CN117074332B - Method for monitoring bioaerosol particles - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 35
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- 238000010183 spectrum analysis Methods 0.000 claims abstract description 10
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- 238000001228 spectrum Methods 0.000 claims description 15
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- JLVVSXFLKOJNIY-UHFFFAOYSA-N Magnesium ion Chemical compound [Mg+2] JLVVSXFLKOJNIY-UHFFFAOYSA-N 0.000 claims description 2
- FKNQFGJONOIPTF-UHFFFAOYSA-N Sodium cation Chemical compound [Na+] FKNQFGJONOIPTF-UHFFFAOYSA-N 0.000 claims description 2
- 229910001424 calcium ion Inorganic materials 0.000 claims description 2
- 229910052742 iron Inorganic materials 0.000 claims description 2
- XEEYBQQBJWHFJM-UHFFFAOYSA-N iron Substances [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 2
- 229910001425 magnesium ion Inorganic materials 0.000 claims description 2
- 229910001414 potassium ion Inorganic materials 0.000 claims description 2
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- 229910001427 strontium ion Inorganic materials 0.000 claims description 2
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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- Biochemistry (AREA)
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Abstract
The invention discloses a method for monitoring bioaerosol particles, belonging to the field of chemistry and biosensing. The bioaerosol monitoring method detects the concentration of the bioaerosol in the air by detecting the concentration of the metal ions contained in the bioaerosol. The method disclosed by the invention can be used for monitoring the concentration of the biological aerosol in the air in real time, and the interference of chemical gas and non-biological particles can be effectively eliminated through the disclosed spectrum analysis algorithm.
Description
Technical Field
The invention relates to the technical field of biological sensing, in particular to a method for monitoring biological aerosol particles.
Background
Biological aerosols are widely distributed in the earth's atmosphere and play an important role in the chemical and physical effects of the atmosphere, ecosystems, climate, public health, and the like. The traditional off-line bioaerosol monitoring method is to collect bioaerosol particles on a collecting medium through gravity, inertia, filtration and static electricity, and then culture and observe the bioaerosol particles to obtain information such as concentration, composition and the like. The on-line monitoring biological aerosol mainly comprises nucleic acid detection, fluorescence spectrometry, mass spectrum, chromatograph, ultraviolet spectrum, infrared spectrum, raman spectrum and other technologies. The nucleic acid detection method has the advantages of specificity, high sensitivity and high detection speed, but the technical operation difficulty is high, the skilled professional is needed, the gene chip can only be used once, and the cost is high. Besides the advantages of high nucleic acid detection sensitivity, strong specificity and trace analysis, the fluorescence spectrometry has the advantages of simple operation and large detection range, but is not easy to exclude non-biological fluorescent particle interference, and the identification of fluorescent particle types is difficult.
The method essentially monitors the bioaerosol by using the excitation light-induced bioluminescence principle, which is to measure the intrinsic fluorescence intensity or spectrum of single particles under the induction of short-wavelength excitation light and distinguish biological particles from non-biological particles according to the fluorescence intensity or fluorescence spectrum characteristics. However, some interference particles such as pollen, paper scraps, plant fragments, particles containing polycyclic aromatic hydrocarbon, part of dust and the like exist in the air, and the intrinsic fluorescence which has the intensity close to that of the microorganism particles and is not easy to identify in spectral characteristics can be emitted under the excitation of short wavelength. The false alarm problem of the bioaerosol monitoring method and equipment based on the excitation light induced intrinsic fluorescence principle is determined in principle.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a method for monitoring bioaerosol particles.
A method of monitoring bioaerosol particles, comprising: monitoring the concentration of bioaerosol particles in the air by detecting the concentration of metal ions contained in the bioaerosol sample;
The bioaerosol sample is a bacterial and/or fungal bioaerosol sample containing metal ions.
According to an embodiment of the present invention, the metal ions may include one or two or more of the following metal ions: potassium ion, calcium ion, sodium ion, strontium ion, iron ion, magnesium ion.
According to an embodiment of the invention, the concentration of the metal ions may be measured by a metal ion detector, for example selected from any one of the following instruments: flame photometric detectors, atomic absorption detectors, inductively coupled plasma detectors, X-ray fluorescence detectors, laser induced breakdown spectroscopy detectors.
According to embodiments of the invention, the bioaerosol sample may be a gas sample or a liquid sample. For example, the liquid sample is a liquid sample after converting the collected bioaerosol sample into a deionized water solution.
According to an embodiment of the invention, the monitoring method comprises: clean air samples were used as blank samples.
According to an embodiment of the invention, the detection of the concentration of the metal ions is obtained by a spectroscopic analysis algorithm.
According to one embodiment of the invention, the method for monitoring bioaerosol ions comprises the steps of:
Step A, starting a metal ion detector, introducing a clean sample into the metal ion detector after a base line is stable, recording the change of a concentration signal of I metal ions in the clean sample (namely a blank sample) along with time, and recording a signal value as a sample background signal S (0,I)＝∑(S(0,i) after the concentration signal of the metal ions is stable;
Step B, introducing a bioaerosol sample into the metal ion detector, detecting metal ions contained in the bioaerosol sample, and causing the change of a metal ion concentration signal, and recording the signal value of the metal ion I at the moment as S (t,I)＝∑(S(t,i));
Step C, calculating the change value of the signal of the concentration of the metal ion I to be S (Δ,I) through a spectrum analysis algorithm F (S (t,I)-S(0,I));
Step D, when S (Δ,I) is greater than the threshold, S (Δ,I) is a trigger signal of the monitoring alarm module, indicating that a bioaerosol sample is monitored, and determining the concentration of bioaerosol particles according to the value of S (Δ,I).
According to an embodiment of the present invention, the spectrum analysis algorithm F (S (t,I)-S(0,I)) calculates the variation value S (Δ,I) of the characteristic signal concentration of the bioaerosol sample by using one metal ion spectrum signal intensity or using the relative spectrum signal intensities of two or more metal ions in combination:
According to one embodiment of the present invention, the calculation of S (Δ,I) by the spectrum analysis algorithm F (S (t,I)-S(0,I)) may be based on any one of the following formulas:
S(Δ,I)＝sqrt(S(Δ,I1))；
S(Δ,I)＝sqrt(S(Δ,I1))×sqrt(S(Δ,I2))；
S(Δ,I)＝sqrt(S(Δ,I1))×sqrt(S(Δ,I2))×……×sqrt(S(Δ,In))，
sqrt represents square, n represents n metal ions in the bioaerosol sample, and n is more than or equal to 3;
Wherein S (Δ,I1)＝S(t,I1)-S(0,I1);
S(Δ,I2)＝S(t,I2)-S(0,I2)；
S(Δ,In)＝S(t,In)-S(0,In)；
preferably, the threshold may be set to 0, such as when S (Δ,I) is greater than 0, indicating that a bioaerosol sample is being monitored, and the value of S (Δ,I) is positively correlated with the particle concentration of the bioaerosol.
The invention also provides the use of a metal ion detector in monitoring bioaerosol particle concentration.
Preferably, the metal ion detector has the options as shown above.
The invention has the beneficial effects that:
(1) The invention provides a biological aerosol monitoring method which is different from the existing biological aerosol monitoring principle, the concentration of the biological aerosol particles in the air is monitored by detecting the concentration of characteristic metal ions contained in the biological aerosol particles, a spectrum analysis algorithm is used, and the biological particles and the non-biological ions are distinguished by utilizing single ion spectrum characteristics or combination of spectrum characteristics of a plurality of ions, so that the method not only can realize the real-time monitoring of the concentration of the biological aerosol, but also can effectively eliminate the interference of chemical gas and the non-biological particles, and the defect of false report of the existing aerosol monitoring method under the interference of the non-biological particles is overcome.
(2) The method is suitable for gas samples and liquid samples, and can be used for directly sampling air samples or converting the air samples into liquid samples after enrichment sampling.
(3) The monitoring method provided by the invention can be conveniently implemented on the existing metal ion detectors with different principles, and special instruments and equipment are not required to be developed.
(4) The monitoring method provided by the invention is simple, flexible and easy to deploy.
Drawings
FIG. 1 is a flame photometric spectrum of a bioaerosol sample and a blank sample.
Fig. 2 is a graph of spectral signal intensity versus time for two metal ions.
Fig. 3 is a graph of spectral signal intensity over time after calculation.
Fig. 4 is a graph of spectral signal over time at 589 and 757 nanometers.
Fig. 5 is a graph of relative concentration of bioaerosols as a function of time.
Detailed Description
The technical scheme of the invention will be further described in detail below with reference to specific embodiments. It is to be understood that the following examples are illustrative only and are not to be construed as limiting the scope of the invention. All techniques implemented based on the above description of the invention are intended to be included within the scope of the invention.
Unless otherwise indicated, the starting materials and reagents used in the following examples were either commercially available or may be prepared by known methods.
Example 1: monitoring bacillus subtilis biological aerosol sample by direct sample injection method
In this example, an exemplary hydrogen flame photometric detector was chosen as the ion detector, and an exemplary bioaerosol sample of bacillus subtilis was used as the experimental sample.
Firstly, a flame photometric spectrum (figure 1, A) of a clean air sample is obtained through a full spectrum scanning mode, then the obtained biological aerosol sample of bacillus subtilis is introduced into a detector to obtain a flame photometric spectrum (figure 1, B) of the biological aerosol sample, and characteristic absorption peaks of sodium (Na +) and potassium (K +) at 589 and 767 nanometers of the biological aerosol sample can be obtained by comparing the two spectra. The experiment continuously monitors two characteristic absorption peaks and judges whether a clean air sample or a biological aerosol sample is introduced according to a spectrum analysis algorithm. The method comprises the following specific steps:
1. the hydrogen flame photometric detector is turned on, a clean air sample (i.e., a blank sample) is introduced into the flame photometric detector, and after the baseline is stabilized, a flame photometric spectrum of 550-800 nm of the clean air sample is recorded (fig. 1, a).
2. Generating a bioaerosol air sample containing bacillus subtilis by utilizing an aerosol generator, introducing the sample into a flame photometric detector, and recording a flame photometric spectrum of the bioaerosol air sample at 550-800 nanometers. Wherein the spectral signals of two metal ions, sodium (Na +) and potassium (K +), appear at 589 and 767 nm, respectively (fig. 1, b). The signal intensities of 589 and 767 nm concentrations in the blank samples were recorded as S (0,Na) and S (0,K), respectively, and then the spectral signal intensities of sodium (Na +) and potassium (K +) at time t 589 and 767 nm were recorded as S (t,Na) and S (t,K). In this example, a signal having an intensity of 3240 or less was recorded as a background noise signal.
3. To improve the anti-interference capability of the method, the spectral signal intensities of two metal ions, namely sodium (Na +) and potassium (K +), are monitored simultaneously in the embodiment. A clean air sample and a bioaerosol sample were alternately vented while the spectral signals at 589 and 767 nanometers were recorded. The spectral signal intensities of the two metal ions sodium (Na +) and potassium (K +) are shown in fig. 2 as a function of time. In this example, it was confirmed that the bacillus subtilis bioaerosol sample contained at least two ions of sodium (Na +) and potassium (K +) at the same time, and therefore, the sample was confirmed to be a bioaerosol sample only when signals of two ions of sodium (Na +) and potassium (K +) could be detected at the same time.
4. Based on the above analysis, the spectral analysis algorithm in the present embodiment:
S(Δ,Na)＝S(t,Na)-S(0,Na)---------------------------------(1)
S(Δ,K)＝S(t,K)-S(0,K)-------------------------------------(2)
S(Δ,I)＝sqrt(S(Δ,Na))×sqrt(S(Δ,K))---------(3)
Since the open square operation can be performed only with positive numbers, S (Δ,I) can correctly output the calculation result only when S (Δ,Na) and S (Δ,K) are equal to or greater than 0 at the same time, as shown in fig. 3. In this embodiment, the threshold of the alarm signal is 0, when S (Δ,I) is greater than 0, it indicates that the bioaerosol sample is detected, and the value of S (Δ,I) is positively correlated with the concentration of the bioaerosol.
Those skilled in the art will appreciate that the present embodiment methods are also applicable to all bacterial and/or fungal bioaerosol samples containing one or more of the metal ions listed in the specification.
Example 2: monitoring riboflavin aerosol interference sample by direct sample injection method
A bioaerosol monitoring instrument based on the principle of bioautofluorescence is used for monitoring bioaerosols by exciting substances with fluorescent properties in organisms through ultraviolet light. And is therefore susceptible to interference from aerosols having fluorescent properties in air. In nature, there are a large number of substances whose emitted fluorescence wavelength range covers or partially coincides with NADH and riboflavin. Such as various polycyclic aromatic compounds, lignin, natural organics, etc., which results in the bioaerosol monitoring and alarm devices being easily disturbed to produce false alarms. To illustrate the interference performance of the embodiment of example 1, a riboflavin aerosol was used as an interference sample in this example. In this example, an experiment for preventing interference of riboflavin aerosol was performed under the same conditions as in example 1. The method comprises the following specific steps:
1. the hydrogen flame photometer was turned on and a clean air sample was introduced into the flame photometer and after the baseline was stabilized, the spectral signals at 589 and 767 nanometers were continuously recorded.
2. And sequentially introducing a clean air sample, a biological aerosol sample, a clean air sample, a riboflavin aerosol sample and a clean air sample to obtain spectrograms of the spectral signals at 589 and 767 nanometers, which change with time, as shown in figure 4.
3. The data were processed as provided in example 1 by a spectral analysis algorithm. Spectra of the resulting bioaerosol over time were obtained fig. 4 and 5.
It can be seen from this experiment that riboflavin aerosols that would interfere with biological monitoring equipment based on the principle of uv-induced bio-fluorescence do not interfere with the method provided by the present invention.
The embodiments of the present invention have been described above. However, the present invention is not limited to the above embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A method of monitoring bioaerosol particles, the method comprising: monitoring the concentration of bioaerosol particles in the air by detecting the concentration of metal ions contained in the bioaerosol sample;
the bioaerosol sample is a bacterial and/or fungal bioaerosol sample containing metal ions;
Taking a clean air sample as a blank sample;
the method comprises the following specific steps:
Step A, starting a metal ion detector, introducing a blank sample into the metal ion detector after a base line is stable, recording the change of a concentration signal of I metal ions in the blank sample along with time, and recording a signal value as a sample background signal S (0,I)＝∑(S(0,i) after the concentration signal of the metal ions is stable;
Step B, introducing a bioaerosol sample into the metal ion detector, detecting metal ions contained in the bioaerosol sample, and causing the change of a metal ion concentration signal, and recording the signal value of the metal ion I at the moment as S (t,I)＝∑(S(t,i));
Step C, calculating the change value of the signal of the concentration of the metal ion I as S (Δ,I) by a spectrum analysis algorithm F (S (t,I)-S(0,I)), namely utilizing the spectrum signal intensity of one metal ion or utilizing the relative spectrum signal intensity of more than two metal ions in combination;
the spectrum analysis algorithm F (S (t,I)-S(0,I)) is calculated to obtain S (Δ,I) based on any one of the following formulas:
S(Δ,I)＝sqrt(S(Δ,I1))；
S(Δ,I)＝sqrt(S(Δ,I1))×sqrt(S(Δ,I2))；
S(Δ,I)＝sqrt(S(Δ,I1))×sqrt(S(Δ,I2))×……×sqrt(S(Δ,In))，
sqrt represents open square operation, n represents n metal ions in the bioaerosol sample, and n is more than or equal to 3;
Wherein S (Δ,I1)＝S(t,I1)-S(0,I1);
S(Δ,I2)＝S(t,I2)-S(0,I2)；
S(Δ,In)＝S(t,In)-S(0,In)；
The threshold is set to 0;
And D, when S (Δ,I) is larger than the threshold value, S (Δ,I) is a trigger signal of the monitoring alarm module, the trigger signal indicates that a bioaerosol sample is monitored, the value of S (Δ,I) is positively correlated with the particle concentration of the bioaerosol, and the concentration of bioaerosol particles is determined according to the value of S (Δ,I).
2. The method of monitoring according to claim 1, wherein the metal ions comprise one or more of the following metal ions: potassium ion, calcium ion, sodium ion, strontium ion, iron ion, magnesium ion.
3. The method of monitoring according to claim 1, wherein the metal ion detector is selected from any one of the following instruments: flame photometric detectors, atomic absorption detectors, inductively coupled plasma detectors, X-ray fluorescence detectors, laser induced breakdown spectroscopy detectors.
4. The method of claim 1, wherein the bioaerosol sample is a gas sample or a liquid sample.
5. Use of a metal ion detector for monitoring the concentration of bioaerosol particles, employing the bioaerosol particle monitoring method of claim 1.
6. The use according to claim 5, wherein the metal ion detector is selected from any one of the following instruments: flame photometric detectors, atomic absorption detectors, inductively coupled plasma detectors, X-ray fluorescence detectors, laser induced breakdown spectroscopy detectors.
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