CN111382506A - Method for evaluating influence of aerosol and radiation interaction on atomization effect - Google Patents
Method for evaluating influence of aerosol and radiation interaction on atomization effect Download PDFInfo
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Abstract
The invention discloses a method for evaluating the influence of aerosol and radiation interaction on atomization effect, which comprises the following steps: establishing a WRF-Chem model, a selection scheme, an optimization scheme, artificial emission analysis, pollution event material drawing and model sensitivity simulation; according to the invention, research is carried out through a meteorological chemical model WRF-Chem, the influence of ARI on the change of the concentration of PM2.5 on the ground is researched on the assumption that temporary emission control measures are adopted in areas A, B and C, four events in 2014 and 2015 are analyzed, the wide PM2.5 pollution conditions in the areas A, B and C are covered, and the result shows that if no ARI exists, the reduction of emission amount leads the surface PM2.5 to be in a linear relation with the concentration of the surface PM2.5, but for ARI, the emission is reduced, and a secondary relation exists between the surface PM2.5 concentration and the concentration of the surface PM.
Description
Technical Field
The invention relates to the technical field of meteorological evaluation, in particular to an evaluation method for the influence of aerosol and radiation interaction on atomization effect.
Background
In recent years PM2.5 air pollution has become more and more severe and previous analytical provisional practice for these has shown that meteorological conditions are very important for determining the reduction in PM2.5 concentration and hence the effectiveness of emission control measures, PM2.5 in turn affects local weather in a short time through aerosol-meteorological interactions, which can directly scatter or absorb solar radiation, leading to fluctuations in the energy budget, defined as aerosol-radiation interactions (ARI), which both scatter and absorb aerosol can increase atmospheric stability, and furthermore, aerosol can serve as a source of cloud condensation nuclei, thus changing cloud lifetime and albedo, and precipitation, so-called aerosol-cloud interactions (ACI);
both ARI and ACI can alter the vertical mixing of the flow velocity and mass and momentum in the planetary boundary layer and disturb the meteorological variables, and therefore these disturbances can affect the concentration of PM2.5 through transport and chemical formation changes, previous studies have shown that aerosol meteorological interactions can severely affect the concentration of PM2.5 and the monthly mean during a contamination event, and one problem that has not been explored to a large extent is how these interactions will respond to temporary emission control measures that are important to reducing the effectiveness of PM2.5, and therefore the present invention proposes a method of assessing the impact of aerosol and radiation interactions on atomization to solve the problems existing in the prior art.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method for evaluating the influence of aerosol and radiation interaction on atomization effect, which is researched by a meteorological chemical model WRF-Chem, supposing that temporary emission control measures are adopted in areas a, B and C, the influence of ARI on ground PM2.5 concentration change is researched, four events in 2014 and 2015 are analyzed, and the wide PM2.5 pollution conditions in the areas a, B and C are covered.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: the method for evaluating the influence of aerosol and radiation interaction on atomization effect comprises the following steps:
the method comprises the following steps: establishing WRF-Chem model
Taking an area A, an area B and an area C as examples, establishing a WRF-Chem model which is an online coupled meteorological chemical model and is used for simulating conversion of chemical species such as trace gas, aerosol and a meteorological field and interaction thereof, firstly using a WRF-Chem version 3.6.1, covering the area A, the area B and the area C in a modeling field, then extracting meteorological initial and transverse boundary conditions from environmental prediction center NCEP operation global analysis data, wherein the resolution is 1-degree × 1 degrees, and then filing the initial and boundary chemical conditions from a global MOZART ozone and related chemical tracer models;
step two: selection scheme
The following physical and chemical schemes were used in the WRF-Chem model: RRTMG protocol for short and long wave radiation, Morrison aerosol microbiology protocol, norasian land plan, PBL plan of the university of time, model version of the simulated aerosol interaction and chemical model MOSAIC, and CBMZ;
step three: optimization scheme
According to step two, mosaiic uses a small-area process of 0.039-0.156, 0.156-0.625, 0.625-2.5 and 2.5-10.0 dry diameter μm nitrate NO3, ammonium NH4, black carbon BC, organic carbon OC and other inorganic substances OIN; the aerosol-radiation interaction ARI effect is the calculation of the optical properties of the aerosol from chemical composition, size distribution, mass concentration and mixing rules using such factors as optical depth of aerosol, single scattering albedo and asymmetry in radiation transport model calculations; the Morrison microphysics project simulates aerosol-cloud interaction ACI by connecting the prognostic aerosol with cloud condensation nuclei, and then uses a specified cloud drop number concentration CDNC of 10cm-3 in the Morrison microphysics project to exclude ACI and artificial influence on clouds;
step four: anthropogenic emission analysis
For artificial emissions, using the 2012 national multiresolution emissions list and the 2010 MIX asia emissions list, which provide artificial emissions of the main PM2.5 and its precursors from the urban facilities and the agricultural sector, natural dust emissions follow the gotart program and are subject to modification by the air force meteorological office AFWA, and the emissions of biological non-methane VOCs are calculated in a model using an emissions model of gas and aerosols from the Nature MEGAN algorithm;
step five: material selection in contamination event
Analyzing four pollution events occurring in areas A, B and C: ep 1: 17-26 days 2 month 2014, Ep 2: 21-25 days 10 month 2014, Ep 3: 11/month 5 to 11/2014, Ep 4: using PM2.5 mass concentration measurement values of each hour from an environmental monitoring center network from 18 days to 24 days 12 months 2015 to obtain the pollution degrees of the four events;
step six: model sensitivity simulation
According to step five, to evaluate the model-simulated PM2.5 concentrations, basic simulations were performed from 2 months 2 to 27 days 2014, from 10 months 13 to 11 months 12 days 2014 and from 9 days 2015 12 to 24 days, the first two days of each period being used for subcontracting, no analysis being performed, ARI and ACI both being on in the basic simulations, while the regional decrement is obtained by the regional city protection agency BMEPB in region a, four sensitivity simulations were performed for each pollution event by turning ARI on, off and with and without emission reduction to study the effect of ARI on the effectiveness of emission control measures, while ACI was disabled in all sensitivity simulations, assuming that the same control measures and related decrement can be applied to other events, defining the effect of ARI attenuated due to emission reduction as Δ ARIV:
dariff ═ (VB-VD) - (VA-VC) (1)
Where V represents the PM2.5 centralized and biological variables WS, surface wind directions WD and RH, for PM2.5, the effect of the emission control measure is estimated and ARI (Δ PM2.5) is taken into account as the difference between running the four sensitivity simulations, and the effect of no ARI, and then the ratio Δ ARIPM2.5/Δ PM2.5 is defined as the degree to which ARI quantifies the effect of ARI on the effectiveness of the emission control measure.
The further improvement lies in that: in the first step, the modeling field covers the area A, the area B and the area C, the horizontal resolution is set to be 36km, the vertical resolution is set to be 37km, and the height extends to 50hPa from the ground.
The further improvement lies in that: in the second step, the CBMZ is used for gas phase chemistry.
The further improvement lies in that: in the third step, it is assumed that the aerosols are mixed inside each bin and that secondary organic aerosols are not included in this study.
The further improvement lies in that: in the fourth step, the urban facilities include power plants, industry, residences and transportation.
The further improvement lies in that: in the fifth step, the average concentration of PM2.5 covered by the area A is 49-188 [ mu ] gm-3, and the average concentration of PM2.5 in the areas A, B and C is 199 [ mu ] gm-3 during the period from 2 months to 17 days to 26 days in 2014.
The further improvement lies in that: in step six, in the base simulation, both ARI and ACI are on, and there is no change in artificial emissions except for the APEC period where emissions control measures are taken from 11 month, 2 days to 12 days 2014.
The invention has the beneficial effects that: the invention is researched through a meteorological chemical model WRF-Chem, supposing that temporary emission control measures are adopted in areas A, B and C, the influence of ARI on the change of the concentration of the PM2.5 on the ground is researched, four events in 2014 and 2015 are analyzed, the wide PM2.5 pollution conditions in the areas A, B and C are covered, and the result shows that if no ARI exists, the reduction of the emission amount leads the surface PM2.5 to be in a linear relation with the concentration of the surface PM2.5, but for ARI, due to the reduction of the emission amount, a quadratic relation exists between the surface PM2.5 concentration and the concentration of the surface PM2.5, which means that the emission control measures are more effective under the heavy pollution condition due to ARI effect, and for the four analyzed events, the reduction amplitude of the average PM2.5 in the areas A due to the emission amount is 6.7% -21.9% larger than the estimation value without using ARI, the invention emphasizes that when the short-term emission control measures are designed and the effectiveness is evaluated, aerosol-gas phase interactions need to be considered.
Drawings
FIG. 1 is a comparison graph of a simulation of a verification example of the present invention.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
The embodiment provides an evaluation method for the influence of aerosol and radiation interaction on atomization effect, which comprises the following steps:
the method comprises the following steps: establishing WRF-Chem model
Taking an area A, an area B and an area C as examples, establishing a WRF-Chem model which is an online coupled meteorological chemical model and is used for simulating conversion of chemical species such as trace gas, aerosol and a meteorological field and interaction thereof, firstly using a WRF-Chem version 3.6.1, covering the area A, the area B and the area C in a modeling field, setting the horizontal resolution to be 36km and the vertical resolution to be 37km, extending from the ground to 50hPa, then extracting meteorological initial and transverse boundary conditions from environmental prediction center NCEP operation global analysis data, setting the resolution to be 1 degree × 1 degrees, and then filing the initial and boundary chemical conditions from a global MOZART ozone and related chemical tracer models;
step two: selection scheme
The following physical and chemical schemes were used in the WRF-Chem model: RRTMG protocol for short and long wave radiation, Morrison aerosol micro physics protocol, norasian land plan, PBL plan of the university of the world, model version of the simulated aerosol interaction and chemical model MOSAIC and CBMZ, CBMZ for gas phase chemistry;
step three: optimization scheme
According to step two, mosaiic treated nitrate NO3, ammonium NH4, black carbon BC, organic carbon OC and other inorganic substances OIN with a dry diameter μm of 0.039-0.156, 0.156-0.625, 0.625-2.5 and 2.5-10.0 using size zones, assuming that the aerosols were mixed inside each bin, secondary organic aerosols were not included in this study; the aerosol-radiation interaction ARI effect is the calculation of the optical properties of the aerosol from chemical composition, size distribution, mass concentration and mixing rules using such factors as optical depth of aerosol, single scattering albedo and asymmetry in radiation transport model calculations; morrison microphysics project links a prognostic aerosol to a cloud condensation nucleusTo simulate aerosol-cloud interaction ACI, and then use 10cm in the Morrison micro-physics protocol-3To rule cloud droplet number concentration CDNC to exclude ACI and human effects on the cloud;
step four: anthropogenic emission analysis
For artificial emissions, using the 2012 national multiresolution emissions list and the 2010 MIX asia emissions list, which provide artificial emissions of the main PM2.5 and its precursors from power plants, industrial, residential, transportation and agricultural sectors, natural dust emissions follow the gotart program and have been modified by the air force meteorological office, AFWA, in models where the emissions of biological non-methane VOCs are calculated using an emissions model of gas and aerosols from the Nature MEGAN algorithm;
step five: material selection in contamination event
Analyzing four pollution events occurring in areas A, B and C: ep 1: 17-26 days 2 month 2014, Ep 2: 21-25 days 10 month 2014, Ep 3: 11/month 5 to 11/2014, Ep 4: using PM2.5 mass concentration measurement values per hour from a China national environmental monitoring center network from 12 months and 18 days to 24 days in 2015 to obtain the pollution degrees of the four events, wherein the average concentration of PM2.5 covered by the area A is 49-188 [ mu ] gm-3, and the average concentration of PM2.5 in areas A, B and C is 199 [ mu ] gm-3 during the period from 2 months and 17 days to 26 days in 2014;
step six: model sensitivity simulation
According to step five, to evaluate the PM2.5 concentration of the model simulation, basic simulations were performed on days 2-27 of 2014, days 13-11 of 2014 and days 9-24 of 2015, the first two days of each period being used for subcontracting, no analysis being performed, in the basic simulation, both ARI and ACI were open, with no change in anthropogenic emissions except for the APEC period where emissions control measures were taken from 11 months, 2 days to 12 days 2014, meanwhile, the BMEPB in the city environmental protection agency of the A area obtains the reduction capacity of the area, four sensitivity simulations are carried out on each pollution event by opening and closing ARI and reducing the emission or not so as to research the influence of the ARI on the effectiveness of emission control measures, while ACI was disabled in all sensitivity simulations, assuming the same control measures and associated displacement reductions could be applied to other events, the ARI effect attenuated due to the reduction in emissions was defined as Δ ARIV:
dariff ═ (VB-VD) - (VA-VC) (1)
Where V represents the PM2.5 centralized and biological variables WS, surface wind directions WD and RH, for PM2.5, the effect of the emission control measure is estimated and ARI (Δ PM2.5) is taken into account as the difference between running the four sensitivity simulations, and the effect of no ARI, and then the ratio Δ ARIPM2.5/Δ PM2.5 is defined as the degree to which ARI quantifies the effect of ARI on the effectiveness of the emission control measure.
Verification example:
the measured and simulated PM2.5 concentration was compared to the actual hourly PM2.5 concentration for three extra large cities (area a, area B and area C) and the model simulation values, see fig. 1: three major cities were 2 months 4 to 27 days 2014, 10 months 15 to 11 months 12 days 2014 and 12 months 11 to 24 days 2015: hourly measured and simulated time series of PM2.5 concentrations per hour for region a, region B and region C. Represents four episodes Ep1-Ep4 analyzed in this study; ep3 is APEC week. The observations (points) are compared to the model results (lines) of the underlying simulation. The numerical inset is the mean over three time periods, including the observation and model results;
in areas a, B, and C, days 2, 4 to 27 in 2014, days 10, 15 to 11, 12 in 2014, and days 11 to 24 in 2015. We average the hourly measurements for all monitoring points in a given city to represent the state at the city level. The model captures most of the observed PM2.5 time changes in three cities with correlation coefficients of 0.59-0.64. During this period, the model-simulated PM2.5 concentrations were-17.5% -2.0% biased in area A, 13.3% -57.0% biased in area B, and-19.4% -4.4% biased in area C. The reason for the large model overestimation of PM2.5 in region B for the last two days of Ep1 may be a south wind anomaly simulated by the model, which is favorable for pollution accumulation. In this study, the cases with the least and the most contamination were analyzed separately. We also evaluated the model simulated surface temperatures, RH, WS, and WD using measurements from the National Climate Data Center (NCDC). And no significant deviation was found in the field of model meteorology. We controlled the areas a, B, C by the high pressure system during Ep1 and Ep4, resulting in stagnation of air conditions and accumulation of pollution, while during Ep3 (one week in APEC), northwest wind was strong, with cold tide intrusion, dominant. Previous studies also showed that emission reduction and weather map both had a significant effect on the area a PM2.5 concentration during APEC, where the observed average PM2.5 concentration was 48.9 μ gm-3, about 60.3 μ gm-3 lower than the previous weeks (109.2 μ gm-3 from 10 months 15 days to 11 months 4 days 2014). The corresponding PM2.5 concentration for the simulation in area A was reduced to 63.7 μ gm-3-3-3 and our results also show that if no emission control measures were taken, the average surface PM2.5 concentration for area A would be 60.0 μ gm-3, lower than the simulated average concentration before APEC (104.9 μ gm-3), but higher than the APEC average in the baseline simulation (41.2 μ gm-3). This supports the previous finding that both the reduction in emissions and meteorological factors during APEC are responsible for the reduction in PM 2.5.
The invention is researched through a meteorological chemical model WRF-Chem, supposing that temporary emission control measures are adopted in areas A, B and C, the influence of ARI on the change of the concentration of the PM2.5 on the ground is researched, four events in 2014 and 2015 are analyzed, the wide PM2.5 pollution conditions in the areas A, B and C are covered, and the result shows that if no ARI exists, the reduction of the emission amount leads the surface PM2.5 to be in a linear relation with the concentration of the surface PM2.5, but for ARI, due to the reduction of the emission amount, a quadratic relation exists between the surface PM2.5 concentration and the concentration of the surface PM2.5, which means that the emission control measures are more effective under the heavy pollution condition due to ARI effect, and for the four analyzed events, the reduction amplitude of the average PM2.5 in the areas A due to the emission amount is 6.7% -21.9% larger than the estimation value without using ARI, the invention emphasizes that when the short-term emission control measures are designed and the effectiveness is evaluated, aerosol-gas phase interactions need to be considered.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. The method for evaluating the influence of aerosol and radiation interaction on atomization effect is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: establishing WRF-Chem model
Taking an area A, an area B and an area C as examples, establishing a WRF-Chem model which is an online coupled meteorological chemical model and is used for simulating conversion of chemical species such as trace gas, aerosol and a meteorological field and interaction thereof, firstly using a WRF-Chem version 3.6.1, covering the area A, the area B and the area C in a modeling field, then extracting meteorological initial and transverse boundary conditions from environmental prediction center NCEP operation global analysis data, wherein the resolution is 1-degree × 1 degrees, and then filing the initial and boundary chemical conditions from a global MOZART ozone and related chemical tracer models;
step two: selection scheme
The following physical and chemical schemes were used in the WRF-Chem model: RRTMG protocol for short and long wave radiation, Morrison aerosol microbiology protocol, norasian land plan, PBL plan of the university of time, model version of the simulated aerosol interaction and chemical model MOSAIC, and CBMZ;
step three: optimization scheme
According to step two, mosaiic uses a small-area process of 0.039-0.156, 0.156-0.625, 0.625-2.5 and 2.5-10.0 dry diameter μm nitrate NO3, ammonium NH4, black carbon BC, organic carbon OC and other inorganic substances OIN; the aerosol-radiation interaction ARI effect is the calculation of the optical properties of the aerosol from chemical composition, size distribution, mass concentration and mixing rules using such factors as optical depth of aerosol, single scattering albedo and asymmetry in radiation transport model calculations; morrison microphysics protocol simulates gas by linking a prognostic aerosol to a cloud condensation nucleusSol-cloud interaction ACI, then using 10cm in the Morrison micro-physics protocol-3To rule cloud droplet number concentration CDNC to exclude ACI and human effects on the cloud;
step four: anthropogenic emission analysis
For artificial emissions, using the 2012 national multiresolution emissions list and the 2010 MIX asia emissions list, which provide artificial emissions of the main PM2.5 and its precursors from the urban facilities and the agricultural sector, natural dust emissions follow the gotart program and are subject to modification by the air force meteorological office AFWA, and the emissions of biological non-methane VOCs are calculated in a model using an emissions model of gas and aerosols from the Nature MEGAN algorithm;
step five: material selection in contamination event
Analyzing four pollution events occurring in areas A, B and C: ep 1: 17-26 days 2 month 2014, Ep 2: 21-25 days 10 month 2014, Ep 3: 11/month 5 to 11/2014, Ep 4: using PM2.5 mass concentration measurement values of each hour from an environmental monitoring center network from 18 days to 24 days 12 months 2015 to obtain the pollution degrees of the four events;
step six: model sensitivity simulation
According to step five, to evaluate the model-simulated PM2.5 concentrations, basic simulations were performed from 2 months 2 to 27 days 2014, from 10 months 13 to 11 months 12 days 2014 and from 9 days 2015 12 to 24 days, the first two days of each period being used for subcontracting, no analysis being performed, ARI and ACI both being on in the basic simulations, while the regional decrement is obtained by the regional city protection agency BMEPB in region a, four sensitivity simulations were performed for each pollution event by turning ARI on, off and with and without emission reduction to study the effect of ARI on the effectiveness of emission control measures, while ACI was disabled in all sensitivity simulations, assuming that the same control measures and related decrement can be applied to other events, defining the effect of ARI attenuated due to emission reduction as Δ ARIV:
dariff ═ (VB-VD) - (VA-VC) (1)
Where V represents the PM2.5 centralized and biological variables WS, surface wind directions WD and RH, for PM2.5, the effect of the emission control measure is estimated and ARI (Δ PM2.5) is taken into account as the difference between running the four sensitivity simulations, and the effect of no ARI, and then the ratio Δ ARIPM2.5/Δ PM2.5 is defined as the degree to which ARI quantifies the effect of ARI on the effectiveness of the emission control measure.
2. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in the first step, the modeling field covers the area A, the area B and the area C, the horizontal resolution is set to be 36km, the vertical resolution is set to be 37km, and the height extends to 50hPa from the ground.
3. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in the second step, the CBMZ is used for gas phase chemistry.
4. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in the third step, it is assumed that the aerosols are mixed inside each bin and that secondary organic aerosols are not included in this study.
5. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in the fourth step, the urban facilities include power plants, industry, residences and transportation.
6. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in the fifth step, the average concentration of PM2.5 covered by the area A is 49-188 [ mu ] gm-3, and the average concentration of PM2.5 in the areas A, B and C is 199 [ mu ] gm-3 during the period from 2 months to 17 days to 26 days in 2014.
7. The method of claim 1 for assessing the effect of aerosol and radiation interaction on aerosolization, wherein: in step six, in the base simulation, both ARI and ACI are on, and there is no change in artificial emissions except for the APEC period where emissions control measures are taken from 11 month, 2 days to 12 days 2014.
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