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HJ 1130-2020: Technical guideline for numerical forecasting of ambient air quality
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Technical guideline for numerical forecasting of ambient air quality
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HJ 1130-2020
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Basic data | Standard ID | HJ 1130-2020 (HJ1130-2020) | | Description (Translated English) | Technical guideline for numerical forecasting of ambient air quality | | Sector / Industry | Environmental Protection Industry Standard | | Classification of Chinese Standard | Z15 | | Word Count Estimation | 10,121 | | Date of Issue | 2020-05-15 | | Date of Implementation | 2020-08-15 | | Regulation (derived from) | Ministry of Ecology and Environment Announcement No. 29, 2020 | | Issuing agency(ies) | Ministry of Ecology and Environment | HJ 1130-2020: Technical guideline for numerical forecasting of ambient air quality---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
Technical guideline for numerical forecasting of ambient air quality
National Environmental Protection Standards of the People's Republic of China
Technical specification for numerical forecast of ambient air quality
2020-05-15 release
2020-08-15 Implementation
Issued by the Ministry of Ecology and Environment
Table of contents
1 Scope of application...
2 Normative references...
3 Terms and definitions...
4 Basic requirements for numerical forecast models of ambient air quality...
5 Ambient air quality numerical prediction model calculation processing...
6 Ambient air quality numerical forecast model effect evaluation method...
Foreword
To implement the Environmental Protection Law of the People’s Republic of China and the Air Pollution Prevention and Control Law of the People’s Republic of
To improve the environment, protect human health, standardize the forecast of ambient air quality, and formulate this standard.
This standard specifies the basic requirements, calculation processing, and effect evaluation methods of ambient air quality numerical forecast models.
This standard is applicable to guide the operational numerical forecast of ambient air quality by the national ecological environment department.
This standard is issued for the first time.
This standard was formulated by the Department of Ecological Environment Monitoring and the Department of Regulations and Standards of the Ministry of Ecology and Environment.
Drafting organizations of this standard. China Environmental Monitoring Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Nanjing University, Shanghai
Environmental Monitoring Center, Guangdong Environmental Monitoring Center, Beijing Environmental Monitoring Center.
This standard was approved by the Ministry of Ecology and Environment on May 15, 2020.
This standard will be implemented on August 15, 2020.
This standard is interpreted by the Ministry of Ecology and Environment.
1 Technical specifications for numerical prediction of ambient air quality
1 Scope of application
This standard specifies the basic requirements, calculation processing, and effect evaluation methods of ambient air quality numerical forecast models.
This standard is applicable to the operational numerical forecast of ambient air quality by the national ecological environment department, and is used to regulate and guide business
The basic performance, composition and simulation effect of the numerical forecast model of ambient air quality for chemical application.
2 Normative references
This standard quotes the following documents or their clauses. For undated reference documents, their valid versions are applicable to this
standard.
GB 3095 Ambient Air Quality Standard
HJ 633 Technical Regulations for Ambient Air Quality Index (AQI)
3 Terms and definitions
The following terms and definitions apply to this standard.
3.1
Numerical forecasting model for ambient air quality
Based on the basic physical and chemical principles in the formation of air pollutants, numerical calculation methods are used to simulate air pollutants
A system that predicts the air quality through physical and chemical processes such as emissions, diffusion, transportation, chemical reactions, and removal.
3.2
Numerical forecasting of ambient air quality
Use the numerical forecast model of ambient air quality to predict the concentration and temporal changes of the main pollutants in the atmosphere.
Measure the environmental air quality status and potential pollution process in cities and regions, and provide guidance for the daily life and production activities of the public
And services to provide a scientific basis for management departments to take response measures.
3.3
Model-ready pollutant emission inventory
Based on the air pollutant source emission inventory and source inventory processing mode, combined with geographic information data such as population and traffic road network,
According to the time distribution and chemical composition of different types of emission sources, according to the temporal and spatial resolution of the numerical forecast model of ambient air quality
And chemical mechanism requirements, processing the obtained gridded source emission data.
3.4
Atmospheric chemical data assimilation
2 Based on the optimal estimation theory, using the temporal and spatial evolution of model state variables and the continuous constraints of physical and chemical properties, the
Multi-source atmospheric chemical composition observation information is continuously integrated into the ambient air quality model system for more accurate estimation or prediction
Unknown variables, methods to reduce uncertainty.
4 Basic requirements for numerical forecast models of ambient air quality
4.1 Spatial scale range
4.1.1 The numerical forecast model of ambient air quality should objectively reflect the level and change of ambient air quality within a certain space
According to the law, the spatial scale range applied by the model can be divided into global scale, continental scale, regional scale and urban scale.
4.1.2 The continental scale covers East Asia, and the spatial extent is usually over 9 million square kilometers.
4.1.3 The regional scale covers urban agglomerations, and the spatial range is usually 1 to 9 million square kilometers.
4.1.4 The urban scale covers the city and its surrounding areas, and the spatial scope is usually less than 1 million square kilometers.
4.2 Spatial resolution
4.2.1 The horizontal resolution of the calculation area of the ambient air quality numerical forecast model, the global scale is not lower than longitude 1ºlatitude 1
º, the continental scale is not less than 50 kilometers × 50 kilometers, the regional scale is not less than 15 kilometers × 15 kilometers, and the urban scale is not less than
5 kilometers × 5 kilometers.
4.2.2 The number of vertical layers in the calculation area of the model shall not be less than 10, among which the number of vertical layers within 1 km near the ground shall not be less than 5.
4.2.3 The spatial resolution of the model pollution source inventory should be consistent with the spatial resolution of the calculation area of the numerical prediction model.
4.3 Forecast duration
4.3.1 The forecast duration calculated by global and continental scale models shall not be less than 7 days.
4.3.2 The forecast period calculated by the regional scale model shall not be less than 7 days.
4.3.3 The forecast period calculated by the city-scale model shall not be less than 5 days.
4.4 Forecast output time interval
The time interval between the output of two consecutive simulation results of the ambient air quality numerical forecast model should be within 1 hour (inclusive).
5 Operational processing of the numerical forecast model of ambient air quality
5.1 Pre-processing of model pollution source inventory
5.1.1 The main purpose is to convert the air pollutant source emission inventory into a gridded, hourly model pollution source inventory.
5.1.2 Input parameters include regional air pollutant source emission inventory, time and space distribution coefficient, chemical composition spectrum, etc.
5.1.3 The basic attributes of the air pollutant source emission inventory include the base year, coverage, types of pollutants emitted, and emission sources.
Source classification, temporal and spatial resolution, etc.
5.1.4 Emission source categories include power plants, industry, transportation, residents, agriculture, biomass combustion, dust, natural sources, etc.
5.1.5 The types of pollutants emitted include fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2),
Nitrogen oxides (NOx), carbon monoxide (CO), organic carbon (OC), black carbon (BC), ammonia (NH3), volatile
3 Organic matter (VOCs), etc.
5.1.6 Based on time and space allocation coefficients, the air pollutant source emission inventory is allocated in time and space, including population
Space allocation factors such as density and land use, and time allocations such as monthly, weekly, and daily variations of different types of emission sources
factor.
5.1.7 Assign the chemical composition of the discharged pollutants based on the chemical composition spectrum.
5.1.8 If conditions permit, dynamically updated pollution source inventory data can be used.
5.2 Pre-processing of model weather forecast field
5.2.1 The main purpose is to convert the original output results of the weather forecast model into the output of the ambient air quality numerical forecast model.
Entry into the weather forecast field shall include diagnostic analysis, unit conversion, spatial interpolation and format conversion.
5.2.2 The basic attributes of the meteorological forecast field should include the starting time, time and space range, time and space resolution, area
Grid coordinate parameters, boundary layer scheme, radiation scheme, land surface process scheme, cloud formation parameterization scheme, etc.
5.2.3 Meteorological elements should include temperature, pressure, humidity, wind, precipitation, clouds, radiation, etc.
5.3 Initial and boundary condition settings
5.3.1 The main purpose is to provide initial operating values and calculation areas of the outermost model for the ambient air quality numerical forecast model.
Boundary value.
5.3.2 The initial value refers to the concentration value of the pollutant in the area calculated by the model at the initial time. The methods of obtaining are. (1) From the acquired model
(2) Assimilation of atmospheric chemistry data; (3) Set as default value.
5.3.3 Boundary value refers to the pollutant concentration value on the boundary of the calculated area calculated by the outermost model during the forecast period. The method of obtaining is as follows. (1)
Extracted from the forecast results of the global model; (2) set to the default value.
5.4 Atmospheric chemistry transmission calculation
5.4.1 The main purpose is to use mathematical equations to characterize the physical and chemical processes of pollutants' evolution in the atmosphere, and to calculate pollution
The temporal and spatial distribution of the concentration of the substance.
5.4.2 Input parameters include model pollution source list, model weather forecast field, model initial and boundary conditions, and geographic experience.
Latitude data, etc.
5.4.3 The main physical and chemical processes should include discharge, advection, diffusion, convection, dry sedimentation, wet sedimentation, gas phase chemistry,
Liquid phase chemistry, inorganic aerosol chemistry, organic aerosol chemistry and heterogeneous chemical reactions, etc.
5.4.4 Combining the calculation of regional topographic characteristics, meteorological conditions, pollutant emission characteristics and other factors, set physical and chemical process
Key parameter optimization program combination.
5.4.5 When conditions permit, atmospheric chemistry data can be assimilated, using optimal interpolation, three-dimensional variation, four-dimensional variation, and ensemble Karl
Mann filtering and other methods analyze fusion observation data and model forecast data.
5.5 Forecast product output
5.5.1 The main purpose is to perform data extraction, diagnostic analysis, unit conversion, grid coordinates and
Data format conversion, etc., to produce air quality forecast products.
5.5.2 The basic air quality forecast products should include the concentration of major pollutants such as PM2.5, PM10, CO, O3, NO2, SO2, etc.
And air quality index (AQI) temporal and spatial distribution.
45.5.3 Optional products for air quality forecasting include particulate matter components, contribution rate of pollution sources, pollution potential, sand dust, gas
Sol optical thickness, etc.
5.5.4 The basic products of weather conditions forecasting shall include wind direction, wind speed, precipitation, temperature, pressure, relative humidity, radiation,
The spatial distribution of cloud cover, etc. Other products can include boundary layer height, atmospheric visibility, atmospheric stability, forward and backward trajectory, etc.
6 Evaluation method of the effect of numerical forecast model of ambient air quality
6.1 Evaluation content
6.1.1 When applying the numerical forecast model of ambient air quality, its forecast effect should be evaluated.
6.1.2 Evaluation object. including PM2.5, PM10, CO, O3, NO2, SO2 concentration, AQI, AQI level, primary pollution
Dyed things.
6.1.3 Assessment categories. including single pollutant concentration forecast statistical assessment, air quality index forecast assessment, heavy pollution weather
Forecast evaluation.
6.1.4 Timeliness of assessment. the forecast results of the air quality numerical forecast model are divided into 24 hours, 48 hours, 72 hours in advance
Don't evaluate.
6.1.5 Evaluation cycle. quarterly and annual evaluation of the effect of the numerical forecast of ambient air quality; such as monthly evaluation,
Refer to the implementation of this standard.
6.1.6 Live data used in the assessment. the city's AQI and the concentration of various pollutants published in the National Ambient Air Quality Index Daily.
6.1.7 Processing and calculation of forecast results. refer to GB 3095 and HJ 633, according to the air quality index calculation method, first
The pollutant determination method and the air quality index level definition process and calculate the numerical forecast results.
6.2 Statistical evaluation of single pollutant concentration forecast
6.2.1 The statistical evaluation of the single pollutant concentration forecast refers to the deviation,
Analysis of errors and correlations to evaluate the prediction effect of numerical models on urban pollutants. Evaluation content main package
Including standardized mean deviation, root mean square error and correlation coefficient.
6.3 Air Quality Index Forecast Evaluation
6.3.1 The air quality index forecast assessment includes AQI range forecast accuracy rate, AQI level forecast accuracy rate, and primary pollution
Accuracy of forecasting.
6.3.2 AQI range forecast accuracy assessment
Based on the numerical model AQI forecast value, set a positive or negative fluctuation of 25% as the AQI forecast range. If the actual AQI is in the forecast
Within the reporting range, it is recorded that the AQI range forecast is accurate.
The percentage of AQI range forecast accuracy days to the total number of days in the assessment period is the AQI range forecast accuracy rate.
Calculated as follows.
6.3.3 Assessment of AQI-level forecast accuracy
According to the AQI forecast range in 6.3.2, the AQI forecast level range is obtained. If the AQI live level is at the AQI forecast level
Within the range, it is recorded that the AQI level forecast is accurate.
The percentage of AQI-level forecast accuracy days to the total number of days in the evaluation period is the AQI-level forecast accuracy rate.
Including the accuracy rate of the sub-level forecast and the accuracy rate of the level forecast. The annual assessment result of the AQI-level forecast accuracy should not be less than 60%.
Calculated as follows.
6.3.4 Assessment of the accuracy of primary pollutants forecast
The criteria for accurately determining the primary pollutant forecast are as follows.
a) When the actual AQI level is level 1, there is no primary pollutant and will not participate in the primary pollutant forecast assessment;
b) When the actual AQI level is level 2 or above, when any forecast primary pollutant is the same as any actual primary pollutant
When, the forecast of the primary pollutant is accurate.
The percentage of the number of days that the primary pollutant forecast is accurate to the total number of days in the assessment period is the primary pollutant forecast standard
The calculation formula is as follows.
6.4 Evaluation of forecast performance on heavily polluted days
6.4.1 Accuracy of forecasting heavily polluted days
Taking the natural day (0-23 o'clock) as the criterion, the day AQI greater than.200 is defined as a heavily polluted day. Live heavy pollution within one year
When the number of days is greater than or equal to 5 days, heavy pollution forecasting performance evaluation can be carried out.
The forecast accuracy rate of heavily polluted days refers to the percentage of days with accurate AQI-level forecasts among the total days with heavy pollution.
The calculation formula is as follows.
6.4.2 Scoring for heavy polluted days forecast inspection
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