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Long-term sub second-response monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry
Author’s Accepted Manuscript Long-term sub second-response monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry Wei Huang, Weiguo Wang, Chuang Chen, Mei Li, Liying Peng, Hang Li, Jiwei Liu, Keyong Hou, Haiyang Li www.elsevier.com/locate/talanta
PII: DOI: Reference:
S0039-9140(17)30799-3 http://dx.doi.org/10.1016/j.talanta.2017.07.076 TAL17775
To appear in: Talanta Received date: 31 March 2017 Revised date: 19 July 2017 Accepted date: 24 July 2017 Cite this article as: Wei Huang, Weiguo Wang, Chuang Chen, Mei Li, Liying Peng, Hang Li, Jiwei Liu, Keyong Hou and Haiyang Li, Long-term sub secondresponse monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry, Talanta, http://dx.doi.org/10.1016/j.talanta.2017.07.076 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 galley proof before it is published in its final citable 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.
Long-term sub second-response monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry Wei Huang 1, Weiguo Wang 1, Chuang Chen 1, Mei Li 1, 3, Liying Peng 1, 3, Hang Li 2, 3, Jiwei Liu 1, 4, Keyong Hou 1, Haiyang Li1* 1. Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, People’s Republic of China 2. Anhui Institute of Optics and Fine Mechanics, Key Laboratory of Environmental Optics and Technology, Chinese Academy of Sciences, Hefei 230031, People’s Republic of China 3. University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China 4. Liaoning Normal university, Dalian, 116029, People’s Republic of China
* E-mail: [email protected]. Tel: +86-411-84379510. Fax: +86-411-84379517.
Abstract: A real-time dynamic measurements of ammonia (NH3) is crucial for understanding the atmospheric nucleation process. A novel method was developed for on line monitoring at the sub-second time scale for the gaseous ammonia in ambient air for months, based on a positive inhaling ion mobility spectrometry (IMS) with a 63Ni ion source. The selective detection of NH3 was achieved using a high resolution IMS with an optimization of the drift tube temperature above 150 oC. This method improved the peak-to-peak resolution significantly, thus avoided the interferences of the adjacent peaks to the quantitative analysis of NH3. The time resolution of the IMS was less than 0.1 s at a data averaging of 10 times. The limit of detection (LOD) achieved at sub-ppb level while a linear response of peak intensity
versus concentration of NH3 in the range of 10 – 60 ppb and 60 – 400 ppb were obtained. The relative standard deviations (RSD), the confidence level and the errors were 1.06%, 95% and ±0.21 ppb by measuring 100 ppb NH3 for 100 times. The effect of ambient humidity could be greatly reduced using the drift temperature of over 150 o
C. At last, the application of measuring the NH3 concentration evolutions of Dalian
city was performed from June 19 to December 3 in 2015. The results illustrated a potential method of using IMS for a real-time measurement of ambient NH3 at an unprecedented accuracy and sensitivity with long-term stability.
Keywords: ion mobility spectrometry; ammonia; fast response; sub-second time scale; long-term; monitoring 1. Introduction Ammonia (NH3) plays important role in atmospheric nucleation. For example, atmospherically relevant ammonia mixing ratio of 100 parts per trillion by volume would increase the nucleation rate of sulphuric acid particles more than 100– 1,000-fold [1, 2]. Moreover, through the atmospheric deposition process, large quantities of NH3 get into soil and water, which may lead to eutrophication and acidification that have adverse impact on biological diversity [3, 4]. Due to these negative impacts, advanced apparatus are in need for NH3 concentration monitoring in atmospheric environment. In particular, it would be desirable to develop NH3
concentration measurement instruments enabling continuous operation on line with fast response time. Many methods of measuring NH3 concentration have been developed in recent years. For a long time, off-line method has been widely used to measure NH3 in air, for example, bulk denuder method sampling gaseous NH3 out of the air steam [5]. However, these off-line methods suffered from many disadvantages, such as time-consuming, labor-intensive, sample contamination, and low temporal resolution. After decades of research effort, absorption spectroscopic methods have become more viable due to their sensitivity and practical nature for the NH3 measurement [6, 7]. One of such new on-line approach could determine the NH3 concentration by absorption spectrophotometry method. The limit of detection (LOD) has achieved ppt-level by analyzing the resultant of NH3 transferring to the liquid phase [8]. Chemical ionization mass spectrometry (CIMS) method has also been adopted for NH3 monitoring [9, 10]. In recent years, some inter-comparisons of NH3 measuring methods have been reported. Von Bobrutzki et al. used eleven instruments to measure the ambient NH3 gas in Southern Scotland, such as optical techniques, wet-chemistry systems, photo-acoustic spectrometers and mass spectrometric apparatus, to assess instrument performance and characterize the instrument response times[11]. These instruments exhibit excellent performances in monitoring NH3. However, the high cost of these methods, capital investment or running or both, prevents them from being applied in large-scaled air quality monitoring program. On the other hand, several gas sensor based methods were developed to monitor NH3 concentrations in the ambient air. However, the minimum response time was from seconds to ten minutes with a LOD of several ppb, which is sensitive to monitor source emission NH3 [12, 13]. Due to fast changing condition for the atmospheric environment, such as airflow transport consists of differently sized eddies, as well as many relevant pollutant concentrations, the required pollutant concentration monitoring time scale should be
as short as 0.1 second. However, few monitoring instruments can meet such a short response time requirement. It is well known that ion mobility spectrometry (IMS) has many advantages over the analytical methods mentioned above, such as fast response, high sensitivity, low cost, robustness, and simple operation. IMS technology has been applied in detection of anaesthetic [14-17], narcotic drugs [18], explosives [19, 20] and chemical warfare agents [21, 22]. Currently, there are a few reports about IMS technology for detecting NH3 gas concentrations in the air and from the human breath [23-27]. Compared with the atmospheric environment, the temperature, humidity and ammonia concentration of human breath have smaller changes. Due to the intermittent operation in short time, it is not very suited for atmospheric environment measurements in a long-term. Therefore, an exhaustive and accurate quantification of the ammonia concentration measurement for the atmospheric environment is needed. Firstly, ambient concentrations range of NH3 is very wide, from several ppb in remote areas [28] to several ppm levels near feeding stock facilities [13, 29-31]. Obtaining the NH3 concentration in such a large range accurately is a big challenge. Secondly, as polar compound, NH3 is easy to stick or interact with the surface materials of the path way, which cause slow response and affect NH3 quantifications [7, 11]. Thirdly, as one of the major components of air, moisture may cause interference response to different instruments [13]. Finally, human activity is one of the most important NH3 emission sources [32], which may cause sample contaminations. In this study, a high resolution IMS with 63Ni ion source was constructed and optimized for on line measuring ambient NH3 with sub-second measurement cycle in the air. The operating conditions of instrument were optimized to detect NH3 selectively. The better LODs and larger quantitative measurement range for NH3 were obtained. Then the effect of relative humidity (RH) in the drift gas and sampling environment was studied. In the final section, the method was applied to on-line monitor the atmospheric NH3 in Dalian city.
2. Experimental 2.1. Instrumentation The high resolution ion mobility spectrometer used in this study was designed in our laboratory. Its setup was described in details previously [33]. As shown in Fig. 1, it contained a radioactive 63Ni ion source, an ion gate (Bradbury-Nielsen), a Faraday plate, an amplifier, a drift region and a high voltage supply module. The drift gas was made from the ambient air by an air compressor (Ustar Co., Ltd., Taiwan) and an air purifier which mainly consisted of a soft polyurethane tube (SMC. Co., Ltd., Japan, model TUS 0805), an oil mist filter (SMC. Co., Ltd., Japan, model AMH150C-01C-R), and a container with molecular sieves and activated charcoals. The drift gas and exhaust gas were controlled and measured by two mass flow meters (Beijing Sevenstar Electronics Co., Ltd., China, model D07-7B). 2.2. Chemicals NH3 standard gas (6 ppm, high purity N2 was substrate) was purchased from Dalian Special Gases Co., Ltd. (Da Lian, China). Different concentration NH3 gas for quantification was obtained from on line diluting the NH3 standard gas by clean air, which was controlled by two mass flow meters respectively and mixed in a 2 mm internal diameter PTFE Tube. Pure water was purchased from Wahaha Group Co., Ltd. (Hang Zhou, China). 2.3. Calculations The reduced ion mobility (K) for analyzed peak was calculated by equation 1:[34] K = Kr (tdr/td)
(1)
where tdr and td are the drift times of reference and analyte respectively. The reaction ion peak (RIP, (H2O)nH+) was used as the reference. Its Kr was 2.31 cm2/V·s with a corresponding drift time as 5.44 ms in this study.
The single peak resolution (Rp) is an important parameter to quantify the resolving power of IMS on target substance, of which calculation formula was shown in equation 2: [35] Rp = td/FWHM
(2)
where td is the drift time, FWHM is the full width at half maximum. The Peak-to-peak resolution (Rp-p) is used to measure separation efficiency of IMS, which calculated by Equation 3: [36, 37], Rp−p = 0.589(td2 − td1)/(FWHM1/2 + FWHM2/2)
(3)
where td1 and td2 are the drift times of the two adjacent peaks; FWHM1 and FWHM2 are the FWHM of the two target ion peaks. 2.4 Methods To promote the separation of NH3 peak in IMS, BN−Grid Structures was used. Detailed information of this structures has been published elsewhere [38]. Briefly, its principle was that enhancing the compression electric field between BN and grid, and lowering the injection field to get better resolutions. The drift tube temperature was keeping at 150 oC to alleviate the influence of environment humidity and improve the resolutions. Then, a probabilistic random method was used for sampling. The gas was inhaled for the measurement, which quantity was calculated by the different flow rates between the two mass flow meters. The operating parameters of the instrument were presented in table 1. In order to get validation parameters, the fluctuation of the high voltage supply module was ≤ 1%, the drift temperature precision was ≤ 1 oC, and the gas flow precision was within 1.5%. Each measurement was averaged 10 times and get an instrumental signal/noise of 261, calculated by the measurement of 100 ppb NH3. Furthermore, Polytetrafluoroethylene filter membranes were used to get rid of particles to keep drift tube clean, and automation control systems of the instrument was used to reduce the manual interference in a long-term.
The on-line monitoring of the atmospheric NH3 concentration in Dalian city. (N 38°53′16.97″, E 121°34′25.90″) was conducted from June 19 to December 3 in 2015, the temperature from -12.7 oC to 36.6 oC, RH between 19- 97%, and air quality index (AQI) from 35 to 392 during the measurement. 3. Results and discussions 3.1. Drift tube temperature optimization for selective detection of NH3 Fig. 2 shows the positive ion spectrums of IMS with the drift tube temperature at 150 oC, the peak presented at 5.44 ms was RIP known as (H2O)nH+ [39]. The peak presented at 4.51 ms was assigned as (H2O)nNH+4 , which was confirmed by its reduced mobility value of 2.77 cm2/V·s calculated by equation 1. It is also compared with the value of 2.65 cm2/V·s reported by Jazan et al. [24]. The (H2O)nNH+4 ion peak presented in all background spectrums at the experimental temperatures. Some scholars attributed this as an inevitable peak to the background ammonia in the drift tube and marked as RIP2 [24]. The background spectrums of the IMS obtained at the experimental conditions presented in Table 1 while varying the drift tube temperature from 90 oC to 170 oC were presented in the supporting information (Fig. S1). As shown in Fig. S1, the intensity of (H2O)nNH+4 peak was increased with the increasing of temperature since more NH3 was released by pyrolysis process [24, 40]. However, the intensity of this peak was stabilized at a definitive temperature with a long term monitoring, with the RSD within 5.8% in 33.3 h (Fig. S2). Therefore, the NH3 concentration could be extracted quantitatively from the total signal after subtracting the background. Fig. 3 showed the evolutions of Rp and Rp−p as a function of the drift tube temperature with 50 ml/min sampling rate with 60 ppb NH3 standard gas. Rp decreased as the drift tube temperature increase (Fig. 3a), while the Rp-p increased as the temperature increase as shown in Fig. 3b. Higher Rp−p could be obtained at a higher temperature. This may be attributed that the high temperature increased the separation of the peaks via enhancing the reduced mobility difference between
(H2O)nH+ and (H2O)nNH+4 [39].. The much higher temperature also accelerated the movement of ions that reduced the drift time. The two adjacent two peaks completely reached the baseline separation at about 150 oC (Fig. 2). The FWHM of (H2O)nNH+4 peak illustrated no significant changes, while the FWHM of RIP was decreased as the drift tube temperature increased until 160 oC where this FWHM became constant at even higher temperature as illustrated in Fig. 3c. Comparatively, in some studies, this FWHM was observed becoming wider when the drift temperature reached more than 150 oC [24, 41]. In our experiments, the higher temperature increased the interference from some new substances by the pyrolysis process, which caused decreasing of the RIP intensity and the appearance of some new background peaks as illustrated in Fig. S1. Thus, 150 oC was selected as the optimal operating temperature. 3.2. Effect of humidity on NH3 measurement Moisture is a major component in the ambient air, which usually indicated by relative humidity (RH). In atmospheric environment, it is constantly changing with temporal and spatial variation. An excellent instrument developed for the atmospheric composition monitoring should be immune to the moisture, or the moisture interference can be eliminated. The IMS operated with a sampling flow rate of 50 ml/min and drift gas of 400 ml/min at tube temperature of 150 oC. The moisture in the drift gas showed great impact on the spectra of IMS. With the increasing of RH from 0% to 10% in drift gas, the ion peaks moved to longer drift time position while the signal intensity of (H2O)nNH+4 increased (Fig. S3a); Rp-p decreased from 2.6 to 1.2 (Fig. S3b); Rp of NH3 increased from 31.6 to 34.1 due to FWHM increasing (Fig. S3c). It has proved that the increases in RH changed the reduced mobility of the ions due to gradually increasing the amount of H2O cluster numbers combined with the target ions, namely, the value of n in (H2O)nNH+4 and (H2O)nH+ [39]. However, when RH increased, there were no new peaks were observed in the IMS spectra. It illustrated that the moisture increasing in the drift gas did not result in any changes in the ionization path [42]. The coalescence of the multiple ions with different number of H2O clusters distributed into
two independent peaks characterized by the equilibrium of the weighted sum of all individual ions [39]. Thus, to keep the drift gas dry the active carbon and the molecular sieve were used. Based on the RH of the operating environment the consumption rate of the drying agent was usually at 1.5 months per kilogram in Dalian city during our measurements. On the other hand, the moisture in the sampling gas, commonly regarded as the environmental humidity in a practical application, showed no significant impact on the spectra of IMS (Fig. 4). We found that the position and the resolution of the peaks experienced little change when the RH in sampling gas increased from 5% to 90%. The average signal intensity of (H2O)nNH+4 was 404 mv, ranging between 389 mv to 420 mv, with a RSD of only 2.5%. Thus, the effect of the environmental humidity was insignificant. This stability may be attributed to the high working temperature (150 oC) in the drift tube, which may reduce the water molecules in the clustered ion and kept (H2O)nNH+4 predominate [39]. Furthermore, the ratio between the sampling gas and the drift gas was rather low (about a ratio of 1:8) so that the dry drift gas diluted the moisture in the sampling gas. 3.3. Relationship among sampling quantity, averaging time and LOD IMS operated at typical conditions, with sampling rate varying from 30 mL/min to 500 mL/min. As shown in Fig. S4, with the increase of the sampling rate, the signal intensity of (H2O)2NH+4 peak presented a rising trend in ladder shape. By comparison, RIP showed a declining trend in ladder shape correspondingly. It can be deduced that the reactant ions transferred the protons to the target compounds and converted them into new ion clusters, as shown in equation 4.
(H2O)n H+ NH3 (H2O)n NH4
(4)
The reduced mobility of (H2O)nH+ and (H2O)nNH+4 were 2.31 and 2.74 cm2/V·s, while the peaks appeared around 5 ms under the current IMS condition. Therefore, the IMS spectrum scan can be finished with a time cycle within 10 ms. Theoretically, NH3 in atmospheric environment can be monitored by IMS with a measuring rate up to 100
Hz. In reality, to obtain lower noise and more accurate results, five times data average was used, which was corresponding to a 20 Hz measurement rate. At the signal to noise ratio of S/N=3, the limit of detection (LOD) measurement at different average times with various sampling quantity were determined 10 ppb NH3 for 10 times. As shown in table 2, with 30 mL/min sampling rate and 5 averaging times, the LOD of IMS was 22.7 ppb. On the other hand, the LOD reached 6.89 ppb with 35 averaging times. Furthermore, using the same averaging times while increasing the sampling rate could also lower LOD. For example, IMS achieved sub-ppb LOD at 80 ml/min sampling rate with 20 times averaging. As listed in Table 2, the best LOD = 0.15 ppb was achieved when averaging time of 35 and sampling rate of 400 ml/min were used. Evidently, the LOD improvement had a saturation effect, i.e., increasing the sampling rate did not improve the LOD linearly, as illustrated in Table 2. A reasonable explanation could be that although the higher sampling rate brought in more NH3 molecules, however, the number of reactant ions, (H2O)nH+ was limited in the reaction region so that less than proportional product ions, (H2O)nNH4+ could be produced. Furthermore, the higher sampling flow rate would also decrease the reaction time according to formula 4. Therefore, increasing the sampling rate can improve the LOD sensitivity. In principle, by adjusting the sampling rate, one can control the detection sensitivity, i.e., using the lower sampling rate for higher concentration NH3 in the air while increasing the sampling rate when the NH3 concentration is relatively low. However, for quantitative measurement, this method cannot be used due to above mentioned non-linear response of the sensitivity versus sampling rate relationship. 3.4. Sensitivity and quantification IMS has fast response time and large linear range for NH3 measurement in the atmospheric environment. A quantitative calibration curve was made by diluting 6 ppm standard NH3 gas with different diluting ratio for the sampling gas, as shown in Fig. 5. The sampling rate kept at 50 ml/min, more than 200 measurements were performed for a sample, with each measurement averaging 10 times. The measurement response time for NH3 in the air reached 0.1 second level while the transition time between two different concentrations was 10 second. The quantitative curve for NH3 concentration measurements illustrated two sections of good linearity
in the range of 10 – 60 ppb and 60 – 400 ppb, with different slops and correlation coefficient R2 of 0.97 and 0.99, respectively. The linear range can be extended by using lower or higher sampling rates as mentioned previously. The accuracy of the data was calculated with 100 times measurements of 100 ppb NH3. The relative standard deviations (RSD) was 1.06%, and the errors were ±0.21 ppb with the confidence level of 95%. Furthermore, the IMS illustrated a short recovery time for measure high concentration NH3. Even at the concentration of 400 ppb, it recovered 80% intensity within 100 s. Sampling more clean air would promote the recovery. As showed in Fig. 5, the signal intensity fell sharply from 276 mv to the background level by increasing the sampling rate of clean air from 50 mL to 100 mL. 3.5. Long-term high frequency measurement of NH3 in outdoor air The experiments of measuring NH3 in outdoor air was carried out on the roof of our laboratory, a building with the height of 30-metre, located on a hillside in Dalian Institute of Chemical Physics. The NH+4 peak intensity had surveyed and recorded each second. Then the concentration of NH3 in atmospheric environment was obtained according the quantification mentioned above. The long-term daily concentration of NH3 from June 19th to December 3th in 2015 was presented in Fig. S5. During the period, the average concentration of gaseous NH3 in air environment was 58.8 ppb. The minimum concentration was 0.01 ppb, the maximum concentration was 252.2 ppb. Fast response time with high frequency measurement usually resulted in large amounts of data. In this study, 6 days’ NH3 concentration measurements were showed in Fig. 6. The massive measurement data were analyzed by origin 9 in speed mode. Within the measurements, the minimum concentration was 18.5 ppb at 7th July, while the maximum concentration was 457.2 ppb at 4th July. Regardless of concentration levels, the peak value of NH3 for each day appeared around 7 a. m. in most days. The sensitivity and stability of this instrument ensured the accurate measurement of the NH3 concentration during the monitoring time period.
4. Conclusion In this study, IMS was developed to measure NH3 concentration in the atmospheric environment for a long term with a sub-second high frequency fashion. The reduced mobility of the NH3 characteristic product ions was 2.77 cm2/V·s, which intensity was used to present concentration of NH3. By increasing sampling rate and averaging times, IMS achieved a LOD of 0.15 ppb. Using a determinant sampling rate, IMS showed a sub-second response time with a large linear response range. RH change in the environment presented no significant impact on the IMS measurement for NH3 in air. A long-term high frequency measurement of NH3 concentration by IMS was performed in Dalian city. The results demonstrated that IMS was a fast, accurate and stable method to provide a long-term sub-second response monitoring data for the NH3 concentrations in the atmospheric environment. Acknowledgements： Funding for this study was provided by the Chinese National Key Research and Development Plans (2016YFC0201200). Notes The authors declare no competing financial interest. Appendix A. Supplementary data Supplementary data related to this article can be found at. Reference: [1] J. Kirkby, J. Curtius, J. Almeida, E. Dunne, J. Duplissy, S. Ehrhart, A. Franchin, S. Gagne, L. Ickes, A. Kurten, A. Kupc, A. Metzger, F. Riccobono, L. Rondo, S. Schobesberger, G. Tsagkogeorgas, D. Wimmer, A. Amorim, F. Bianchi, M. Breitenlechner, A. David, J. Dommen, A. Downard, M. Ehn, R.C. Flagan, S. Haider, A. Hansel, D. Hauser, W. Jud, H. Junninen, F. Kreissl, A. Kvashin, A. Laaksonen, K. Lehtipalo, J. Lima, E.R. Lovejoy, V. Makhmutov, S. Mathot, J. Mikkila, P. Minginette, S. Mogo, T. Nieminen, A. Onnela, P. Pereira, T. Petaja, R. Schnitzhofer, J.H. Seinfeld, M. Sipila, Y. Stozhkov, F. Stratmann, A. Tome, J. Vanhanen, Y. Viisanen, A. Vrtala, P.E. Wagner, H. Walther, E. Weingartner, H. Wex, P.M. Winkler, K.S. Carslaw, D.R. Worsnop, U. Baltensperger, M. Kulmala, Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation, Nature, 476 (2011) 429-U477.
[2] K. Na, C. Song, C. Switzer, D.R. Cocker, Effect of ammonia on secondary organic aerosol formation from alpha-Pinene ozonolysis in dry and humid conditions, Environmental Science & Technology, 41 (2007) 6096-6102. [3] O. Hertel, C.A. Skjoth, S. Reis, A. Bleeker, R.M. Harrison, J.N. Cape, D. Fowler, U. Skiba, D. Simpson, T. Jickells, M. Kulmala, S. Gyldenkaerne, L.L. Sorensen, J.W. Erisman, M.A. Sutton, Governing processes for reactive nitrogen compounds in the European atmosphere, Biogeosciences, 9 (2012) 4921-4954. [4] R. Bobbink, K. Hicks, J. Galloway, T. Spranger, R. Alkemade, M. Ashmore, M. Bustamante, S. Cinderby, E. Davidson, F. Dentener, B. Emmett, J.W. Erisman, M. Fenn, F. Gilliam, A. Nordin, L. Pardo, W. De Vries, Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis, Ecological Applications, 20 (2010) 30-59. [5] M.P. Keuken, A. Wayers-Ijpelaan, R.P. Otjes, J. Slanina, Determination of NH3, HNO3 and NH4NO3 in Ambient Air by Automated Thermodenuder Systems and a Wet Annular Denuder System, in: G. Restelli, G. Angeletti (Eds.) Physico-Chemical Behaviour of Atmospheric Pollutants, Springer Netherlands1990, pp. 6-11. [6] C.W. Du, J. Wang, Z.J. Zhou, Y.Z. Shen, J.M. Zhou, In Situ Measurement of Ammonia Concentration in Soil Headspace Using Fourier Transform Mid-Infrared Photoacoustic Spectroscopy, Pedosphere, 25 (2015) 605-612. [7] J. Sintermann, C. Ammann, U. Kuhn, C. Spirig, R. Hirschberger, A. Gärtner, A. Neftel, Determination of field scale ammonia emissions for common slurry spreading practice with two independent methods, Atmospheric Measurement Techniques, 4 (2011) 1821-1840. [8] F. Bianchi, J. Dommen, S. Mathot, U. Baltensperger, On-line determination of ammonia at low pptv mixing ratios in the CLOUD chamber, Atmospheric Measurement Techniques, 5 (2012) 1719-1725. [9] J. Zheng, Y. Ma, M.D. Chen, Q. Zhang, L. Wang, A.F. Khalizov, L. Yao, Z. Wang, X. Wang, L.X. Chen, Measurement of atmospheric amines and ammonia using the high resolution time-of-flight chemical ionization mass spectrometry, Atmospheric Environment, 102 (2015) 249-259. [10] H. Yu, S.H. Lee, Chemical ionisation mass spectrometry for the measurement of atmospheric amines, Environmental Chemistry, 9 (2012) 190-201. [11] K. von Bobrutzki, C.F. Braban, D. Famulari, S.K. Jones, T. Blackall, T.E.L. Smith, M. Blom, H. Coe, M. Gallagher, M. Ghalaieny, M.R. McGillen, C.J. Percival, J.D. Whitehead, R. Ellis, J. Murphy, A. Mohacsi, A. Pogany, H. Junninen, S. Rantanen, M.A. Sutton, E. Nemitz, Field inter-comparison of eleven atmospheric ammonia measurement techniques, Atmospheric Measurement Techniques, 3 (2010) 91-112. [12] B. Timmer, W. Olthuis, A. van den Berg, Ammonia sensors and their applications - a review, Sensors and Actuators B-Chemical, 107 (2005) 666-677. [13] Y. Huang, L. Wieck, S. Tao, Development and evaluation of optical fiber NH3 sensors for application in air quality monitoring, Atmospheric Environment, 66 (2013) 1-7.
[14] Q. Zhou, L. Hua, C. Wang, E. Li, H. Li, Improved Analytical Performance of Negative 63Ni Ion Mobility Spectrometry for On-line Measurement of Propofol Using Dichloromethane as Dopant, Journal of The American Society for Mass Spectrometry, 26 (2014) 190-193. [15] Q. Zhou, W. Wang, H. Cang, Y. Du, F. Han, C. Chen, S. Cheng, J. Li, H. Li, On-line measurement of propofol using membrane inlet ion mobility spectrometer, Talanta, 98 (2012) 241-246. [16] Q.H. Zhou, E.Y. Li, X. Wang, Y.L. Gong, L. Hua, W.G. Wang, T.S. Qu, J.H. Li, Y.P. Liu, C.S. Wang, H.Y. Li, Trap-and-release membrane inlet ion mobility spectrometry for on-line measurement of trace propofol in exhaled air, Analytical Methods, 6 (2014) 698-703. [17] Q.H. Zhou, E.Y. Li, Z.X. Wang, Y.L. Gong, C.S. Wang, L. Guo, H.Y. Li, Time-resolved dynamic dilution introduction for ion mobility spectrometry and its application in end-tidal propofol monitoring, Journal of Breath Research, 9 (2015). [18] K.M. Roscioli, J.A. Tufariello, X. Zhang, S.X. Li, G.H. Goetz, G.L. Cheng, W.F. Siems, H.H. Hill, Desorption electrospray ionization (DESI) with atmospheric pressure ion mobility spectrometry for drug detection, Analyst, 139 (2014) 1740-1750. [19] S. Cheng, J. Dou, W. Wang, C. Chen, L. Hua, Q. Zhou, K. Hou, J. Li, H. Li, Dopant-assisted negative photoionization ion mobility spectrometry for sensitive detection of explosives, Analytical Chemistry, 85 (2013) 319-326. [20] L.Y. Peng, L. Hua, W.G. Wang, Q.H. Zhou, H.Y. Li, On-site Rapid Detection of Trace Non-volatile Inorganic Explosives by Stand-alone Ion Mobility Spectrometry via Acid-enhanced Evaporization, Scientific Reports, 4 (2014). [21] G.A. Eiceman, Ion mobility spectrometry as detector and sensor for chemical warfare agents and toxic industrial chemicals., Abstracts of Papers of the American Chemical Society, 224 (2002) U145-U145. [22] S.S. Cheng, C. Chen, W.G. Wang, H.Y. Li, Detection of Chemical Warfare Agents by Differential Mobility Spectrometry and Drift-time Ion Mobility Spectrometry Hybrid Technology, Chinese Journal of Analytical Chemistry, 42 (2014) 1264-1269. [23] G.A. Eiceman, M.R. Salazar, M.R. Rodriguez, T.F. Limero, S.W. Beck, J.H. Cross, R. Young, J.T. James, Ion Mobility Spectrometry of Hydrazine, Monomethylhydrazine, and Ammonia in Air with 5-Nonanone Reagent Gas, Analytical Chemistry, 65 (1993) 1696-1702. [24] E. Jazan, H. Mirzaei, Direct analysis of human breath ammonia using corona discharge ion mobility spectrometry, Journal of Pharmaceutical and Biomedical Analysis, 88 (2014) 315-320. [25] Z. Karpas, Ion mobility spectrometry of aliphatic and aromatic amines, Analytical Chemistry, 61 (1989) 684-689. [26] L. Myles, T.P. Meyers, L. Robinson, Atmospheric ammonia measurement with an ion mobility spectrometer, Atmospheric Environment, 40 (2006) 5745-5752.
[27] G. Neri, A. Lacquaniti, G. Rizzo, N. Donato, M. Latino, M. Buemi, Real-time monitoring of breath ammonia during haemodialysis: use of ion mobility spectrometry (IMS) and cavity ring-down spectroscopy (CRDS) techniques, Nephrology Dialysis Transplantation, 27 (2012) 2945-2952. [28] R. Janson, K. Rosman, A. Karlsson, H.C. Hansson, Biogenic emissions and gaseous precursors to forest aerosols, Tellus Series B-Chemical and Physical Meteorology, 53 (2001) 423-440. [29] Z.-Y. Meng, X.-B. Xu, T. Wang, X.-Y. Zhang, X.-L. Yu, S.-F. Wang, W.-L. Lin, Y.-Z. Chen, Y.-A. Jiang, X.-Q. An, Ambient sulfur dioxide, nitrogen dioxide, and ammonia at ten background and rural sites in China during 2007–2008, Atmospheric Environment, 44 (2010) 2625-2631. [30] A.L. Zbieranowski, J. Aherne, Ambient concentrations of atmospheric ammonia, nitrogen dioxide and nitric acid across a rural–urban–agricultural transect in southern Ontario, Canada, Atmospheric Environment, 62 (2012) 481-491. [31] M.B. Rhoades, D.B. Parker, N.A. Cole, R.W. Todd, E.A. Caraway, B.W. Auvermann, D.R. Topliff, G.L. Schuster, Continuous Ammonia Emission Measurements from a Commercial Beef Feedyard in Texas, Transactions of the Asabe, 53 (2010) 1823-1831. [32] Y. Zhou, S.Y. Cheng, J.L. Lang, D.S. Chen, B.B. Zhao, C. Liu, R. Xu, T.T. Li, A comprehensive ammonia emission inventory with high-resolution and its evaluation in the Beijing-Tianjin-Hebei (BTH) region, China, Atmospheric Environment, 106 (2015) 305-317. [33] Y.Z. Du, W.G. Wang, H.Y. Li, Resolution Enhancement of Ion Mobility Spectrometry by Improving the Three-Zone Properties of the Bradbury-Nielsen Gate, Analytical Chemistry, 84 (2012) 1725-1731. [34] L.Y. Peng, L. Hua, E.Y. Li, W.G. Wang, Q.H. Zhou, X. Wang, C.S. Wang, J.H. Li, H.Y. Li, Dopant titrating ion mobility spectrometry for trace exhaled nitric oxide detection, Journal of Breath Research, 9 (2015). [35] A.B. Kanu, M.M. Gribb, H.H. Hill, Predicting optimal resolving power for ambient pressure ion mobility spectrometry, Analytical Chemistry, 80 (2008) 6610-6619. [36] E.J. Davis, K.F. Grows, W.F. Siems, H.H. Hill, Improved Ion Mobility Resolving Power with Increased Buffer Gas Pressure, Analytical Chemistry, 84 (2012) 4858-4865. [37] M. Tabrizchi, F. Rouholahnejad, Pressure effects on resolution in ion mobility spectrometry, Talanta, 69 (2006) 87-90. [38] Y.Z. Du, W.G. Wang, H.Y. Li, Bradbury-Nielsen-Gate-Grid Structure for Further Enhancing the Resolution of Ion Mobility Spectrometry, Analytical Chemistry, 84 (2012) 5700-5707. [39] G.A. Eiceman, Z. Karpas, Ion Mobility Spectrometry(2nd), Taylor & Franics, DOI (2005) 2005, 2080-2097.
[40] S.H. Kim, K.R. Betty, F.W. Karasek, Mobility Behavior and Composition of Hydrated Positive Reactant Ions in Plasma Chromatography with Nitrogen Carrier Gas, Analytical Chemistry, 50 (1978) 2006-2012. [41] R. Fernandez-Maestre, C. Wu, H.H. Hill, Ammonia as a Modifier in Ion Mobility Spectrometry: Effects on Ion Mobilities and Potential as a Separation Tool, Journal of the Chilean Chemical Society, 59 (2014) 2398-2403. [42] H. Borsdorf, P. Fiedler, T. Mayer, The effect of humidity on gas sensing with ion mobility spectrometry, Sensors and Actuators B: Chemical, 218 (2015) 184-190.
Fig. 1. Schematic diagram of IMS for monitoring NH3.
Fig. 2. The positive ion spectrums of IMS with the drift tube temperature in 150 oC.
Fig. 3. Rp (a), Rp-p (b) and FWHM (c) changed with the drift tube temperature (90 170 oC)
Fig. 4. Spectra of IMS with different RH in sampling gas.
Fig. 5. Quantify the NH3 by IMS on-line measuring
Fig. 6. High frequency measurement of NH3
Table 1. Commonly used operating parameters for IMS Operating parameters
Setting
Ionization source
63
Ni
Drift field
400 V cm-1
Drift gas flow
400 mL min-1
Sample gas flow
50 mL min-1
Drift temperature
150 ºC
Drift tube length
6 cm
Injection pulse
0.2 ms
Scan time
9 ms
Averaging times
10 times
Table 2. LODs of IMS with different averaging times and sampling quantities. Average
Sampling quantity (mL/min)
(times)
30
50
80
100
200
300
400
5
22.7
4.31
1.95
1.48
0.68
0.52
0.48
8
19.9
3.77
1.71
1.30
0.60
0.46
0.42
10
15.0
2.85
1.29
0.98
0.45
0.35
0.32
15
13.4
2.54
1.15
0.88
0.40
0.31
0.28
20
10.9
2.08
0.94
0.72
0.33
0.25
0.23
25
8.51
1.62
0.73
0.56
0.26
0.20
0.18
30
7.70
1.46
0.66
0.50
0.23
0.18
0.16
35
6.89
1.31
0.59
0.45
0.21
0.16
0.15
Highlights： 1. Ion mobility spectrometry was developed to monitor gaseous ammonia in the ambient air in a long-term measurement. 2. The quantitative analysis frequency has achieved 10 Hz with a data averaging of 10 times. 3. The limit of detection of sub-ppb level was obtained. 4. The affect of ambient humidity was greatly reduced using drift temperature of over 150 oC.
PII: DOI: Reference:
S0039-9140(17)30799-3 http://dx.doi.org/10.1016/j.talanta.2017.07.076 TAL17775
To appear in: Talanta Received date: 31 March 2017 Revised date: 19 July 2017 Accepted date: 24 July 2017 Cite this article as: Wei Huang, Weiguo Wang, Chuang Chen, Mei Li, Liying Peng, Hang Li, Jiwei Liu, Keyong Hou and Haiyang Li, Long-term sub secondresponse monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry, Talanta, http://dx.doi.org/10.1016/j.talanta.2017.07.076 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 galley proof before it is published in its final citable 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.
Long-term sub second-response monitoring of gaseous ammonia in ambient air by positive inhaling ion mobility spectrometry Wei Huang 1, Weiguo Wang 1, Chuang Chen 1, Mei Li 1, 3, Liying Peng 1, 3, Hang Li 2, 3, Jiwei Liu 1, 4, Keyong Hou 1, Haiyang Li1* 1. Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, People’s Republic of China 2. Anhui Institute of Optics and Fine Mechanics, Key Laboratory of Environmental Optics and Technology, Chinese Academy of Sciences, Hefei 230031, People’s Republic of China 3. University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China 4. Liaoning Normal university, Dalian, 116029, People’s Republic of China
* E-mail: [email protected]. Tel: +86-411-84379510. Fax: +86-411-84379517.
Abstract: A real-time dynamic measurements of ammonia (NH3) is crucial for understanding the atmospheric nucleation process. A novel method was developed for on line monitoring at the sub-second time scale for the gaseous ammonia in ambient air for months, based on a positive inhaling ion mobility spectrometry (IMS) with a 63Ni ion source. The selective detection of NH3 was achieved using a high resolution IMS with an optimization of the drift tube temperature above 150 oC. This method improved the peak-to-peak resolution significantly, thus avoided the interferences of the adjacent peaks to the quantitative analysis of NH3. The time resolution of the IMS was less than 0.1 s at a data averaging of 10 times. The limit of detection (LOD) achieved at sub-ppb level while a linear response of peak intensity
versus concentration of NH3 in the range of 10 – 60 ppb and 60 – 400 ppb were obtained. The relative standard deviations (RSD), the confidence level and the errors were 1.06%, 95% and ±0.21 ppb by measuring 100 ppb NH3 for 100 times. The effect of ambient humidity could be greatly reduced using the drift temperature of over 150 o
C. At last, the application of measuring the NH3 concentration evolutions of Dalian
city was performed from June 19 to December 3 in 2015. The results illustrated a potential method of using IMS for a real-time measurement of ambient NH3 at an unprecedented accuracy and sensitivity with long-term stability.
Keywords: ion mobility spectrometry; ammonia; fast response; sub-second time scale; long-term; monitoring 1. Introduction Ammonia (NH3) plays important role in atmospheric nucleation. For example, atmospherically relevant ammonia mixing ratio of 100 parts per trillion by volume would increase the nucleation rate of sulphuric acid particles more than 100– 1,000-fold [1, 2]. Moreover, through the atmospheric deposition process, large quantities of NH3 get into soil and water, which may lead to eutrophication and acidification that have adverse impact on biological diversity [3, 4]. Due to these negative impacts, advanced apparatus are in need for NH3 concentration monitoring in atmospheric environment. In particular, it would be desirable to develop NH3
concentration measurement instruments enabling continuous operation on line with fast response time. Many methods of measuring NH3 concentration have been developed in recent years. For a long time, off-line method has been widely used to measure NH3 in air, for example, bulk denuder method sampling gaseous NH3 out of the air steam [5]. However, these off-line methods suffered from many disadvantages, such as time-consuming, labor-intensive, sample contamination, and low temporal resolution. After decades of research effort, absorption spectroscopic methods have become more viable due to their sensitivity and practical nature for the NH3 measurement [6, 7]. One of such new on-line approach could determine the NH3 concentration by absorption spectrophotometry method. The limit of detection (LOD) has achieved ppt-level by analyzing the resultant of NH3 transferring to the liquid phase [8]. Chemical ionization mass spectrometry (CIMS) method has also been adopted for NH3 monitoring [9, 10]. In recent years, some inter-comparisons of NH3 measuring methods have been reported. Von Bobrutzki et al. used eleven instruments to measure the ambient NH3 gas in Southern Scotland, such as optical techniques, wet-chemistry systems, photo-acoustic spectrometers and mass spectrometric apparatus, to assess instrument performance and characterize the instrument response times[11]. These instruments exhibit excellent performances in monitoring NH3. However, the high cost of these methods, capital investment or running or both, prevents them from being applied in large-scaled air quality monitoring program. On the other hand, several gas sensor based methods were developed to monitor NH3 concentrations in the ambient air. However, the minimum response time was from seconds to ten minutes with a LOD of several ppb, which is sensitive to monitor source emission NH3 [12, 13]. Due to fast changing condition for the atmospheric environment, such as airflow transport consists of differently sized eddies, as well as many relevant pollutant concentrations, the required pollutant concentration monitoring time scale should be
as short as 0.1 second. However, few monitoring instruments can meet such a short response time requirement. It is well known that ion mobility spectrometry (IMS) has many advantages over the analytical methods mentioned above, such as fast response, high sensitivity, low cost, robustness, and simple operation. IMS technology has been applied in detection of anaesthetic [14-17], narcotic drugs [18], explosives [19, 20] and chemical warfare agents [21, 22]. Currently, there are a few reports about IMS technology for detecting NH3 gas concentrations in the air and from the human breath [23-27]. Compared with the atmospheric environment, the temperature, humidity and ammonia concentration of human breath have smaller changes. Due to the intermittent operation in short time, it is not very suited for atmospheric environment measurements in a long-term. Therefore, an exhaustive and accurate quantification of the ammonia concentration measurement for the atmospheric environment is needed. Firstly, ambient concentrations range of NH3 is very wide, from several ppb in remote areas [28] to several ppm levels near feeding stock facilities [13, 29-31]. Obtaining the NH3 concentration in such a large range accurately is a big challenge. Secondly, as polar compound, NH3 is easy to stick or interact with the surface materials of the path way, which cause slow response and affect NH3 quantifications [7, 11]. Thirdly, as one of the major components of air, moisture may cause interference response to different instruments [13]. Finally, human activity is one of the most important NH3 emission sources [32], which may cause sample contaminations. In this study, a high resolution IMS with 63Ni ion source was constructed and optimized for on line measuring ambient NH3 with sub-second measurement cycle in the air. The operating conditions of instrument were optimized to detect NH3 selectively. The better LODs and larger quantitative measurement range for NH3 were obtained. Then the effect of relative humidity (RH) in the drift gas and sampling environment was studied. In the final section, the method was applied to on-line monitor the atmospheric NH3 in Dalian city.
2. Experimental 2.1. Instrumentation The high resolution ion mobility spectrometer used in this study was designed in our laboratory. Its setup was described in details previously [33]. As shown in Fig. 1, it contained a radioactive 63Ni ion source, an ion gate (Bradbury-Nielsen), a Faraday plate, an amplifier, a drift region and a high voltage supply module. The drift gas was made from the ambient air by an air compressor (Ustar Co., Ltd., Taiwan) and an air purifier which mainly consisted of a soft polyurethane tube (SMC. Co., Ltd., Japan, model TUS 0805), an oil mist filter (SMC. Co., Ltd., Japan, model AMH150C-01C-R), and a container with molecular sieves and activated charcoals. The drift gas and exhaust gas were controlled and measured by two mass flow meters (Beijing Sevenstar Electronics Co., Ltd., China, model D07-7B). 2.2. Chemicals NH3 standard gas (6 ppm, high purity N2 was substrate) was purchased from Dalian Special Gases Co., Ltd. (Da Lian, China). Different concentration NH3 gas for quantification was obtained from on line diluting the NH3 standard gas by clean air, which was controlled by two mass flow meters respectively and mixed in a 2 mm internal diameter PTFE Tube. Pure water was purchased from Wahaha Group Co., Ltd. (Hang Zhou, China). 2.3. Calculations The reduced ion mobility (K) for analyzed peak was calculated by equation 1:[34] K = Kr (tdr/td)
(1)
where tdr and td are the drift times of reference and analyte respectively. The reaction ion peak (RIP, (H2O)nH+) was used as the reference. Its Kr was 2.31 cm2/V·s with a corresponding drift time as 5.44 ms in this study.
The single peak resolution (Rp) is an important parameter to quantify the resolving power of IMS on target substance, of which calculation formula was shown in equation 2: [35] Rp = td/FWHM
(2)
where td is the drift time, FWHM is the full width at half maximum. The Peak-to-peak resolution (Rp-p) is used to measure separation efficiency of IMS, which calculated by Equation 3: [36, 37], Rp−p = 0.589(td2 − td1)/(FWHM1/2 + FWHM2/2)
(3)
where td1 and td2 are the drift times of the two adjacent peaks; FWHM1 and FWHM2 are the FWHM of the two target ion peaks. 2.4 Methods To promote the separation of NH3 peak in IMS, BN−Grid Structures was used. Detailed information of this structures has been published elsewhere [38]. Briefly, its principle was that enhancing the compression electric field between BN and grid, and lowering the injection field to get better resolutions. The drift tube temperature was keeping at 150 oC to alleviate the influence of environment humidity and improve the resolutions. Then, a probabilistic random method was used for sampling. The gas was inhaled for the measurement, which quantity was calculated by the different flow rates between the two mass flow meters. The operating parameters of the instrument were presented in table 1. In order to get validation parameters, the fluctuation of the high voltage supply module was ≤ 1%, the drift temperature precision was ≤ 1 oC, and the gas flow precision was within 1.5%. Each measurement was averaged 10 times and get an instrumental signal/noise of 261, calculated by the measurement of 100 ppb NH3. Furthermore, Polytetrafluoroethylene filter membranes were used to get rid of particles to keep drift tube clean, and automation control systems of the instrument was used to reduce the manual interference in a long-term.
The on-line monitoring of the atmospheric NH3 concentration in Dalian city. (N 38°53′16.97″, E 121°34′25.90″) was conducted from June 19 to December 3 in 2015, the temperature from -12.7 oC to 36.6 oC, RH between 19- 97%, and air quality index (AQI) from 35 to 392 during the measurement. 3. Results and discussions 3.1. Drift tube temperature optimization for selective detection of NH3 Fig. 2 shows the positive ion spectrums of IMS with the drift tube temperature at 150 oC, the peak presented at 5.44 ms was RIP known as (H2O)nH+ [39]. The peak presented at 4.51 ms was assigned as (H2O)nNH+4 , which was confirmed by its reduced mobility value of 2.77 cm2/V·s calculated by equation 1. It is also compared with the value of 2.65 cm2/V·s reported by Jazan et al. [24]. The (H2O)nNH+4 ion peak presented in all background spectrums at the experimental temperatures. Some scholars attributed this as an inevitable peak to the background ammonia in the drift tube and marked as RIP2 [24]. The background spectrums of the IMS obtained at the experimental conditions presented in Table 1 while varying the drift tube temperature from 90 oC to 170 oC were presented in the supporting information (Fig. S1). As shown in Fig. S1, the intensity of (H2O)nNH+4 peak was increased with the increasing of temperature since more NH3 was released by pyrolysis process [24, 40]. However, the intensity of this peak was stabilized at a definitive temperature with a long term monitoring, with the RSD within 5.8% in 33.3 h (Fig. S2). Therefore, the NH3 concentration could be extracted quantitatively from the total signal after subtracting the background. Fig. 3 showed the evolutions of Rp and Rp−p as a function of the drift tube temperature with 50 ml/min sampling rate with 60 ppb NH3 standard gas. Rp decreased as the drift tube temperature increase (Fig. 3a), while the Rp-p increased as the temperature increase as shown in Fig. 3b. Higher Rp−p could be obtained at a higher temperature. This may be attributed that the high temperature increased the separation of the peaks via enhancing the reduced mobility difference between
(H2O)nH+ and (H2O)nNH+4 [39].. The much higher temperature also accelerated the movement of ions that reduced the drift time. The two adjacent two peaks completely reached the baseline separation at about 150 oC (Fig. 2). The FWHM of (H2O)nNH+4 peak illustrated no significant changes, while the FWHM of RIP was decreased as the drift tube temperature increased until 160 oC where this FWHM became constant at even higher temperature as illustrated in Fig. 3c. Comparatively, in some studies, this FWHM was observed becoming wider when the drift temperature reached more than 150 oC [24, 41]. In our experiments, the higher temperature increased the interference from some new substances by the pyrolysis process, which caused decreasing of the RIP intensity and the appearance of some new background peaks as illustrated in Fig. S1. Thus, 150 oC was selected as the optimal operating temperature. 3.2. Effect of humidity on NH3 measurement Moisture is a major component in the ambient air, which usually indicated by relative humidity (RH). In atmospheric environment, it is constantly changing with temporal and spatial variation. An excellent instrument developed for the atmospheric composition monitoring should be immune to the moisture, or the moisture interference can be eliminated. The IMS operated with a sampling flow rate of 50 ml/min and drift gas of 400 ml/min at tube temperature of 150 oC. The moisture in the drift gas showed great impact on the spectra of IMS. With the increasing of RH from 0% to 10% in drift gas, the ion peaks moved to longer drift time position while the signal intensity of (H2O)nNH+4 increased (Fig. S3a); Rp-p decreased from 2.6 to 1.2 (Fig. S3b); Rp of NH3 increased from 31.6 to 34.1 due to FWHM increasing (Fig. S3c). It has proved that the increases in RH changed the reduced mobility of the ions due to gradually increasing the amount of H2O cluster numbers combined with the target ions, namely, the value of n in (H2O)nNH+4 and (H2O)nH+ [39]. However, when RH increased, there were no new peaks were observed in the IMS spectra. It illustrated that the moisture increasing in the drift gas did not result in any changes in the ionization path [42]. The coalescence of the multiple ions with different number of H2O clusters distributed into
two independent peaks characterized by the equilibrium of the weighted sum of all individual ions [39]. Thus, to keep the drift gas dry the active carbon and the molecular sieve were used. Based on the RH of the operating environment the consumption rate of the drying agent was usually at 1.5 months per kilogram in Dalian city during our measurements. On the other hand, the moisture in the sampling gas, commonly regarded as the environmental humidity in a practical application, showed no significant impact on the spectra of IMS (Fig. 4). We found that the position and the resolution of the peaks experienced little change when the RH in sampling gas increased from 5% to 90%. The average signal intensity of (H2O)nNH+4 was 404 mv, ranging between 389 mv to 420 mv, with a RSD of only 2.5%. Thus, the effect of the environmental humidity was insignificant. This stability may be attributed to the high working temperature (150 oC) in the drift tube, which may reduce the water molecules in the clustered ion and kept (H2O)nNH+4 predominate [39]. Furthermore, the ratio between the sampling gas and the drift gas was rather low (about a ratio of 1:8) so that the dry drift gas diluted the moisture in the sampling gas. 3.3. Relationship among sampling quantity, averaging time and LOD IMS operated at typical conditions, with sampling rate varying from 30 mL/min to 500 mL/min. As shown in Fig. S4, with the increase of the sampling rate, the signal intensity of (H2O)2NH+4 peak presented a rising trend in ladder shape. By comparison, RIP showed a declining trend in ladder shape correspondingly. It can be deduced that the reactant ions transferred the protons to the target compounds and converted them into new ion clusters, as shown in equation 4.
(H2O)n H+ NH3 (H2O)n NH4
(4)
The reduced mobility of (H2O)nH+ and (H2O)nNH+4 were 2.31 and 2.74 cm2/V·s, while the peaks appeared around 5 ms under the current IMS condition. Therefore, the IMS spectrum scan can be finished with a time cycle within 10 ms. Theoretically, NH3 in atmospheric environment can be monitored by IMS with a measuring rate up to 100
Hz. In reality, to obtain lower noise and more accurate results, five times data average was used, which was corresponding to a 20 Hz measurement rate. At the signal to noise ratio of S/N=3, the limit of detection (LOD) measurement at different average times with various sampling quantity were determined 10 ppb NH3 for 10 times. As shown in table 2, with 30 mL/min sampling rate and 5 averaging times, the LOD of IMS was 22.7 ppb. On the other hand, the LOD reached 6.89 ppb with 35 averaging times. Furthermore, using the same averaging times while increasing the sampling rate could also lower LOD. For example, IMS achieved sub-ppb LOD at 80 ml/min sampling rate with 20 times averaging. As listed in Table 2, the best LOD = 0.15 ppb was achieved when averaging time of 35 and sampling rate of 400 ml/min were used. Evidently, the LOD improvement had a saturation effect, i.e., increasing the sampling rate did not improve the LOD linearly, as illustrated in Table 2. A reasonable explanation could be that although the higher sampling rate brought in more NH3 molecules, however, the number of reactant ions, (H2O)nH+ was limited in the reaction region so that less than proportional product ions, (H2O)nNH4+ could be produced. Furthermore, the higher sampling flow rate would also decrease the reaction time according to formula 4. Therefore, increasing the sampling rate can improve the LOD sensitivity. In principle, by adjusting the sampling rate, one can control the detection sensitivity, i.e., using the lower sampling rate for higher concentration NH3 in the air while increasing the sampling rate when the NH3 concentration is relatively low. However, for quantitative measurement, this method cannot be used due to above mentioned non-linear response of the sensitivity versus sampling rate relationship. 3.4. Sensitivity and quantification IMS has fast response time and large linear range for NH3 measurement in the atmospheric environment. A quantitative calibration curve was made by diluting 6 ppm standard NH3 gas with different diluting ratio for the sampling gas, as shown in Fig. 5. The sampling rate kept at 50 ml/min, more than 200 measurements were performed for a sample, with each measurement averaging 10 times. The measurement response time for NH3 in the air reached 0.1 second level while the transition time between two different concentrations was 10 second. The quantitative curve for NH3 concentration measurements illustrated two sections of good linearity
in the range of 10 – 60 ppb and 60 – 400 ppb, with different slops and correlation coefficient R2 of 0.97 and 0.99, respectively. The linear range can be extended by using lower or higher sampling rates as mentioned previously. The accuracy of the data was calculated with 100 times measurements of 100 ppb NH3. The relative standard deviations (RSD) was 1.06%, and the errors were ±0.21 ppb with the confidence level of 95%. Furthermore, the IMS illustrated a short recovery time for measure high concentration NH3. Even at the concentration of 400 ppb, it recovered 80% intensity within 100 s. Sampling more clean air would promote the recovery. As showed in Fig. 5, the signal intensity fell sharply from 276 mv to the background level by increasing the sampling rate of clean air from 50 mL to 100 mL. 3.5. Long-term high frequency measurement of NH3 in outdoor air The experiments of measuring NH3 in outdoor air was carried out on the roof of our laboratory, a building with the height of 30-metre, located on a hillside in Dalian Institute of Chemical Physics. The NH+4 peak intensity had surveyed and recorded each second. Then the concentration of NH3 in atmospheric environment was obtained according the quantification mentioned above. The long-term daily concentration of NH3 from June 19th to December 3th in 2015 was presented in Fig. S5. During the period, the average concentration of gaseous NH3 in air environment was 58.8 ppb. The minimum concentration was 0.01 ppb, the maximum concentration was 252.2 ppb. Fast response time with high frequency measurement usually resulted in large amounts of data. In this study, 6 days’ NH3 concentration measurements were showed in Fig. 6. The massive measurement data were analyzed by origin 9 in speed mode. Within the measurements, the minimum concentration was 18.5 ppb at 7th July, while the maximum concentration was 457.2 ppb at 4th July. Regardless of concentration levels, the peak value of NH3 for each day appeared around 7 a. m. in most days. The sensitivity and stability of this instrument ensured the accurate measurement of the NH3 concentration during the monitoring time period.
4. Conclusion In this study, IMS was developed to measure NH3 concentration in the atmospheric environment for a long term with a sub-second high frequency fashion. The reduced mobility of the NH3 characteristic product ions was 2.77 cm2/V·s, which intensity was used to present concentration of NH3. By increasing sampling rate and averaging times, IMS achieved a LOD of 0.15 ppb. Using a determinant sampling rate, IMS showed a sub-second response time with a large linear response range. RH change in the environment presented no significant impact on the IMS measurement for NH3 in air. A long-term high frequency measurement of NH3 concentration by IMS was performed in Dalian city. The results demonstrated that IMS was a fast, accurate and stable method to provide a long-term sub-second response monitoring data for the NH3 concentrations in the atmospheric environment. Acknowledgements： Funding for this study was provided by the Chinese National Key Research and Development Plans (2016YFC0201200). Notes The authors declare no competing financial interest. Appendix A. Supplementary data Supplementary data related to this article can be found at. Reference: [1] J. Kirkby, J. Curtius, J. Almeida, E. Dunne, J. Duplissy, S. Ehrhart, A. Franchin, S. Gagne, L. Ickes, A. Kurten, A. Kupc, A. Metzger, F. Riccobono, L. Rondo, S. Schobesberger, G. Tsagkogeorgas, D. Wimmer, A. Amorim, F. Bianchi, M. Breitenlechner, A. David, J. Dommen, A. Downard, M. Ehn, R.C. Flagan, S. Haider, A. Hansel, D. Hauser, W. Jud, H. Junninen, F. Kreissl, A. Kvashin, A. Laaksonen, K. Lehtipalo, J. Lima, E.R. Lovejoy, V. Makhmutov, S. Mathot, J. Mikkila, P. Minginette, S. Mogo, T. Nieminen, A. Onnela, P. Pereira, T. Petaja, R. Schnitzhofer, J.H. Seinfeld, M. Sipila, Y. Stozhkov, F. Stratmann, A. Tome, J. Vanhanen, Y. Viisanen, A. Vrtala, P.E. Wagner, H. Walther, E. Weingartner, H. Wex, P.M. Winkler, K.S. Carslaw, D.R. Worsnop, U. Baltensperger, M. Kulmala, Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation, Nature, 476 (2011) 429-U477.
[2] K. Na, C. Song, C. Switzer, D.R. Cocker, Effect of ammonia on secondary organic aerosol formation from alpha-Pinene ozonolysis in dry and humid conditions, Environmental Science & Technology, 41 (2007) 6096-6102. [3] O. Hertel, C.A. Skjoth, S. Reis, A. Bleeker, R.M. Harrison, J.N. Cape, D. Fowler, U. Skiba, D. Simpson, T. Jickells, M. Kulmala, S. Gyldenkaerne, L.L. Sorensen, J.W. Erisman, M.A. Sutton, Governing processes for reactive nitrogen compounds in the European atmosphere, Biogeosciences, 9 (2012) 4921-4954. [4] R. Bobbink, K. Hicks, J. Galloway, T. Spranger, R. Alkemade, M. Ashmore, M. Bustamante, S. Cinderby, E. Davidson, F. Dentener, B. Emmett, J.W. Erisman, M. Fenn, F. Gilliam, A. Nordin, L. Pardo, W. De Vries, Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis, Ecological Applications, 20 (2010) 30-59. [5] M.P. Keuken, A. Wayers-Ijpelaan, R.P. Otjes, J. Slanina, Determination of NH3, HNO3 and NH4NO3 in Ambient Air by Automated Thermodenuder Systems and a Wet Annular Denuder System, in: G. Restelli, G. Angeletti (Eds.) Physico-Chemical Behaviour of Atmospheric Pollutants, Springer Netherlands1990, pp. 6-11. [6] C.W. Du, J. Wang, Z.J. Zhou, Y.Z. Shen, J.M. Zhou, In Situ Measurement of Ammonia Concentration in Soil Headspace Using Fourier Transform Mid-Infrared Photoacoustic Spectroscopy, Pedosphere, 25 (2015) 605-612. [7] J. Sintermann, C. Ammann, U. Kuhn, C. Spirig, R. Hirschberger, A. Gärtner, A. Neftel, Determination of field scale ammonia emissions for common slurry spreading practice with two independent methods, Atmospheric Measurement Techniques, 4 (2011) 1821-1840. [8] F. Bianchi, J. Dommen, S. Mathot, U. Baltensperger, On-line determination of ammonia at low pptv mixing ratios in the CLOUD chamber, Atmospheric Measurement Techniques, 5 (2012) 1719-1725. [9] J. Zheng, Y. Ma, M.D. Chen, Q. Zhang, L. Wang, A.F. Khalizov, L. Yao, Z. Wang, X. Wang, L.X. Chen, Measurement of atmospheric amines and ammonia using the high resolution time-of-flight chemical ionization mass spectrometry, Atmospheric Environment, 102 (2015) 249-259. [10] H. Yu, S.H. Lee, Chemical ionisation mass spectrometry for the measurement of atmospheric amines, Environmental Chemistry, 9 (2012) 190-201. [11] K. von Bobrutzki, C.F. Braban, D. Famulari, S.K. Jones, T. Blackall, T.E.L. Smith, M. Blom, H. Coe, M. Gallagher, M. Ghalaieny, M.R. McGillen, C.J. Percival, J.D. Whitehead, R. Ellis, J. Murphy, A. Mohacsi, A. Pogany, H. Junninen, S. Rantanen, M.A. Sutton, E. Nemitz, Field inter-comparison of eleven atmospheric ammonia measurement techniques, Atmospheric Measurement Techniques, 3 (2010) 91-112. [12] B. Timmer, W. Olthuis, A. van den Berg, Ammonia sensors and their applications - a review, Sensors and Actuators B-Chemical, 107 (2005) 666-677. [13] Y. Huang, L. Wieck, S. Tao, Development and evaluation of optical fiber NH3 sensors for application in air quality monitoring, Atmospheric Environment, 66 (2013) 1-7.
[14] Q. Zhou, L. Hua, C. Wang, E. Li, H. Li, Improved Analytical Performance of Negative 63Ni Ion Mobility Spectrometry for On-line Measurement of Propofol Using Dichloromethane as Dopant, Journal of The American Society for Mass Spectrometry, 26 (2014) 190-193. [15] Q. Zhou, W. Wang, H. Cang, Y. Du, F. Han, C. Chen, S. Cheng, J. Li, H. Li, On-line measurement of propofol using membrane inlet ion mobility spectrometer, Talanta, 98 (2012) 241-246. [16] Q.H. Zhou, E.Y. Li, X. Wang, Y.L. Gong, L. Hua, W.G. Wang, T.S. Qu, J.H. Li, Y.P. Liu, C.S. Wang, H.Y. Li, Trap-and-release membrane inlet ion mobility spectrometry for on-line measurement of trace propofol in exhaled air, Analytical Methods, 6 (2014) 698-703. [17] Q.H. Zhou, E.Y. Li, Z.X. Wang, Y.L. Gong, C.S. Wang, L. Guo, H.Y. Li, Time-resolved dynamic dilution introduction for ion mobility spectrometry and its application in end-tidal propofol monitoring, Journal of Breath Research, 9 (2015). [18] K.M. Roscioli, J.A. Tufariello, X. Zhang, S.X. Li, G.H. Goetz, G.L. Cheng, W.F. Siems, H.H. Hill, Desorption electrospray ionization (DESI) with atmospheric pressure ion mobility spectrometry for drug detection, Analyst, 139 (2014) 1740-1750. [19] S. Cheng, J. Dou, W. Wang, C. Chen, L. Hua, Q. Zhou, K. Hou, J. Li, H. Li, Dopant-assisted negative photoionization ion mobility spectrometry for sensitive detection of explosives, Analytical Chemistry, 85 (2013) 319-326. [20] L.Y. Peng, L. Hua, W.G. Wang, Q.H. Zhou, H.Y. Li, On-site Rapid Detection of Trace Non-volatile Inorganic Explosives by Stand-alone Ion Mobility Spectrometry via Acid-enhanced Evaporization, Scientific Reports, 4 (2014). [21] G.A. Eiceman, Ion mobility spectrometry as detector and sensor for chemical warfare agents and toxic industrial chemicals., Abstracts of Papers of the American Chemical Society, 224 (2002) U145-U145. [22] S.S. Cheng, C. Chen, W.G. Wang, H.Y. Li, Detection of Chemical Warfare Agents by Differential Mobility Spectrometry and Drift-time Ion Mobility Spectrometry Hybrid Technology, Chinese Journal of Analytical Chemistry, 42 (2014) 1264-1269. [23] G.A. Eiceman, M.R. Salazar, M.R. Rodriguez, T.F. Limero, S.W. Beck, J.H. Cross, R. Young, J.T. James, Ion Mobility Spectrometry of Hydrazine, Monomethylhydrazine, and Ammonia in Air with 5-Nonanone Reagent Gas, Analytical Chemistry, 65 (1993) 1696-1702. [24] E. Jazan, H. Mirzaei, Direct analysis of human breath ammonia using corona discharge ion mobility spectrometry, Journal of Pharmaceutical and Biomedical Analysis, 88 (2014) 315-320. [25] Z. Karpas, Ion mobility spectrometry of aliphatic and aromatic amines, Analytical Chemistry, 61 (1989) 684-689. [26] L. Myles, T.P. Meyers, L. Robinson, Atmospheric ammonia measurement with an ion mobility spectrometer, Atmospheric Environment, 40 (2006) 5745-5752.
[27] G. Neri, A. Lacquaniti, G. Rizzo, N. Donato, M. Latino, M. Buemi, Real-time monitoring of breath ammonia during haemodialysis: use of ion mobility spectrometry (IMS) and cavity ring-down spectroscopy (CRDS) techniques, Nephrology Dialysis Transplantation, 27 (2012) 2945-2952. [28] R. Janson, K. Rosman, A. Karlsson, H.C. Hansson, Biogenic emissions and gaseous precursors to forest aerosols, Tellus Series B-Chemical and Physical Meteorology, 53 (2001) 423-440. [29] Z.-Y. Meng, X.-B. Xu, T. Wang, X.-Y. Zhang, X.-L. Yu, S.-F. Wang, W.-L. Lin, Y.-Z. Chen, Y.-A. Jiang, X.-Q. An, Ambient sulfur dioxide, nitrogen dioxide, and ammonia at ten background and rural sites in China during 2007–2008, Atmospheric Environment, 44 (2010) 2625-2631. [30] A.L. Zbieranowski, J. Aherne, Ambient concentrations of atmospheric ammonia, nitrogen dioxide and nitric acid across a rural–urban–agricultural transect in southern Ontario, Canada, Atmospheric Environment, 62 (2012) 481-491. [31] M.B. Rhoades, D.B. Parker, N.A. Cole, R.W. Todd, E.A. Caraway, B.W. Auvermann, D.R. Topliff, G.L. Schuster, Continuous Ammonia Emission Measurements from a Commercial Beef Feedyard in Texas, Transactions of the Asabe, 53 (2010) 1823-1831. [32] Y. Zhou, S.Y. Cheng, J.L. Lang, D.S. Chen, B.B. Zhao, C. Liu, R. Xu, T.T. Li, A comprehensive ammonia emission inventory with high-resolution and its evaluation in the Beijing-Tianjin-Hebei (BTH) region, China, Atmospheric Environment, 106 (2015) 305-317. [33] Y.Z. Du, W.G. Wang, H.Y. Li, Resolution Enhancement of Ion Mobility Spectrometry by Improving the Three-Zone Properties of the Bradbury-Nielsen Gate, Analytical Chemistry, 84 (2012) 1725-1731. [34] L.Y. Peng, L. Hua, E.Y. Li, W.G. Wang, Q.H. Zhou, X. Wang, C.S. Wang, J.H. Li, H.Y. Li, Dopant titrating ion mobility spectrometry for trace exhaled nitric oxide detection, Journal of Breath Research, 9 (2015). [35] A.B. Kanu, M.M. Gribb, H.H. Hill, Predicting optimal resolving power for ambient pressure ion mobility spectrometry, Analytical Chemistry, 80 (2008) 6610-6619. [36] E.J. Davis, K.F. Grows, W.F. Siems, H.H. Hill, Improved Ion Mobility Resolving Power with Increased Buffer Gas Pressure, Analytical Chemistry, 84 (2012) 4858-4865. [37] M. Tabrizchi, F. Rouholahnejad, Pressure effects on resolution in ion mobility spectrometry, Talanta, 69 (2006) 87-90. [38] Y.Z. Du, W.G. Wang, H.Y. Li, Bradbury-Nielsen-Gate-Grid Structure for Further Enhancing the Resolution of Ion Mobility Spectrometry, Analytical Chemistry, 84 (2012) 5700-5707. [39] G.A. Eiceman, Z. Karpas, Ion Mobility Spectrometry(2nd), Taylor & Franics, DOI (2005) 2005, 2080-2097.
[40] S.H. Kim, K.R. Betty, F.W. Karasek, Mobility Behavior and Composition of Hydrated Positive Reactant Ions in Plasma Chromatography with Nitrogen Carrier Gas, Analytical Chemistry, 50 (1978) 2006-2012. [41] R. Fernandez-Maestre, C. Wu, H.H. Hill, Ammonia as a Modifier in Ion Mobility Spectrometry: Effects on Ion Mobilities and Potential as a Separation Tool, Journal of the Chilean Chemical Society, 59 (2014) 2398-2403. [42] H. Borsdorf, P. Fiedler, T. Mayer, The effect of humidity on gas sensing with ion mobility spectrometry, Sensors and Actuators B: Chemical, 218 (2015) 184-190.
Fig. 1. Schematic diagram of IMS for monitoring NH3.
Fig. 2. The positive ion spectrums of IMS with the drift tube temperature in 150 oC.
Fig. 3. Rp (a), Rp-p (b) and FWHM (c) changed with the drift tube temperature (90 170 oC)
Fig. 4. Spectra of IMS with different RH in sampling gas.
Fig. 5. Quantify the NH3 by IMS on-line measuring
Fig. 6. High frequency measurement of NH3
Table 1. Commonly used operating parameters for IMS Operating parameters
Setting
Ionization source
63
Ni
Drift field
400 V cm-1
Drift gas flow
400 mL min-1
Sample gas flow
50 mL min-1
Drift temperature
150 ºC
Drift tube length
6 cm
Injection pulse
0.2 ms
Scan time
9 ms
Averaging times
10 times
Table 2. LODs of IMS with different averaging times and sampling quantities. Average
Sampling quantity (mL/min)
(times)
30
50
80
100
200
300
400
5
22.7
4.31
1.95
1.48
0.68
0.52
0.48
8
19.9
3.77
1.71
1.30
0.60
0.46
0.42
10
15.0
2.85
1.29
0.98
0.45
0.35
0.32
15
13.4
2.54
1.15
0.88
0.40
0.31
0.28
20
10.9
2.08
0.94
0.72
0.33
0.25
0.23
25
8.51
1.62
0.73
0.56
0.26
0.20
0.18
30
7.70
1.46
0.66
0.50
0.23
0.18
0.16
35
6.89
1.31
0.59
0.45
0.21
0.16
0.15
Highlights： 1. Ion mobility spectrometry was developed to monitor gaseous ammonia in the ambient air in a long-term measurement. 2. The quantitative analysis frequency has achieved 10 Hz with a data averaging of 10 times. 3. The limit of detection of sub-ppb level was obtained. 4. The affect of ambient humidity was greatly reduced using drift temperature of over 150 oC.