine reaction model. The combined utilization of model-free, model-fitting and 𝑧(𝛼) master plots method to evaluate kinetic parameters is validated to be more efficient than any single method.
21
4. Conclusions
In this study, thermal decomposition kinetics of mercury species from spent HgCl2/AC catalysts were developed. The activation energy values estimated by several model-free methods were compared and the Starink method was found to be more convenient than others in design and prediction procedures. The derived results showed that the thermal desorption of mercury from spent mercury chloride was a complex process. This can be seen from the activation energy as a function of conversion. With the combined utilization of model-fitting and 𝑧(𝛼) master method, it can be concluded that the whole mercury desorption process followed diffusion mechanism, specially with change from D1 to D2 and finally D4 and D3 diffusion. The results can provide theoretical support for optimizing process and developing new equipment for mercury desorption with the diffusion of gaseous products being the key consideration. This may eventually contribute to meeting increasingly strict environmental concerns and reducing costs by selecting proper operating condtions and equipment.
Acknowledgements
This work was supported by National Natural Science Foundation of China (51522405) and Yunnan Provincial Science and Technology Innovation Talents Scheme Technological Leading Talent of China (2013HA002).
22
References
[1] L.D. Hylander, M.E. Goodsite, Environmental costs of mercury pollution, Sci. Total Environ. 368 (2006) 352-370. [2] C. Sonne, R. Dietz, P.S. Leifsson, G. Asmund, E.W. Born, M. Kirkegaard, Are liver and renal lesions in East Greenland polar bears (Ursus maritimus) associated with high mercury levels?, Environ. Health 6 (2007) 11. [3] X.Y.
Zhang,
Q.C.
Wang,
S.Q.
Zhang,
X.J.
Sun,
Z.S.
Zhang,
Stabilization/solidification (S/S) of mercury-contaminated hazardous wastes using thiol-functionalized zeolite and Portland cement, J. Hazard. Mater. 168 (2009) 1575-1580. [4] P. Randall, S. Chattopadhyay, Advances in encapsulation technologies for the management of mercury-contaminated hazardous wastes, J. Hazard. Mater. 114 (2004) 211-223. [5] E.B. Swain, P.M. Jakus, G. Rice, F. Lupi, P.A. Maxson, J.M. Pacyna, A. Penn, S.J. Spiegel, M.M. Veiga, Socioeconomic Consequences of Mercury Use and Pollution, AMBIO: J. Human Environ. 36 (2007) 45-61. [6] Y. Busto, F.M.G. Tack., L.M. Peralta, X. Cabrera, L.E. Arteaga-Perez, An investigation on the modelling of kinetics of thermal decomposition of hazardous mercury wastes, J. Hazard. Mater. 260 (2013) 358-367. [7] F. Wang, L. Wang, J. Wang, Y. Zhao, Y. Wang, D. Yang, Bimetallic Pd-K/Y-zeolite catalyst in acetylene hydrochlorination for PVC production, React. Kinet. Mech. Catal. 114 (2014) 725-734. 23
[8] M. Conte, C.J. Davies, D.J. Morgan, T.E. Davies, D.J. Elias, A.F. Carley, P. Johnston, G.J. Hutchings, Aqua regia activated Au/C catalysts for the hydrochlorination of acetylene, J. Catal. 297 (2013) 128-136. [9] X. Wei, H. Shi, W. Qian, G. Luo, Y. Jin, F. Wei, Gas-Phase Catalytic Hydrochlorination of Acetylene in a Two-Stage Fluidized-Bed Reactor, Ind. Eng. Chem. Res. 48 (2009) 128-133. [10] X. Li, X. Pan, L. Yu, P. Ren, X. Wu, L. Sun, F. Jiao, X. Bao, Silicon carbide-derived carbon nanocomposite as a substitute for mercury in the catalytic hydrochlorination of acetylene, Nat. Commun. 5 (2014) 3688. [11] G. Hutchings, Vapor phase hydrochlorination of acetylene: Correlation of catalytic activity of supported metal chloride catalysts, J. Catal. 96 (1985) 292-295. [12] H. Zhang, B. Dai, W. Li, X. Wang, J. Zhang, M. Zhu, J. Gu, Non-mercury catalytic acetylene hydrochlorination over spherical activated-carbon-supported Au–Co(III)–Cu(II) catalysts, J. Catal. 316 (2014) 141-148. [13] H. Zhang, B. Dai, X. Wang, L. Xu, M. Zhu, Hydrochlorination of acetylene to vinyl chloride monomer over bimetallic Au–La/SAC catalysts, J. Ind. Eng. Chem. 18 (2012) 49-54. [14] L. He, Y. N. Tan, W. Han, Industrial process progress of acetylene to vinyl chloride, J. Chem. Ind. Eng. 34 (2013) 61-65. (in Chinese) [15] K. Zhou, J. Jia, C. Li, H. Xu, J. Zhou, G. Luo, F. Wei, A low content Au-based catalyst for hydrochlorination of C2H2 and its industrial scale-up for future PVC 24
processes, Green Chem. 17 (2015) 356-364. [16] J. Zhang, N. Liu, W. Li, B. Dai, Progress on cleaner production of vinyl chloride monomers over non-mercury catalysts, Front. Chem. Sci. Eng. 5 (2011) 514-520. [17] T.C. Chang, S.J. You, B.S. Yu, C.M. Chen, Y.C. Chiu, Treating high-mercury-containing lamps using full-scale thermal desorption technology, J. Hazard. Mater. 162 (2009) 967-972. [18] Y. Busto, X. Cabrera, F.M. Tack, M.G. Verloo, Potential of thermal treatment for decontamination of mercury containing wastes from chlor-alkali industry, J. Hazard. Mater. 186 (2011) 114-118. [19] A. Khawam, D.R. Flanagan, Basics and applications of solid-state kinetics: a pharmaceutical perspective, J. Pharm. Sci. 95 (2006) 472-498. [20] M. Bentley, M. Fan, B. Dutcher, M. Tang, M.D. Argyle, A.G. Russell, Y. Zhang, M.P. Sharma, S.M. Swapp, Catalytic regeneration of mercury sorbents, J. Hazard. Mater. 262 (2013) 642-648. [21] F.A. López, M.J. Sierra, O. Rodríguez, R. Millán, F.J. Alguacil, Non-isothermal kinetics of the thermal desorption of mercury from a contaminated soil, Rev. Metalurgia 50 (2014) e001. [22] USEPA, Stabilization and Testing of Mercury Containing Wastes: Borden Sludge, 2002, Available from: http://nepis.epa.gov/Exe/ZyPDF.cgi/2000CZ0H.PDF?Dockey=2000CZ0H.PDF (Retrieved 5.16.16) [23] Chinese Standard Testing Method for Hg in coal; GB/T16659- 2008. 25
[24] S. Tong, M. Fan, L. Mao, C.Q. Jia, Sequential extraction study of stability of adsorbed mercury in chemically modified activated carbons, Environ. Sci. Technol. 45 (2011) 7416-7421. [25] C. Gleyzes, S. Tellier, M. Astruc, Fractionation studies of trace elements in contaminated soils and sediments: a review of sequential extraction procedures, Trends Anal. Chem. 21 (2002) 451-467. [26] Y. Han, H.M. Kingston, H.M. Boylan, G.M. Rahman, S. Shah, R.C. Richter, D.D. Link, S. Bhandari, Speciation of mercury in soil and sediment by selective solvent and acid extraction, Anal. Bioanal. Chem. 375 (2003) 428-436. [27] C. Foldi, C.A. Andree, T. Mansfeldt, Sequential extraction of inorganic mercury in dumped blast furnace sludge, Environ. Sci. Pollut. Res. Int. 22 (2015) 15755-15762. [28] G.E.M. Hall, P. Pelchat, The design and application of sequential extractions for mercury, Part 2. Resorption of mercury onto the sample during leaching, Geochem. Explor. Environ. Anal. 5 (2005) 115-121. [29] J.W. Graydon, X. Zhang, D.W. Kirk, C.Q. Jia, Sorption and stability of mercury on activated carbon for emission control, J. Hazard. Mater. 168 (2009) 978-982. [30] S. Vyazovkin, C.A. Wight, Model-free and model-fitting approaches to kinetic analysis of isothermal and nonisothermal data, Thermochim. Acta 340-341 (1999) 53-68. [31] J.R. Opfermann, E. Kaisersberger, H.J. Flammersheim, Model-free analysis of thermoanalytical data-advantages and limitations, Thermochim. Acta 391 (2002) 26
119-127. [32] M.J. Starink, The determination of activation energy from linear heating rate experiments: a comparison of the accuracy of isoconversion methods, Thermochim. Acta 404 (2003) 163-176. [33] H.L. Friedman, Kinetics of thermal degradation of char-forming plastics from thermogravimetry. Application to a phenolic plastic, J. Polymer Sci. 6 (2007) 183-195. [34] H.E. Kissinger, Variation of peak temperature with heating rate in differential thermal analysis, J. Res. Nat. Bur. Stand. 57 (1956) 217. [35] H.E. Kissinger, Reaction Kinetics in Differential Thermal Analysis, Anal. Chem. 29 (1957) 1702-1706. [36] T. Ozawa, A New Method of Analyzing Thermogravimetric Data, Bull. Chem. Soc. Jpn. 38 (1965) 1881-1886. [37] J.H. Flynn, L.A. Wall, General treatment of the thermogravimetry of polymers, J. Res. Nat. Bur. Stand. 70A (1966) 487. [38] J.H. Flynn, L.A. Wall, A quick, direct method for the determination of activation energy from thermogravimetric data, J. Polym. Sci. 4 (1966) 323-328. [39] T. Akahira, T. Sunose, Method of determining activation deterioration constant of electrical insulating materials. Res. Report Chiba Inst. Technol. 16 (1971) 22–23. [40] M.J. Starink, A new method for the derivation of activation energies from experiments performed at constant heating rate, Thermochim. Acta 288 (1996) 97-104. 27
[41] A.W. Coats, J.P. Redfern, Kinetic parameters from thermogravimetric data. II, J. Polymer Sci.
3 (1965) 917-920.
[42] S. Vyazovkin, A.K. Burnham, J.M. Criado, L.A. Pérez-Maqueda, C. Popescu, N. Sbirrazzuoli, ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data, Thermochim. Acta 520 (2011) 1-19. [43] K. Chen, L. Kang, M. Zhu, B. Dai, Mesoporous carbon with controllable pore sizes as a support of the AuCl3 catalyst for acetylene hydrochlorination, Catal. Sci. Technol. 5 (2015) 1035-1040. [44] Q.L. Song, S.J. Wang, B.X. Shen, J.G. Zhao, Palladium-Based Catalysts for the Hydrochlorination of Acetylene: Reasons for Deactivation and Its Regeneration, Pet. Sci. Technol. 28 (2010) 1825-1833. [45] M.D. Adams, The mechanisms of adsorption of Hg(CN)2 and HgCl2 on to activated carbon, Hydrometallurgy 26 (1991) 201-210. [46] J.D.D.
Lopez-Gonzalez,
C.
Moreno-Castilla,
A.
Guerrero-Ruiz,
F.
Rodriguez-Reinoso, Effect of carbon-oxygen and carbon-sulphur surface complexes on the adsorption of mercuric chloride in aqueous solutions by activated carbons, J. Chem. Technol. Biotechnol. 32 (1982) 575-579. [47] G.J. Hutchings, D.T. Grady, Hydrochlorination of acetylene: The effect of mercuric chloride concentration on catalyst life, Appl. Catal. 17 (1985) 155-160. [48] C.H. Bartholomew, Mechanisms of catalyst deactivation, Appl. Catal. B 212 (2001) 17-60. 28
[49] W. Fitzharris, J.R. Katzer, W.H. Manogue, Sulfur deactivation of nickel methanation catalysts, J. Catal. 76 (1982) 369-384. [50] A.M. Beale, E.K. Gibson, M.G. O’Brien, S.D.M. Jacques, R.J. Cernik, M.D. Michiel, P.D. Cobden, Ö. Pirgon-Galin, L.v.d. Water, M.J. Watson, B.M. Weckhuysen, Chemical imaging of the sulfur-induced deactivation of Cu/ZnO catalyst bodies, J. Catal. 314 (2014) 94-100. [51] B. Dai, C. Zhang, L. Kang, M. Zhu, Poisoning effect of H2S on catalytic performance of AuCl3/AC in acetylene hydrochlorination, CIESC Journal 66 (2015) 3476-3482. (in Chinese) [52] M. Sedlar, M. Pavlin, A. Popovič, M. Horvat, Temperature stability of mercury compounds in solid substrates, Open Chem. 13 (2014). [53] A.T. Reis, J.P. Coelho, S.M. Rodrigues, R. Rocha, C.M. Davidson, A.C. Duarte, E. Pereira, Development and validation of a simple thermo-desorption technique for mercury speciation in soils and sediments, Talanta 99 (2012) 363-368. [54] M. Rumayor, M.A. Lopez-Anton, M. Díaz-Somoano, M.R. Martínez-Tarazona, A new approach to mercury speciation in solids using a thermal desorption technique, Fuel 160 (2015) 523-530. [55] C. Raposo, C.C. Windmöller, W.A. Durão Júnior, Mercury speciation in fluorescent lamps by thermal release analysis, Waste Manag. 23 (2003) 879-886. [56] W.M. Haynes, CRC handbook of chemistry and physics. CRC press, 95th ed., Boca Raton, 2014. [57] G. Mishra, T. Bhaskar, Non isothermal model free kinetics for pyrolysis of rice 29
straw, Bioresour. Technol. 169 (2014) 614-621. [58] R.Z. Hu, Q.Z. Shi, Thermal Analysis Kinetics, Science Press, Beijing, 2001. (in Chinese)
30
Fig. 1. Mercury extraction by each step shown as a percentage of total mercury extracted for both 0.1g and 1g of spent catalyst sample. The mercury species extracted and corresponding extraction conditions for each step are as follows: (step 1) soluble and exchangeable using 0.01 mol/L Ca(NO3)2, (step 2) labile organic using 0.1 mol/L Na4P2O7, (step 3) amorphous Fe/Al oxides using 0.25 mol/L NH2OH·HCl in 0.25 mol/L HCl, (step 4) crystalline Fe/Al oxides using 1 mol/L NH2OH·HCl in 25% CH3COOH, (step 5) non-labile organic and elemental Hg using 6.4 mol/L (40%) HNO3, and (step 6) HgS and residual, using aqua regia. Error bars represent standard deviations of three repeated experiments.
31
Fig. 2a. TG curves of spent HgCl2/AC catalyst at different heating rates.
Fig. 2b. DTG curves of spent HgCl2/AC catalyst at different heating rates.
32
Fig. 3. The estimated values of activation energy as a function of conversion.
33
Fig. 4. Comparasion of experimental and theoretical z(α) master plots: (a) model curves (D1, D2, D3 and D4) and experimental curves at different heating rates (EXP); (b) model curves (F1, F2, F3, R2 and R3) and experimental curves at different heating rates (EXP). Different model curves 34
are presented in two sub-figure (a) and (b) for clear identification. (Note that D1, D2, D3, D4, F1, F2, F3, R2 and R3 are the symbols of decelerating kinetic models reported in Table 5)
35
Table 1 Several commonly used model-free methods and corresponding linear equations. Method
Linear equation
Friedman
𝑙𝑛[𝛽(
𝑑𝛼 𝐸𝛼 )] = 𝑙𝑛[𝐴𝑓(𝛼)] − 𝑑𝑇 𝑅𝑇 𝛽 𝐴𝑅 ′ 𝐸𝛼 𝑙𝑛[ 2 ] = 𝑙𝑛 [− 𝑓 (𝛼𝑚 )] − 𝑇𝑚 𝐸𝛼 𝑅𝑇𝑚
Kissinger
𝐴𝐸𝛼 𝐸𝛼 𝑙𝑛𝛽 = 𝑙𝑛[ ] − 5.331 − 1.052 𝑅𝑔(𝛼) 𝑅𝑇
Flynn Wall Ozawa (FWO) Kissinger
Akahira
and
Sunose
𝑙𝑛[
𝛽 𝐴𝑅 𝐸𝛼 ] = 𝑙𝑛[ ]− 𝑇2 𝐸𝛼 𝑔(𝛼) 𝑅𝑇
Equation number
Reference
(7)
[33]
(8)
[34,35]
(9)
[36-38]
(10)
[34,35,39]
(11)
[40]
(KAS) Starink
𝛽 𝐸𝛼 𝑙𝑛 ( 1.92 ) = 𝐶𝑜𝑛𝑠𝑡. −1.0008 ( ) 𝑇 𝑅𝑇
36
Table 2 Main element contents of spent catalyst sample. Element
Total Content (%)*
Hg
3.31 ± 0.25
Ca
1.55 ± 0.12
Fe
1.08 ± 0.10
Mg
0.39 ± 0.05
Al
0.31 ± 0.08
K
0.17 ± 0.03
Cl
2.12 ± 0.05 Total Content (mg/kg) *
Ce
388 ± 18
Ba
33 ± 4
*means ± standard deviations (n = 3).
37
Table 3 Available literature data about the thermal desorption temperature of mercury compounds in N2 flow at atmospheric pressure. Mercury
Desorption temperature region (oC), peak temperature (oC)
Hgo
25-180, 150
Hg2Cl2
50-300, 75
HgCl2
50-300, 75
61-154, 110
125-225, 180
135
HgS
170-450, 313
252-343, 305
225-325, 300
303
Matrix
None
Contaminated soils
Aluminium oxide
Silica and carbon
Reference
[52]
100-250, 225
[21]
[53]
[54]
150-340, 275
Phosphorus powder [55]
38
Table 4 Equations and thermodynamic parameters for reactions related to potential mercury species absorbed on waste HgCl2/AC catalyst. Reaction
Reaction
Reference
Number
o ΔH400 oC
o ΔG400 oC
o ΔS400 oC
(kJ/mol)
(kJ/mol)
(kJ/mol K)
Hg2 Cl2 (s) = Hgo (g) + HgCl2(s)
R(1)
[55]
92.85
12.26
0.12
HgCl2 (s) = Hgo (g) + Cl2 (g)
R(2)
[55]
283.13
124.60
0.24
2HgS (s) = 2Hgo (g) + S2 (g)
R(3)
[52] [55]
340.26
85.06
0.38
HgCl2 (s) = HgCl2(g)
R(4)
[6]
76.87
-14.28
0.14
HgS (s) = HgS (g)
R(5)
[6]
171.14
67.58
0.15
Hgo (l) = Hgo (g)
R(6)
[6]
58.93
-3.99
0.09
39
Table 5 Common kinetic model functions expressions 𝑓(𝛼) and 𝑔(𝛼) for solid state thermal decomposition reactions. Symbol
Differential form 𝑓(𝛼)
Integral form 𝑔(𝛼)
E1
𝛼
ln𝛼
Avarami-Erofe’ev
A2
2(1 − 𝛼)[−ln(1 − 𝛼)]1/2
[−ln(1 − 𝛼)]1/2
Avarami-Erofe’ev
A3
3(1 − 𝛼)[−ln(1 − 𝛼)]2/3
[−ln(1 − 𝛼)]1/3
Avarami-Erofe’ev
A4
4(1 − 𝛼)[−ln(1 − 𝛼)]3/4
[−ln(1 − 𝛼)]1/4
Contracting area
R2
2(1 − 𝛼)1/2
1 − (1 − 𝛼)1/2
Contracting volume
R3
3(1 − 𝛼)2/3
1 − (1 − 𝛼)1/3
D1
1/2𝛼
𝛼2
Valesi, two-dimensional diffusion
D2
[−ln(1 − 𝛼)]−1
(1 − 𝛼) ln(1 − 𝛼) + 𝛼
Jander, three-dimensional diffusion
D3
(3/2)(1 − 𝛼)2/3 [1 − (1 − 𝛼)1/3 ]−1
[1 − (1 − 𝛼)1/3 ]2
Ginstling–Brounshtein,
D4
(3/2)[(1 − 𝛼)−1/3 − 1]−1
1 − 2𝛼/3 − (1 − 𝛼)2/3
First order
F1
1−𝛼
−ln(1 − 𝛼)
Second order
F2
(1 − 𝛼)2
(1 − 𝛼)−1 − 1
Third order
F3
2(1 − 𝛼)3
[(1 − 𝛼)−2 − 1]/2
Model Accelerating type Exponential law Sigmoidal type Nucleation models
Decelerating type Geometrical contraction models
Diffusion models Parabolic law, one-dimensional diffusion
three-dimensional diffusion Reaction-order models
40
Table 6 Kinetic parameters obtained for the decomposition process of mercury species using different decelerating models. Model
𝐸𝛼 (kJ/mol)
𝑙𝑜𝑔𝐴 (min-1)
R2
R2
55.6 ± 1.1
3.93 ± 0.18
0.9947 ± 0.0008
R3
59.3 ± 1.1
4.15 ± 0.18
0.9972 ± 0.0013
D1
101.2 ± 1.8
8.27 ± 0.17
0.9817 ± 0.0009
D2
112.9 ± 2.0
9.21 ± 0.18
0.9916 ± 0.0003
D3
127.8 ± 2.4
10.10 ± 0.19
0.9977 ± 0.0012
D4
117.8 ± 2.2
9.06 ± 0.18
0.9946 ± 0.0005
F1
67.2 ± 1.3
5.48 ± 0.18
0.9974 ± 0.0024
F2
96.6 ± 1.9
8.6 ± 0.17
0.9688 ± 0.0048
F3
132.8 ± 2.7
12.3 ± 0.23
0.9262 ± 0.0062
41
S0304-3894(16)30885-8 http://dx.doi.org/doi:10.1016/j.jhazmat.2016.09.063 HAZMAT 18069
To appear in:
Journal of Hazardous Materials
Received date: Revised date: Accepted date:
17-6-2016 26-8-2016 27-9-2016
Please cite this article as: Chao Liu, Jinhui Peng, Aiyuan Ma, Libo Zhang, Jing Li, Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst, Journal of Hazardous Materials http://dx.doi.org/10.1016/j.jhazmat.2016.09.063 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Study on non-isothermal kinetics of the thermal desorption of mercury from spent mercuric chloride catalyst Chao Liu a, b, c, d, Jinhui Peng a, b, c, d, Aiyuan Ma a, b, c, d Libo Zhang a, b, c, d,*, Jing Li a, b, c, d
a
State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization, Kunming
University of Science and Technology, Kunming, Yunnan 650093, China b
Yunnan Provincial Key Laboratory of Intensification Metallurgy, Kunming, Yunnan 650093,
China c
National Local Joint Laboratory of Engineering Application of Microwave Energy and
Equipment Technology, Kunming, Yunnan 650093, China d
Faculty of Metallurgical and Energy Engineering, Kunming University of Science and
Technology, Kunming, Yunnan 650093, China
* Corresponding author. E-mail address: [email protected] (L. Zhang) 1
Highlights
Thermal desorption of mercury from spent HgCl2 catalyst is investigated.
Apparent activation energy is revealed as a function of conversion.
Diffusion mechanisms are found to govern the whole process.
A complex process related to mercury release is validated.
2
ABSTRACT Kinetics of the thermal desorption of mercury from spent mercury chloride catalysts were investigated using non-isothermal thermal analysis technique. Complex mercury species absorbed on waste catalysts were revealed by sequential extraction procedure. A scheme of six reactions was applied to elucidate mercury desorption kinetics. Activation energy estimated by model-free isoconversional methods is a slightly increasing function of conversion, implying a variation in the mechanism controlling mercury desorption. Average value of apparent activation energy (116.32 kJ/mol) calculated by isoconversional Starink method was used to determine reaction mechanism using model-fitting and 𝑧(𝛼) master method. One dimensional diffusion appears to govern mercury desorption process in the conversion range of 10%-40%, and then the reaction kinetic is controlled by two and three dimensional diffusion at greater conversion. Key words: Mercury chloride catalysts Mercury desorption Non-isothermal kinetics
1. Introduction
All forms of mercury have been considered as toxic [1]. Mercury containing wastes can constitute a potential threat to the human survival environment as mercury tends to bio-accumulate and cause damage to kidney and central nervous system of 3
living organisms [2-4]. Anthropogenic emissions of mercury should be largely responsible for the mercury contamination. Mercuric chloride supported on activated carbon (HgCl2/AC) used as catalyst for the production of vinyl chloride monomer (VCM) is considered as one of the three largest secondary sources of mercury anthropogenic emissions [5,6]. VCM is an indispensible material for the synthesis of polyvinyl chloride (PVC), which functioned as the second largest general plastic in the fields of industry, agriculture and national defense [7]. The industrial routes for manufacturing VCM are either through oxychlorination process using ethylene made from petroleum as raw material or through hydrochlorination process using acetylene made from coal as raw material with the assistant of HgCl2/AC catalyst [8,9]. In the early 1960s, hydrochlorination process is replaced by oxychlorination process in most developed countries due to the widely exploitation and utilization of inexpensive oil resource. However, hydrochlorination process for manufacture of PVC still prevails in developing countries with abundant coal reserves to date [10]. In order to fundamentally eliminate the harmful and scarce mercury, many efforts have been made to explore non-mercury catalysts to replace the HgCl2/AC catalyst [11-13]. Nevertheless, the development of substitutable catalysts remains at the stage in laboratory [14]. China served as the largest PVC producing country in the world, more than 13 Mt PVC are synthesized based on the acetylene hydrochlorination method per year, which occupies over 70% of the PVC production in China [15,16]. After using for a 4
certain time, HgCl2/AC catalysts will deactivate, yielding waste HgCl2/AC catalysts, which are classified as “high mercury waste” (total Hg content > 260 mg/kg) according to the US Land Disposal Restrictions [6]. Thermal treatment process is recommended by US EPA for “high mercury waste” [17,18]. In fact, chemical preprocessing followed by thermal treatment at a elevated temperature to desorb mercury and retorting process operating in controlled atmosphere were two main methods for handling waste HgCl2/AC catalysts. However, a complete recovery for mercury is actually difficult to be achieved as nearly all the researchers have focused on optimizing process parameters and few studies with regard to thermal desorption mechanisms of mercury species from deactivated HgCl2/AC catalysts are reported. In order to reduce processing costs and enhance mercury recovery to meet the increasing environmental requirement, a deep understanding for desorption kinetics of mercury is indispensable. Model-free and model-fitting methods are commonly used to study thermal decomposition kinetics [19]. Several researchers used these methods to study thermal decomposition of mercury containing wastes. Decomposition of HgCl2 supported on pure activated carbon as well as activated carbon treated with FeCl3 or NaCl has been developed, and it was proved that FeCl3 or NaCl were suitable catalysts for HgCl2 decomposition by decreasing activation energy [20]. Model-free and reaction order methods were used to understand the kinetic parameters and reaction mechanism of the thermal decomposition for mercury waste generated by chlor-alkali plants, and it was found that at 250 oC the process was controlled by D1-diffusion mechanism 5
whereas a combination of the diffusion mechanism (D1) and the third order reaction mechanism (F3) seemed to fit the decomposition kinetics at 450 oC [6]. For studying the thermal desorption of mercury from a contaminated soil, a combination of model-free and model-fitting method was performed to evaluate the activation energy and reaction mechanism respectively using non-isothermal experimental approach [21]. This research aims to elucidate the thermal desorption kinetics of mercury species from the spent HgCl2/AC catalysts using non-isothermal experimental data. A scheme of six reactions with regard to mercury compounds absorbed on waste catalysts was proposed. Apparent activation energy was obtained by model-free methods and served as a useful evaluation for subsequent analysis. Model-fitting method combined with 𝑧(𝛼) master plots method was employed to determine reaction mechanisms. This study intends to obtain kinetic parameters of mercury thermal
desorption
and
a
preliminary
understanding
to
the
complex
multiple-component system of spent catalyst. If possible, further investigations will be done to explore new process and develop novel equipment for disposing of deactivated HgCl2/AC catalysts based on the results obtained from this work. In addition, more work is required to study the complex system of spent catalysts further.
2. Experimental
2.1. Sample and chemical analysis
The spent mercuric chloride catalyst sample used for this study was collected 6
from a chemical plant for producing polyvinyl chloride in China. The catalyst support activated carbon (AC) is derived from coal. In the laboratory, samples were dried at 60 oC to constant weight, followed by ground in an agate mortar to pass through a 75 μm sieve. Deactivated catalyst sample was subject to Toxicity Characteristic Leaching Procedure (TCLP) test for evaluating mercury toxicity levels according to US EPA [22]. A standardized procedure designed for analyzing Hg in coal was used to analyze Hg in spent HgCl2/AC catalyst [23,24]. Inductively coupled plasma optical emission spectrometry (ICP-OES, Leeman labs, America) was used to determine mercury in the solution. The metals content in waste catalyst was quantified using 0.5 g of sample by digestion for 2 h at 150 oC with aqua regia [18], and then, employing ICP-OES. All reagents used were analytical grade. All experiments were carried out in triplicate. Mean value and standard deviations were represented. ICP-OES measurements were performed in triplicate for each solution and averages were reported. The standard solutions were achieved by diluting the 1000 mg/l stock solution to different concentrations. The calibration curve was obtained using 5 points including the blank. Only the calibration curve with correlation coefficient larger than 0.995 was used. The precision expressed as relative standard deviation (RSD) was less than 2%.
2.2. Fractionation of mercury
Sequential extraction procedure is considered as an effective method to identify various species of an element and to determine its gross content in each class. A lot of 7
methods for mercury sequential extraction from soil, sludge and sediment samples have been proposed [25-27]. However, no methods are applied to the sequential extraction of mercury species absorbed on activated carbon or carbon based catalysts. Hall and Pelchat [28] designed a six-step sequential extraction scheme to extract different mercury species from geological samples, which can especially separate HgS from other forms of Hg using 40% HNO3. This method has been used by researchers [24, 29] for fractionating mercury absorbed on chemically modified activated carbons. The extraction experiment in this study was modified by using only 0.1g of sample instead of 1g while maintaining the concentration of extraction reagents. This change aims to increase liquid-solid ratio and then minimize the mercury readsorption onto the sample for its high mercury contents. The extraciton test for 1g of sample was also performed for comparison. Mercury concentration in the extracted solutions was determined using ICP-OES. Tests were carried out in triplicate. Averages and standard deviations were calculated. Standard deviations were represented by error bars.
2.3. Thermal analysis experiments
A Mettler Toledo Star SW 13.00 thermogravimetric analyzer operated in dry nitrogen atmosphere with a flow rate of 20 ml/min, was used for thermal analysis experiments. The sample was heated from room temperature to 1200 oC at four different heating rates of 5, 10, 15 and 20 oC/min. About 20 mg sample passed through a 75 μm sieve was placed in alumina crucible for each experiment.
8
2.4. Thermodynamic analysis
Thermodynamic analysis was carried out by using thermodynamic software FactSage. Thermodynamic parameters, i.e. standard Gibbs free energy change (ΔGo ), standard enthalpy change (ΔH o ) and standard entropy change (ΔS o ) of the reactions proposed based on the sequential extraction results and thermogravimetric analysis were calculated. ΔH o and ΔGo are used to estimate the heat of reactions and probability of occurrence of reactions, respectively.
2.5. Theoretical background of thermal analysis kinetics
The scheme for reactions involved a single solid reactant (e.g. sublimation or decomposition) can be generally described by 𝐴(𝑠) → 𝐵(𝑠) + 𝐶(𝑔)
(1)
Thermal analysis methods are commonly used to study kinetics of thermal decomposition for solid materials. For isothermal experimental data, the reaction rate follows the general law below, 𝑑𝛼 = 𝑘(𝑇)𝑓(𝛼) 𝑑𝑡
（2）
with 𝑇(𝐾) being the absolute temperature, 𝑓(𝛼) being the differential expression of reaction model, the reacted fraction 𝛼 at time 𝑡(𝑚𝑖𝑛) is defined as, 𝛼=
𝑚0 − 𝑚𝑡 𝑚0 − 𝑚∞
（3）
where, 𝑚0 is the initial sample weight, 𝑚𝑡 is the remaining sample weight at time 𝑡, 𝑚∞ is the final sample weight. Substituting 𝑘 (𝑇) according to Arrhenius equation, Eq. (2) can be rewritten as, 9
𝐸𝛼 𝑑𝛼 = 𝐴 𝑒 −𝑅𝑇 𝑓(𝛼) 𝑑𝑡
where,
𝐴(𝑚𝑖𝑛−1 )
represents
the
(4)
pre-exponential
factor,
𝐸𝛼 (kJ/mol)
represents the activation energy, 𝑅(8.314 kJ/mol K) represents gas constant. For evaluating non-isothermal kinetic, heating rate 𝛽 is introduced into Eq. (2) to form the non-isothermal reaction rate expression as follows, 𝑑𝛼 𝐴 − 𝐸𝛼 = 𝑒 𝑅𝑇 𝑓(𝛼) 𝑑𝑇 𝛽
(5)
Integrating both the left and right sides of Eq. (5) in interval 𝑇0 − 𝑇 and 0 − 𝛼 respectively gives the integral reaction model 𝑔(𝛼), 𝛼
1 𝐴 𝑇 − 𝐸𝛼 𝑔(𝛼) = ∫ 𝑑𝛼 = ∫ 𝑒 𝑅𝑇 𝑑𝑇 𝑓(𝛼) 𝛽 𝑇0 0
(6)
Differential Eqs. (4) and (5) and integral Eq. (6) are the basic formulas for studying thermal decomposition kinetics based on the thermal analysis data. Approximations with different precision were proposed for solving the famous 𝑇
temperature integral ∫𝑇 𝑒 −
𝐸𝛼
𝑑𝑇 in Eq. (6) with no analytical solution, leading to the
various integral methods.
2.5.1. Model-free method
Model-free method has attractive characteristics that as can be used to analyze either isothermal or nonisothermal data and the results from isothermal and nonisothermal experiments are internally consistent [29]. It is considered as a reliable approach to obtain kinetic parameters as it can actually reveal thermal decomposition mechanisms at different conversion for system with complex and multiple reactions [30-32]. Model-free methods usually refer to isoconversional methods which evaluate 10
the activation energy at a fixed conversion using multi-curves. It is worth noting that not all model-free methods are isoconversional such as Kissinger method discussed below. The information of the model-free methods used in this paper and corresponding linear equations derived from the general reaction rate formulas with separation of 𝐸𝛼 and other kinetic parameters are listed in Table 1. Plots of the left side of linear equations versus 1/𝑇 at fixed conversion value allow determinating the activation energy from the slope of the fitting line. Note that 𝐸𝛼 obtained by model-free methods is a function of conversion except Kissinger method as it is not isoconversional method.
2.5.2. Evaluation of reaction mechanism
2.5.2.1. Model-fitting method
Only the activation energy values can be obtained by model-free methods whereas model-fitting methods give “kinetic triplet” (𝐸𝛼 , 𝐴 and 𝑓(𝛼)) simutaneously. For non-isothermal data, many model-fitting methods allow evaluation for kinetic parameters wherein Coats–Redfern equation [40] was used in this paper, which shows as follows, 𝑙𝑛[
𝑔(𝛼) 𝐴𝑅 𝐸𝛼 ] = 𝑙𝑛 [ ] − 𝑇2 𝛽𝐸𝛼 𝑅𝑇
(12)
the kinetic mechanism function with good correlation coefficient for the fitting straight line obtained by plotting 𝑙𝑛 *
𝑔(𝛼) 𝑇2
+ vs.
1
at fixed conversion under different
𝑇
heating rate 𝛽 was selected as the reaction model. 11
2.5.2.2. 𝒛(𝜶) master plots method
The use of 𝑧(𝛼) master plots method [40] mainly adopts the following expressions of theoretical and experimental 𝑧(𝛼), 𝑧(𝛼) = 𝑓(𝛼) 𝑔(𝛼) 𝑧(𝛼) = 𝜋(𝑢) =
𝑑𝛼 )𝑇 𝑑𝑡 𝛽
𝜋(𝑢) (
(13) (14)
𝑢3 + 18𝑢2 + 86𝑢 + 96 𝑢4 + 20𝑢3 + 120𝑢2 + 240𝑢 + 120
(15)
Where 𝑢 is 𝐸𝛼 /𝑅𝑇, 𝜋(𝑢) is taken from the forth Senum-Yang approximations of the temperature integral. The plots of 𝑧(𝛼) vs. 𝛼 can be obtained by substituting model expressions considered and experimental data from TG/DTG to Eq. (13) and Eq. (14), respectively. Comparing the experimental curves with theoretical curves allow determination of the best fit model.
3. Results and discussion
3.1. Characteristics of sample
The waste catalyst is considered as hazardous materials with mercury concentration leached by TCLP test being 64.18 mg/L, which is highly greater than the TCLP reference value 0.2 mg/L [20]. Spent HgCl2/AC catalyst is characterized as “high mercury waste” as its total mercury concentration of 3.31 wt% (33100 mg/kg) (Table 2) far exceeds 260 mg/kg according to the US Land Disposal Restrictions [6]. High levels of Ca, Fe, Mg, Al, K and Cl were found in the spent catalyst (Table 2). These are expected as some alkaline and alkaline earth metal chlorides are added to 12
the HgCl2/AC catalyst during the process of catalyst preparation, enhancing catalytic activity and the stability of HgCl2. Ca, Fe, Mg and Al may exist in activated carbon in the oxides forms [22]. Traces of Ce and Ba are also attributed to addition of corresponding metal chlorides to catalyst acting as catalytic additives.
3.2. Sequential extraction procedure
Fig. 1 shows the sequential extraction results for both 0.1g and 1g of sample. It can be seen from Fig. 1 that there is an obvious difference in the extraction ratio at each step between the samples of 0.1g and 1g, especilly in the first two steps. For the sample of 0.1g, 56.35% and 16.62% of mercury were leached in step 1 and step 2, respectively. While there was an opposite tendency for the sample of 1g, only 6.48% of mercury was extracted in step 1, but step 2 extracted 45.56% of mercury. This is likely due to the readsorption of mercury extracted in the leachate onto AC for the sample of 1g and the high mercury content (3.31%, table 2) in the spent catalyst sample, which is much larger than those of literatures [24, 28, 29]. According to Fig. 1, it was proved to be useful to minimize the mercury readsorption by reducing the sample mass from 1g to 0.1g. Therefore the extraction results for the sample of 0.1g were considered as more reliable and were used for subsequent analysis. For sample of 0.1g (Fig. 1), mercury was extracted in each step, indicating the presence of various mercury compounds in the spent catalyst. This reminded us that mercury species absorbed on spent catalyst is not just HgCl2 but the mercury in other forms. About 94% of mercury was leached in the first four steps under weak 13
conditions, indicating highly instability of mercury absorbed on the waste catalyst. Therefore, it is necessary to conduct strict management and storage for spent HgCl2/AC catalyst. The total amount of mercury extracted in all the six steps as a percentage of the mercury determined by the standardized procedure mentioned in section 2.1 was 88.9%. This mass unbalance may be likely due to the testing error of mercury content and volatility of mercury involved in the six-step extraction procedure. However, this result is still acceptable for sequential extraction [29]. The first step was able to extract a majority (56.35%) of the mercury that was in the “easily soluble” forms, attributing to the main component, HgCl2, supported on the catalyst. 16.62% of mercury was extracted by the second step, showing the presence of mercury associated with labile organic phases, possibly carbon deposition. Formation of the carbon deposition on the surface of catalysts used for acetylene hydrochlorination has been observed by researchers [43, 44]. 21.06% of mercury was extracted by the third and fourth step, indicating that a large proportion of mercury was absorbed to Fe/Al oxides, which existed in the catalyst support AC derived from coal [24]. The fifth step extracted only 3.25% of mercury using 40% HNO3, however, it suggested the possibility of presence of elemental mercury, Hg2Cl2 or mercury combined with nonlabile organic phases containing carbon deposits and oxygen functionality in the AC [24]. In general, the existence of Hgo and Hg2Cl2 is derived from the reduction of HgCl2 at the reductive reaction atmosphere during the utilization of HgCl2/AC catalysts. Moreover, HgCl2 tends to form Hg2Cl2 after 14
absorbing on the AC, which is validated by Adams [45] using potentiometric analysis. The presence of hydroquinonic, phenolic and hydrosulphide groups on the surface of the activated carbon can also reduce Hg (II) to Hg (I) [46]. The mercury extracted by the last step proved that a minor fraction of mercury formed HgS, which was likely the deactivation product of HgCl2. Recently, many researchers [47-50] reported that the presence of H2S derived from feed gas can easily lead to the deactivation of catalysts, yielding metal sulfides covered on the surface of reactive metal. This is obvious under the reductive atmosphere such as acetylene for hydrochlorination reaction process [51].
3.3. Thermogravimetric analysis
The thermogravimetry (TG) and differential thermogravimetry (DTG) curves of thermal decomposition of waste catalysts in N2 at different heating rates are shown in Figs. 2a and 2b, respectively. It can be observed that heating rates affect the positions of thermogravimetric curves, and therefore the peak temperatures. When the heating rates increase, initial, maximum and end temperatures of peaks also increase. Take the heating rate 10 oC/min for analysis. The first stage till 150 oC mainly relates to the evaporation of moisture, trace of weak absorbed mercury and some highly volatile impurities may release at this temperature region. These impurities mainly are products derived from the side reaction during the acetylene hydrochlorination process. The second stage corresponding to the temperature range of 150 oC to 380 oC is the major devolatilization zone with weight loss of 11.3%, 15
which can be largely attributed to the thermal desorption of mercury species i.e. Hg2Cl2, HgCl2 and HgS according to the results of sequential extraction procedure. In addition, the desorption temperatures of these mercury species are below 400 oC regardless of matrix according to accessible literature data (Table 3). Carbon deposition and trace of remaining mercury wrapped in AC is possibly responsible for the third region (380-776 oC). The last stage corresponding to the weak peak 3 at the temperatures ranging from 776 oC to 1120 oC is due to the volatilization of metal chlorides e.g. CaCl2, KCl, BaCl2 and CeCl3 [56]. Note that the release of carbon deposition from deactivated HgCl2/AC catalyst may occur throughout the whole heating process either by thermal decomposition or by taking away along with the desorption of mercury. This is explained by the complexity of carbon deposition, which may include crushed carbon dust and various organics with different volatility. Further study is required to recognize the carbon containing species. In this study, kinetic analysis is conducted at the temperature interval 150-400 o
C representing the main thermal decomposition region of mercury species [21,
52-55].
3.4. Thermodynamic analysis of the potential reactions
A scheme of six reactions with regard to mercury species is proposed to elucidate mercury desorption kinetics (Table 4). Note that R(1) and R(2) may occur in series. Thermodynamic parameters were calculated at the temperature of 400 oC representing the end temperature of reactions for kinetic analysis. The positive values of ΔH o
16
imply that all the reactions are endothermic. Generally, the negative value of ΔGo indicates the reaction can proceed spontaneously. According to Table 4, only the two phase change reactions R(4) and R(6) presented negative ΔGo . However, this cannot indicate that other reactions do not have the potential to occur below 400 oC as the partial pressures of the gaseous products related to the calculation of ΔGo were assumed as one bar pressure. Actually, the reactions proceeded in a 20 ml/min N2 flow in this study. The actual pressure of gas products is far less than one bar. Thus, the ΔG value will reduce if the actual partial pressure is taken into account. In addition, according to the experimental data from literature available (Table 3), the reactions proposed in table 4 actually were proved to occur below 400 oC.
3.5. Determination of activation energy
All the isoconversional methods mentioned above i.e. Friedman, KAS, FWO and Starink methods were used for kinetic studies to obtain the isoconversion plot of activation energy 𝐸𝛼 with conversion 𝛼 under conversion range of 0.1-0.9 with an increment of 0.05. All methods used show a nice fit to the experimental data with the correlation coefficients greater than 0.99. Plots of the activation energy versus conversion for the considered kinetic methods are shown in Fig. 3. It can be seen from Fig. 3 that the shape of the curves derived from different methods are similar and the activation energy values estimated by Friedman, KAS and Starink methods are almost the same except
FWO method. Similar phenomenon was
observed by
Lopez-Gonzalez [46], who studied the decomposition activation energy of mercury 17
species in contaminated soil and found that the activation values obtained with the FWO method were higher than those obtained by the Friedman method. This may be ascribed to a systematic error associated with the simplified approximation of temperature integral when using FWO method. The activation energy values obtained by Friedman method are slightly greater than KAS and Starink methods. Friedman method is a differential method which is susceptible to experimental noise and thus gives scattered activation energy values. This also has been confirmed in the estimation of decomposition activation energy of rice straw [57]. KAS and Starink methods yield nearly overlapping activation energy values. Average activation energy of 116.3 kJ/mol derived from Starink method with employment of a more precise approximation of temperature integral is used as a global estimation for subsequent analysis. In addition, Kissinger method also gives a good fit to experimental data with linear correlation coefficient being 0.98 and a single activation energy value of 114.9 kJ/mol was obtained, which is very close to the value estimated by Starink method. Fig. 3 visually shows that the activation energy values practically fluctuate as the conversion with a slightly rising trend as a whole, revealing occurrence of complex mechanism during the thermal decomposition process of mercury species. It should be reminded that spent HgCl2/AC catalyst is also a multi-component and poly-disperse system similar to mercury polluted sludge [6], the activation energy values determined cannot represent any individual step, and therefore, the term “apparent” activation energy is used in this study. Nevertheless, the average value of apparent activation energy obtained in this work is slightly greater than that of the 18
decomposition of HgCl2-AC, HgCl2–FeCl3–AC and HgCl2–NaCl–AC with 𝐸𝛼 being 97.5, 95.1 and 99.1 kJ/mol, respectively [20]. This may be possibly ascribed to the more complex system of spent HgCl2/AC catalyst. It is of importance to further study the thermal decomposition of different mercury species supported on waste AC.
3.6. Evaluation of reaction mechanism
3.6.1. Model-fitting methods
Forty-one kinetic models are developed by researchers [58], nevertheless all can be reduced to three major types: accelerating, decelerating, and sigmoidal [42]. Common kinetic models are shown in Table 5. In this study, only decelerating models were considered based on the shape of isothermal experimental conversion curve. Decelerating kinetic model functions (Table 5) and the original data 𝛼, 𝑑𝛼/𝑑𝑇, 𝑇𝛼 from TG–DTG curves under various linear heating rates were substituted into Eq. (7) for calculation. The average value and standard deviation of activation energy, logarithm of pre-exponential factor and correlation coefficient determined from four heating rates using deceleratory models are given in Table 6. It can be seen that the experimental data shows a good fitting to nearly all the models considered whereas only the four diffusion models have 𝐸𝛼 closest to the average value of apparent activation energy (116.32 kJ/mol) estimated by model-free Starink model. Although models D1 and D2 reveal themselves as potential ones by showing good fit to the experimental data, the achieved activation energy seems inferior to that of D4. Because the activation energy (117.8 kJ/mol) determined by D4 is closest to 19
the value (116.32 kJ/mol) obtained by model-free Starink model. In addition, the correlation coefficients of D3 (0.9977) and D4 (0.9946) are also superior to those of D1 (0.9817) and D2 (0.9916). Therefore, D1 and D2 model among all the diffusion models cannot be considered as the best fitting model with combined consideration of correlation coefficient and 𝐸𝛼 . Generally, D3 model with highest correlation efficient should be considered as the optimum fitting model. But further taking into account activation energy, D4 model is superior to D3. Thus there is an ambiguity in selecting a proper model to describe the overall process, suggesting the whole mechanism cannot be predicted by a single rate equation, which may meet distinct mechanism model at different extent of conversion. However, diffusion models with the 𝐸𝛼 closest to that of model-free Starink model show their distinct fitting potential to experimental data than other models evaluated. This may be helpful to determine the most probable model using 𝑧(𝛼) master plots method discussed in the section below.
3.6.2. 𝒛(𝜶) master plots method
Fig. 4 (a) and (b) shows the experimental and theoretical 𝑧(𝛼) curves. The experimental curves for four different heating rates are nearly overlapping whereas they are not in accord with any single model curve estimated. The experimental curves practically conform to different model functions with change of conversion. It is close to the curve of D1 at conversion 0.1-0.4, and then transfers to the curve of D2 and D4. At the conversion greater than 0.6 the decomposition mechanism roughly follows D3 model. D1 model also showed robust fitting to the decomposition of 20
HgCl2 absorbed on AC [20]. The whole reaction course is oriented by diffusion mechanism. These are expected as the mercury species i.e. Hg, HgCl2, Hg2Cl2 and HgS are prone to sublimate or decompose at the temperature interval of peak two in the DTG pattern while diffusion is blocked by gas products, pores of AC and carbon deposition. The temperature corresponds to conversion 0.4 is 282-297 oC for different heating curves, which is on the verge of the peak temperature 285-316 oC. When conversion less than 0.4 the decomposition rate of mercury compounds is slow so that the process only refers to one dimensional diffusion. At higher conversions (>0.4) corresponding to higher temperatures, the decomposition reactions rate increased, with greater release of gaseous products. The reaction process was controlled by two and then three dimensional diffusion, showing increasing diffusion resistance. The best fitting kinetic model cannot be determined by model-fitting method as more than one kinetic model can fit the experimental data well. The utilization of 𝑧(𝛼) master plots can visually reveal the variation of reaction mechanism with conversion, which is especially useful for the complex system of this study. As model-free method involves no hypothesis with regard to any mechanism of the process, it can give the activation energy a precise prediction and assist to determine reaction model. The combined utilization of model-free, model-fitting and 𝑧(𝛼) master plots method to evaluate kinetic parameters is validated to be more efficient than any single method.
21
4. Conclusions
In this study, thermal decomposition kinetics of mercury species from spent HgCl2/AC catalysts were developed. The activation energy values estimated by several model-free methods were compared and the Starink method was found to be more convenient than others in design and prediction procedures. The derived results showed that the thermal desorption of mercury from spent mercury chloride was a complex process. This can be seen from the activation energy as a function of conversion. With the combined utilization of model-fitting and 𝑧(𝛼) master method, it can be concluded that the whole mercury desorption process followed diffusion mechanism, specially with change from D1 to D2 and finally D4 and D3 diffusion. The results can provide theoretical support for optimizing process and developing new equipment for mercury desorption with the diffusion of gaseous products being the key consideration. This may eventually contribute to meeting increasingly strict environmental concerns and reducing costs by selecting proper operating condtions and equipment.
Acknowledgements
This work was supported by National Natural Science Foundation of China (51522405) and Yunnan Provincial Science and Technology Innovation Talents Scheme Technological Leading Talent of China (2013HA002).
22
References
[1] L.D. Hylander, M.E. Goodsite, Environmental costs of mercury pollution, Sci. Total Environ. 368 (2006) 352-370. [2] C. Sonne, R. Dietz, P.S. Leifsson, G. Asmund, E.W. Born, M. Kirkegaard, Are liver and renal lesions in East Greenland polar bears (Ursus maritimus) associated with high mercury levels?, Environ. Health 6 (2007) 11. [3] X.Y.
Zhang,
Q.C.
Wang,
S.Q.
Zhang,
X.J.
Sun,
Z.S.
Zhang,
Stabilization/solidification (S/S) of mercury-contaminated hazardous wastes using thiol-functionalized zeolite and Portland cement, J. Hazard. Mater. 168 (2009) 1575-1580. [4] P. Randall, S. Chattopadhyay, Advances in encapsulation technologies for the management of mercury-contaminated hazardous wastes, J. Hazard. Mater. 114 (2004) 211-223. [5] E.B. Swain, P.M. Jakus, G. Rice, F. Lupi, P.A. Maxson, J.M. Pacyna, A. Penn, S.J. Spiegel, M.M. Veiga, Socioeconomic Consequences of Mercury Use and Pollution, AMBIO: J. Human Environ. 36 (2007) 45-61. [6] Y. Busto, F.M.G. Tack., L.M. Peralta, X. Cabrera, L.E. Arteaga-Perez, An investigation on the modelling of kinetics of thermal decomposition of hazardous mercury wastes, J. Hazard. Mater. 260 (2013) 358-367. [7] F. Wang, L. Wang, J. Wang, Y. Zhao, Y. Wang, D. Yang, Bimetallic Pd-K/Y-zeolite catalyst in acetylene hydrochlorination for PVC production, React. Kinet. Mech. Catal. 114 (2014) 725-734. 23
[8] M. Conte, C.J. Davies, D.J. Morgan, T.E. Davies, D.J. Elias, A.F. Carley, P. Johnston, G.J. Hutchings, Aqua regia activated Au/C catalysts for the hydrochlorination of acetylene, J. Catal. 297 (2013) 128-136. [9] X. Wei, H. Shi, W. Qian, G. Luo, Y. Jin, F. Wei, Gas-Phase Catalytic Hydrochlorination of Acetylene in a Two-Stage Fluidized-Bed Reactor, Ind. Eng. Chem. Res. 48 (2009) 128-133. [10] X. Li, X. Pan, L. Yu, P. Ren, X. Wu, L. Sun, F. Jiao, X. Bao, Silicon carbide-derived carbon nanocomposite as a substitute for mercury in the catalytic hydrochlorination of acetylene, Nat. Commun. 5 (2014) 3688. [11] G. Hutchings, Vapor phase hydrochlorination of acetylene: Correlation of catalytic activity of supported metal chloride catalysts, J. Catal. 96 (1985) 292-295. [12] H. Zhang, B. Dai, W. Li, X. Wang, J. Zhang, M. Zhu, J. Gu, Non-mercury catalytic acetylene hydrochlorination over spherical activated-carbon-supported Au–Co(III)–Cu(II) catalysts, J. Catal. 316 (2014) 141-148. [13] H. Zhang, B. Dai, X. Wang, L. Xu, M. Zhu, Hydrochlorination of acetylene to vinyl chloride monomer over bimetallic Au–La/SAC catalysts, J. Ind. Eng. Chem. 18 (2012) 49-54. [14] L. He, Y. N. Tan, W. Han, Industrial process progress of acetylene to vinyl chloride, J. Chem. Ind. Eng. 34 (2013) 61-65. (in Chinese) [15] K. Zhou, J. Jia, C. Li, H. Xu, J. Zhou, G. Luo, F. Wei, A low content Au-based catalyst for hydrochlorination of C2H2 and its industrial scale-up for future PVC 24
processes, Green Chem. 17 (2015) 356-364. [16] J. Zhang, N. Liu, W. Li, B. Dai, Progress on cleaner production of vinyl chloride monomers over non-mercury catalysts, Front. Chem. Sci. Eng. 5 (2011) 514-520. [17] T.C. Chang, S.J. You, B.S. Yu, C.M. Chen, Y.C. Chiu, Treating high-mercury-containing lamps using full-scale thermal desorption technology, J. Hazard. Mater. 162 (2009) 967-972. [18] Y. Busto, X. Cabrera, F.M. Tack, M.G. Verloo, Potential of thermal treatment for decontamination of mercury containing wastes from chlor-alkali industry, J. Hazard. Mater. 186 (2011) 114-118. [19] A. Khawam, D.R. Flanagan, Basics and applications of solid-state kinetics: a pharmaceutical perspective, J. Pharm. Sci. 95 (2006) 472-498. [20] M. Bentley, M. Fan, B. Dutcher, M. Tang, M.D. Argyle, A.G. Russell, Y. Zhang, M.P. Sharma, S.M. Swapp, Catalytic regeneration of mercury sorbents, J. Hazard. Mater. 262 (2013) 642-648. [21] F.A. López, M.J. Sierra, O. Rodríguez, R. Millán, F.J. Alguacil, Non-isothermal kinetics of the thermal desorption of mercury from a contaminated soil, Rev. Metalurgia 50 (2014) e001. [22] USEPA, Stabilization and Testing of Mercury Containing Wastes: Borden Sludge, 2002, Available from: http://nepis.epa.gov/Exe/ZyPDF.cgi/2000CZ0H.PDF?Dockey=2000CZ0H.PDF (Retrieved 5.16.16) [23] Chinese Standard Testing Method for Hg in coal; GB/T16659- 2008. 25
[24] S. Tong, M. Fan, L. Mao, C.Q. Jia, Sequential extraction study of stability of adsorbed mercury in chemically modified activated carbons, Environ. Sci. Technol. 45 (2011) 7416-7421. [25] C. Gleyzes, S. Tellier, M. Astruc, Fractionation studies of trace elements in contaminated soils and sediments: a review of sequential extraction procedures, Trends Anal. Chem. 21 (2002) 451-467. [26] Y. Han, H.M. Kingston, H.M. Boylan, G.M. Rahman, S. Shah, R.C. Richter, D.D. Link, S. Bhandari, Speciation of mercury in soil and sediment by selective solvent and acid extraction, Anal. Bioanal. Chem. 375 (2003) 428-436. [27] C. Foldi, C.A. Andree, T. Mansfeldt, Sequential extraction of inorganic mercury in dumped blast furnace sludge, Environ. Sci. Pollut. Res. Int. 22 (2015) 15755-15762. [28] G.E.M. Hall, P. Pelchat, The design and application of sequential extractions for mercury, Part 2. Resorption of mercury onto the sample during leaching, Geochem. Explor. Environ. Anal. 5 (2005) 115-121. [29] J.W. Graydon, X. Zhang, D.W. Kirk, C.Q. Jia, Sorption and stability of mercury on activated carbon for emission control, J. Hazard. Mater. 168 (2009) 978-982. [30] S. Vyazovkin, C.A. Wight, Model-free and model-fitting approaches to kinetic analysis of isothermal and nonisothermal data, Thermochim. Acta 340-341 (1999) 53-68. [31] J.R. Opfermann, E. Kaisersberger, H.J. Flammersheim, Model-free analysis of thermoanalytical data-advantages and limitations, Thermochim. Acta 391 (2002) 26
119-127. [32] M.J. Starink, The determination of activation energy from linear heating rate experiments: a comparison of the accuracy of isoconversion methods, Thermochim. Acta 404 (2003) 163-176. [33] H.L. Friedman, Kinetics of thermal degradation of char-forming plastics from thermogravimetry. Application to a phenolic plastic, J. Polymer Sci. 6 (2007) 183-195. [34] H.E. Kissinger, Variation of peak temperature with heating rate in differential thermal analysis, J. Res. Nat. Bur. Stand. 57 (1956) 217. [35] H.E. Kissinger, Reaction Kinetics in Differential Thermal Analysis, Anal. Chem. 29 (1957) 1702-1706. [36] T. Ozawa, A New Method of Analyzing Thermogravimetric Data, Bull. Chem. Soc. Jpn. 38 (1965) 1881-1886. [37] J.H. Flynn, L.A. Wall, General treatment of the thermogravimetry of polymers, J. Res. Nat. Bur. Stand. 70A (1966) 487. [38] J.H. Flynn, L.A. Wall, A quick, direct method for the determination of activation energy from thermogravimetric data, J. Polym. Sci. 4 (1966) 323-328. [39] T. Akahira, T. Sunose, Method of determining activation deterioration constant of electrical insulating materials. Res. Report Chiba Inst. Technol. 16 (1971) 22–23. [40] M.J. Starink, A new method for the derivation of activation energies from experiments performed at constant heating rate, Thermochim. Acta 288 (1996) 97-104. 27
[41] A.W. Coats, J.P. Redfern, Kinetic parameters from thermogravimetric data. II, J. Polymer Sci.
3 (1965) 917-920.
[42] S. Vyazovkin, A.K. Burnham, J.M. Criado, L.A. Pérez-Maqueda, C. Popescu, N. Sbirrazzuoli, ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data, Thermochim. Acta 520 (2011) 1-19. [43] K. Chen, L. Kang, M. Zhu, B. Dai, Mesoporous carbon with controllable pore sizes as a support of the AuCl3 catalyst for acetylene hydrochlorination, Catal. Sci. Technol. 5 (2015) 1035-1040. [44] Q.L. Song, S.J. Wang, B.X. Shen, J.G. Zhao, Palladium-Based Catalysts for the Hydrochlorination of Acetylene: Reasons for Deactivation and Its Regeneration, Pet. Sci. Technol. 28 (2010) 1825-1833. [45] M.D. Adams, The mechanisms of adsorption of Hg(CN)2 and HgCl2 on to activated carbon, Hydrometallurgy 26 (1991) 201-210. [46] J.D.D.
Lopez-Gonzalez,
C.
Moreno-Castilla,
A.
Guerrero-Ruiz,
F.
Rodriguez-Reinoso, Effect of carbon-oxygen and carbon-sulphur surface complexes on the adsorption of mercuric chloride in aqueous solutions by activated carbons, J. Chem. Technol. Biotechnol. 32 (1982) 575-579. [47] G.J. Hutchings, D.T. Grady, Hydrochlorination of acetylene: The effect of mercuric chloride concentration on catalyst life, Appl. Catal. 17 (1985) 155-160. [48] C.H. Bartholomew, Mechanisms of catalyst deactivation, Appl. Catal. B 212 (2001) 17-60. 28
[49] W. Fitzharris, J.R. Katzer, W.H. Manogue, Sulfur deactivation of nickel methanation catalysts, J. Catal. 76 (1982) 369-384. [50] A.M. Beale, E.K. Gibson, M.G. O’Brien, S.D.M. Jacques, R.J. Cernik, M.D. Michiel, P.D. Cobden, Ö. Pirgon-Galin, L.v.d. Water, M.J. Watson, B.M. Weckhuysen, Chemical imaging of the sulfur-induced deactivation of Cu/ZnO catalyst bodies, J. Catal. 314 (2014) 94-100. [51] B. Dai, C. Zhang, L. Kang, M. Zhu, Poisoning effect of H2S on catalytic performance of AuCl3/AC in acetylene hydrochlorination, CIESC Journal 66 (2015) 3476-3482. (in Chinese) [52] M. Sedlar, M. Pavlin, A. Popovič, M. Horvat, Temperature stability of mercury compounds in solid substrates, Open Chem. 13 (2014). [53] A.T. Reis, J.P. Coelho, S.M. Rodrigues, R. Rocha, C.M. Davidson, A.C. Duarte, E. Pereira, Development and validation of a simple thermo-desorption technique for mercury speciation in soils and sediments, Talanta 99 (2012) 363-368. [54] M. Rumayor, M.A. Lopez-Anton, M. Díaz-Somoano, M.R. Martínez-Tarazona, A new approach to mercury speciation in solids using a thermal desorption technique, Fuel 160 (2015) 523-530. [55] C. Raposo, C.C. Windmöller, W.A. Durão Júnior, Mercury speciation in fluorescent lamps by thermal release analysis, Waste Manag. 23 (2003) 879-886. [56] W.M. Haynes, CRC handbook of chemistry and physics. CRC press, 95th ed., Boca Raton, 2014. [57] G. Mishra, T. Bhaskar, Non isothermal model free kinetics for pyrolysis of rice 29
straw, Bioresour. Technol. 169 (2014) 614-621. [58] R.Z. Hu, Q.Z. Shi, Thermal Analysis Kinetics, Science Press, Beijing, 2001. (in Chinese)
30
Fig. 1. Mercury extraction by each step shown as a percentage of total mercury extracted for both 0.1g and 1g of spent catalyst sample. The mercury species extracted and corresponding extraction conditions for each step are as follows: (step 1) soluble and exchangeable using 0.01 mol/L Ca(NO3)2, (step 2) labile organic using 0.1 mol/L Na4P2O7, (step 3) amorphous Fe/Al oxides using 0.25 mol/L NH2OH·HCl in 0.25 mol/L HCl, (step 4) crystalline Fe/Al oxides using 1 mol/L NH2OH·HCl in 25% CH3COOH, (step 5) non-labile organic and elemental Hg using 6.4 mol/L (40%) HNO3, and (step 6) HgS and residual, using aqua regia. Error bars represent standard deviations of three repeated experiments.
31
Fig. 2a. TG curves of spent HgCl2/AC catalyst at different heating rates.
Fig. 2b. DTG curves of spent HgCl2/AC catalyst at different heating rates.
32
Fig. 3. The estimated values of activation energy as a function of conversion.
33
Fig. 4. Comparasion of experimental and theoretical z(α) master plots: (a) model curves (D1, D2, D3 and D4) and experimental curves at different heating rates (EXP); (b) model curves (F1, F2, F3, R2 and R3) and experimental curves at different heating rates (EXP). Different model curves 34
are presented in two sub-figure (a) and (b) for clear identification. (Note that D1, D2, D3, D4, F1, F2, F3, R2 and R3 are the symbols of decelerating kinetic models reported in Table 5)
35
Table 1 Several commonly used model-free methods and corresponding linear equations. Method
Linear equation
Friedman
𝑙𝑛[𝛽(
𝑑𝛼 𝐸𝛼 )] = 𝑙𝑛[𝐴𝑓(𝛼)] − 𝑑𝑇 𝑅𝑇 𝛽 𝐴𝑅 ′ 𝐸𝛼 𝑙𝑛[ 2 ] = 𝑙𝑛 [− 𝑓 (𝛼𝑚 )] − 𝑇𝑚 𝐸𝛼 𝑅𝑇𝑚
Kissinger
𝐴𝐸𝛼 𝐸𝛼 𝑙𝑛𝛽 = 𝑙𝑛[ ] − 5.331 − 1.052 𝑅𝑔(𝛼) 𝑅𝑇
Flynn Wall Ozawa (FWO) Kissinger
Akahira
and
Sunose
𝑙𝑛[
𝛽 𝐴𝑅 𝐸𝛼 ] = 𝑙𝑛[ ]− 𝑇2 𝐸𝛼 𝑔(𝛼) 𝑅𝑇
Equation number
Reference
(7)
[33]
(8)
[34,35]
(9)
[36-38]
(10)
[34,35,39]
(11)
[40]
(KAS) Starink
𝛽 𝐸𝛼 𝑙𝑛 ( 1.92 ) = 𝐶𝑜𝑛𝑠𝑡. −1.0008 ( ) 𝑇 𝑅𝑇
36
Table 2 Main element contents of spent catalyst sample. Element
Total Content (%)*
Hg
3.31 ± 0.25
Ca
1.55 ± 0.12
Fe
1.08 ± 0.10
Mg
0.39 ± 0.05
Al
0.31 ± 0.08
K
0.17 ± 0.03
Cl
2.12 ± 0.05 Total Content (mg/kg) *
Ce
388 ± 18
Ba
33 ± 4
*means ± standard deviations (n = 3).
37
Table 3 Available literature data about the thermal desorption temperature of mercury compounds in N2 flow at atmospheric pressure. Mercury
Desorption temperature region (oC), peak temperature (oC)
Hgo
25-180, 150
Hg2Cl2
50-300, 75
HgCl2
50-300, 75
61-154, 110
125-225, 180
135
HgS
170-450, 313
252-343, 305
225-325, 300
303
Matrix
None
Contaminated soils
Aluminium oxide
Silica and carbon
Reference
[52]
100-250, 225
[21]
[53]
[54]
150-340, 275
Phosphorus powder [55]
38
Table 4 Equations and thermodynamic parameters for reactions related to potential mercury species absorbed on waste HgCl2/AC catalyst. Reaction
Reaction
Reference
Number
o ΔH400 oC
o ΔG400 oC
o ΔS400 oC
(kJ/mol)
(kJ/mol)
(kJ/mol K)
Hg2 Cl2 (s) = Hgo (g) + HgCl2(s)
R(1)
[55]
92.85
12.26
0.12
HgCl2 (s) = Hgo (g) + Cl2 (g)
R(2)
[55]
283.13
124.60
0.24
2HgS (s) = 2Hgo (g) + S2 (g)
R(3)
[52] [55]
340.26
85.06
0.38
HgCl2 (s) = HgCl2(g)
R(4)
[6]
76.87
-14.28
0.14
HgS (s) = HgS (g)
R(5)
[6]
171.14
67.58
0.15
Hgo (l) = Hgo (g)
R(6)
[6]
58.93
-3.99
0.09
39
Table 5 Common kinetic model functions expressions 𝑓(𝛼) and 𝑔(𝛼) for solid state thermal decomposition reactions. Symbol
Differential form 𝑓(𝛼)
Integral form 𝑔(𝛼)
E1
𝛼
ln𝛼
Avarami-Erofe’ev
A2
2(1 − 𝛼)[−ln(1 − 𝛼)]1/2
[−ln(1 − 𝛼)]1/2
Avarami-Erofe’ev
A3
3(1 − 𝛼)[−ln(1 − 𝛼)]2/3
[−ln(1 − 𝛼)]1/3
Avarami-Erofe’ev
A4
4(1 − 𝛼)[−ln(1 − 𝛼)]3/4
[−ln(1 − 𝛼)]1/4
Contracting area
R2
2(1 − 𝛼)1/2
1 − (1 − 𝛼)1/2
Contracting volume
R3
3(1 − 𝛼)2/3
1 − (1 − 𝛼)1/3
D1
1/2𝛼
𝛼2
Valesi, two-dimensional diffusion
D2
[−ln(1 − 𝛼)]−1
(1 − 𝛼) ln(1 − 𝛼) + 𝛼
Jander, three-dimensional diffusion
D3
(3/2)(1 − 𝛼)2/3 [1 − (1 − 𝛼)1/3 ]−1
[1 − (1 − 𝛼)1/3 ]2
Ginstling–Brounshtein,
D4
(3/2)[(1 − 𝛼)−1/3 − 1]−1
1 − 2𝛼/3 − (1 − 𝛼)2/3
First order
F1
1−𝛼
−ln(1 − 𝛼)
Second order
F2
(1 − 𝛼)2
(1 − 𝛼)−1 − 1
Third order
F3
2(1 − 𝛼)3
[(1 − 𝛼)−2 − 1]/2
Model Accelerating type Exponential law Sigmoidal type Nucleation models
Decelerating type Geometrical contraction models
Diffusion models Parabolic law, one-dimensional diffusion
three-dimensional diffusion Reaction-order models
40
Table 6 Kinetic parameters obtained for the decomposition process of mercury species using different decelerating models. Model
𝐸𝛼 (kJ/mol)
𝑙𝑜𝑔𝐴 (min-1)
R2
R2
55.6 ± 1.1
3.93 ± 0.18
0.9947 ± 0.0008
R3
59.3 ± 1.1
4.15 ± 0.18
0.9972 ± 0.0013
D1
101.2 ± 1.8
8.27 ± 0.17
0.9817 ± 0.0009
D2
112.9 ± 2.0
9.21 ± 0.18
0.9916 ± 0.0003
D3
127.8 ± 2.4
10.10 ± 0.19
0.9977 ± 0.0012
D4
117.8 ± 2.2
9.06 ± 0.18
0.9946 ± 0.0005
F1
67.2 ± 1.3
5.48 ± 0.18
0.9974 ± 0.0024
F2
96.6 ± 1.9
8.6 ± 0.17
0.9688 ± 0.0048
F3
132.8 ± 2.7
12.3 ± 0.23
0.9262 ± 0.0062
41