R. López¹, I. Cabeza¹, J. R. Lock-Wah-Hoon¹, I. Giráldez ², M. Ruíz³, M. J. Díaz³

¹ Instituto de Recursos Naturales y Agrobiología de Sevilla-CSIC, Avda. Reina Mercedes 10, 41012 Sevilla. rlnunez@irnase.csic.es.

² Departamento de Química y Ciencia de los Materiales, Facultad de Ciencias Experimentales, Univ. de Huelva, Campus Universitario El Carmen, Avenida de las Fuerzas Armadas, 21071-Huelva.

³ Departamento de Ingeniería Química, Química Física y Química Orgánica, Facultad de Ciencias Experimentales, Univ. de Huelva, Campus Universitario El Carmen, Avenida de las Fuerzas Armadas, 21071-Huelva.

Keywords: Volatile organic compounds, terpenoid

Abstract

The volatile organic compound (VOC) α-pinene, one of the most abundant component emitted during the composting of urban waste (MSW) and pruning waste (P), was treated in biofilters filled up with a MSW compost or a MSW+P compost. A photoionization detector was used to carry out the monitoring of the biofilters efficiency but GC-MS and an electronic nose were also used for the process study. Moisture content in biofilters below 66% (dw, MSW) or 51% (dw, MSWP) made efficiency decrease to less than 90%. GC-MS spectra indicated no intermediate products from α-pinene degradation appeared but e-nose data indicates a “smell” corresponding to S-compounds produced in MSW biofilter. These results show that electronic noses could become a powerful tool for the monitoring of VOC compounds in biofiltering and composting processes.

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1. Introduction

The composting facilities are an important source of unpleasant odours which produce the non-acceptance of this installations by the community and may entail health problems and affect the quality of life of the workers and the habitants belonging to the surroundings of these plants ( Tsai et al., 2008). The most important group of pollutants associated to this smells are the volatile organic compounds (VOCs) produced during the biodegradation of organic residues. Since the compounds emitted during composting have a natural origin, are expected to be susceptible to experiment biodegradation. In this way, the biofiltration is considered an advantageous system for deodorisation and the treatment of VOCs due to its low operative costs and the absent of secondary residues (Schlegelmilch et al., 2005). In the composting process, the family of terpenes is one of the more representative class of VOCs emitted from different vegetal materials, among them, the α-pinene is frequently the predominant compound, representing from 10,2 to 72,7 % of the total emissions (Büyüksönmez and Evans, 2007).

Biofilters monitoring is usually carried out using GC/MS and olfactometric techniques, when odours quantification is required ( Chen et al., 2008; Delgado-Rodríguez et al., 2011). Previous works have demonstrated the advantages of the use of electronic noses to monitor the processes that involve VOCs and odours (Littarru, 2007). Also, some practical instruments like the photoionization detector (PID) have been proposed to obtain rapid information on the concentration of VOCs in different processes ( Delgado-Rodríguez et al., 2010).

In this work, the removal efficiency of two kind of biofilters using MSW and MSW-Prunning residues composts as packing materials to treat an artificial stream of gases containing α-pinene is studied. This evaluation is performed with the support of several analytical techniques like VOC analyser, electronic nose and GC/MS. The influence of the biofilters moisture content in the operation efficiency of the biological technique was specifically evaluated.

2. Materials and Methods

2.1 Experimental Design

The biofiltration system consisted of two biofilters using as packing material two different mature composts. One biofilter was filled with MSW compost and the other one with compost from MSW:Pruning Residues (MSWP) in a volumetric ratio 1:1. Additional details about the composting carried out to obtain the biofilter media are published in Delgado-Rodríguez et al. (2010). In all cases, the particle size ranged from 7 to 20 mm. Selected physico-chemical characteristics of the packing materials are shown in Table 1.

At the beginning of the experiment, the packing materials were saturated with water. Later, during the course of the experiment the moisture content of the materials was adjusted periodically, depending of the stage of the assay, by the weight difference of the complete biofilter bed to the initial. The moisture content was expressed on a dry weight basis (d.w) to be able to compare both kinds of biofilter media.

Each biofilter consisted in a PVC tube of 11 cm diameter and 1 m height. The upper part of 95 cm height (bed volume 9.0 L) was filled with the compost. The inlet gas stream was supplied from the bottom of the column (ascending flow).

The pressurized air was obtained using an oil-free compressor. Subsequently and depending of the stage of the experiment, the air was pre-humidified by sparging the stream in a reservoir filled with water. A portion of the humidified air stream was fed to a sparger, which contained liquid α-pinene (Merck, >95% purity).

The inlet concentration of the contaminant was adjusted by the flow rate of the gas stream containing α-pinene. Finally, the main line of contaminated air was divided into two lines feeding each biofilter. Also, a sampling port was set in the inlet stream of the biofilters. The empty bed residence time (EBRT) was adjusted to 66±3 s. Each day, the concentration of the contaminant was maintained during 6-8 hours. The average of this concentration during all the stages of the assay was 11.6 ppm_v of α-pinene.

Table 1 . Physico-chemical properties of the compost used in the biofiltration system (average of 4 replicates ± standard deviation))

The experiment was separated in different stages modifying some operative conditions of the system proposed: a) Days 1-40: α-pinene concentrations below 5 ppm_v with maximum moisture content of the packing materials; b) Days 80-144: Increase of the inlet concentration of α-pinene in the inlet stream until a maximum of 1600 ppm_v; c) Days 154-184: Decrease of the moisture content of the biofilter media maintaining constant the α-pinene concentration.

2.2 Analytical Determinations

The in situ measurements of the α-pinene concentrations in the different sampling ports were carried out using a portable VOCs analyser fitted with a 10.6 eV lamp for photo-ionization (MULTIRAE IR, PGM-54, RAE systems, San José, CA, USA). The sensibility of this instrument is 0.1 ppm_v. Previous experiments have employed this instrument to obtain semi-quantitative information of the VOCs mixtures emissions with good results ( Karlik et al., 2002; Ojala et al., 2006). Having in mind that the unique contaminant present in the streams is α-pinene, the response of the PID detector is directly proportional to its concentration. Although the instrument was calibrated with isobutylene, all the readings obtained were transformed to α-pinene concentrations using the correction factor 0.31 (RAE_Systems, 2002).

The sampling ports of gas were placed immediately before the inlet stream of contaminated air and in the output of each biofilter. Gas samples were taken from the lines by means of and internal sampling pump with a flow rate of 0.150 Lmin-1. The readings were register during each sampling when signal stabilisation was observed, usually in a time less than 30 s. This instrument does not detect water but its condensation on UV lamp could provoke variations of the signal obtained (Ojala et al., 2006). With the purpose to avoid this problem, sampling lines were kept to a minimum and a teflon filter (0.2 µm pore size) was used as a water and particulate material trap. Each day, three replicate of readings, with intervals of one hour, associated to each sampling port were obtained. Also, a portable electronic nose provided with an array of 10 different metal oxide sensors (MOS) (Airsense Analytics GmbH, Hagenover, Schwerin, Germany) was used as a monitoring instrument for the biofiltration system.

The large data sets from e-nose were elaborated through statistical multivariate methods such as Principal Component Analysis (PCA) and Discriminant Analysis (DFA) for data reduction. Each measurement was made three times to obtain enough replicates, as well as readings of the ambient air (blank) near to the feed-point of the compressor used in the experiment. The time necessary to achieve signal stabilisation was about 60 s for all the range of α-pinene concentrations. The set of data for the statistical analysis selected were the corresponding to the 50 to 60 s of the sampling time. Although were realized several samplings and measurements, the PCA analysis in this case was done using samples collected the day 24/10/2011 which corresponds to the day 223 of the experiment.

The GC/MS analyses were done using samples corresponding to the day 184 of the experiment.

3. Results and Discussion

In the Fig. 1 is represented the performance of the packing materials used in the biofiltration system proposed, during the first two stages of the experiment. In the first stage of the assay (1-40 days), the moisture of the biofilters bed was adjusted in the range of 112-101% (dw) and 100%-89% (dw) for MSW biofilter and MSW-P biofilter respectively. During this period, the acclimation of the system occurred. Specifically, the MSW biofilter needed around 10 days to reach removal efficiencies greater than 90 % and the MSW-P biofilter took 25 days to reach 80 % of α-pinene removal efficiency. These acclimation periods were higher that the reported by Bagherpour et al. (2005) using a biofilter filled with compost-woodchips, the time in this case was 2 days, due to the previous aging of the raw materials during 6 months. Otherwise, others researchers reported periods of acclimation around 1-2 months in the biofiltration of α-pinene (Van Groenestijn and Liu, 2002). This indicates that starts up periods between 10 to 25 days must be considered as normal in biofiltration systems using natural packing materials.

In the next stage of the experimentation (days 80-144), the α-pinene concentration in the inlet stream of gas was progressively raised. The removal efficiency of the biofilters in the system decrease to less than 90 % for α-pinene concentrations greater than 30 ppm_v. After the sharp decline of the efficiency in the system from day 121, which corresponds to the higher inlet concentrations, it was observed a better performance for the biological treatment of α-pinene by the MSW-P based biofilter. Specifically, when the mean concentration of the contaminant in the inlet stream was 672 ppmv, the average efficiency was 33.8 % and 48.4 % in the MSW and MSWP biofilter respectively. These values correspond to an elimination capacity of α-pinene by the system of 79 g.m^-3 bed media.h^-1 (MSW biofilter) and 113 g.m^-3 bed media.h^-1 (MSWP biofilter)

Mohseni and Allen (2000 ) reported lower elimination capacities (40-45 g.m-3 bed media.h-1) of α-pinene using similar packing materials (woodchips-mushroom compost), employing an EBRT of 20 s, inlet concentrations of 109 ppm_v, and reaching removal efficiencies around 95 %. Bagherpour et al. (2005) reached values for this efficiency parameter of 227 g m^-3 bed media.h^-1 with removal efficiency values of 95 %.

In the third phase of the experiment which corresponds to the 154 and 184 days of experimentation (Fig. 2) the moisture content of the packing materials used in the biofilters was reduced progressively, removing the pre-humidification unit. In this case, the inlet concentration of α-pinene was set at 17 ppmv. The acclimation time after the transition phase of the experiment, corresponding to the modifying of the moisture content, was 3 days. Afterwards this period of time, when the moisture content was 77% (d.w) and 91 % (d.w) for the MSW and the MSW-P biofilter respectively, the removal efficiency values for both biofilters were 100 %. Nevertheless, when the moisture content of the beds was set below 66 % (d.w) for the MSW and 51 % (d.w) for the MSW-P, removal efficiency values never exceed 90 %.

These results allow concluding that the optimum range of moisture content, for the packing materials and the EBRT used in this experiment, were between 112-66 % (d.w) in the case of the MSW biofilter and between 100-51 % (d.w) for the MSW-P biofilter. These values coincide with previous works where the minimum moisture content suggested for the composts utilised as biofilter bed was 66 % (d.w) (40 % (w.w)).

The GC/MS analysis realised corresponds to different samples with a concentration of α-pinene of 17.6 ppmv in the inlet stream, 0 ppmv in the output sampling port of the MSW biofilter and 10.4 ppmv in the output of the MSW-P biofilter. In any case, the chromatographs did not detect any compound related to a partial degradation of the α-pinene in the biofiltration system or a natural emission of VOCs coming from the biofilter natural materials.

In the Fig. 3 is represented the Principal Components Analysis (PCA) carried out using the data sets obtained with the commercial electronic nose. During this sampling, the moisture content of the biofilters was 57.5 % (d.w) for the MSW biofilter and 43.5 % (d.w) for the MSW-P biofilter. Due to the low moisture content of the materials,the removal efficiency found in the MSWP biofilter was reduced considerably: The inlet air contained 7.8 ppm_v of α-pinene, the output of the MSW biofilter 0.2 ppm_v (Removal efficiency of 98%) and the output stream of the MSW-P biofilter 4.3 ppm _v (Removal efficiency of 45%). Also, in this statistical analysis was included the samples coming from ambience air. By other hand, the sensors included in the analysis were the hydrogen (W6S), the sulphur-organic (W1W) and the methane-aliphatic sensor (W3S) which had more importance in the analysis to describe the system.

The Fig. 3 shows that the MSW-P biofilter and the input samples are poorly separated between them and clearly separated of the air and the MSW biofilter samples. This differentiation of classes was mainly due to the W6S and the W1W sensors responsible for the differences along the χ axis.

Having in mind that these compounds are not related directly with the α-pinene, whose chemical structure appears in the Fig.3, the differentiation between the samples could be due to a natural emission of compounds belonging to these groups by the biofilter, generating a characteristic smell fingerprint associated to each packing material. It is important to notice that these compounds were not detected by the GC/MS technique. The hydrogen could be associated to anaerobic conditions and its presence can be due to saturated zones of moisture inside the biofilter. The differences in the vertical axis, with a few associated variance, are influenced by the sensor W3S-methane and aliphatics which are families of compounds widely found using the GC/MS technique.

Figure 3. Principal Components Analysis (PCA) carried out using the data sets obtained with a commercial electronic nose after 223 days and structure of α-pinene.

4. Conclusions

The moisture content affects seriously the removal efficiency of a biofiltration system using different compost as packing materials. The acclimation periods necessary to reach high removal efficiency in this case were moderate (10 days for MSW biofilter and 25 days for the MSW-P). Once the maximum efficiency was reached, this was affected proportionally when the moisture was reduced to values under 66 % d.w (MSW) or 51 d.w (MSW-P).

In general terms, the MSW-P biofilter showed a higher efficiency in the different phases of the experiment. The GC/MS results did not detect any compound related to a partial degradation of the α-pinene in the biofiltration system, although the electronic nose data analysis showed that the MSW biofilter, even during complete degradation of the α-pinene, emitted a “smell”, not detected by the GC/MS and that is therefore “very subtle”. This last, could be attributed to organic compounds with sulphur in its structures and to anaerobic micro-zones in the biofilter.

5. Acknowledgements

The authors acknowledge financial support from the CICYT (Science, technology Inter Ministerial commission, Spanish Goverment-cofinanced FEDER), project number CTM2007-62117/TECNO. Special thanks to the European Social Fund (ESR) and the Ministry of Economy and Competiveness of Spain for funding the Cabeza I.O Ph.D grant.

6. References

Bagherpour, M.B., Nikazar, M., Welander, U., Bonakdarpour, B., Sanati, M., 2005. Effects of irrigation and water content of packings on alpha-pinene vapours biofiltration performance. Biochemical Engineering Journal 24, 185-193.

Büyüksönmez, F., Evans, J., 2007. Biogenic Emissions from Green Waste and Comparison to the Emissions Resulting from Composting Part II: Volatile Organic Compounds (VOCs)." Compost Science & Utilization. 2007. Compost Science & Utilization 15, 191-199.

Chen, L., Hoff, S.J., Koziel, J.A., Cai, L., Zelle, B., Sun, G., 2008. Performance evaluation of a wood-chip based biofilter using solid-phase microextraction and gas chromatography–mass spectroscopy–olfactometry. Bioresource Technology 99, 7767-7780.

Delgado-Rodríguez, M., Ruiz-Montoya, M., Giraldez, I., Cabeza, I.O., López, R., Díaz, M.J., 2010. Effect of control parameters on emitted volatile compounds in municipal solid waste and pine trimmings composting. Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering 45, 855-862.

Delgado-Rodríguez, M., Ruiz-Montoya, M., Giraldez, I., López, R., Madejón, E., Díaz, M.J., 2011. Influence of Control Parameters in VOCs Evolution during MSW Trimming Residues Composting. Journal of Agricultural and Food Chemistry 59, 13035-13042.

Karlik, J.F., McKay, A.H., Welch, J.M., Winer, A.M., 2002. A survey of California plant species with a portable VOC analyzer for biogenic emission inventory development. Atmospheric Environment 36, 5221-5233.

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Mohseni, M., Allen, D.G., 2000. Biofiltration of mixtures of hydrophilic and hydrophobic volatile organic compounds. Chemical Engineering Science 55, 1545-1558.

Morales, M., Hernández, S., Cornabé, T., Revah, S., Auria, R., 2003. Effect of Drying on Biofilter Performance:  Modeling and Experimental Approach. Environmental Science & Technology 37, 985-992.

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