CN115713980A - High-value tracing method for VOCs in industrial park - Google Patents

Abstract

The invention relates to a high-value tracing method for VOCs in an industrial park, which screens enterprise discharge mouths possibly polluting sites by intelligently identifying the high value of VOCs real-time monitoring data of the sites and fully considering the chemical composition change condition and meteorological conditions in the process of increasing the concentration of the VOCs, and quantitatively estimates the contribution of each enterprise discharge mouth to the high-value VOCs concentration of the sites by using a chemical mass balance principle. The method can intelligently identify the VOCs pollution time period, finely analyze the source of the VOCs pollution time in real time, quantify the contribution of the enterprise discharge port to the concentration of the VOCs, and provide timely and effective support for the VOCs pollution control of the industrial park.

Description

High-value tracing method for VOCs in industrial park

Technical Field

The invention relates to the technical field of VOCs pollution prevention, in particular to a high-value tracing method for VOCs in an industrial park.

Background

Volatile Organic Compounds (VOCs) are an important class of atmospheric pollutants, and are important precursors for ozone and secondary Organic aerosols. In recent years, the problem of ozone pollution is increasingly prominent, so that the development of VOCs source analysis work has important significance for making an accurate and efficient ozone pollution prevention strategy and realizing the cooperative control of ozone and particulate matters.

Industrial parks are as the key area that atmospheric pollution administers, and industrial enterprise is numerous in the garden, and the VOCs discharge situation is complicated and discharge area is concentrated, not only brings great risk to near resident and staff health, has also brought great challenge for ozone pollution prevention and cure. How to rapidly and accurately identify main discharge enterprises of the VOCs in the park and quantify the contribution of the enterprises is a difficult problem of managing and controlling the VOCs pollution of the park.

At present, VOCs source analysis methods are mainly divided into a source analysis method based on a receptor model and a source analysis method based on an air quality mode. The source analysis method based on the air quality mode is a technology for estimating the contribution value of the pollution source by simulating the space-time distribution conditions of pollutants under different conditions such as emission, migration, diffusion and chemical conversion of the pollution source on the basis of having a detailed pollution source list and the emission amount of the pollution source. The air quality model can well establish the quantitative relation between the organized emission source and the atmospheric environment quality, but has poor effect on the unorganized emission source with the source strength difficult to determine. In addition, the air quality model requires the input of accurate pollutant emissions inventory and meteorological data, which are difficult to obtain and thus limit the use of this method. The VOCs source analysis method based on the receptor model does not need detailed meteorological field forecast information and pollution source discharge lists, so that the method is widely applied. The most mainly used models in the receptor modeling method are the CMB model and the PMF model. In recent years, with the popularization and application of high-time-resolution online monitoring instruments for VOCs, PMF models are applied more in online VOCs source analysis work.

However, the source analysis by the PMF model depends on the physical significance of factors, and only the contribution of a large class of sources can be obtained through analysis, so that the PMF model is difficult to correspond to the complex industrial enterprise emission in a garden. Therefore, at present, there is an urgent need to develop a source analysis technology suitable for real-time tracing of VOCs in industrial parks to meet the requirements of pollution control of VOCs in parks.

Disclosure of Invention

The invention provides a high-value tracing method for VOCs in an industrial park, which screens enterprise drains possibly polluting sites by intelligently identifying the high value of VOCs real-time monitoring data of the sites and fully considering the chemical composition change condition and meteorological conditions in the process of increasing the concentration of the VOCs, and quantitatively estimates the contribution of each enterprise drain to the high-value VOCs concentration of the sites by using a chemical mass balance principle.

In order to achieve the above object, the present invention provides a method for tracing high values of VOCs in an industrial park, which comprises the following steps:

step S1, acquiring VOCs real-time monitoring data, and performing data auditing: and automatically acquiring real-time monitoring data of the VOCs components of the site, summing the concentrations of the VOCs components to obtain TVOCs concentration monitoring data, and automatically auditing the concentrations of the VOCs components and the TVOCs concentration data to remove abnormal values.

S2, analyzing the high value of the TVOCs real-time monitoring data: the TVOCs ramp period and peak concentration are automatically identified by waveform analysis. Screening high-concentration VOCs (HCVOCs) at the peak time of the TVOCs, and screening high-concentration change Rate Species (HRVOCs) in the climbing period of the TVOCs.

Step S3, establishing a localization source spectrum database (PL): the localization source spectrum database comprises the species composition proportion of VOCs discharged by each known pollution source discharge outlet in the industrial park, the geographic position information of the discharge outlet and the like.

S4, screening source composition spectrum data (SP) from the localization source spectrum database (PL): and (4) screening the row ports in a source spectrum database (PL) by using a wind direction back-pushing method, and preliminarily screening the row ports of the wind direction on the monitoring point positions. And (3) using high-value species and high-change-rate species as limitations, and further screening by analyzing the similarity between the discharge component spectrum and the chemical composition of the VOCs to obtain source component spectrum data (SP) which possibly influences the pollution of the VOCs at the monitoring point position.

Step S5, calculating the contribution proportion of the source component spectrum data (SP) to the site peak value VOCs by using a multiple linear regression method: and calculating the contribution proportion of the source component Spectrum (SP) to the VOCs by using a multivariate linear regression method on the basis of VOCs component monitoring data and the source component spectrum data (SP) at the peak time of the VOCs at the site.

Preferably, in step S1, the step of automatically auditing the real-time monitoring data of the components of the VOCs includes:

judging whether the concentration data of the VOCs species is null or lower than an instrument detection limit (MDL), and judging that invalid data are obtained for samples with the null or lower than the instrument detection limit and the proportion of the VOCs species exceeding 60%; and judging whether the TVOCs concentration value is an abnormally high value, namely judging whether the TVOCs concentration value exceeds 10 times of the average value of the first 10 samples, and judging the sample as invalid data if the TVOCs concentration value exceeds 10 times. Samples that were judged to be invalid data were not included in the subsequent analysis.

Preferably, in step S2, the step of automatically identifying the TVOCs climb period and the peak concentration includes:

and performing waveform analysis on the TVOCs concentration monitoring data, identifying the wave crest and the wave trough of the TVOCs real-time monitoring data, taking the wave crest data as TVOCs high-value data if the wave crest data exceed a set threshold value, and taking the monitoring time period from the wave trough to the wave crest as a TVOCs climbing time period.

Preferably, in step S2, the step of screening the high-concentration VOCs species comprises: after the species concentrations are sorted, the species with the percentage of the VOCs in the TVOCs Concentration of more than 80% are screened out as High-Concentration VOCs (High Concentration VOCs) by calculating the cumulative contribution rate of the species.

Preferably, in step S2, the step of screening for high concentration rate of change species comprises:

analyzing the ascending time period of the TVOCs, calculating the concentration change Rate of each VOCs species concentration from the trough time period to the peak time period, comparing the concentration change Rate with the change Rate of the TVOCs concentration, and taking the species with the concentration change Rate 1.5 times higher than the TVOCs concentration change Rate as High-Rate VOCs (HRVOCs).

Preferably, in step S3, the method of building a localized source spectrum database (PL) comprises:

the method comprises the following steps of firstly, carrying out three-level division on a source spectrum, wherein the first level is an industrial enterprise, the second level is all pollution source items related to VOCs emission in the industrial enterprise, including a storage tank area, a loading and unloading area, a wastewater treatment system, process waste gas emission and the like, and the third level is all corresponding discharge ports in the pollution source items and needs to include specific longitude and latitude of the discharge ports. And (4) sorting the VOCs chemical composition data obtained after sampling and analyzing at all the discharge outlets to obtain a source component spectrum.

Preferably, in step S4, the step of performing a preliminary screening on the row openings in the source spectrum database by using a wind direction inverse method includes:

combining actual measurement wind direction information at the peak moment of TVOCs, position information of monitoring points and geographical position information of row ports in a localized source spectrum database (PL), drawing a sector area with the radius of R on a map by taking the monitoring points as the center of a circle, the wind direction as a center line and theta as an angular arc, and obtaining source component spectrums (SP 01) of the row ports, wherein the row ports of enterprises falling in the sector area are wind direction row ports of the primarily screened monitoring points. Where θ and R are set according to actual conditions, and suggested values are 45 ° and 5km, respectively.

Preferably, in step S4, the method for analyzing the similarity between the discharge composition spectrum and the chemical composition of the VOCs comprises:

after the high-value time VOCs chemical data (C) and the preliminarily screened enterprise discharge source composition spectrum (SP 01) are subjected to species correspondence, weighting processing is carried out on the C and SP01 species to obtain C 'and SP01', wherein the weight coefficients of the high-concentration VOCs species and the high-concentration change rate species are 2, and the weight coefficients of other species are 1;

calculating a vector cosine included angle cos theta of the C 'and the SP01', wherein the closer the cosine included angle cos theta is to 1, the more similar the two vectors are, and the closer the cosine included angle cos theta is to 0, the more dissimilar the two vectors are;

the vector cosine included angle cos theta is calculated according to the following formula:

based on the technical scheme, the invention has the advantages that:

the invention introduces VOCs monitoring data automatic audit and waveform analysis, intelligently identifies the TVOCs concentration climbing process and TVOCs high-value concentration, and automatically analyzes VOCs species with higher concentration change rate and VOCs species with higher content in the TVOCs concentration climbing process. And screening enterprise discharge component spectrums possibly causing pollution to VOCs at the monitoring point positions from a localized source spectrum database by using a wind direction reverse deduction method and chemical composition similarity calculation, and calculating the contribution of the enterprise discharge to the concentration of the VOCs at the sites by using a multiple linear regression method. The method can intelligently identify the VOCs pollution time period, finely analyze the source of the VOCs pollution time in real time, quantify the contribution of the enterprise discharge port to the concentration of the VOCs, and provide timely and effective support for the VOCs pollution control of the industrial park.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

FIG. 1 is a flow diagram of a method for high value tracing of VOCs in an industrial park;

FIG. 2 is a diagram of steps in a VOCs high value traceability method for an industrial park;

FIG. 3 is a high value identification diagram of an embodiment of a high value traceability method for VOCs of an industrial park;

FIG. 4 is a wind back-push screening of enterprise results for an embodiment of a VOCs high value traceability method for an industrial park;

FIG. 5 is a diagram of the chemical composition of VOCs at high value times for an embodiment of a method for tracing high value of VOCs at an industrial park;

FIG. 6 is a diagram of a screened enterprise discharge source in an embodiment of a high value traceability method for VOCs in an industrial park;

FIG. 7 is a pie chart of the source resolution result of an embodiment of the industrial park VOCs high value tracing method.

Detailed Description

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

The invention provides a high-value tracing method for VOCs in an industrial park, which is shown in figures 1 to 7, wherein a preferred embodiment of the invention is shown.

Because industrial park is as the key area that atmospheric pollution administers, industrial enterprise is numerous in the garden, and the VOCs discharges the complicated and discharge area of condition and concentrates, has brought the difficult problem for VOCs pollution management and control. The traditional PMF source analysis method can only analyze and obtain large source contributions, so that the method is difficult to correspond to complex industrial enterprise emission in a garden. The invention provides a high-value tracing method for VOCs in an industrial park, which is characterized in that the high value of VOCs in a site is intelligently identified, simultaneously, the chemical composition change condition and meteorological conditions in the process of increasing the concentration of VOCs are fully considered, enterprise discharge openings which possibly pollute the site are screened, and the contribution of each enterprise discharge opening to the high-value VOCs concentration of the site is quantitatively estimated by utilizing a chemical mass balance principle.

To further explain the method for real-time source analysis of VOCs according to the present invention, it is illustrated below by way of example.

The online monitoring data of the VOCs components in the embodiment is from the monitoring of an online monitoring instrument of the VOCs components near an industrial park of Zhenjiang and Jiangsu province in China, and monitoring items comprise common alkane, alkene, alkyne, aromatic hydrocarbon, halogenated hydrocarbon, OVOCs and other species, and the total number of the monitoring items is 109.

Automatically auditing the real-time VOCs monitoring data, judging whether the VOCs species concentration data in the hour are null values or are lower than the instrument detection limit (MDL), and if the null values or the VOCs species ratio lower than the instrument detection limit exceeds 60%, judging that the hour sample is invalid data; and (4) judging whether the TVOCs concentration value is an abnormally high value in the hour, namely judging whether the TVOCs concentration value exceeds 10 times of the average value of the first 10 samples, and if the TVOCs concentration value exceeds 10 times, judging the samples as invalid data to be removed without being included in subsequent analysis.

And performing waveform analysis on the TVOCs concentration data within a 24-hour period before the moment, identifying the peak and the trough of the TVOCs real-time monitoring data, and if the peak data exceeds a set threshold (100 mu g/m & lt 3 & gt), taking the peak data as TVOCs high-value data, and taking the monitoring period from the trough to the peak as a TVOCs climbing period. As shown in FIG. 3, the peak concentration of TVOCs was 130.3. Mu.g/m 3 since the peak concentration was observed as a peak at 1 month, 14 th and 10 th of 2022 and the peak at 1 month, 14 th and 12 th of 2022. After the species concentrations at the High-value time are sorted, the species with the percentage of the TVOCs Concentration of more than 60% are screened out as High-Concentration VOCs (High Concentration VOCs) by calculating the cumulative contribution rate of the species. Analyzing the ascending time period of the TVOCs, calculating the concentration change Rate of each VOCs species concentration from the trough time period to the peak time period, comparing the concentration change Rate with the change Rate of the TVOCs concentration, and taking the species with the concentration change Rate 1.5 times higher than the TVOCs concentration change Rate as High-Rate VOCs (HRVOCs).

The chemical composition of VOCs at the peak time is shown in fig. 4, and the concentrations of isobutane, dichloromethane, ethyl acetate and other substances are high, and are defined as HCVOCs, and are marked by squares in the figure. The change rates of butanone, ethyl acetate, chloroform, etc. are high (higher than 1.5 times of the change rate of TVOCs), and are defined as HRVOCs, and are marked by circles in the figure.

Establishing a localized source spectrum database (PL), and carrying out three-level division on a source spectrum, wherein the first level is an industrial enterprise, the second level is all pollution source items related to VOCs emission in the industrial enterprise and comprises a storage tank area, a loading and unloading area, a wastewater treatment system, process waste gas emission and the like, and the third level is all corresponding discharge ports in all the pollution source items and needs to comprise the specific longitude and latitude of the discharge ports. And (4) sorting the VOCs chemical composition data obtained after sampling and analyzing at all the discharge outlets to obtain a source component spectrum. The spatial distribution of the discharge ports of the pollution sources and the monitoring points in the source spectrum database is shown in fig. 5.

The wind direction at the peak time of the TVOCs is 60 degrees, and the influence on the VOCs pollution at the monitoring point position can be possibly caused by the fact that the discharge port in the fan-shaped area is presumed by using a wind direction reverse deduction method. The specific method of the wind direction reverse pushing method comprises the following steps: assuming that the environmental wind direction has certain fluctuation, assuming that the fluctuation of the wind direction can fluctuate up and down by 22.5 degrees in the average wind direction within one hour, the backward wind direction range is 37.5-82.5 degrees, assuming that the influence of enterprise emission with the distance from a station exceeding 5km is relatively small, the distance range R of the search exhaust outlet is set to 5km. Therefore, a sector area with the radius of 5km is drawn on a map by taking the wind direction 60 degrees as a center line at the monitoring time and taking 45 degrees as an angular arc, an enterprise row port falling in the sector area is a wind direction row port on the preliminarily screened monitoring point, and a source component spectrum SP01 of the row ports is obtained by using pink marks in the map. And after carrying out species correspondence on the high-value time VOCs chemical data (C) and the preliminarily screened enterprise discharge source composition spectrum (SP 01), carrying out weighting treatment on the C and SP01 species to respectively obtain C 'and SP01', wherein the weight coefficients of the high-concentration VOCs species and the high-concentration change rate species are 2, and the weight coefficients of other species are 1. Calculating the vector cosine included angle cos theta of C 'and SP01', setting the similarity threshold value to be 0.4, further screening the source spectrum exceeding the similarity threshold value to serve as an input source spectrum SP for subsequent source analysis, wherein the screened SP is shown in FIG. 6.

The contribution of SP to C was calculated using a multiple linear regression algorithm, and the results are shown in fig. 7.

The invention introduces VOCs monitoring data automatic audit and waveform analysis, intelligently identifies the TVOCs concentration climbing process and TVOCs high-value concentration, and automatically analyzes VOCs species with higher concentration change rate and VOCs species with higher content in the TVOCs concentration climbing process. And screening enterprise discharge component spectrums possibly causing pollution to VOCs at the monitoring point positions from a localized source spectrum database by using a wind direction reverse deduction method and chemical composition similarity calculation, and calculating the contribution of the enterprise discharge to the concentration of the VOCs at the sites by using a multiple linear regression method. The method can intelligently identify the VOCs pollution time period, finely analyze the source of the VOCs pollution time in real time, quantify the contribution of the enterprise discharge port to the concentration of the VOCs, and provide timely and effective support for the VOCs pollution control of the industrial park.

Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present invention and not to limit the same; although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: modifications to the specific embodiments of the invention or equivalent substitutions for parts of the technical features may be made; without departing from the spirit of the present invention, it is intended to cover all aspects of the invention as defined by the appended claims.

Claims (8)

1. A high-value tracing method for VOCs in an industrial park is characterized by comprising the following steps: the VOCs high-value tracing method comprises the following steps:

step S1, acquiring VOCs real-time monitoring data, and performing data auditing: acquiring site VOCs component real-time monitoring data, summing VOCs component concentrations to obtain TVOCs concentration monitoring data, and automatically auditing the VOCs component concentrations and the TVOCs concentration data to remove abnormal values;

s2, analyzing the high value of the TVOCs real-time monitoring data: automatically identifying the rising time period and the peak concentration of the TVOCs through waveform analysis, and screening high-concentration VOCs species at the peak time of the TVOCs and high-concentration change rate species in the rising time period of the TVOCs;

s3, establishing a localization source spectrum database: the localization source spectrum database comprises the species composition proportion of VOCs discharged by each known pollution source discharge outlet in the industrial park and the geographic position information of the discharge outlet;

s4, screening source component spectrum data from the localization source spectrum database: primarily screening the discharge ports in the source spectrum database by using a wind direction reverse deduction method, primarily screening the discharge ports in the wind direction on the monitoring point positions, then using the high-concentration VOCs species at the peak time of TVOCs and the high-concentration change rate species in the climbing period of TVOCs as limits, and further screening to obtain source component spectrum data influencing VOCs pollution of the monitoring point positions by analyzing the similarity of the discharge port component spectrum and the chemical composition of VOCs;

step S5, calculating the contribution ratio of the source component spectrum data to the site peak value VOCs by applying a multiple linear regression method: and calculating the contribution proportion of the source component spectrum to the VOCs by using a multiple linear regression method on the basis of VOCs component monitoring data and source component spectrum data at the peak time of the VOCs at the site.

2. The method of claim 1, wherein the VOCs high value tracing comprises: in step S1, the automatic auditing step of the real-time monitoring data of the VOCs components includes:

judging whether the concentration data of the VOCs species is a null value or is lower than the detection limit of an instrument, and judging that invalid data exist for samples with the null value or the proportion of the VOCs species lower than the detection limit of the instrument and exceeding 60%;

and judging whether the TVOCs concentration value is an abnormal value, namely judging whether the TVOCs concentration value exceeds 10 times of the average value of the first 10 samples, and judging the sample as invalid data if the TVOCs concentration value exceeds 10 times.

3. The method of claim 1, wherein the VOCs high value tracing comprises: in step S2, the step of automatically identifying the TVOCs ramp period and the peak concentration includes:

and performing waveform analysis on the TVOCs concentration monitoring data, identifying the wave crest and the wave trough of the TVOCs real-time monitoring data, taking the wave crest data as TVOCs high-value data if the wave crest data exceed a set threshold value, and taking the monitoring time period from the wave trough to the wave crest as a TVOCs climbing time period.

4. The method of claim 1, wherein the VOCs high value tracing comprises: in step S2, the step of screening the high-concentration VOCs species includes:

and after the species concentrations are sequenced, the VOCs species accounting for more than 80% of the TVOCs concentrations are screened out as high-concentration VOCs species by calculating the cumulative contribution rate of the species.

5. The method of claim 1, wherein the VOCs high value tracing comprises: in step S2, the step of screening the high concentration rate of change species comprises:

and analyzing the ascending time period of the TVOCs, calculating the concentration change rate of the concentration of each VOCs species from the trough time period to the peak time period, comparing the concentration change rate with the change rate of the TVOCs concentration, and taking the species with the concentration change rate 1.5 times higher than the TVOCs concentration change rate as the high concentration change rate species.

6. The method of claim 1, wherein the VOCs high value tracing comprises: in step S3, the method for building a localized source spectrum database includes:

the method comprises the following steps of performing three-level division on a source spectrum, wherein the first level is an industrial enterprise, the second level is all pollution source items related to VOCs emission in the industrial enterprise and comprises a storage tank area, a loading and unloading area, a wastewater treatment system and process waste gas emission, and the third level is all corresponding discharge openings in the pollution source items and comprises specific longitude and latitude information of the discharge openings;

and (4) sorting the VOCs chemical composition data obtained after sampling and analyzing at all the discharge outlets to obtain a source component spectrum.

7. The method of claim 1, wherein the VOCs high value tracing comprises: in step S4, the step of performing a preliminary screening on the discharge openings in the source spectrum database by using a wind direction inverse method includes:

combining actual measurement wind direction information at the peak time of TVOCs, position information of monitoring points and geographical position information of row ports in a localized source spectrum database, drawing a sector area with the radius of R on a map by taking the monitoring points as the center of a circle, the wind direction as a center line and theta as an angular arc, and obtaining source component spectrums of the row ports, wherein enterprise row ports falling on the sector area are wind direction row ports of the primarily screened monitoring points.

8. The method of claim 1, wherein the VOCs high value tracing comprises: in step S4, the method for analyzing the similarity between the discharge composition spectrum and the chemical composition of VOCs includes:

after carrying out species correspondence on the high-value time VOCs chemical data (C) and an enterprise drainage source component spectrum (SP 01) preliminarily screened, carrying out weighting treatment on the C and SP01 species to respectively obtain C 'and SP01', wherein the weight coefficients of the high-concentration VOCs species and the high-concentration change rate species are 2, and the weight coefficients of other species are 1;

calculating a vector cosine included angle cos theta of the C 'and the SP01', wherein the closer the cosine included angle cos theta is to 1, the more similar the two vectors are, and the closer the cosine included angle cos theta is to 0, the more dissimilar the two vectors are;

the vector cosine included angle cos theta is calculated according to the following formula:

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