A high-sensitivity bioaerosol monitor based on a single 365 nm LED is developed and a calibration approach is discussed for the first time. The fluorescence detection system, which is the core part of the monitor, contains an optical detection module and a fluorescence signal processor configured with a phase sensitive detector (PSD). B800 fluorescent microspheres and staphylococcus are used for performance evaluation of the monitor. B800 microspheres are appropriate as calibration material. The experimental results demonstrate the PSD plays a significant role in improving sensitivity and signal-to-noise ratio (SNR) of detection. Our monitor can detect staphylococcus concentration above 1800 cfu/L of air stably.
© 2013 Optical Society of America
Biological aerosol is a suspension of airborne particles that contain living organisms or were released from living organisms . These airborne particles usually include bacteria, fungi, pollens, viruses, protein allergens from animals or plants. Bioaerosols play an important role in climate change and has detrimental effects on human health and agriculture. Therefore, it is important to accurately measure concentration of bioaerosols promptly in different environments . Many automated detection systems utilizing various microbiological techniques for analysis of collected microbes have been developed and, in some cases, portable bioaerosol samplers have been integrated .
In the past several decades, optical detection techniques have received considerable attention in the field of bioaerosol monitoring and analysis due to its advantages of rapid response, undamage and high sensitivity . For fluorescence based sensors, the size, shape and intrinsic fluorescence of an aerosol particle are generally the three conditions for discriminating its biological attribution with low false alarm rate [5,6]. Intrinsic fluorescence is the inherent characteristics of bioaerosols, and it is usually generated from the organic substances (such as amino acids, riboflavin and reduced nicotinamide adenine dinucleotide (NADH), etc.) under excitation of ultraviolet light . Ultra violet light induced fluorescence (UV-LIF) remains one of the most prevalent approaches for the real time detection of biological aerosols .
Most fluorescence analysis systems use laser sources to induce individual bioaerosol particle and a fluorescence spectrometer to analyze the spectrum [9–11]. UV lasers deliver high-power monochromatic exciting light, and at the same time, they are normally more expensive than LEDs. Also, some UV lasers such as semiconductor UV optical sources have been applied for low cost and low power . Due to the requirement of compact and low cost in the field monitoring, LEDs are an attractive alternative to lasers because of reduced power of operation, and increased flexibility in spectral control . A particular configuration composed of a linear array of LEDs was proposed for the fluorescence-based detection of single flowing aerosol particles for the first time . Bioaerosol detection systems incorporating dual wavelength UV LED arrays for single airborne particle were demonstrated . Other LED-based environmental detection instruments have also been developed .
Single LED induced fluorescence (LED-IF) system is a good choice for field bioaerosol monitoring. This system usually detects the fluorescence intensity of a group of bioaerosol particles collected by a conventional plate impactor  or a virtual impactor . However, it still requires more efforts to improve the sensitivity (or the lower limit of detection) and SNR of real-time bioaerosol monitoring. Besides, calibration of the bioaerosol monitor to date is pending and interesting to be discussed.
This paper reports our work on development and calibration of a high SNR and sensitivity bioaerosol monitor with a single 365 nm LED. The designed optical fluorescence detection module targets key biomolecules such as NADH and riboflavin. The fluorescence signal processor with a PSD can improve the performance of the monitor significantly. The calibration approach with B800 fluorescent microspheres is proposed for the fluorescence detection system. With the advantages of lower limit, high SNR and low cost, the monitor could have a potential application for distributed bio-aerosol sensor network in future .
2. Monitor design
Besides the electric control system, the single LED based bioaerosol monitor consists of three main function parts: a commercialized laser particle counter, a conventional plate impactor for aerosol particle collection and a fluorescence detection system. The laser particle counter is employed to measure the concentration of aerosols particles with different equivalent optical diameter. The conventional plate impactor is designed with cutoff diameter of 0.5 μm based on inertial impaction and separation, and thus most pathogenic bioaerosol particles whose sizes are almost above 0.5 μm can be trapped into a spot on the collection plate efficiently. The fluorescence detection system is made up of an optical detection module and a fluorescence signal processor configured with a PSD.
The bioaerosol monitor periodically detects the aerosol concentration and fluorescence intensity. As shown in Fig. 1(a), every automatic detection cycle has four steps: collection plate clearing, fluorescence background detection, particle collection by sampling for a period such as one minute, and fluorescence detection. In the process of particle collection, the laser particle counter continually measures the aerosol particle concentration.
In each cycle, the real fluorescence value (called the fluorescence value for short in following sections) can be calculated by subtracting the background fluorescence value from the fluorescence detection value measured after particle collection. The monitor will alarm when both the fluorescence value and particle concentration value exceed the threshold value which is preset according to the environment conditions. The exterior of the instrument is shown in Fig. 1(b).
3. Fluorescence detection system
3.1 Optical fluorescence detection module design
NADH is a type of highly biological fluorescent substance, with absorption and emission maxima at 340 nm and 460 nm, respectively. Therefore, a UV LED (Model NSHU591B from Nichia Corporation, Japan) with peak wavelength of 365 nm, is selected as the exciting light source. Its full width of half maximum spectrum is as narrow as 10 nm.
The layout of fluorescence detection system of the bioaerosol monitor is shown in Fig. 2. The optical system includes two light paths. In the excitation light path, the incident beam from the LED goes through a narrow band-pass filter and a collimating lens, then is reflected by the dichroic mirror and ultimately focused onto the particle spot of the collecting plate. In the fluorescence detection optical path, the fluorescence is collimated by the spherical lenses and transmits the dichroic mirror and the long-pass filter (Model JB450, made in China) with a cutoff value of 450 nm, then is focused on the photosensitive area of the photomultiplier tube (PMT, Model 1P21 from Hamamatsu, Japan) by the back focusing lens. The narrow band-pass filter (Model ZWB2, made in China) centered at 365 nm with transmission of more than 80%, and possessing a cutoff value of 405 nm with transmission of less than 8%, is adopted in the excitation light path to filter out the spectrum components overlapping with fluorescence spectrum. The dichroic mirror with a reflection wavelength range of 340-410 nm and transmission of 420-650 nm is used to separate the excitation and fluorescence signals.
The stray light and the residual exciting light can be blocked by the filters and the aperture in front of PMT, and thus, the signal to noise ratio (SNR) of the optical fluorescence detection module can be improved significantly. The electronic signal from the PMT module is regarded as a measure of fluorescence intensity. The photodiode (PD) in the light trap is utilized to monitor the light intensity of LED source, which can be referred for normalization of fluorescence intensity.
To verify the validation of the optical fluorescence detection module, we smear the NADH sample uniformly on the collection plate and alternate the PMT with a spectrometer (Model QE65000 from Ocean Optics, USA) to detect the fluorescence spectrum. As shown in Fig. 3, the measured fluorescence spectrum is consistent with emission spectrum of NADH in the wavelength range from 450 nm to 700 nm.
3.2 Fluorescence signal processor with a PSD
Intrinsic fluorescence of biological fluorophores is generally very weak. The stray light from ambient space and dark current of the detector could interfere the fluorescence signals of bioaerosols in the monitor.
Demodulation with a PSD is a valid method in filtering optical and electrical noises . The light source is modulated by a reference signal with a frequency of 2kHz. When the fluorescence signal and the reference signal with the same frequency and phase pass through a PSD and a low-pass filter, the signals with different frequency from the reference signal or the same frequency at 90° phase difference will be reduced obviously.
In our fluorescence signal processor, the square wave of 50% duty ratio generated by Model STM32 single-chip microprocessor is set as the reference signal which also chops the excitation LED intensity as a switching signal. The fluorescence signal output from the PMT module is resulted from the chopped LED illumination in intensity at the same frequency. By a DC block circuit, the fluorescence voltage signal from the PMT module is diverted into an alternative symmetric square wave of 50% duty ratio. Then the alternative fluorescence signal and the reference signal are simultaneously input into a phase sensitive demodulator. The Model AD630 microchip is a high precision balanced modulator which combines a flexible commutating architecture and it is fit to be applied as phase sensitive detection and square wave multiplication. To further eliminate the noise, the output signals of AD630 go through a RC low-pass filter. Processed by a phase reverser, a positive expecting voltage signal is output as the fluorescence intensity value. On the other hand, when the duty ratio of chopped LED intensity is 50%, the allowable forward current of the LED can be increased and more optical output power can be obtained than the case of constant direct current driving.
The square wave with 2 kHz frequency is tested to be sufficient to avoid the dominant noise such as the power line interference with 50 Hz. As shown in Fig. 4, the contrast result demonstrates that the fluorescence signal processor with the PSD can eliminate the noise effectively and the acquired fluorescence value is more stable and precise. In the case of no PSD, the fluorescence signals need special smoothing processing to reduce the influence of fluctuation.
4. Performance evaluation and calibration
In order to evaluate the performance of the bioaerosol monitor, two particulate samples are chosen respectively. One is a kind of fluorescent microspheres used for calibration of the monitor, and the other is staphylococcus used for the sensitivity detection.
As shown in Fig. 5, an aerosol generator is adopted to generate the target aerosol in a buffer bottle to evaluate and calibrate the performance of the bioaerosol monitor. The standard fluorescent microspheres of Model B800 (Thermo Scientific, USA) is chosen as the substitute of the biologic particles. This type of microspheres have close excitation and fluorescence spectrum to NADH, which is one of the main targets in the 365 nm LED based fluorescence detection system. The mean diameter of B800 microspheres is 0.8 μm, and the size uniformity (standard deviation) is less than 3%. The concentration of B800 aerosol can be controlled by adjusting the aerosol generator.
The measured fluorescence values for different B800 aerosol concentrations are displayed in Fig. 6. For comparison, the corresponding measured fluorescence results in the case of no PSD are also shown in this figure and the LED is driven by typical constant direct current. The correlation coefficient of the fitted line with PSD is 98.3% and that without PSD is 96.6%. These results show that the linear relationship of the fluorescence value to particle concentration is well, and furthermore, the B800 microspheres are appropriate for calibration and performance evaluation of the bioaerosol monitor.
The lowest fluorescence value of detection is set to 0.1V on the basis of a large amount of test results. According to the linear fitting results shown in Fig. 6, the lower limit of detection is improved when the PSD is applied. And our monitor can detect B800 aerosol concentration above 350 particles/L stably. B800 microspheres are made of polystyrene with fluorescent dyes and quantum efficiency of B800 is much higher than real bioaerosol simulants. To evaluate and verify the sensitivity of bioaerosol detection, aerosolized staphylococcus was measured by our monitor. The measured fluorescence results for different staphylococcus concentrations of the monitor are shown in Fig. 7(a). The fluorescence value increases with staphylococcus concentration of air linearly. More results for sensitivity detection of the monitor in the case of PSD and no PSD are displayed in Fig. 7(b) when staphylococcus concentration varies between 1500 and 3000 cfu/L. It can be concluded that in the case of PSD our monitor can detect staphylococcus with concentration above 1800 cfu/L of air stably. By contrast, in the case of no PSD, the monitor can merely detect staphylococcus with concentration of 2500 cfu/L of air. So, the lower limit of detection of our monitor has been improved significantly when the fluorescence signal processor works with the PSD.
This paper works on development and calibration of the high-sensitivity bioaerosol monitor based on a single 365 nm LED. With B800 fluorescent microspheres as the calibration material, the calibration approach is proposed for the bioaerosol monitor. NADH sample can be detected by the designed optical fluorescence detection module in the experiment. The fluorescence signal processor with the PSD is verified to play a significant role in improving sensitivity and SNR of detection. Our monitor can detect staphylococcus concentration above 1800 cfu/L of air stably.
Weak fluorescent intensity measurement may suffer from interferences caused by other chromophores and scattering components in the sample. A good method to lower the false alarm rate is to add another LED based fluorescence detection system with a different wavelength, which targets tryptophan or other biological substance in bioaerosols. As the key biomolecules, tryptophan and NADH are already the main reference targets. We have explored calibration of dual-channel UV LED induced fluorescence systems and discussed preliminary methods of lowering false alarm rate of detection . The ratio of 280 nm induced fluorescence intensity to 365 nm induced fluorescence intensity may be regarded as a further criterion of discriminating biological particles from non-biological particles. In the future, more efforts are needed to assure the false alarm rate of detection and accomplish precise identification for bioaerosols.
Our work was supported by the Shanghai Municipal Natural Science Foundation (No. 11ZR1441700). We gratefully acknowledge the contributions by Chao Xiong and Ao Xu, who have graduated from Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences.
References and links
1. C. M. Watches and C. B. Cox, Bioaerosols Handbook (Lewis Publishers, 1995), Chap. 1.
2. P. S. Chen and C. S. Li, “Real-time monitoring for bioaerosols—flow cytometry,” Analyst (Lond.) 132(1), 14–16 (2006). [CrossRef]
3. E. V. Usachev, A. V. Pankova, E. A. Rafailova, O. V. Pyankov, and I. E. Agranovski, “Portable automatic bioaerosol sampling system for rapid on-site detection of targeted airborne microorganisms,” J. Environ. Monit. 14(10), 2739–2745 (2012). [CrossRef] [PubMed]
4. Z. Xu, Y. Wu, F. Shen, Q. Chen, M. Tan, and M. Yao, “Bioaerosol science, technology, and engineering: past, present, and future,” Aerosol Sci. Technol. 45(11), 1337–1349 (2011). [CrossRef]
5. M. J. Shelton, S. P. Evans, P. D. Smith, I. A. Simpson, P. H. Kaye, and J. M. Clarke, “Real-time biological agent detection using particle size, shape and fluorescence characterisation,” Proc. SPIE 5617, 284–291 (2004). [CrossRef]
6. C. Feng, L. Huang, J. Wang, Y. Zhao, and H. Huang, “Theoretical studies on bioaerosol particle size and shape measurement from spatial scattering profiles,” Chin. Opt. Lett. 9(9), 092901–092904 (2011). [CrossRef]
7. J. R. Lakowicz, Principles of Fluorescence Spectroscopy (Springer Science and Business Media, 2006), Chap. 3.
8. D. Richard, “LIF bio-aerosol threat triggers: then and now,” Proc. SPIE 7484, 74840H, 74840H-15 (2009). [CrossRef]
10. U. Bundke, B. Reimann, B. Nillius, R. Jaenicke, and H. Bingemer, “Development of a bioaerosol single particle detector (BIO IN) for the fast ice nucleus chamber FINCH,” Atmos. Meas. Tech. 3(1), 263–271 (2010). [CrossRef]
11. Y. L. Pan, S. C. Hill, R. G. Pinnick, J. M. House, R. C. Flagan, and R. K. Chang, “Dual-excitation-wavelength fluorescence spectra and elastic scattering for differentiation of single airborne pollen and fungal particles,” Atmos. Environ. 45(8), 1555–1563 (2011). [CrossRef]
12. J. Cabalo, M. DeLucia, A. Goad, J. Lacis, F. Narayanan, and D. Sickenberger, “Overview of the TAC-BIO detector,” Proc. SPIE 7116, 71160D, 71160D-11 (2008). [CrossRef]
13. A. E. Moe, S. Marx, N. Banani, M. Liu, B. Marquardt, and D. M. Wilson, “Improvements in LED-based fluorescence analysis systems,” Sensor Actuat. Biol. Chem. 111–112, 230–241 (2005).
14. K. Davitt, Y. K. Song, W. Patterson Iii, A. V. Nurmikko, M. Gherasimova, J. Han, Y. L. Pan, and R. Chang, “290 and 340 nm UV LED arrays for fluorescence detection from single airborne particles,” Opt. Express 13(23), 9548–9555 (2005). [CrossRef] [PubMed]
15. Y. L. Pan, V. Boutou, R. K. Chang, I. Ozden, K. Davitt, and A. V. Nurmikko, “Application of light-emitting diodes for aerosol fluorescence detection,” Opt. Lett. 28(18), 1707–1709 (2003). [CrossRef] [PubMed]
16. C. J. Collins, A. Altman, W. Roth, and J. C. Carrano, “Low cost, LED-based xMAP analyzer for multiplexed diagnosis and environmental detection of biological agents,” Proc. SPIE 7116, 711605, 711605-7 (2008). [CrossRef]
17. D. J. Rader and V. A. Marple, “Effect of ultra-Stokesian drag and particle interception on impaction characteristics,” Aerosol Sci. Technol. 4(2), 141–156 (1985). [CrossRef]
19. J. M. Clark, M. J. Shelton, S. P. Evans, P. D. Smith, I. A. Simpson, and P. H. Kaye, “A new real-time biological agent characterisation system,” Proc. SPIE 5990, 59900Z, 59900Z-8 (2005). [CrossRef]
20. J. Gao, Detection of Weak Signals (Tsinghua University, 2011), Chap. 4.
21. A. Xu, C. Xiong, P. Zhang, Y. Zhao, and H. Huang, “Research on dual-channel detection technology of bio-aerosols with intrinsic fluorescence measurement,” Acta Opt. Sin. 33(8), 0812005 (2013) (in Chinese). [CrossRef]