meic2wrf_GUI.py

###############################################  meic2wrf  ########################################################
# Authors:     Fan Jin; Zhou Yong-long; Zhang Lei; Xu Xuan-ye; Jiang Pei-ya; Li Zhuo                              #
# Institution: Chengdu AeriDice Environment Technology Co., Ltd.; Chengdu University of Information & Technology; #
#              Chinese Academy of Meteorological Sciences                                                         #
# E-mail:      jin.fan@outlook.com                                                                                #
# Environment: Python 3.7.7; pynio 1.5.5                                                                          #
###################################################################################################################

import Nio
import tkinter as tk
from tkinter import filedialog
import numpy as np
import os
from int_dis import *
from tkinter import messagebox
import fnmatch 
import shutil 

root=tk.Tk()
root.title('MEIC污染源清单向WRF-Chem模式网格插值分配程序')

lbl=tk.Label(root, text='1. 整合MEIC清单中各污染物不同部门的排放数据')
lbl.grid(row=0,column=0,sticky=tk.W)

lbl=tk.Label(root, text='MEIC清单数据所在文件夹路径:')
lbl.grid(row=1,column=0,sticky=tk.E)

ent_dir = tk.Entry(root, width=65)
ent_dir.grid(row=1,column=1)

def bws_meic(): 
    dirname = filedialog.askdirectory()
    ent_dir.delete(0,tk.END)
    ent_dir.insert(0, dirname)
    
def merge_meic_dept(): 
    if os.path.exists(ent_dir.get()+'/merged/'): 
        shutil.rmtree(ent_dir.get()+'/merged/')
        os.mkdir(ent_dir.get()+'/merged/')
        for i,j in zip(['*BC*','*CO[!2]*','*CO2*','*NH3*','*NOx*','*[!V]OC*','*PM2.5*','*PMcoarse*','*ALD*',\
        '*CSL*','*ETH*','*GLY*','*HC3*','*HC5*','*HC8*','*HCHO*',\
        '*ISO*','*KET*','*MACR*','*MGLY*','*MVK*','*NR*','*NVOL*',\
        '*OL2*','*OLI*','*OLT*','*ORA1*','*ORA2*','*TOL*','*XYL*','*SO2*','*VOC*',], ['BC','CO','CO2','NH3','NOx','OC','PM2.5','PMcoarse','ALD',\
        'CSL','ETH','GLY','HC3','HC5','HC8','HCHO',\
        'ISO','KET','MACR','MGLY','MVK','NR','NVOL',\
        'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL','SO2','VOC',]):
            fn_act=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*agr*nc')[0]
            fn_idt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*ind*nc')[0]
            fn_pwr=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*pow*nc')[0]
            fn_rdt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*res*nc')[0]
            fn_tpt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*tra*nc')[0]

            f_act=Nio.open_file(fn_act)
            f_idt=Nio.open_file(fn_idt)
            f_pwr=Nio.open_file(fn_pwr)
            f_rdt=Nio.open_file(fn_rdt)
            f_tpt=Nio.open_file(fn_tpt)

            act=f_act.variables['z'][:].reshape((200, 320),)[::-1]
            act=np.where(act>0.0,act*1,0.0)
            idt=f_idt.variables['z'][:].reshape((200, 320),)[::-1]
            idt=np.where(idt>0.0,idt*1,0.0)
            pwr=f_pwr.variables['z'][:].reshape((200, 320),)[::-1]
            pwr=np.where(pwr>0.0,pwr*1,0.0)
            rdt=f_rdt.variables['z'][:].reshape((200, 320),)[::-1]
            rdt=np.where(rdt>0.0,rdt*1,0.0)
            tpt=f_tpt.variables['z'][:].reshape((200, 320),)[::-1]
            tpt=np.where(tpt>0.0,tpt*1,0.0)

            lon=np.arange(70.125,150,0.25,dtype=np.float32) 
            lat=np.arange(10.125,60,0.25,dtype=np.float32)
            lon,lat=np.meshgrid(lon,lat)

            f=Nio.open_file(ent_dir.get()+'/merged/'+j+'.nc','c')
            f.create_dimension('lon',320)
            f.create_dimension('lat',200)

            for var,val in zip(['act','idt','pwr','rdt','tpt','lon','lat'],[act,idt,pwr,rdt,tpt,lon,lat]):
                f.create_variable(var,'f',('lat','lon',))
                f.variables[var][:] = val

            f.close()
    else:
        os.mkdir(ent_dir.get()+'/merged/') 
        for i,j in zip(['*BC*','*CO[!2]*','*CO2*','*NH3*','*NOx*','*[!V]OC*','*PM2.5*','*PMcoarse*','*ALD*',\
        '*CSL*','*ETH*','*GLY*','*HC3*','*HC5*','*HC8*','*HCHO*',\
        '*ISO*','*KET*','*MACR*','*MGLY*','*MVK*','*NR*','*NVOL*',\
        '*OL2*','*OLI*','*OLT*','*ORA1*','*ORA2*','*TOL*','*XYL*','*SO2*','*VOC*',], ['BC','CO','CO2','NH3','NOx','OC','PM2.5','PMcoarse','ALD',\
        'CSL','ETH','GLY','HC3','HC5','HC8','HCHO',\
        'ISO','KET','MACR','MGLY','MVK','NR','NVOL',\
        'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL','SO2','VOC',]):
            fn_act=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*agr*nc')[0]
            fn_idt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*ind*nc')[0]
            fn_pwr=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*pow*nc')[0]
            fn_rdt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*res*nc')[0]
            fn_tpt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*tra*nc')[0]

            f_act=Nio.open_file(fn_act)
            f_idt=Nio.open_file(fn_idt)
            f_pwr=Nio.open_file(fn_pwr)
            f_rdt=Nio.open_file(fn_rdt)
            f_tpt=Nio.open_file(fn_tpt)

            act=f_act.variables['z'][:].reshape((200, 320),)[::-1]
            act=np.where(act>0.0,act*1,0.0)
            idt=f_idt.variables['z'][:].reshape((200, 320),)[::-1]
            idt=np.where(idt>0.0,idt*1,0.0)
            pwr=f_pwr.variables['z'][:].reshape((200, 320),)[::-1]
            pwr=np.where(pwr>0.0,pwr*1,0.0)
            rdt=f_rdt.variables['z'][:].reshape((200, 320),)[::-1]
            rdt=np.where(rdt>0.0,rdt*1,0.0)
            tpt=f_tpt.variables['z'][:].reshape((200, 320),)[::-1]
            tpt=np.where(tpt>0.0,tpt*1,0.0)

            lon=np.arange(70.125,150,0.25,dtype=np.float32) 
            lat=np.arange(10.125,60,0.25,dtype=np.float32)
            lon,lat=np.meshgrid(lon,lat)

            f=Nio.open_file(ent_dir.get()+'/merged/'+j+'.nc','c')
            f.create_dimension('lon',320)
            f.create_dimension('lat',200)

            for var,val in zip(['act','idt','pwr','rdt','tpt','lon','lat'],[act,idt,pwr,rdt,tpt,lon,lat]):
                f.create_variable(var,'f',('lat','lon',))
                f.variables[var][:] = val

            f.close()

b_btn = tk.Button(root, text='浏览', command=bws_meic, width=15) 
b_btn.grid(row=1,column=2)

r_btn = tk.Button(root, text='运行', command=merge_meic_dept, width=15)
r_btn.grid(row=1,column=3)


lbl=tk.Label(root, text='2. 向WRF-Chem模式网格插值分配')
lbl.grid(row=2,column=0,sticky=tk.W)

lbl=tk.Label(root, text='wrfinput文件路径:')
lbl.grid(row=3,column=0,sticky=tk.E)

ent_inp = tk.Entry(root, width=65)
ent_inp.grid(row=3,column=1)

def bws_wrfipt(): 
    wrfiptname = filedialog.askopenfilename()
    ent_inp.delete(0,tk.END)
    ent_inp.insert(0, wrfiptname)
    
b_btn = tk.Button(root, text='浏览', command=bws_wrfipt, width=15)
b_btn.grid(row=3,column=2)#padx=10,pady=10

agr_z_d=[1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
ind_z_d=[0.602,0.346,0.052,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
pow_z_d=[0.034,0.140,0.349,0.227,0.167,0.059,0.024,0.000,0.000,0.000,0.000]
res_z_d=[0.900,0.100,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
tra_z_d=[0.950,0.050,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]

sec_z_d=[agr_z_d,ind_z_d,pow_z_d,res_z_d,tra_z_d,]

agr_t_d=[1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,
       1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000,  1.000]
ind_t_d=[0.045,  0.068,  0.068,  0.068,  0.068,  0.068,  0.068,  0.068,  0.068,  0.045,  0.039,  0.033,
       0.027,  0.021,  0.021,  0.021,  0.021,  0.021,  0.021,  0.021,  0.021,  0.027,  0.033,  0.039]
pow_t_d=[0.0460, 0.0500, 0.0505, 0.0500, 0.0510, 0.0515, 0.0515, 0.0510, 0.0490, 0.0460, 0.0465, 0.0470,
       0.0450, 0.0420, 0.0395, 0.0300, 0.0350, 0.0295, 0.0240, 0.0250, 0.0305, 0.0335, 0.0355, 0.0405]
res_t_d=[0.051,  0.066,  0.114,  0.105,  0.041,  0.029,  0.023,  0.041,  0.070,  0.097,  0.062,  0.035,
       0.011,  0.015,  0.014,  0.010,  0.014,  0.013,  0.017,  0.009,  0.017,  0.045,  0.049,  0.052]
tra_t_d=[0.0640, 0.0600, 0.0580, 0.0530, 0.0505, 0.0570, 0.0575, 0.0590, 0.0595, 0.0635, 0.0575, 0.0470,
       0.0445, 0.0420, 0.0360, 0.0270, 0.0200, 0.0145, 0.0105, 0.0090, 0.0080, 0.0130, 0.0300, 0.0590]

sec_t_d=[agr_t_d,ind_t_d,pow_t_d,res_t_d,tra_t_d,]

state=tk.StringVar() 
state.set('disable') 

def disable():
    ent_agr_z.config(state=state.get())
    ent_ind_z.config(state=state.get())
    ent_pow_z.config(state=state.get())
    ent_res_z.config(state=state.get())
    ent_tra_z.config(state=state.get())
    ent_agr_t.config(state=state.get())
    ent_ind_t.config(state=state.get())
    ent_pow_t.config(state=state.get())
    ent_res_t.config(state=state.get())
    ent_tra_t.config(state=state.get())

def activate():
    ent_agr_z.config(state=state.get())
    ent_ind_z.config(state=state.get())
    ent_pow_z.config(state=state.get())
    ent_res_z.config(state=state.get())
    ent_tra_z.config(state=state.get())
    ent_agr_t.config(state=state.get())
    ent_ind_t.config(state=state.get())
    ent_pow_t.config(state=state.get())
    ent_res_t.config(state=state.get())
    ent_tra_t.config(state=state.get())

rdb_default = tk.Radiobutton(root, text='使用默认分配因子', variable=state, value='disable', command=disable)
rdb_default.grid(row=4,column=1,sticky=tk.W)
rdb_custom = tk.Radiobutton(root, text='自定义分配因子', variable=state, value='normal', command=activate)
rdb_custom.grid(row=4,column=1,sticky=tk.E)

lbl=tk.Label(root, text='农业垂直排放因子:')
lbl.grid(row=5,column=0,sticky=tk.E)

ent_agr_z=tk.Entry(root, state='disable',width=65)
ent_agr_z.grid(row=5,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=5,column=2)

lbl=tk.Label(root, text='工业垂直排放因子:')
lbl.grid(row=6,column=0,sticky=tk.E)

ent_ind_z=tk.Entry(root, state='disable',width=65)
ent_ind_z.grid(row=6,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=6,column=2)

lbl=tk.Label(root, text='电力垂直排放因子:')
lbl.grid(row=7,column=0,sticky=tk.E)

ent_pow_z=tk.Entry(root, state='disable',width=65)
ent_pow_z.grid(row=7,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=7,column=2)

lbl=tk.Label(root, text='民用垂直排放因子:')
lbl.grid(row=8,column=0,sticky=tk.E)

ent_res_z=tk.Entry(root, state='disable',width=65)
ent_res_z.grid(row=8,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=8,column=2)

lbl=tk.Label(root, text='交通垂直排放因子:')
lbl.grid(row=9,column=0,sticky=tk.E)

ent_tra_z=tk.Entry(root, state='disable',width=65)
ent_tra_z.grid(row=9,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=9,column=2)

lbl=tk.Label(root, text='农业逐小时排放因子:')
lbl.grid(row=10,column=0,sticky=tk.E)

ent_agr_t=tk.Entry(root, state='disable',width=65)
ent_agr_t.grid(row=10,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=10,column=2)

lbl=tk.Label(root, text='工业逐小时排放因子:')
lbl.grid(row=11,column=0,sticky=tk.E)

ent_ind_t=tk.Entry(root, state='disable',width=65)
ent_ind_t.grid(row=11,column=1,)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=11,column=2)

lbl=tk.Label(root, text='电力逐小时排放因子:')
lbl.grid(row=12,column=0,sticky=tk.E)

ent_pow_t=tk.Entry(root, state='disable',width=65)
ent_pow_t.grid(row=12,column=1)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=12,column=2)

lbl=tk.Label(root, text='民用逐小时排放因子:')
lbl.grid(row=13,column=0,sticky=tk.E)

ent_res_t=tk.Entry(root, state='disable',width=65)
ent_res_t.grid(row=13,column=1)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=13,column=2)

lbl=tk.Label(root, text='交通逐小时排放因子:')
lbl.grid(row=14,column=0,sticky=tk.E)

ent_tra_t=tk.Entry(root, state='disable',width=65)
ent_tra_t.grid(row=14,column=1)

lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=14,column=2)

def itp_dis():
    if state.get() == 'normal':
        if fnmatch.fnmatch(ent_agr_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_ind_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_pow_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_res_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_tra_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_agr_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_ind_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_pow_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_res_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_tra_t.get().replace(' ', '').replace('.',''), '*[!0-9]*'):
            tk.messagebox.showerror(title='error',message='input format must be 0.23 0.34 ...')
        elif not len(ent_agr_z.get().strip().split(' '))==len(ent_ind_z.get().strip().split(' '))==len(ent_pow_z.get().strip().split(' '))==len(ent_res_z.get().strip().split(' '))==len(ent_tra_z.get().strip().split(' ')):
            tk.messagebox.showerror(title='error',message='number of z factor must be equal')
        elif not len(ent_agr_t.get().strip().split(' '))==len(ent_ind_t.get().strip().split(' '))==len(ent_pow_t.get().strip().split(' '))==len(ent_res_t.get().strip().split(' '))==len(ent_tra_t.get().strip().split(' '))==24:
            tk.messagebox.showerror(title='error',message='number of t factor must be 24')            
        else: 
            agr_z=[float(i) for i in ent_agr_z.get().strip().split(' ')]
            ind_z=[float(i) for i in ent_ind_z.get().strip().split(' ')]
            pow_z=[float(i) for i in ent_pow_z.get().strip().split(' ')]
            res_z=[float(i) for i in ent_res_z.get().strip().split(' ')]
            tra_z=[float(i) for i in ent_tra_z.get().strip().split(' ')]
            sec_z=[agr_z,ind_z,pow_z,res_z,tra_z,]
            agr_t=[float(i) for i in ent_agr_t.get().strip().split(' ')]
            ind_t=[float(i) for i in ent_ind_t.get().strip().split(' ')]
            pow_t=[float(i) for i in ent_pow_t.get().strip().split(' ')]
            res_t=[float(i) for i in ent_res_t.get().strip().split(' ')]
            tra_t=[float(i) for i in ent_tra_t.get().strip().split(' ')]
            sec_t=[agr_t,ind_t,pow_t,res_t,tra_t,]
            
            f_inp=Nio.open_file(ent_inp.get(),format='nc')
            lon_inp=f_inp.variables['XLONG'][0,:]
            lat_inp=f_inp.variables['XLAT'][0,:]
            time_inp=f_inp.variables['Times'][:][0]
            time_inp=''.join([i.decode('utf-8') for i in time_inp]).split('_')[0]
            f_inp.close()

        #put all the distributed meic species into meic_spec_emis:

            meic_spec_emis=[]
        #inorganic gas: ton/(grid.month) to mole/(km2.h)
            for spec,M in zip(['CO','CO2','NH3','NOx','SO2',],[28,44,17,46,64]):
                f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
                lon=f_post.variables['lon'][:]
                lat=f_post.variables['lat'][:]
                section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24*M) for sec in ['act','idt','pwr','rdt','tpt',]]
                f_post.close()
                sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
                c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
                c=sum(c)
                meic_spec_emis.append(c)
        #organic gas: million_mole/(grid.month) to mole/(km2.h)
            for spec in ['ALD','CSL','ETH','GLY','HC3','HC5','HC8','HCHO','ISO','KET','MACR','MGLY','MVK','NR','NVOL',
            'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL',]:
                f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
            #lon=f_post.variables['lon'][:]
            #lat=f_post.variables['lat'][:]
                section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24) for sec in ['act','idt','pwr','rdt','tpt',]]
                f_post.close()
                sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
                c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
                c=sum(c)
                meic_spec_emis.append(c)
        #aerosol: ton/(grid.month) to ug/(m2.s)
            for spec in ['BC','OC','PM2.5','PMcoarse',]:
                f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
            #lon=f_post.variables['lon'][:]
            #lat=f_post.variables['lat'][:]
                section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24*3600) for sec in ['act','idt','pwr','rdt','tpt',]]
                f_post.close()
                sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
                c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
                c=sum(c)
                meic_spec_emis.append(c)

            #meic emission to RADM2 chemistry scheme:

            wrf_spec_emis=[np.zeros(meic_spec_emis[0][:].shape, dtype='float32')]*31

            wrf_spec_emis[0]=meic_spec_emis[0] #wrf: CO
            wrf_spec_emis[1]=meic_spec_emis[2] #wrf: NH3
            wrf_spec_emis[2]=meic_spec_emis[3]*0.9 #wrf: NO
            wrf_spec_emis[3]=meic_spec_emis[3]*0.1 #wrf: NO2
            wrf_spec_emis[4]=meic_spec_emis[4]*0.9 #wrf: SO2
            wrf_spec_emis[5]=meic_spec_emis[5] #wrf: ALD
            wrf_spec_emis[6]=meic_spec_emis[6] #wrf: CSL
            wrf_spec_emis[7]=meic_spec_emis[7] #wrf: ETH
            wrf_spec_emis[8]=meic_spec_emis[9] #wrf: HC3
            wrf_spec_emis[9]=meic_spec_emis[10] #wrf: HC5
            wrf_spec_emis[10]=meic_spec_emis[11] #wrf: HC8
            wrf_spec_emis[11]=meic_spec_emis[12] #wrf: HCHO
            wrf_spec_emis[12]=meic_spec_emis[13] #wrf: ISO
            wrf_spec_emis[13]=meic_spec_emis[14] #wrf: KET
            wrf_spec_emis[14]=meic_spec_emis[20]*1.1 #wrf: OL2
            wrf_spec_emis[15]=meic_spec_emis[21]*1.1 #wrf: OLI
            wrf_spec_emis[16]=meic_spec_emis[22]*1.1 #wrf: OLT
            wrf_spec_emis[17]=meic_spec_emis[24] #wrf: ORA2
            wrf_spec_emis[18]=meic_spec_emis[25]*1.1 #wrf: TOL
            wrf_spec_emis[19]=meic_spec_emis[26]*1.1 #wrf: XYL
            wrf_spec_emis[20]=meic_spec_emis[27]*0.2 #wrf: ECi
            wrf_spec_emis[21]=meic_spec_emis[27]*0.8 #wrf: ECj
            wrf_spec_emis[22]=meic_spec_emis[28]*0.2 #wrf: ORGi
            wrf_spec_emis[23]=meic_spec_emis[28]*0.8 #wrf: ORGj
            wrf_spec_emis[24]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.2 #wrf: PM25i
            wrf_spec_emis[25]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.8 #wrf: PM25j
            wrf_spec_emis[26]=meic_spec_emis[30]*0.8 #wrf: PM10
            wrf_spec_emis[27]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4i
            wrf_spec_emis[28]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4j
            wrf_spec_emis[29]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3i
            wrf_spec_emis[30]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3j

            #generate wrfchemi_00z_d01 anthropogenic emission data for wrf-chem model run:
            if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]):
                os.remove(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
                f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')

                f_chem.create_dimension('Time',None)
                f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
                f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
                f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
                f_chem.create_dimension('DateStrLen',19)

                f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
                for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
            time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
            time_inp+'_11:00:00',]):
                    f_chem.variables['Times'][i]=list(time) #split the string to char

                for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                    f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                    f_chem.variables[LL][:]=ll

                radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
                radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

                for gas in radm_gas:
                    f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[gas].FieldType = np.int16(104)
                    f_chem.variables[gas].MemoryOrder = 'XYZ'
                    f_chem.variables[gas].description = 'EMISSIONS'
                    f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                    f_chem.variables[gas].stagger = 'Z'
                    #f_chem.variables[gas].ordinates = 'XLONG XLAT'
                for aerosol in radm_aerosol:
                    f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[aerosol].FieldType = np.int16(104)
                    f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                    f_chem.variables[aerosol].description = 'EMISSIONS'
                    f_chem.variables[aerosol].units = 'ug/m3 m/s'
                    f_chem.variables[aerosol].stagger = 'Z'
                    #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

                radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
            'E_SO4J','E_NO3I','E_NO3J',]

                for i,spec in enumerate(radm_spec):
                    f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination

                f_chem.close()
                os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
            else:
                f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
                f_chem.create_dimension('Time',None)
                f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
                f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
                f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
                f_chem.create_dimension('DateStrLen',19)

                f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
                for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
            time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
            time_inp+'_11:00:00',]):
                    f_chem.variables['Times'][i]=list(time) #split the string to char

                for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                    f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                    f_chem.variables[LL][:]=ll

                radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
                radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

                for gas in radm_gas:
                    f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[gas].FieldType = np.int16(104)
                    f_chem.variables[gas].MemoryOrder = 'XYZ'
                    f_chem.variables[gas].description = 'EMISSIONS'
                    f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                    f_chem.variables[gas].stagger = 'Z'
                    #f_chem.variables[gas].ordinates = 'XLONG XLAT'
                for aerosol in radm_aerosol:
                    f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[aerosol].FieldType = np.int16(104)
                    f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                    f_chem.variables[aerosol].description = 'EMISSIONS'
                    f_chem.variables[aerosol].units = 'ug/m3 m/s'
                    f_chem.variables[aerosol].stagger = 'Z'
                    #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

                radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
            'E_SO4J','E_NO3I','E_NO3J',]

                for i,spec in enumerate(radm_spec):
                    f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination

                f_chem.close()
                os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
            
            #generate wrfchemi_12z_d01 anthropogenic emission data for wrf-chem model run:
            if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]):
                os.remove(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
                f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')

                f_chem.create_dimension('Time',None)
                f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
                f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
                f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
                f_chem.create_dimension('DateStrLen',19)

                f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
                for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
            time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
            time_inp+'_23:00:00',]):
                    f_chem.variables['Times'][i]=list(time)

                for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                    f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                    f_chem.variables[LL][:]=ll

                radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
                radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

                for gas in radm_gas:
                    f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[gas].FieldType = np.int16(104)
                    f_chem.variables[gas].MemoryOrder = 'XYZ'
                    f_chem.variables[gas].description = 'EMISSIONS'
                    f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                    f_chem.variables[gas].stagger = 'Z'
                    #f_chem.variables[gas].ordinates = 'XLONG XLAT'
                for aerosol in radm_aerosol:
                    f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[aerosol].FieldType = np.int16(104)
                    f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                    f_chem.variables[aerosol].description = 'EMISSIONS'
                    f_chem.variables[aerosol].units = 'ug/m3 m/s'
                    f_chem.variables[aerosol].stagger = 'Z'
                    #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

                radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
            'E_SO4J','E_NO3I','E_NO3J',]

                for i,spec in enumerate(radm_spec):
                    f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination

                f_chem.close()
                os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
            else:
                f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
                f_chem.create_dimension('Time',None)
                f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
                f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
                f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
                f_chem.create_dimension('DateStrLen',19)

                f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
                for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
            time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
            time_inp+'_23:00:00',]):
                    f_chem.variables['Times'][i]=list(time)

                for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                    f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                    f_chem.variables[LL][:]=ll

                radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
                radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

                for gas in radm_gas:
                    f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[gas].FieldType = np.int16(104)
                    f_chem.variables[gas].MemoryOrder = 'XYZ'
                    f_chem.variables[gas].description = 'EMISSIONS'
                    f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                    f_chem.variables[gas].stagger = 'Z'
                    #f_chem.variables[gas].ordinates = 'XLONG XLAT'
                for aerosol in radm_aerosol:
                    f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                    f_chem.variables[aerosol].FieldType = np.int16(104)
                    f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                    f_chem.variables[aerosol].description = 'EMISSIONS'
                    f_chem.variables[aerosol].units = 'ug/m3 m/s'
                    f_chem.variables[aerosol].stagger = 'Z'
                    #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

                radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
             'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
            'E_SO4J','E_NO3I','E_NO3J',]

                for i,spec in enumerate(radm_spec):
                    f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination

                f_chem.close()
                os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])

    elif state.get() =='disable':
        f_inp=Nio.open_file(ent_inp.get(),format='nc')
        lon_inp=f_inp.variables['XLONG'][0,:]
        lat_inp=f_inp.variables['XLAT'][0,:]
        time_inp=f_inp.variables['Times'][:][0]
        time_inp=''.join([i.decode('utf-8') for i in time_inp]).split('_')[0]
        f_inp.close()
                                     
    #put all the distributed meic species into meic_spec_emis:
        meic_spec_emis=[]
    #inorganic gas: ton/(grid.month) to mole/(km2.h)
        for spec,M in zip(['CO','CO2','NH3','NOx','SO2',],[28,44,17,46,64]):
            f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
            lon=f_post.variables['lon'][:]
            lat=f_post.variables['lat'][:]
            section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24*M) for sec in ['act','idt','pwr','rdt','tpt',]]
            f_post.close()
            sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
            c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
            c=sum(c)
            meic_spec_emis.append(c)
    #organic gas: million_mole/(grid.month) to mole/(km2.h)
        for spec in ['ALD','CSL','ETH','GLY','HC3','HC5','HC8','HCHO','ISO','KET','MACR','MGLY','MVK','NR','NVOL',
        'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL',]:
            f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
        #lon=f_post.variables['lon'][:]
        #lat=f_post.variables['lat'][:]
            section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24) for sec in ['act','idt','pwr','rdt','tpt',]]
            f_post.close()
            sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
            c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
            c=sum(c)
            meic_spec_emis.append(c)
    #aerosol: ton/(grid.month) to ug/(m2.s)
        for spec in ['BC','OC','PM2.5','PMcoarse',]:
            f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
        #lon=f_post.variables['lon'][:]
        #lat=f_post.variables['lat'][:]
            section=[(f_post.variables[sec][:,:]*10e6)/(ll_area(lat,0.25)*30*24*3600) for sec in ['act','idt','pwr','rdt','tpt',]]
            f_post.close()
            sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
            c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
            c=sum(c)
            meic_spec_emis.append(c)

        #meic emission to RADM2 chemistry scheme:

        wrf_spec_emis=[np.zeros(meic_spec_emis[0][:].shape, dtype='float32')]*31

        wrf_spec_emis[0]=meic_spec_emis[0] #wrf: CO
        wrf_spec_emis[1]=meic_spec_emis[2] #wrf: NH3
        wrf_spec_emis[2]=meic_spec_emis[3]*0.9 #wrf: NO
        wrf_spec_emis[3]=meic_spec_emis[3]*0.1 #wrf: NO2
        wrf_spec_emis[4]=meic_spec_emis[4]*0.9 #wrf: SO2
        wrf_spec_emis[5]=meic_spec_emis[5] #wrf: ALD
        wrf_spec_emis[6]=meic_spec_emis[6] #wrf: CSL
        wrf_spec_emis[7]=meic_spec_emis[7] #wrf: ETH
        wrf_spec_emis[8]=meic_spec_emis[9] #wrf: HC3
        wrf_spec_emis[9]=meic_spec_emis[10] #wrf: HC5
        wrf_spec_emis[10]=meic_spec_emis[11] #wrf: HC8
        wrf_spec_emis[11]=meic_spec_emis[12] #wrf: HCHO
        wrf_spec_emis[12]=meic_spec_emis[13] #wrf: ISO
        wrf_spec_emis[13]=meic_spec_emis[14] #wrf: KET
        wrf_spec_emis[14]=meic_spec_emis[20]*1.1 #wrf: OL2
        wrf_spec_emis[15]=meic_spec_emis[21]*1.1 #wrf: OLI
        wrf_spec_emis[16]=meic_spec_emis[22]*1.1 #wrf: OLT
        wrf_spec_emis[17]=meic_spec_emis[24] #wrf: ORA2
        wrf_spec_emis[18]=meic_spec_emis[25]*1.1 #wrf: TOL
        wrf_spec_emis[19]=meic_spec_emis[26]*1.1 #wrf: XYL
        wrf_spec_emis[20]=meic_spec_emis[27]*0.2 #wrf: ECi
        wrf_spec_emis[21]=meic_spec_emis[27]*0.8 #wrf: ECj
        wrf_spec_emis[22]=meic_spec_emis[28]*0.2 #wrf: ORGi
        wrf_spec_emis[23]=meic_spec_emis[28]*0.8 #wrf: ORGj
        wrf_spec_emis[24]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.2 #wrf: PM25i
        wrf_spec_emis[25]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.8 #wrf: PM25j
        wrf_spec_emis[26]=meic_spec_emis[30]*0.8 #wrf: PM10
        wrf_spec_emis[27]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4i
        wrf_spec_emis[28]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4j
        wrf_spec_emis[29]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3i
        wrf_spec_emis[30]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3j

        #generate wrfchemi_00z_d01 anthropogenic emission data for wrf-chem model run:
        if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]):
            os.remove(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
            f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')

            f_chem.create_dimension('Time',None)
            f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
            f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
            f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
            f_chem.create_dimension('DateStrLen',19)

            f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
            for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
        time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
        time_inp+'_11:00:00',]):
                f_chem.variables['Times'][i]=list(time) #split the string to char

            for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                f_chem.variables[LL][:]=ll

            radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
            radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

            for gas in radm_gas:
                f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[gas].FieldType = np.int16(104)
                f_chem.variables[gas].MemoryOrder = 'XYZ'
                f_chem.variables[gas].description = 'EMISSIONS'
                f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                f_chem.variables[gas].stagger = 'Z'
                #f_chem.variables[gas].ordinates = 'XLONG XLAT'
            for aerosol in radm_aerosol:
                f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[aerosol].FieldType = np.int16(104)
                f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                f_chem.variables[aerosol].description = 'EMISSIONS'
                f_chem.variables[aerosol].units = 'ug/m3 m/s'
                f_chem.variables[aerosol].stagger = 'Z'
                #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

            radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
        'E_SO4J','E_NO3I','E_NO3J',]

            for i,spec in enumerate(radm_spec):
                f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination

            f_chem.close()
            os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
        else:
            f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
            f_chem.create_dimension('Time',None)
            f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
            f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
            f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
            f_chem.create_dimension('DateStrLen',19)

            f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
            for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
        time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
        time_inp+'_11:00:00',]):
                f_chem.variables['Times'][i]=list(time) #split the string to char

            for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                f_chem.variables[LL][:]=ll

            radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
            radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

            for gas in radm_gas:
                f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[gas].FieldType = np.int16(104)
                f_chem.variables[gas].MemoryOrder = 'XYZ'
                f_chem.variables[gas].description = 'EMISSIONS'
                f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                f_chem.variables[gas].stagger = 'Z'
                #f_chem.variables[gas].ordinates = 'XLONG XLAT'
            for aerosol in radm_aerosol:
                f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[aerosol].FieldType = np.int16(104)
                f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                f_chem.variables[aerosol].description = 'EMISSIONS'
                f_chem.variables[aerosol].units = 'ug/m3 m/s'
                f_chem.variables[aerosol].stagger = 'Z'
                #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

            radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
        'E_SO4J','E_NO3I','E_NO3J',]

            for i,spec in enumerate(radm_spec):
                f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination

            f_chem.close()
            os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])

        #generate wrfchemi_12z_d01 anthropogenic emission data for wrf-chem model run:
        if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]):
            os.remove(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
            f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
            f_chem.create_dimension('Time',None)
            f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
            f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
            f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
            f_chem.create_dimension('DateStrLen',19)

            f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
            for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
        time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
        time_inp+'_23:00:00',]):
                f_chem.variables['Times'][i]=list(time)

            for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                f_chem.variables[LL][:]=ll

            radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
            radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

            for gas in radm_gas:
                f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[gas].FieldType = np.int16(104)
                f_chem.variables[gas].MemoryOrder = 'XYZ'
                f_chem.variables[gas].description = 'EMISSIONS'
                f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                f_chem.variables[gas].stagger = 'Z'
                #f_chem.variables[gas].ordinates = 'XLONG XLAT'
            for aerosol in radm_aerosol:
                f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[aerosol].FieldType = np.int16(104)
                f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                f_chem.variables[aerosol].description = 'EMISSIONS'
                f_chem.variables[aerosol].units = 'ug/m3 m/s'
                f_chem.variables[aerosol].stagger = 'Z'
                #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

            radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
        'E_SO4J','E_NO3I','E_NO3J',]

            for i,spec in enumerate(radm_spec):
                f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination

            f_chem.close()
            os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
        else:
            f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')

            f_chem.create_dimension('Time',None)
            f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
            f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
            f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
            f_chem.create_dimension('DateStrLen',19)

            f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
            for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
        time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
        time_inp+'_23:00:00',]):
                f_chem.variables['Times'][i]=list(time)

            for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
                f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
                f_chem.variables[LL][:]=ll

            radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
            radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]

            for gas in radm_gas:
                f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[gas].FieldType = np.int16(104)
                f_chem.variables[gas].MemoryOrder = 'XYZ'
                f_chem.variables[gas].description = 'EMISSIONS'
                f_chem.variables[gas].units = 'mol km^-2 hr^-1'
                f_chem.variables[gas].stagger = 'Z'
                #f_chem.variables[gas].ordinates = 'XLONG XLAT'
            for aerosol in radm_aerosol:
                f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
                f_chem.variables[aerosol].FieldType = np.int16(104)
                f_chem.variables[aerosol].MemoryOrder = 'XYZ'
                f_chem.variables[aerosol].description = 'EMISSIONS'
                f_chem.variables[aerosol].units = 'ug/m3 m/s'
                f_chem.variables[aerosol].stagger = 'Z'
                #f_chem.variables[aerosol].ordinates = 'XLONG XLAT'

            radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
         'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
        'E_SO4J','E_NO3I','E_NO3J',]

            for i,spec in enumerate(radm_spec):
                f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination

            f_chem.close()
            os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])

btn = tk.Button(root, text='运行', command=itp_dis, width=15)
btn.grid(row=15, column=3)

tk.mainloop()