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BDSNP Module——用于改善CMAQ模型中土壤氮氧化物(NO)排放估计的模块

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发布2025-02-18 12:13:17
发布2025-02-18 12:13:17
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BDSNP Module for Improved Soil NO Emission Estimates for CMAQ Model, Conterminous USA

简介

该数据集是一个用于改善CMAQ模型中土壤氮氧化物(NO)排放估计的BDSNP模块,涵盖了美国本土的范围。该数据集提供了详细的土壤氮氧化物排放估计,有助于提高对大气中NO浓度和分布的预测精度。

数据集包括土壤类型、土壤pH值、土壤含水量、土壤温度等因素,这些因素对土壤中NO的生成和释放起着重要作用。通过将这些因素结合到CMAQ模型中,可以更准确地模拟土壤中NO的排放过程,从而提高模型对大气中NO浓度的预测精度。

摘要

Spatial Coverage: CMAQ model domain for Continental United States and portions of northern Mexico and southern Canada

Spatial Resolution: 12- by 12-km grid

Temporal Coverage: Input fertilizer data: 20110101 - 20120101; Outputs: 20110621 - 20110622

Temporal Resolution: Hourly

Study Area:

Site

Westernmost Longitude

Easternmost Longitude

Northernmost Latitude

Southernmost Latitude

CONUS

-129.79

-65.00

51.76

22.75

Table 1. Fortran source files

Filename

Description

BDSNP_MOD_EPIC.F

Gives soil NO parameterization as given by Hudman et al. (2012) with options of enhancement in terms of 'new' soil biome (NLCD40 for 2006) and dynamic fertilizer nitrogen pool from EPIC (Cooter et al., 2012; see Data Acquisition, Materials, and Methods)

canopy_nox_mod.F

Source code for incorporating canopy reduction of soil NO as proposed by Hudman et al. (2012)

cldproc_acm.F and vdiffacm2.F

Two source code files for obtaining total mass of nitrogen per unit area deposited to the ground from the atmosphere through wet (cldproc_acm.F) and dry (vdiffacm2.F) deposition.

tmpbeis.F

Source code to create model-ready biogenic emissions from gridded land use data with emissions inputs in moles/second; in this implementation, tmpbeis.F has been modified to give the option to calculate soil NO emission either from Yienger and Levy (1995) parameterization or from BDSNP (see Data Acquisition, Materials, and Methods)

Table 2. Data variables in soil biome type maps

Variable

Description

Units

LANDFRAC

Biome classification *

TFLAG

Timestep **

x

Synthesized coordinate from XORIG XCELL ***

km

y

Synthesized coordinate from YORIG YCELL ***

km

Table 3. Data variables for NetCDF inputs for soil biome type

Variable

Description

Units

TFLAG *

Timestep *

x

Synthesized coordinate from XORIG XCELL **

km

y

Synthesized coordinate from YORIG YCELL **

km

Arid

Arid land climate ***

0/1

NonArid

NonArid land climate ***

0/1

* No data for this variable. All values are 0.

** See BDSNPmodule_UserGuide_GMD_Supplement.pdf companion file for model grid description.

*** Arid and NonArid variables only exist in their respective NetCDF files listed above.

Table 4. Data variables for CCTM_V5g_Linux2_x86_64ifort_SOILFERT12US2.CONUS.nc

Variable

Description

Units

FERTDAY(001-366)

Nitrogen from manure and fertilizer for day ### *

ng N/m2

TFLAG

Timestep **

x

Synthesized coordinate from XORIG XCELL ***

km

y

Synthesized coordinate from YORIG YCELL ***

km

* 366 variables give the daily fertilizer nitrogen inputs for 20110101 - 20120101.

** No data for this variable. All values are 0.

*** See BDSNPmodule_UserGuide_GMD_Supplement.pdf companion file for model grid description.

Table 5. Data variables for SOILFERT_EPIC_Potter_2011MMDD.nc

Variable

Description

Units

T1_EPIC

Fertilizer nitrogen from EPIC

ng N/m2

TFLAG

Timestep *

x

Synthesized coordinate from XORIG XCELL **

km

y

Synthesized coordinate from YORIG YCELL **

km

* No data for this variable. All values are 0.

** See BDSNPmodule_UserGuide_GMD_Supplement.pdf companion file for model grid description.

able 6. Data variables for soil instate/soilout restart files.

Variable

Description

Units

PFACTOR

NO emission current pulse factor

0-1

DRYPERIOD

Length of the dry period

hr

NDEPRES

Soil N reservoir from deposition

Ng/m2

SOILMPREV

Soil moisture ratio for previous time step

m3/m3

THETA_DIAG

Moisture water-filled pore space *

0-1

WET_TERM_DIAG

Moisture scale factor *

0-1

TEMP_DIAG

Temperature in last simulation hour *

K

A_DIAG

Base emission factor from soil biome type *

0-1

NRES_FERT_DIAG

NRES fertilizer only *

0-1

AFERT_DIAG

Fertilizer emission factor *

0-1

NDEPRATE_DIAG

Daily average N deposition rate *

gm/s

CRFAVG

Daily average canopy reduction factor *

0-1

PULSEAVG

Daily average pulse factor *

0-1

* Diagnostic parameters

able 7. Data variables for sample output files. Units are grams per second for a 12- by 12-km grid cell.

Variable

Description

Units

ALD2

Acetaldehyde

gm/s

ALDX

Propionaldehyde and higher aldehydes

gm/s

CO

Carbon monoxide

gm/s

ETH

Ethene

gm/s

ETHA

Ethane

gm/s

ETOH

Ethanol

gm/s

FORM

Formaldehyde

gm/s

IOLE

Internal olefin carbon bond (R-C=C-R)

gm/s

ISOP

Isoprene

gm/s

MEOH

Methanol

gm/s

NO

Nitric oxide

gm/s

OLE

Terminal olefin carbon bond (R-C=C)

gm/s

PAR

Paraffin carbon bond (C-C)

gm/s

SESQ

Sesquiterpene

gm/s

TERP

Terpene

gm/s

time

synthesized coordinate from SDATE, STIME, STEP

seconds since 2011-06-21 01:00:00 UTC

x

synthesized coordinate from XORIG XCELL

km

y

synthesized coordinate from YORIG YCELL

km

Fig 1. Soil nitric oxide emissions (tonnes/day) from three CMAQ parameterizations (from Rasool et al., 2016)

代码

代码语言:javascript
代码运行次数:0
复制
!pip install leafmap
!pip install pandas
!pip install folium
!pip install matplotlib
!pip install mapclassify
 
import pandas as pd
import leafmap
 
url = "https://github.com/opengeos/NASA-Earth-Data/raw/main/nasa_earth_data.tsv"
df = pd.read_csv(url, sep="\t")
df
 
leafmap.nasa_data_login()
 
 
results, gdf = leafmap.nasa_data_search(
    short_name="BDSNP_CMAQ_Model_1351",
    cloud_hosted=True,
    bounding_box=(-129.79, 22.75, -65.0, 51.76),
    temporal=("1950-01-01", "2016-11-16"),
    count=-1,  # use -1 to return all datasets
    return_gdf=True,
)
 
 
gdf.explore()
 
#leafmap.nasa_data_download(results[:5], out_dir="data")

引用

Rasool, Q.Z., R. Zhang, D.S. Cohan, E.J. Cooter, L.N. Lamsal, J.O. Bash, and B. Lash. 2016. BDSNP Module for Improved Soil NO Emission Estimates for CMAQ Model, Conterminous USA. ORNL DAAC, Oak Ridge, Tennessee, USA. BDSNP Module for Improved Soil NO Emission Estimates for CMAQ Model, Conterminous USA, https://doi.org/10.3334/ORNLDAAC/1351

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