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WO2002063539A1 - Systeme servant a controler la qualite de l'air - Google Patents

Systeme servant a controler la qualite de l'air Download PDF

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Publication number
WO2002063539A1
WO2002063539A1 PCT/NZ2002/000012 NZ0200012W WO02063539A1 WO 2002063539 A1 WO2002063539 A1 WO 2002063539A1 NZ 0200012 W NZ0200012 W NZ 0200012W WO 02063539 A1 WO02063539 A1 WO 02063539A1
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WO
WIPO (PCT)
Prior art keywords
individual
air quality
pollutant
database
health
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.)
Ceased
Application number
PCT/NZ2002/000012
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English (en)
Inventor
Geoffrey Stephen Henshaw
David E Williams
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Aeroqual Ltd
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Aeroqual Ltd
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 Aeroqual Ltd filed Critical Aeroqual Ltd
Publication of WO2002063539A1 publication Critical patent/WO2002063539A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0073—Control unit therefor
    • G01N33/0075—Control unit therefor for multiple spatially distributed sensors, e.g. for environmental monitoring

Definitions

  • the invention relates to air quality monitoring. More particularly but not exclusively it relates to the monitoring of air quality over a geographic area, storage of this data over time, and use of this temporal and spatial data in downstream applications.
  • An individual's respiratory health is a function of both their genetic disposition (as may be determined by medical tests) and their environmental exposure.
  • One component of the environment is the exposure of an individual to airborne pollutants, both outdoors (such as pollutants arising from car emissions) and indoors (pollutants arising from photocopiers in the workplace, for example).
  • a database of air quality data wherein the database includes a plurality of, or continuous, air quality data records derived from air quality readings taken or observed at a plurality of times or continuously, and at individual recording sites distributed over a plurality of geographic and/or spatial locations, and wherein the air quality data stored in the database is temporally and spatially resolved.
  • the air quality data correlates with the spatial and temporal locations of a specific individual or group of individuals.
  • the air quality readings have been taken or observed at regular intervals.
  • the air quality readings may be taken or observed at, or over, a predetermined sample time, the predetermined sample time being relevant to the character or nature of a particular recording site (for example, during the day if an inner city or vocational site; or during the night, if a residential site), or the presence or absence of an individual or group of individuals.
  • each air quality record includes air quality data pertaining to levels of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations).
  • air quality data pertaining to levels of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations).
  • the air quality records may be employed to calculate an air quality index for a defined location, the air quality index being a numerical indicator of air quality. More preferably the database will include temporal and spatial air quality indices. Preferably each defined location may contain one or more recording sites.
  • the air quality index will reflect the presence of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, terpenes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations).
  • the air quality data and/or air quality record and/or air quality indices may be relevant to and/or used by one or more individuals/entities/companies.
  • a computer program is used to calculate, or to facilitate calculation of th? air quality index.
  • the database may also contain pollutant paniculate information relevant to one or more of the recording sites.
  • pollutant particulates may include soot, smog and/or smoke.
  • the database may also contain data relating to UV light and/or sunlight hours recorded at the recording sites.
  • each individual air quality reading correlates with or may be relevant to the spatial and temporal locations of a specific individual or group of individuals.
  • the air quality readings may be taken or observed at regular intervals.
  • the air quality readings may be continuously taken or observed.
  • each air quality record includes air quality data pertaining to levels of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations).
  • air quality data pertaining to levels of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations).
  • the air quality data and/or air quality record and/or air quality indices may be relevant to and/or used by one or more individuals/entities/companies.
  • the air quality data is taken or observed using a network of air pollution sensors.
  • the air pollution sensors are located in rural and/or urban sites. More preferably the air pollution sensors are located in indoor and/or outdoor sites.
  • readings are further taken and recorded to reflect relative humidity and/or UN light recorded at the recording sites.
  • the air pollution sensor network is linked via radio, internet or phone to a central data storage facility such as a computer.
  • a third aspect of the invention there is provided a method of preparing a pollutant exposure profile for a particular air quality recording site comprising or including the steps of:
  • the pollution profile reflects the level of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations), present at the particular air quality recording site over time.
  • the pollutant exposure profile may be relevant to and or used by one or more individuals/entities/companies.
  • the pollutant exposure profile may be numerical and/or graphical or any other representation.
  • the pollution profile may also indicate UN light levels and/or sunlight hours recorded at the recording sites.
  • a computer program is used to prepare, or to facilitate preparation, of the pollutant exposure profile.
  • a pollutant exposure profile for a particular air quality recording site comprising or including a representation of historical air quality for the recording site, prepared according to the abovementioned method.
  • a method for determining an individual pollutant exposure profile relevant for a particular individual/entity/corporation including the steps of:
  • the individual pollution profile reflects the level of one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PMIO, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity (as a proxy for dust mite populations) present at the particular air quality recording site over time.
  • the pollutant exposure profile may be numerical and or graphical or any other representation.
  • the pollutant exposure profile may also contain data relating to UN light and/or sunlight hours recorded at the recording sites.
  • the pollutant exposure profile may be taken or observed at, or over, a predetermined sample time, the predetermined sample time being relevant to the character or nature of a particular recording site (for example, during the day if an inner city or vocational site; or during the night, if a residential site).
  • a computer program is used to determine, or to facilitate determination of the individual pollutant exposure profile for the particular individual/entity/co ⁇ oration.
  • the individual pollution profile is calculated according to
  • Ep ., exposure of person p to pollutant i at location x for period t
  • a method for determining a health index for a particular individual including the steps of: -determining the individual pollutant exposure profile for the individual, as previously described,
  • the personal information includes any genetic susceptibility of the individual.
  • a computer program is used to determine, or to facilitate determination of a health index for a particular individual.
  • a method for estimating the risk of the onset of a respiratory illness for an individual including the steps of:
  • the illnesses of interest may include asthma, and/or lung cancer.
  • the risk of onset of the illness may be correlated with the place or residence and/or vocation of the individual.
  • a computer program is used to determine, or to facilitate determination of the risk of the onset of a respiratory illness for an individual.
  • a method of determining a health risk factor for a particular individual including the steps of: -determining the individual pollutant exposure profile for the individual, as previously described, -determining the health index of the individual, as previously described, -taking into consideration any relevant epidemiological studies and/or results and/or correlations -calculating the health risk factor for the individual.
  • the epidemiological studies/results/correlations may relate to respiratory illnesses including asthma, or lung cancer.
  • the health risk factor for an individual may be used by a health care provider or health care insurer to quantify or estimate the insurance risk of the person, due to their present and/or historical and/or future exposure to pollutants.
  • the health risk factor may be correlated with the place or residence and/or vocation of the individual.
  • a computer program is used to determine, or to facilitate determination of the health risk factor for a particular individual.
  • a computer program substantially as previously described.
  • a method of assessing the risk (to provide a risk assessment) presented by one or more air pollutants to the respiratory health of an individual comprising or including the steps of: a) in respect of one or more air pollutants, obtaining a pollutant exposure profile according to the method as described in claim 18, for a site or relevance to the individual, b) collecting respiratory health data of the individual, including time and duration of a respiratory illness, and c) calculating a personal dose-response curve for the individual, using
  • Rpi is the response of a person to exposure to pollutant i
  • Epi is the measured exposure of a person to pollutant i fpi() is the function that relates a person's response to exposure to pollutant I d) using the personal dose-response curve to directly or indirectly estimate the health risk to that person of the particular location.
  • said one or more air pollutants are indoor pollutants and the particular location is an indoor location.
  • said one or more air pollutants is one or more of carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic compounds, particulates, PMIO, PM2.5, chlorine, hydrogen sulfide, ammoni. , te ⁇ enes, pollens, formaldehyde, paraldehyde, carbon dioxide, humidity, relative humidity
  • a method of calculating a health insurance premium for an individual comprising or including the steps of: a) assessing the risk presented by one or more air pollutants to the respiratory health of the individual as claimed in any one of claims 41 to 43, b) using the risk assessment as a weighting factor to calculate the premium.
  • a method of identifying a building with the potential to pose a respiratory health risk to one or more building occupants comprising or including the steps of: a) collection of air pollution concentration data for one or more air pollutants from a one or more sensors located in the building, and b) undertaking a health risk assessment substantially as claimed in claim 41, according on one or more of the building's occupants.
  • a thirteenth aspect of the present invention consists of a method of identifying potential rooms, offices or areas in a building which may have a detrimental effect on worker productivity rates due to poor air quality comprising or including the steps of: a) collecting air pollutant exposure data specific to locations of workers in the building via a plurality of sensors located in the building; b) compiling a database of air pollutant data which is temporally and/or spatially resolved c) correlating worker productivity with the air pollutant exposure data to analyse the offices and rooms in a building according to their propensity to have a detrimental effect on worker productivity due to poor wellness suffered as a result of poor indoor air quality.
  • the database compilation occurs via connection of the plurality of sensors to a computer data storage device or database via a packet switched network rr over a circuit switched network.
  • Figure 1 Example pollutant- dose-response correlation for an individual.
  • a sensor network consisting of a distributed network of monitors in one or more of rural and urban, indoor and outdoor sites that measure the local concentrations of individual pollutants.
  • Gas sensor technology based on gas sensitive semi-conducting metal oxides, infra-red spectroscopy, electrochemical devices, colorimetric devices etc could be used to detect gases at specific locations in both outdoor and indoor, urban and rural environments for the pu ⁇ ose of quantifying an individuals pollutant exposure profile.
  • UN and meteorological detectors could also be inco ⁇ orated into the network to provide such data as a function of location.
  • the sensor network is made up of a plurality of in-expensive air pollution sensors that are linked via radio, internet or phone to a central data storage facility such as a computer.
  • the network collects individual-centric data ie, the pollutant concentration data at a time and place in which an individual is located, ie at home and at work or school.
  • Air pollutants that are measured include SO 2 , CO, O 3 , Volatile organic compounds, volatile aldehydes, formaldehyde, humidity, ⁇ O 2 , NO, chlorine, ammonia, hydrogen sulfide, hydrocarbons, benzene, relative humidity (a proxy for dust mite populations), dust (PM2.5 or PMIO) etc.
  • a grading system of air quality for each of the sites as a function of the average local pollution level will be calculated and housed within the database.
  • the grading system may be in a number of forms without departing from the scope of the invention. For example it may be a 1-10 pollution index (1 being low ambient pollution, 10 being high). This grading system may not be linear as there may be a threshold level for a pollutant below which there is no measurable effect on an individual's health.
  • the database of the invention is a time-resolved, and spatially/geographically-resolved database including pollutant levels for each site.
  • the main pollutants inco ⁇ orated are carbon monoxide, sulfur dioxide, nitrogen dioxide, nitric oxide, ozone, hydrocarbons, toluene, benzene, volatile organic carbons, particulates, PM10, PM2.5, chlorine, hydrogen sulfide, ammonia, te ⁇ enes, although additional pollutants or other factors may be measured or inco ⁇ orated without departing from the scope of the invention.
  • the database may be made available over the world wide web or a mobile phone network to enable consumers to make informed choices about their behaviour (eg not going for a run because pollution levels are too high).
  • the database or pollution index may be used by medical agencies and research groups to assess the effect of pollution on health thereby improving our understanding of the health effects of pollutants. Thus this concept is a research tool.
  • the pollutant exposure profile will provide an historical profile of levels of pollutants or other measured or observed species for a particular site. It will be appreciated that such historical data may be presented in any one of a number of ways without departing from the scope of the invention. For example, presentation may be graphical, numerical or combined.
  • information collected is C, (ambient air concentration of pollutant i) and t (time of measurement) at each of the places the person (p) is located.
  • the database stores personal pollution exposure data and personal medical history. It can be used to determine the health index for a particular individual.
  • the personal exposure is calculated as the sum of the concentrations of pollutants measured, integrated over the measurement time for each place in which the person is located.
  • the personal exposure (Ep) to pollutant i is calculated by the equation below:
  • the total exposure of a person (p) at a location for a given period is calculated as the sum of exposures to individual pollutants.
  • the exposure (Ep) can be averaged over a time period as required such as daily, weekly, monthly or yearly giving average daily, weekly or yearly doses.
  • the invention enables the reliability and accuracy of the health risk calculation to improve with time due to:
  • the health index of the individual is used, with known factors relating to particular illnesses (particularly respiratory), to predict the onset of a particular illness. This may be used to inform an individual that "given your predisposition to an illness, your history in this particular air quality location, and the historical air quality profile of this location, if you don't move workplace or residence you are likely to develop." for example.
  • G Health risk factor for a particular individual
  • the individual exposure profile for a person is used in conjunction with their medical condition and epidemiological studies to give a method of determining the effect of an individual's work and home locations on their health due to the atmospheric environment to which they are exposed. This would then provide a way of accurately determining the health risk of an individual for insurance and healthcare purposes.
  • An algorithm that calculates the health risk of an individual given his/her genetic susceptibilities and the pollution index of the individuals home and work environments is used.
  • This algorithm could be embodied in software without departing from the scope of the invention, that takes input of an individuals susceptibility and work/home address and outputs a risk assessment and/or insurance premium.
  • Our invention will enable this health risk to be assessed for an individual or co ⁇ oration.
  • exposure-response data is available from prior art for example from the Environmental Protection Agency, US and Agency for Toxic Substances and Disease Registry, US and based on toxicological and epidemiological studies.
  • the relationship between exposure and response is defined by a function:
  • Rp is the response of a person to exposure to pollutant i
  • Epi is the measured exposure of a person to pollutant i fp,() is the function that relates a person's response to exposure to pollutant i
  • the function f ; 0 is specific to a pollutant, a person and a measurement interval .
  • Prior art has established function f() for a number of pollutants for the general population (for example, "Breath Taking: Premature Mortality due to Particulate Air Pollution in 239 American Cities" - a May 1996 report by the Natural Resources Defense Council) however these fail to take into account an individual's susceptibility or response to a particular pollutant.
  • the method thus describes a means by which an individual can determine which pollutants they are particularly affected by.
  • the MRL can then be used by the individual to make choices about the places they live and the identification and positioning of pollutant sources within their indoor environment.
  • the air quality database could also be used to detect fugitive emissions and enable the source to be accurately located, the emissions stopped and party fined for non-compliance. Pollution/meteorological data could be used to remotely cause an action eg closing a greenhouse window due to the wind-carry of herbicide from a neighbouring farm.
  • Co ⁇ orations may use the pollution index to make informed choices about their indoor air quality and therefore manage their employee healthcare.
  • Semiconducting metal oxide gas sensors sensitive to ozone and volatile organic compounds are interfaced to two PCs via RS232 cables.
  • One PC installed in the home and one in the place of work (office), respectively, of a person.
  • the PCs are then be connected to the internet and the data collected by the sensors obtained from the PCs by a remote computer via the internet.
  • the concentration of ozone and VOCs are thus measured and the total dose of these pollutants that the person was exposed to calculated over a period of 3 months. During that time the person is able to keep a record of asthma attacks, recording time, place, severity of attack on a scale of 1 to 5 and duration. This database of dose-response data is then be used to calculate an individual's dose-response function and minimum risk level.
  • a plot of number of asthma attacks or severity of asthma attack versus ozone dose per day may show a correlation that would allow a personal dose-response curve to be created that would indicate the minimum risk level (MRL) specific for the person.
  • MTL minimum risk level
  • the database of ozone concentrations might indicate that the office environment exceeded this MRL when the printer was used for extended periods which increased the persons risk of asthma. Removal of the printer from the office would therefore reduce the asthma attacks of the person.
  • Example 2 A dose-response curve for ozone is developed for a person using the procedure described in Example 1 and a minimum risk level (MRL) established. The total exposure data obtained by the sensor network and database described in Example 1 is then used to determine whether the person's MRL was exceeded during a given time period. This information is then be used by an health insurance company to set the price of premiums or level of rebates thus encouraging a person with a susceptibility to ozone-induced asthma to choose to live in an environment with low ozone levels to reduce their incidence of asthma.
  • MRL minimum risk level
  • Example 3 A dose-response curve for one or more of formaldehyde, sulfur dioxide, carbon monoxide, carbon dioxide etc is developed for a person as in Example 1 and used in a similar way in Example 2.
  • a plurality of sensors that detect one or more of SO 2 , CO, O 3 , Volatile organic compounds, volatile aldehydes, formaldehyde, humidity, NO2, NO, chlorine, ammonia, hydrogen sulfide, hydrocarbons, benzene, relative humidity (a proxy for dust mite populations) or dust, are distributed through a building and connected via a wired or wireless network to a computer or computers that may be located in the building or elsewhere such that the ambient air concentrations of the gas or gases are recorded in a database.
  • the database also specifies the place and time of the gas concentration reading.
  • the database is used to establish the dose of the gas or gases that the inhabitants of the building are exposed to. This dose is compared to the minimum risk levels, established by a procedure outlined in Example 1, of each inhabitant. If the dose of a gas exceeds the MRL of an individual or individuals in a particular location (office or room) then they and/or the building owner may be notified to take remedial steps.

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Abstract

Procédés servant à mettre en correspondance des données de qualité d'air résolues sur les plans temporel et spatial avec l'emplacement temporel et/ou spatial d'un individu ou d'un groupe d'individus. L'invention concerne également des mises en application de ce procédé et des données obtenues à cet effet afin de prédire l'évolution de la santé d'un individu et de calculer, par exemple, ses primes d'assurance médicales.
PCT/NZ2002/000012 2001-02-08 2002-02-07 Systeme servant a controler la qualite de l'air Ceased WO2002063539A1 (fr)

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Cited By (14)

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WO2009063106A1 (fr) * 2007-11-12 2009-05-22 Farmbiocontrol, S.L. Procédé de contrôle et de sécurité biologique dans des installations pour du bétail et dans des fermes
WO2012023136A1 (fr) 2010-08-15 2012-02-23 Airbase Systems Ltd. Dispositif, système et procédé de surveillance d'état de santé personnel en fonction de données environnementales en une multitude de points
CN103455720A (zh) * 2013-08-27 2013-12-18 柳州市博源环科科技有限公司 水的生产和供应业环境风险源评价方法
WO2014194480A1 (fr) * 2013-06-05 2014-12-11 Microsoft Corporation Inférence de la qualité de l'air à partir de sources de données multiples
WO2014183100A3 (fr) * 2013-05-10 2015-02-19 Wello, Inc. Système et procédé permettant une notification des états de risque de contagion et une atténuation de ce risque
CN107992454A (zh) * 2017-12-25 2018-05-04 安徽大学 一种基于在线顺序回归的空气质量等级预测方法
CN108829642A (zh) * 2018-04-24 2018-11-16 中国环境科学研究院 一种利用特征雷达图分析环境质量数据的方法
CN105630842B (zh) * 2014-11-07 2019-06-14 阿里巴巴集团控股有限公司 建立空气质量信息数据库、确定受污染信息的方法及装置
US10627380B2 (en) 2017-02-08 2020-04-21 International Business Machines Corporation Multi-source data assimilation for three-dimensional environmental monitoring
CN111897810A (zh) * 2020-07-29 2020-11-06 上海大学 建立定量化不同尺度区域间大气污染联防联控方案的方法
CN112782364A (zh) * 2020-12-30 2021-05-11 华南智能机器人创新研究院 一种自动检测挥发性有机污染物的方法及系统
US11185252B2 (en) 2018-10-18 2021-11-30 Koninklijke Philips N.V. Determining a risk level posed by an air pollutant
US11307187B2 (en) 2019-10-01 2022-04-19 International Business Machines Corporation Detection of area of abnormal air quality within a geographical area
CN118692679A (zh) * 2024-08-23 2024-09-24 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) 一种基于环境图像的生理健康状态评估方法、装置和介质

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WO2000037933A1 (fr) * 1998-12-18 2000-06-29 Raytheon Company Traitement matriciel stochastique de mesures de detection pour detecter et quantifier des analytes
WO2000065996A1 (fr) * 1999-05-04 2000-11-09 Nokia Corporation Procede et appareil d'analyse de la qualite de l'air reposant sur les reactions humaines et des methodes d'agregation

Cited By (22)

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ES2349208A1 (es) * 2007-11-12 2010-12-29 Farmbiocontrol, S.L. Procedimiento de control y de seguridad biologica en instalaciones ganaderas y granjas.
WO2009063106A1 (fr) * 2007-11-12 2009-05-22 Farmbiocontrol, S.L. Procédé de contrôle et de sécurité biologique dans des installations pour du bétail et dans des fermes
EP2699888A4 (fr) * 2010-08-15 2015-08-26 Airbase Systems Ltd Dispositif, système et procédé de surveillance d'état de santé personnel en fonction de données environnementales en une multitude de points
WO2012023136A1 (fr) 2010-08-15 2012-02-23 Airbase Systems Ltd. Dispositif, système et procédé de surveillance d'état de santé personnel en fonction de données environnementales en une multitude de points
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WO2014194480A1 (fr) * 2013-06-05 2014-12-11 Microsoft Corporation Inférence de la qualité de l'air à partir de sources de données multiples
CN105493109A (zh) * 2013-06-05 2016-04-13 微软技术许可有限责任公司 使用多个数据源的空气质量推断
CN105493109B (zh) * 2013-06-05 2018-01-30 微软技术许可有限责任公司 使用多个数据源的空气质量推断
CN103455720A (zh) * 2013-08-27 2013-12-18 柳州市博源环科科技有限公司 水的生产和供应业环境风险源评价方法
CN105630842B (zh) * 2014-11-07 2019-06-14 阿里巴巴集团控股有限公司 建立空气质量信息数据库、确定受污染信息的方法及装置
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