CN116384777A - Indoor VOCs exposure risk prediction method and device for children group - Google Patents

Indoor VOCs exposure risk prediction method and device for children group Download PDF

Info

Publication number
CN116384777A
CN116384777A CN202310658718.9A CN202310658718A CN116384777A CN 116384777 A CN116384777 A CN 116384777A CN 202310658718 A CN202310658718 A CN 202310658718A CN 116384777 A CN116384777 A CN 116384777A
Authority
CN
China
Prior art keywords
vocs
indoor environment
harmful substances
toxic
children
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202310658718.9A
Other languages
Chinese (zh)
Other versions
CN116384777B (en
Inventor
高学鸿
赵海越
黄国忠
李浩轩
蒋慧灵
周亮
邓青
张磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Science and Technology Beijing USTB
Original Assignee
University of Science and Technology Beijing USTB
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Science and Technology Beijing USTB filed Critical University of Science and Technology Beijing USTB
Priority to CN202310658718.9A priority Critical patent/CN116384777B/en
Publication of CN116384777A publication Critical patent/CN116384777A/en
Application granted granted Critical
Publication of CN116384777B publication Critical patent/CN116384777B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
    • G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
    • Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Operations Research (AREA)
  • Data Mining & Analysis (AREA)
  • Educational Administration (AREA)
  • General Business, Economics & Management (AREA)
  • Mathematical Analysis (AREA)
  • Computational Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Mathematical Physics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Development Economics (AREA)
  • Quality & Reliability (AREA)
  • Game Theory and Decision Science (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Primary Health Care (AREA)
  • Probability & Statistics with Applications (AREA)
  • General Health & Medical Sciences (AREA)
  • Algebra (AREA)
  • Child & Adolescent Psychology (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing Resistance To Weather, Investigating Materials By Mechanical Methods (AREA)

Abstract

The invention discloses a method and a device for predicting indoor VOCs exposure risk for children, comprising the following steps: combining the history data of children suffering from the indoor VOCs, calculating the possibility of occurrence of various gases of the VOCs in the indoor environment based on an uncertain theory, and judging the exposure possibility of the target toxic and harmful substances; calculating risk quotient of various gases of VOCs in the indoor environment, and judging the gas harmfulness of the target toxic and harmful substances as the dangerous degree of the toxic and harmful substances in the current indoor environment to the children group; based on expert experience, calculating expert scoring mean values of various gases of VOCs in the indoor environment for the children population, and performing detectability judgment on the target toxic and harmful substances; according to the three calculation results, evaluating risk values of various gases of VOCs in the indoor environment for children; and predicting the exposure risk of the indoor VOCs facing the child group according to the risk value evaluation result. The invention is less influenced by environmental factors, and stable results can be obtained in complex environments.

Description

Indoor VOCs exposure risk prediction method and device for children group
Technical Field
The invention relates to the technical field of indoor VOCs exposure, in particular to an indoor VOCs exposure prediction method and device for children groups.
Background
The life of modern people spends a lot of time indoors, especially a part of children stay in choking almost all the day, so the quality of indoor air can be said to directly influence the health of children. Among them, volatile organic compounds (Volatile Organic Compounds, VOCs) are also a main representative of indoor pollutants, and are considered to be an important cause of high incidence of diseases such as thrombocytopenia, various respiratory diseases, acute and chronic aplastic anemia, malignant leukemia, and even partial cancers.
To ensure that children are moving in a relatively safe environment, current detection methods for VOCs are commonly based on semiconductor metal oxide gas sensors sensing various gases to assess and predict the exposure risk of VOCs in the current environment. However, various gases exist in the indoor environment, and the sensitive materials in the sensor have the same problems for different gases, so that the detected gases cannot be accurately judged and the risks can be estimated. For example: the sensitivity of the porphyrin-based sensitive material to toluene and formaldehyde is the same, and when the two gases are simultaneously present in the environment, the formaldehyde gas is difficult to distinguish by the sensor.
Disclosure of Invention
The invention provides a method and a device for predicting the exposure risk of indoor VOCs facing a child group, which are used for predicting the exposure risk of indoor VOCs facing the child group. The technical scheme is as follows:
in one aspect, a method for predicting exposure risk of indoor VOCs for a group of children is provided, including:
s1, combining historical data of children suffering from indoor VOCs, calculating the possibility of occurrence of various gases of the VOCs in an indoor environment based on an uncertain theory, and judging the exposure possibility of the target toxic and harmful substances;
s2, calculating risk quotient of various gases of VOCs in the indoor environment, and judging the gas harmfulness of the target toxic and harmful substances as the dangerous degree of the toxic and harmful substances in the current indoor environment to the children group;
s3, calculating expert scoring mean values of various gases of VOCs in the indoor environment for the children group based on expert experience, and performing detectability judgment on the target toxic and harmful substances;
s4, evaluating the risk values of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
s5, predicting the indoor VOCs exposure risk facing the children group according to the risk value evaluation results of various gases of the VOCs in the indoor environment.
Optionally, the S1 specifically includes:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … ,ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is an uncertainty variable ζ m N is the number of years;
in the embodiment of the invention, xi is arranged m To obey the normal uncertainty distribution N (e, σ), and the uncertainty variable for which the expected value eunknown, variance σ is unknown, is expressed as follows:
Figure SMS_1
（1）
Figure SMS_2
（2）
Figure SMS_3
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure SMS_4
（4）
Figure SMS_5
（5）
in the embodiment of the invention, assuming that ζ is obeying a normal uncertainty distribution N (e, σ), then:
Figure SMS_6
（6）
simplifying and obtaining:
Figure SMS_7
（7）
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure SMS_8
（8）
optionally, the S2 specifically includes:
taking the child health guidance concentration of the VOCs gas in the toxic substance and environmental health database TSCAT as a standard concentration, and taking the exposure concentration of the VOCs gas in the detected air as a quotient of risks of various gases of the VOCs in the indoor environment as the dangerous degree of toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure SMS_9
（9）
optionally, the step S3 specifically includes:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three sides of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less perceptible, the higher the score is, the detectability score A of different dangerous substances is obtained j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure SMS_10
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure SMS_11
（10）
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure SMS_12
（11）
optionally, the S4 specifically includes:
risk value
Figure SMS_13
The (j=1, 2,3 …, m) evaluation formula is as follows:
Figure SMS_14
（12）
in another aspect, there is provided an indoor VOCs exposure risk prediction apparatus for a group of children, comprising:
the exposure possibility judging module is used for calculating the possibility of occurrence of various gases of the VOCs in the indoor environment based on an uncertain theory by combining the history data of the children suffering from the VOCs in the indoor environment and judging the exposure possibility of the target toxic and harmful substances;
the gas hazard judging module is used for calculating risk quotient of various gases of VOCs in the indoor environment, and judging gas hazard of the target toxic and harmful substances as the hazard degree of the toxic and harmful substances in the current indoor environment to the children group;
the detectability judgment module is used for calculating expert scoring average values of various gases of VOCs in the indoor environment for the children group based on expert experience and carrying out detectability judgment on the target toxic and harmful substances;
the risk value evaluation module is used for evaluating the risk value of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
and the exposure risk prediction module is used for predicting the exposure risk of the indoor VOCs facing the children group according to the risk value evaluation results of various gases of the VOCs facing the children in the indoor environment.
Optionally, the exposure possibility judging module is specifically configured to:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … ,ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is an uncertainty variable ζ m N is the number of years;
setting xi m To obey the normal uncertainty distribution N (e, σ), and the uncertainty variable for which the expected value eunknown, variance σ is unknown, is expressed as follows:
Figure SMS_15
（1）
Figure SMS_16
（2）
Figure SMS_17
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure SMS_18
（4）
Figure SMS_19
（5）
assuming ζ is compliant with a normal uncertainty distribution N (e, σ), then:
Figure SMS_20
（6）
simplifying and obtaining:
Figure SMS_21
（7）
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure SMS_22
（8）
optionally, the gas hazard assessment module is specifically configured to:
taking the child health guidance concentration of the VOCs gas in the TSCAT of the database of toxic substances and environmental health as a standard concentration, and taking the exposure concentration of the VOCs gas in the air and the standard concentration as a quotient of risks of various gases of the VOCs in the indoor environment as the dangerous degree of toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure SMS_23
（9）
optionally, the detectability evaluation module is specifically configured to:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three sides of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less perceptible, the higher the score is, the detectability score A of different dangerous substances is obtained j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure SMS_24
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure SMS_25
(10)
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure SMS_26
（11）
optionally, the risk value evaluation module is specifically configured to:
risk value
Figure SMS_27
The (j=1, 2,3 …, m) evaluation formula is as follows:
Figure SMS_28
（12）
in another aspect, an electronic device is provided that includes a processor and a memory having at least one instruction stored therein that is loaded and executed by the processor to implement the child-population-oriented indoor VOCs exposure risk prediction method described above.
In another aspect, a computer readable storage medium having stored therein at least one instruction that is loaded and executed by a processor to implement the child-population oriented indoor VOCs exposure risk prediction method described above is provided.
Compared with the prior art, the technical scheme has at least the following beneficial effects:
the invention provides a novel indoor VOCs exposure risk prediction method and device for children, which are used for introducing an uncertain theory from the perspective of historical case data, providing a basis for the possibility of breaking VOCs gas, combining a detection result of a gas sensor and expert experience to carry out exposure risk assessment prediction, accurately judging the types of VOCs in an indoor environment, being less influenced by environmental factors, still obtaining a stable result in a complex environment, overcoming the defect of reduced accuracy of a current gas sensor under the influence of complex conditions and various gases, timely warning people, judging whether to further test toxic and harmful substances in the current air or not, assisting doctors to definitely cause diseases and timely taking therapeutic measures.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for predicting indoor exposure risk of VOCs facing a child group according to an embodiment of the present invention;
fig. 2 is a block diagram of an indoor VOCs exposure risk prediction device for a child group according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for predicting exposure risk of indoor VOCs for a child group, including:
s1, combining historical data of children suffering from indoor VOCs, calculating the possibility of occurrence of various gases of the VOCs in an indoor environment based on an uncertain theory, and judging the exposure possibility of the target toxic and harmful substances;
s2, calculating risk quotient of various gases of VOCs in the indoor environment, and judging the gas harmfulness of the target toxic and harmful substances as the dangerous degree of the toxic and harmful substances in the current indoor environment to the children group;
s3, calculating expert scoring mean values of various gases of VOCs in the indoor environment for the children group based on expert experience, and performing detectability judgment on the target toxic and harmful substances;
s4, evaluating the risk values of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
s5, predicting the indoor VOCs exposure risk facing the children group according to the risk value evaluation results of various gases of the VOCs in the indoor environment.
The indoor waiting time of children is far longer than that of adults, and the VOCs are more breathed in than the adults; moreover, the body organs of children are not yet developed completely, and a small amount of VOCs can cause serious injury to the children. Children are exposed to the VOCs environment for a long time, diseases such as asthma, leukemia and childhood acquired heart diseases are easy to cause, and the risk of suffering from cancer is higher than that of adults, so that the indoor VOCs exposure risk prediction method for childhood groups provided by the embodiment of the invention comprises the following detailed description:
s1, combining historical data of children suffering from indoor VOCs, calculating the possibility of occurrence of various gases of the VOCs in an indoor environment based on an uncertain theory, and judging the exposure possibility of the target toxic and harmful substances;
when historical data is processed, since domestic research on VOCs starts later, data sample statistics are fewer, statistics on probability distribution of cases cannot be made, and probability theory based on large samples is not applicable in this case. In response to this problem, embodiments of the present invention introduce uncertainty theory, providing more accurate results with less historical data.
Optionally, the S1 specifically includes:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … ,ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is an uncertainty variable ζ m N is the number of years;
setting xi m To obey the normal uncertainty distribution N (e, σ), and the uncertainty variable for which the expected value eunknown, variance σ is unknown, is expressed as follows:
Figure SMS_29
（1）
Figure SMS_30
（2）
Figure SMS_31
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure SMS_32
(4)
Figure SMS_33
(5)
assuming ζ is compliant with a normal uncertainty distribution N (e, σ), then:
Figure SMS_34
(6)
simplifying and obtaining:
Figure SMS_35
(7)
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure SMS_36
（8）
s2, calculating risk quotient of various gases of VOCs in the indoor environment, and judging the gas harmfulness of the target toxic and harmful substances as the dangerous degree of the toxic and harmful substances in the current indoor environment to the children group;
optionally, the S2 specifically includes:
taking the child health guidance concentration of the VOCs gas in the toxic substance and environmental health database TSCAT as a standard concentration, and taking the exposure concentration (which can be detected by a gas sensor) of the VOCs gas in the detected air as a quotient of the standard concentration to obtain a risk quotient of various gases of the VOCs in the indoor environment, wherein the risk quotient is taken as the risk degree of the toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure SMS_37
（9）
s3, calculating expert scoring mean values of various gases of VOCs in the indoor environment for the children group based on expert experience, and performing detectability judgment on the target toxic and harmful substances;
optionally, the step S3 specifically includes:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three sides of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less perceptible, the higher the score is, the detectability score A of different dangerous substances is obtained j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure SMS_38
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure SMS_39
(10)
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure SMS_40
(11)
s4, evaluating the risk values of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
optionally, the S4 specifically includes:
risk value
Figure SMS_41
The (j=1, 2,3 …, m) evaluation formula is as follows:
Figure SMS_42
（12）
in the embodiment of the invention, S1 and S3 are relatively wide, the target toxic and harmful substances in the general indoor environment are judged according to the history data and expert experience of the illness of the VOCs in the children, S2 is specific to a certain indoor environment to be predicted, the target toxic and harmful substances in the indoor environment to be predicted are judged according to the exposure concentration of the VOCs in the air detected by the gas sensor, the embodiment of the invention integrates the three (when various gases exist in the indoor environment as recorded in the prior art, the detection gas cannot be accurately and accurately judged and the risk thereof can be estimated simply by the gas sensor, and therefore, the embodiment of the invention adopts a method for integrating the three), and the accurate estimation and prediction of the exposure risk of the VOCs is realized under the conditions of small data sample size and complex gas.
According to the historical case data, the possibility that various gases in the VOCs appear in the indoor environment is calculated by utilizing an uncertain theory, the hazard of the VOCs is judged by utilizing a risk quotient on the basis of acquiring which VOCs gas possibly appears, the detectability of the VOCs is judged by utilizing a Delphi method, the risk values of the various gases in the indoor environment facing children are evaluated, and a VOCs gas risk table is formed, as shown in table 1:
TABLE 1
Figure SMS_43
S5, predicting the indoor VOCs exposure risk facing the children group according to the risk value evaluation results of various gases of the VOCs in the indoor environment.
According to the embodiment of the invention, the risk grades (red, yellow and green corresponding to strong, medium and weak) can be divided according to the historical risk assessment results, the risk intervals are divided according to the risk values, the exposure risk level of the current indoor environment is judged, and the risk prediction and early warning are carried out.
As shown in fig. 2, the embodiment of the present invention further provides an indoor VOCs exposure risk prediction apparatus facing a child group, including:
the exposure probability judging module 210 is configured to calculate, based on an uncertain theory, the probability of occurrence of various gases of VOCs in the indoor environment in combination with historical data of children suffering from indoor VOCs, and judge the exposure probability of the target toxic and harmful substances;
the gas hazard assessment module 220 is configured to calculate risk quotient of various gases of VOCs in the indoor environment, and perform gas hazard assessment on the target toxic and harmful substances as the hazard degree of the toxic and harmful substances in the current indoor environment to the children population;
the detectability judgment module 230 is configured to calculate expert score means of various gases of VOCs in the indoor environment for the group of children based on expert experience, and perform detectability judgment on the target toxic and harmful substances;
the risk value evaluation module 240 is configured to evaluate a child-oriented risk value of each gas of VOCs in the indoor environment according to the likelihood of occurrence of each gas of VOCs in the indoor environment, the risk quotient and the expert score average;
the exposure prediction module 250 is configured to predict exposure of the VOCs in the children-oriented group according to the evaluation result of the risk values of the VOCs in the indoor environment.
Optionally, the exposure possibility judging module is specifically configured to:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … ,ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is uncertainVariable xi m N is the number of years;
setting xi m To obey the normal uncertainty distribution N (e, σ), and the uncertainty variable for which the expected value eunknown, variance σ is unknown, is expressed as follows:
Figure SMS_44
（1）
Figure SMS_45
（2）
Figure SMS_46
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure SMS_47
（4）
Figure SMS_48
（5）
assuming ζ is compliant with a normal uncertainty distribution N (e, σ), then:
Figure SMS_49
（6）
simplifying and obtaining:
Figure SMS_50
（7）
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure SMS_51
（8）
optionally, the gas hazard assessment module is specifically configured to:
taking the child health guidance concentration of the VOCs gas in the TSCAT of the database of toxic substances and environmental health as a standard concentration, and taking the exposure concentration of the VOCs gas in the air and the standard concentration as a quotient of risks of various gases of the VOCs in the indoor environment as the dangerous degree of toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure SMS_52
(9)
optionally, the detectability evaluation module is specifically configured to:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three sides of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less perceptible, the higher the score is, the detectability score A of different dangerous substances is obtained j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure SMS_53
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure SMS_54
(10)
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure SMS_55
(11)
optionally, the risk value evaluation module is specifically configured to:
risk value
Figure SMS_56
The (j=1, 2,3 …, m) evaluation formula is shown below: -j +>
Figure SMS_57
(12)
The functional structure of the indoor VOCs exposure risk prediction device for the children group provided by the embodiment of the invention corresponds to the indoor VOCs exposure risk prediction method for the children group provided by the embodiment of the invention, and is not repeated here.
Fig. 3 is a schematic structural diagram of an electronic device 300 according to an embodiment of the present invention, where the electronic device 300 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 301 and one or more memories 302, where at least one instruction is stored in the memories 302, and the at least one instruction is loaded and executed by the processors 301 to implement the steps of the method for predicting exposure risk of indoor VOCs facing a child group.
In an exemplary embodiment, a computer readable storage medium, such as a memory comprising instructions executable by a processor in a terminal to perform the above-described method of predicting exposure to indoor VOCs for a group of children is also provided. For example, the computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.

Claims (10)

1. An indoor VOCs exposure prediction method for a child group is characterized by comprising the following steps:
s1, combining historical data of children suffering from indoor VOCs, calculating the possibility of occurrence of various gases of the VOCs in an indoor environment based on an uncertain theory, and judging the exposure possibility of the target toxic and harmful substances;
s2, calculating risk quotient of various gases of VOCs in the indoor environment, and judging the gas harmfulness of the target toxic and harmful substances as the dangerous degree of the toxic and harmful substances in the current indoor environment to the children group;
s3, calculating expert scoring mean values of various gases of VOCs in the indoor environment for the children group based on expert experience, and performing detectability judgment on the target toxic and harmful substances;
s4, evaluating the risk values of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
s5, predicting the indoor VOCs exposure risk facing the children group according to the risk value evaluation results of various gases of the VOCs in the indoor environment.
2. The method according to claim 1, wherein S1 specifically comprises:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … , ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is an uncertainty variable ζ m N is the number of years;
setting xi m To obey normal uncertainty distributionN (e, σ), and the uncertainty variable for which the expected value e is unknown, the variance σ is unknown, is expressed as follows:
Figure QLYQS_1
（1）
Figure QLYQS_2
（2）
Figure QLYQS_3
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure QLYQS_4
（4）
Figure QLYQS_5
（5）
assuming ζ is compliant with a normal uncertainty distribution N (e, σ), then:
Figure QLYQS_6
（6）
simplifying and obtaining:
Figure QLYQS_7
(7)
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure QLYQS_8
(8)。
3. the method according to claim 2, wherein S2 comprises in particular:
taking the child health guidance concentration of the VOCs gas in the toxic substance and environmental health database TSCAT as a standard concentration, and taking the exposure concentration of the VOCs gas in the detected air as a quotient of risks of various gases of the VOCs in the indoor environment as the dangerous degree of toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure QLYQS_9
(9)。
4. a method according to claim 3, wherein S3 comprises:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three sides of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less perceptible, the higher the score is, the detectability score A of different dangerous substances is obtained j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure QLYQS_10
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure QLYQS_11
(10)
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure QLYQS_12
(11)。
5. the method according to claim 4, wherein S4 specifically comprises:
risk value
Figure QLYQS_13
The (j=1, 2,3 …, m) evaluation formula is as follows:
Figure QLYQS_14
(12)。
6. indoor VOCs exposure prediction device towards children's crowd, characterized in that includes:
the exposure possibility judging module is used for calculating the possibility of occurrence of various gases of the VOCs in the indoor environment based on an uncertain theory by combining the history data of the children suffering from the VOCs in the indoor environment and judging the exposure possibility of the target toxic and harmful substances;
the gas hazard judging module is used for calculating risk quotient of various gases of VOCs in the indoor environment, and judging gas hazard of the target toxic and harmful substances as the hazard degree of the toxic and harmful substances in the current indoor environment to the children group;
the detectability judgment module is used for calculating expert scoring average values of various gases of VOCs in the indoor environment for the children group based on expert experience and carrying out detectability judgment on the target toxic and harmful substances;
the risk value evaluation module is used for evaluating the risk value of the various gases of the VOCs in the indoor environment for children according to the possibility of occurrence of the various gases of the VOCs in the indoor environment, the risk quotient and the expert scoring average value;
and the exposure risk prediction module is used for predicting the exposure risk of the indoor VOCs facing the children group according to the risk value evaluation results of various gases of the VOCs facing the children in the indoor environment.
7. The device according to claim 6, wherein the exposure likelihood assessment module is specifically configured to:
the uncertain variable is defined, and the number of children disease history cases caused by various gases in VOCs every year is defined as an uncertain variable xi 1 , ξ 2 , … ,ξ m M is the kind of gas;
let z be 1 , z 2 , … ,z n Is an uncertainty variable ζ m N is the number of years;
setting xi m To obey the normal uncertainty distribution N (e, σ), and the uncertainty variable for which the expected value eunknown, variance σ is unknown, is expressed as follows:
Figure QLYQS_15
（1）
Figure QLYQS_16
（2）
Figure QLYQS_17
（3）
in uncertainty theory, entropy is defined as the difficulty level of predicting an uncertainty variable implementation, and assuming ζ is an uncertainty variable with an uncertainty distribution Φ, its entropy is defined as:
Figure QLYQS_18
(4)
Figure QLYQS_19
(5)
assuming ζ is compliant with a normal uncertainty distribution N (e, σ), then:
Figure QLYQS_20
（6）
simplifying and obtaining:
Figure QLYQS_21
(7)
the probability of the occurrence of various gases of VOCs in the indoor environment is calculated as follows:
Figure QLYQS_22
(8)。
8. the device according to claim 7, wherein the gas hazard assessment module is specifically configured to:
taking the child health guidance concentration of the VOCs gas in the TSCAT of the database of toxic substances and environmental health as a standard concentration, and taking the exposure concentration of the VOCs gas in the air and the standard concentration as a quotient of risks of various gases of the VOCs in the indoor environment as the dangerous degree of toxic and harmful substances in the current environment;
assuming that j toxic and harmful substances p exist in the current environment 1 ，p 2 ，……p j (j=1, 2,3 …, m) with standard concentration of toxic and harmful substances p j standard The exposure concentration of toxic and harmful substances is p j exposure of Then the risk quotient:
Figure QLYQS_23
(9)。
9. the apparatus of claim 8, wherein the detectability evaluation module is specifically configured to:
using Delphi method, based on experience of n experts, assigning values of target toxic and harmful substances from three directions of vision, smell and touch, wherein each index is 10 points, and the target toxic and harmful substances are less noticeable and are less visibleThe higher the perceived score A for different dangerous substances j (j=1, 2,3 … …, m), the scores of different experts for a certain gas are expressed as
Figure QLYQS_24
(i=1, 2,3 …, n; j=1, 2,3 …, m), the scoring result is normalized:
Figure QLYQS_25
(10)
and (3) integrating the opinions of all the experts, and calculating the average value of the expert scores of all the gases of the VOCs in the indoor environment for the children group:
Figure QLYQS_26
(11)。
10. the apparatus of claim 9, wherein the risk value evaluation module is specifically configured to:
risk value
Figure QLYQS_27
The (j=1, 2,3 …, m) evaluation formula is as follows:
Figure QLYQS_28
(12)。
CN202310658718.9A 2023-06-06 2023-06-06 Indoor VOCs exposure risk prediction method and device for children group Active CN116384777B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310658718.9A CN116384777B (en) 2023-06-06 2023-06-06 Indoor VOCs exposure risk prediction method and device for children group

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310658718.9A CN116384777B (en) 2023-06-06 2023-06-06 Indoor VOCs exposure risk prediction method and device for children group

Publications (2)

Publication Number Publication Date
CN116384777A true CN116384777A (en) 2023-07-04
CN116384777B CN116384777B (en) 2023-08-15

Family

ID=86977296

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310658718.9A Active CN116384777B (en) 2023-06-06 2023-06-06 Indoor VOCs exposure risk prediction method and device for children group

Country Status (1)

Country Link
CN (1) CN116384777B (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102508992A (en) * 2011-09-28 2012-06-20 天津渤海化工集团公司劳动卫生研究所 Workplace benzene occupational exposure and carcinogenic risk analysis method
US20150073957A1 (en) * 2013-09-09 2015-03-12 Bank Of America Corporation Extended range model risk rating
CN104881575A (en) * 2015-05-14 2015-09-02 沈阳环境科学研究院 Automation system for acquiring and evaluating pollution field information and acquiring and evaluating method
CN113990496A (en) * 2021-10-19 2022-01-28 清华大学 Skin exposure evaluation model and human health risk evaluation method and device
CN114943441A (en) * 2022-05-17 2022-08-26 北京师范大学 POI data-based regional soil pollution health risk assessment method
CN115116612A (en) * 2022-07-01 2022-09-27 中南大学 Intelligent risk assessment system and method for child patient state of illness
CN115345463A (en) * 2022-08-09 2022-11-15 生态环境部南京环境科学研究所 Risk assessment method for pesticide non-calibration pollutants

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102508992A (en) * 2011-09-28 2012-06-20 天津渤海化工集团公司劳动卫生研究所 Workplace benzene occupational exposure and carcinogenic risk analysis method
US20150073957A1 (en) * 2013-09-09 2015-03-12 Bank Of America Corporation Extended range model risk rating
CN104881575A (en) * 2015-05-14 2015-09-02 沈阳环境科学研究院 Automation system for acquiring and evaluating pollution field information and acquiring and evaluating method
CN113990496A (en) * 2021-10-19 2022-01-28 清华大学 Skin exposure evaluation model and human health risk evaluation method and device
CN114943441A (en) * 2022-05-17 2022-08-26 北京师范大学 POI data-based regional soil pollution health risk assessment method
CN115116612A (en) * 2022-07-01 2022-09-27 中南大学 Intelligent risk assessment system and method for child patient state of illness
CN115345463A (en) * 2022-08-09 2022-11-15 生态环境部南京环境科学研究所 Risk assessment method for pesticide non-calibration pollutants

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
刘雨晴: "家庭环境中挥发性有机污染物暴露特征及风险评估", 中国优秀硕士学位论文全文数据库 工程科技I辑, pages 027 - 363 *
宫庆超;牛志广;陈彦熹;张颖;: "环境空气中挥发性有机物的健康风险评价研究进展", 安全与环境学报, no. 03, pages 86 - 90 *
尤汉虎;庞智锋;梁雅慧;林仰锋;: "佛山市某城区饮用水重金属健康危害风险初步评估", 华南预防医学, no. 03 *
王鑫璇;张鸿;王艳萍;罗骥;: "中国七大流域全氟烷基酸污染水平与饮水暴露风险", 环境科学, no. 02 *
陈寰;马振邦;: "深圳市室内空气的健康风险评价", 环境科学与技术, no. 2 *

Also Published As

Publication number Publication date
CN116384777B (en) 2023-08-15

Similar Documents

Publication Publication Date Title
Gissi et al. Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: the bioconcentration factor (BCF)
Henderson et al. Identification and efficacy of longitudinal markers for survival
Kang et al. Biochemically-verified smoking rate trends and factors associated with inaccurate self-reporting of smoking habits in Korean women
CN110197020B (en) Method for analyzing influence of environmental change on hydrological drought
JP2020514689A5 (en)
Koen et al. From humans to rats and back again: Bridging the divide between human and animal studies of recognition memory with receiver operating characteristics
Calzolai et al. Transcriptomics and proteomics. Applications to ecotoxicology
Zeng et al. Alternatives of perfluoroalkyl acids and hepatitis B virus surface antibody in adults: Isomers of C8 Health Project in China
CN116384777B (en) Indoor VOCs exposure risk prediction method and device for children group
Rhee et al. Blood lead levels and lung cancer mortality: An updated analysis of NHANES II and III
Leelapongwattana et al. Induction of genotoxicity and mutagenic potential of heavy metals in Thai occupational workers
Worsfold et al. Estimating uncertainties in oceanographic trace element measurements
Hill et al. Airborne levels of cadmium are correlated with urinary cadmium concentrations among young children living in the New York state city of Syracuse, USA
Sakuragi et al. Variation in benchmark dose (BMD) and the 95% lower confidence limit of benchmark dose (BMDL) among general Japanese populations with no anthropogenic exposure to cadmium
Santonen et al. Biological monitoring of metals and biomarkers
Corradi et al. A review on airway biomarkers: exposure, effect and susceptibility
CN108051428A (en) A kind of water-quality test method, apparatus, online Toxicity Monitoring instrument
Lee et al. Impact of muffle furnace preparation on the results of crystalline silica analysis
Hayes Biomarkers in occupational cancer epidemiology: considerations in study design.
CN115436633A (en) Biomarker for colorectal cancer detection and application thereof
Haque et al. Validation of blood arsenic and manganese assessment from archived clotted erythrocyte fraction in an urban cohort of mother-child dyads
CN115440375A (en) Colorectal cancer prediction system and application thereof
Verdonck et al. Probabilistic ecological risk assessment framework for chemical substances
Kusmahendra et al. System Design for Air Quality Monitoring and Classification using Artificial Neural Network with Hyperparameters Optimization
CN107194202A (en) Transition metal protects the non-carcinogenic EDs Forecasting Methodologies of health water quality benchmark

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant