Annual sulfur deposition through fog,wet and dry deposition in the Kinki Region of Japan
Hikari Shimadera *,Akira Kondo,Kundan Lal Shrestha,Akikazu Kaga,Yoshio Inoue
Division of Sustainable Energy and Environmental Engineering,Graduate School of Engineering,Osaka University,2-1Yamadaoka,Suita,Osaka 565-0871,Japan
a r t i c l e i n f o
Article history:
Received 17March 2011Received in revised form 17August 2011
Accepted 19August 2011Keywords:
Fog deposition Acid deposition
Transboundary air pollution WRF/CMAQ
Fog water deposition model
a b s t r a c t
This study estimated annual sulfur (SO 2tSO 42à
)deposition through fog,wet and dry deposition in the Kinki Region of Japan from April 2004to March 2005.The numerical models used in this study include the Weather Research and Forecasting model (WRF),the Community Multiscale Air Quality model (CMAQ),and a fog deposition model.WRF well predicted mountain fog at Mt.Rokko,the meteorology near the ground surface in the Kinki Region and the upper air meteorology in Japan during the simu-lation period.CMAQ well predicted the long-range atmospheric transport of aerosol SO 42à
from the Asian
Continent to Japan.The mean SO 42à
concentration in fog water was approximately 6times higher than that in precipitation in the Kinki Region.Ratios of fog water deposition to precipitation reached up to more than 10%in some mountainous areas in the Kinki Region.Consequently,the amount of sulfur deposition through fog water deposition was larger than that through dry deposition and comparable to that through wet deposition in some mountainous areas in the Kinki Region.
ó2011Elsevier Ltd.All rights reserved.
1.Introduction
Fog is a cloud on the ground surface and reduces the horizontal visibility to less than 1000m.Fog can be classi ?ed into several types,such as radiation fog and mountain fog,in accordance with the formation mechanism.Radiation fog occurs through radiative cool-ing of humid air masses typically from night to early in the morning on ?at terrains and in valleys.Mountain fog mainly occurs through orographic lifting of humid air masses or horizontal advection of low-level cloud to mountain ranges (Klemm et al.,2005).
Fog can affect forest ecosystems in mountainous areas,in which fog occurs more frequently than in other areas.Fog water deposi-tion through the interception of fog droplets by vegetation can be an important part of the hydrologic budget of forests (Vong et al.,1991;Dawson,1998).Ionic concentrations in fog water are much higher than those in rain water (Igawa et al.,1998;Aikawa et al.,2001).Consequently,fog can contribute signi ?cantly to atmo-spheric deposition in mountainous forest areas (Baumgardner et al.,2003;Klemm and Wrzesinsky,2007).The effects of fog may be more pronounced in Japan than in other regions because approximately two-thirds of the land area are covered with forests,most of which are located in mountainous regions.
The amounts of fog water deposition have been measured using various approaches,such as the through fall measurement (e.g.,Shubzda et al.,1995;Lange et al.,2003)and the eddy covariance method (e.g.,Burkard et al.,2003;Klemm et al.,2005;Eugster et al.,2006).Numerical models also have been utilized to estimate fog water deposition.A one-dimensional model developed by Lovett (1984)has been widely used to predict fog water deposition in various mountain forests (e.g.,Miller et al.,1993;Herckes et al.,2002a;Baumgardner et al.,2003).Katata et al.(2008)also developed a one-dimensional land surface model to better predict fog water deposi-tion,and showed the model agreed better with the measurement data by Klemm et al.(2005)than the model developed by Lovett (1984).The study of fog on a spatial scale requires numerical simulations because few fog monitoring sites exist and fog is highly variable according to regions.Mesoscale meteorological models have been employed for regional forecasting of particular fog events (e.g.,Ballard et al.,1991;Pagowski et al.,2004).Shimadera et al.(2008)applied the 5th generation Mesoscale Model (MM5)(Grell et al.,1994)to fog simulation for months in the Kinki Region of Japan,and showed that the model well reproduced occurrence of fog.Shimadera et al.(2009)utilized MM5and the Community Multiscale Air Quality model (CMAQ)(Byun and Ching,1999)to predict concentrations of acidic compounds in fog water in the Kinki Region in March 2005.Shimadera et al.(2010)developed a two-dimensional fog water deposition model,and showed that the model was applicable to the estimate of spatial distribution of fog deposition with the meteorology and air quality modeling system.
*Corresponding author.Tel./fax:t810668797670.
E-mail addresses:shimadera@ea.see.eng.osaka-u.ac.jp ,simadera@criepi.denken.or.jp (H.
Shimadera).
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Atmospheric Environment
journal homep age:www.elsevi
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1352-2310/$e see front matter ó2011Elsevier Ltd.All rights reserved.doi:10.1016/j.atmosenv.2011.08.055
Atmospheric Environment 45(2011)6299e 6308
The present study utilized the Weather Research and Fore-casting model(WRF)(Skamarock et al.,2008),CMAQ and the fog deposition model in order to estimate annual sulfur(SO2tSO42à) deposition through fog(not included in wet deposition in this study),wet and dry deposition in the Kinki Region of Japan from April2004to March2005.
2.Numerical models
2.1.Meteorology and air quality modeling system
Meteorology and air quality models used in the present study are WRF version ARW3.2.1and CMAQ version4.7.1.WRF is a three-dimensional,nonhydrostatic,terrain-following sigma-pressure coordinate mesoscale model with a multiple-nest capability,several physics options,and a four-dimensional data assimilation capability. CMAQ is a three-dimensional Eulerian air quality modeling system that simulates the transport,transformation,and dry and wet deposition of various air pollutants and their precursors across spatial scales ranging from local to hemispheric.For the present study,CMAQ was modi?ed to output ionic concentrations in fog (cloud water at the?rst layer).The following relationship between the horizontal visibility(x vis)(m)and the liquid water content of fog(LWC)(g mà3)obtained from Stoelinga and Warner(1999)was utilized to judge whether fog occurred or not:
x vis?à1000?
lne0:02T
144:7LWC
:(1)
It was considered that fog occurred when x vis<1000m,i.e.
LWC>0.017g mà3at the?rst layer.
The WRF/CMAQ modeling system was run for the period from
April2004to March2005with an initial spin-up period of March
2004.Fig.1shows modeling domains for CMAQ prediction.
The study region is centered at(122.5 E,32.5 N)on the Lambert
conformal conic projection map of Asia.The horizontal domains
consist of4domains from domain1(D1)covering a wide area of
Asia to domain4(D4)covering most of the Kinki Region of Japan.
The horizontal resolutions and the number of grid cells in the
domains are81,27,9and3km,and128?96,66?66,69?69and
72?72for D1,domain2(D2),domain3(D3)and D4,respectively.
The vertical layers for the WRF and CMAQ predictions consist of
24and16sigma-pressure coordinated layers from the surface to
100hPa,respectively.The middle heights of the?rst,second and
third layers are approximately15,50,and110m,respectively.
The observation data used for the WRF/CMAQ evaluations were
obtained from fog sampling by the Hyogo Prefectural Government
on Mt.Rokko,surface meteorological observation in D4and
upper air meteorological observation in Japan conducted by the
Japan Meteorological Agency(JMA),air pollution monitoring by the
Osaka Prefectural Government,and acid deposition monitoring by
the Ministry of the Environment(MOE)of Japan.The locations of
the observation sites are shown in Fig.1.The fog sampling on Mt.
Rokko was performed by using an active fog collector with a net
consisting of Te?on string.The liquid water content of fog was
estimated from volume of sampled fog water,sampling time,
sampling?ow rate,and collection ef?ciency.The concentrations
of Fig.1.Modeling domains for CMAQ prediction and locations of observation sites.
H.Shimadera et al./Atmospheric Environment45(2011)6299e6308
6300
chemical species of sampled fog water were measured with an ion chromatograph.The details of the method are described in Aikawa et al.(2005).
For the meteorological prediction,WRF was con ?gured with the Kain-Fritsch scheme (Kain,2004)for the cumulus parameterization of D1e D3,the Yonsei University scheme (Hong et al.,2006)for planetary boundary layer parameterization,the WRF single-moment 3-class microphysics scheme (Hong et al.,2004;Hong and Lim,2006),the Noah land surface model (Chen and Dudhia,2001),the rapid radiative transfer model (Mlawer et al.,1997)for the long wave radiation and the scheme of Dudhia (1989)for the shortwave radiation simulations.Input data for WRF include the National Centers for Environmental Prediction ?nal analysis (NCEP FNL)data,and the grid point value derived from the mesoscale model (GPV MSM)data by JMA.Initial and lateral boundary condi-tions for WRF were obtained from the NCEP FNL for D1and the GPV MSM for D2.The WRF simulations from D2to D4were conducted with two-way nesting.Three-dimensional analysis nudging was applied to the west e east and north e south wind components in D1and D2with the nudging coef ?cient set to 3.0à5s à1for the entire simulation period.
For the air quality prediction,CMAQ was con ?gured with the Statewide Air Pollution Research Center version 99(SAPRC99)(Carter,2000)mechanism for the gas-phase chemistry,the 5th generation CMAQ aerosol module (U.S.EPA,2008)for the aerosol processes,and the cloud and aqueous phase chemistry option based on Chang et al.(1987)and Pleim and Chang (1992).The hourly results of WRF were processed using the Meteorology e Chemistry Interface Processor (MCIP)version 3.6.Initial and boundary condi-tions for D1were obtained from the CMAQ default concentration pro ?les.
Emission data applied in this study include anthropogenic,biogenic volatile organic compounds (BVOC),biomass burning and volcanic SO 2emissions.Anthropogenic and BVOC emissions for the Japan region were derived from an emissions inventory for Japan in the year 2000called EAGrid2000-Japan (Kannari et al.,2007).For the other South and East Asia regions,anthropogenic emissions were obtained from an emissions inventory for Asia in the year 2006developed by Zhang et al.(2009).Emissions of NH 3were derived from predicted values for the year 2004and 2005of the regional emission inventory in Asia (Ohara et al.,2007).BVOC and biomass burning emissions were derived from Murano (2006)and Streets et al.(2003),respectively.For the other regions in D1,anthropogenic and biomass burning emissions were obtained from an emissions inventory prepared for Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (https://www.doczj.com/doc/ae2556451.html,/arctas_premission ),and BVOC emissions were derived from Guenther (1995).The volcanic SO 2emissions
were obtained from Andres and Kasgnoc (1998)for volcanoes erupting continuously,and observation data by JMA for Miyakejima located to the south of Tokyo.Emissions from international ship-ping estimated by Corbett and Koehler (2003,2004)were allocated with the ship emissions allocation factor by Wang et al.(2008).
To estimate the contribution of the transboundary air pollution from the other regions to Japan,the CMAQ simulations were con-ducted in two emission cases.The ?rst is a baseline emission case with the total emissions described above (EB),and the other is an emission case where anthropogenic emissions in the land areas except Japan are set to be 0(EJ).Fig.2shows spatial distributions of SO 2emission rates in EB.The total emissions of SO 2in EB and EJ are 57.1and 7.5Tg year à1,respectively.2.2.Fog deposition model
The fog water deposition model used in the present study is based on the two-dimensional model developed by Shimadera et al.(2010).The study showed that the model-predicted fog deposition velocity increased with increasing horizontal wind speed,and considerably varied with forest parameters.Moreover,the model-predicted fog deposition velocity was the largest at the windward edge of forest.It was also showed that the model well reproduced the deposition ?ux of mountain fog observed by Eugster et al.(2006).
Equations to simulate turbulent air ?ow in and above a forest canopy are based on equations used by Yamada (1982).An equation of mean motion is
v U v t ?v v z K M v U
v z
àC D A S U j U j ;(2)
where U is the horizontal wind component (m s à1),K M is the eddy diffusivity of momentum (m 2s à1),C D is the drag coef ?cient for a forest canopy and A S is the one-sided surface area density (m 2m à3).The vertical distribution of A S was obtained from a func-tion proposed by Kondo and Akashi (1976).
An advection e diffusion equation of fog is
v LWC
v t
?àU $V LWC tV eK H $V LWC TàS IM àS S ;(3)
where K H is the eddy diffusivity of heat (m 2s à1),S IM and S S are respectively fog water deposition terms by inertial impaction and gravitational settling of fog droplets on leaves.Inertial impaction is generally the dominant deposition mechanism,but gravitational settling can be important under low wind speed conditions (Lovett,1984).K M and K H were obtained with the closure model of Mellor and Yamada (1982).S IM and S S are given
by
Fig.2.Spatial distribution of annual mean SO 2emission rate in EB.
H.Shimadera et al./Atmospheric Environment 45(2011)6299e 63086301
S IM ?A L k x 3IM j U j LWC ;(4)S s ?A L k z v s LWC ;
(5)
where A L is the one-sided leaf area density (m 2m à3),3IM is the ef ?ciency of inertial impaction,v S is the gravitational settling velocity of fog droplets,k x and k z are respectively the portions of the effective leaf area for deposition of fog droplets by inertial impac-tion and gravitational settling.The ef ?ciencies of inertial impaction 3IM for needle and broad leaves were obtained with an empirical function proposed by Katata et al.(2008).The gravitational settling velocity v S is given by
v s ?
gd 2p er W àr A T
m A
;(6)
where g is the acceleration of gravity (m s à2),d p is the volume-weighted mean diameter of fog droplet (m),r W and r A are respectively the densities of liquid water and air (kg m à3),and m A is the viscosity coef ?cient of air (kg m à1s à1).Droplet size of fog can be expressed as a function of LWC (e.g.,Eugster et al.,2006;Katata et al.,2008).Because of lack of observation data on droplet size of fog in the study region,this study utilized the observation data by Burkard et al.(2003)at the L?geren research site in Switzerland to obtain the following relationship between d p and LWC :
d P ? 11:6LWC 0:305t15:8LWC t4:0
?10à6:
(7)
According to Petroff et al.(2009),k x and k z are expressed by
k x ?
Z
2=p q L ?0Z
2p f L ?0
4q L 4f L sin q L j cos f L j d q L d f L ;
(8)
k z ?
Z
2=p q L ?0
4q L cos q L d q L ;
(9)
4q L ea L T?2p G em L tv L TG em L TG ev L T 1à2a L p m L à1 2a L p v L à1;a L ? 0;2
p
;
(10)
4f L ea L T?
1
2p
;a L ??0;2p ;(11)
where q L and f L are respectively the inclination and azimuth of leaves,4q L and 4f L are the leaf angular densities associated with each angle,G is the Euler Gamma-function,m L and n L are parameters depending on the canopy species,location and time.For
simpli ?cation,it was assumed that all leaf orientations were equi-probable,i.e.,m L and n L were set to be 1.
Fig.3shows the modeling domain for the fog deposition model.The width of the objective region is set to 3km for predictions of fog water deposition in 3-km grid cells in D4.Horizontal and vertical resolutions are 60and 1m,respectively.Forest areas are allocated to the objective region from its edges according to forest fraction.Spatial distribution of forest fractions in D4was obtained from the 100-m land use dataset of the Digital National Land Information in Japan (http://nlftp.mlit.go.jp/ksj/).Forest areas cover 69%of the land areas and 95%of the mountainous areas with elevation !500m in D4.Spatial distributions of leaf area index (LAI)in D4were derived from the global datasets of monthly 1-km LAI with the Moderate resolution imaging spectroradiometer (MODIS)(https://www.doczj.com/doc/ae2556451.html,/modismisr/index.html ).Mean values of LAI in the forest areas in D4are 2.5in the spring (April and May 2004,and March 2005),2.8in the summer (June,July and August 2004),2.2in the fall (September,October and November 2004)and 1.4in the winter (December 2004,January and February 2005).
Spatial
Fig.3.Modeling domain for two-dimensional fog deposition model.
Table 1
Statistical performance for meteorological predictions near the ground surface at the meteorological observatories in D4and at 925hPa surface above the aerological observatories in Japan from April 2004to March 2005.
Surface
925hPa
Temperature
Sample number 139823(8625e 8760)14580(714e 730)Mean Obs.( C)16.4(15.2e 17.7)11.8(2.8e 19.3)Mean WRF ( C)16.2(14.2e 17.8)11.3(1.3e 18.5)MAE ( C) 1.6(1.2e 1.8) 1.2(0.9e 2.9)IA
0.99(0.97e 0.99)
0.99(0.95e 1.00)Humidity Sample number
139970(8637e 8760)14574(710e 730)Mean Obs.(g kg à1)9.0(8.3e 9.9)8.4(4.3e 12.4)Mean WRF (g kg à1)9.1(8.6e 9.9)8.6(4.5e 13.3)MAE (g kg à1)0.9(0.8e 1.0) 1.1(0.7e 1.9)IA
0.98(0.98e 0.99)
0.98(0.75e 0.98)Wind speed Sample number
138868(8467e 8752)14526(714e 730)Mean Obs.(m s à1) 2.8(1.5e 4.2)8.6(7.0e 10.7)Mean WRF (m s à1) 3.9(2.5e 4.9)9.0(6.8e 10.3)RMSE (m s à1) 2.5(1.4e 3.4) 3.2(2.2e 5.0)IA
0.70(0.41e 0.83)
0.90(0.73e 0.94)Wind U-component Sample number 138868(8467e 8752)14526(714e 730)Mean Obs.(m s à1)
0.4(à0.3e 0.9) 1.7(à3.6e 5.3)Mean WRF (m s à1)0.7(à0.3e 1.4) 1.6(à4.8e 6.4)RMSE (m s à1) 2.5(1.6e 3.0) 3.3(2.2e 4.9)IA
0.77(0.53e 0.87)
0.95(0.82e 0.97)Wind V-component Sample number 138868(8467e 8752)14526(714e 730)Mean Obs.(m s à1)
à0.3(à0.8e 0.3)0.1(à1.5e 1.7)Mean WRF (m s à1)à0.2(à1.0e 0.6)à0.2(à3.0e 1.8)RMSE (m s à1) 2.6(1.8e 2.8) 3.4(2.8e 4.4)IA
0.78(0.52e 0.89)0.93(0.79e 0.97)
Precipitation Annual Obs.(mm)
2135(1458e 5316)Annual WRF (mm)1893(1169e 3505)
Parenthetical values show ranges of values at the individual observatories.
H.Shimadera et al./Atmospheric Environment 45(2011)6299e 6308
6302
distribution of tree species in D4was obtained from the 1-km vegetation dataset of the 5th National Survey on the Natural Environment in Japan (http://www.biodic.go.jp/kiso/fnd_f.html ).Needle-leaved and broad-leaved forest areas account for 69and 31%of the total forest area in D4,respectively.Height of the forest canopy was assumed to be 15m.Meteorological input data,including the wind speed at the upper boundary and the liquid water content over the forest canopy,were derived from the WRF predictions at the ?rst and second layers.Although the chemical composition of fog droplets can vary with droplet size (Herckes et al.,2002b;Fahey et al.,2005),CMAQ can predict only the bulk aqueous phase chemistry.In this study,hourly sulfur deposition through fog was estimated though multiplication of the model-predicted fog water deposition by the CMAQ-predicted concen-trations in fog.
3.Results of meteorology and air quality predictions 3.1.Meteorology prediction
The performance for WRF predictions was evaluated using the mean absolute error (MAE),the root mean square error (RMSE)and the index of agreement (IA)(Willmott,1981).The statistical measures are de ?ned as
MAE ?1N X
N i ?1j M i
àO i j ;
(12)
RMSE ?
"
1N X
N i ?1
eM i àO i T2
#1;(13)
Fog frequency
Observation WRF
Liquid water content
L i q u i d w a t e r c o n t e n t (g m -3)
F o g f r e q u e n c y (%)
Observation WRF
20042005
Fig.4.Observed and WRF-predicted monthly fog frequency and mean liquid water content of fog at the Mt.Rokko fog sampling site from April 2004to March 2005.
Observation (μmol L -1)
Observation (μg m -3)
EB Spring Summer Fall Winter EJ Spring Summer Fall Winter
Observation (ppb)Observation (μmol L -1)
C M A Q (μm o l L -1)
C M A Q (μg m -3)
C M A Q (p p b )
C M A Q (μm o l L -1)
a
b
c
d
Fig.5.Scatter plots of the observed versus CMAQ-predicted seasonal mean concentrations of (a)SO 2,(b)aerosol SO 42à,(c)SO 42àin precipitation and (d)SO 42à
in fog for the period from April 2004to March 2005at the individual observation sites.2:1,1:2and 1:1reference lines are provided.
H.Shimadera et al./Atmospheric Environment 45(2011)6299e 63086303
IA ?1àP N
i ?1eM i
àO i T2
P N
i ?1ej M i àO j tj O i àO jT
2
;(14)
where M and O are mean model-predicted and observed values,M i and O i are model-predicted and observed values,and N is the number of samples,respectively.Emery et al.(2001)set bench-marks with the statistical measures for the meteorology model performance:MAE 2 C and IA !0.8for temperature,MAE 2g kg à1and IA !0.6for humidity,RMSE 2m s à1and IA !0.6for wind speed.
Table 2
CMAQ-predicted seasonal and annual mean concentrations of sulfur compounds in the land areas in EB-D4from April 2004to March 2005.
Spring
Summer Fall Winter Annual SO 2(ppb)
1.7(22)
1.1(0) 1.1(8)0.8(18) 1.2(12)Aerosol SO 42à
(m g m à3)
4.5(61) 4.5(32) 2.8(47)0.8(46) 3.1(47)SO 42àin precipitation (m mol L à1)
21(38)20(16)13(21)13(36)16(28)SO 42
à
in fog (m mol L à1)
125(43)
127(31)
84(30)
30(29)
94(35)
Parenthetical values are corresponding contribution rates of transboundary air pollution (%).
Fig.6.Spatial distributions of CMAQ-predicted annual mean concentrations of (a)SO 2,(b)aerosol SO 42à,(c)SO 42àin precipitation and (d)SO 42à
in fog from April 2004to March 2005.
The results of SO 42à
concentrations in fog are not shown in grid cells with fog frequencies <2%.
H.Shimadera et al./Atmospheric Environment 45(2011)6299e 6308
6304
Table 1summarizes WRF performance for meteorological predictions near the ground surface at the meteorological obser-vatories in D4and at 925hPa surface above the aerological obser-vatories in Japan from April 2004to March 2005.For temperature and humidity near the ground surface,the WRF predictions met the benchmarks for MAE and IA at all the meteorological observatories.The results indicate that WRF well captured variations in temper-ature and humidity associated with changes of seasons and synoptic scale factors such as passages of low pressure systems.For wind near the ground surface,while the WRF predictions met the benchmark for IA,the model performance was inferior to that for temperature and humidity.This may be attributed to the dif ?culty in predictions of weak and variable winds near the ground surface.Results of meteorology predictions in some other studies also indicated such tendencies (e.g.,Gilliam et al.,2006;Lee et al.,2007).For wind at the 925hPa surface,however,the WRF predictions well
agreed with the observations.For precipitation,WRF tended to underestimate the amounts at the meteorological observatories,but approximately captured the regional variations.Overall,WRF successfully simulated the meteorology ?elds from April 2004to March 2005.
Fig.4shows observed and WRF-predicted monthly frequency of fog occurrence and mean liquid water content during fog events at the Mt.Rokko fog sampling site from April 2004to March 2005.The WRF predictions approximately captured monthly variations of fog frequency and liquid water content.Consequently,the predicted annual values well agreed with the observed ones,with the observed and predicted annual fog frequencies being 19%and 17%and annual mean liquid water contents being 0.15g m à3and 0.21g m à3,respectively.3.2.Air quality prediction
Fig.5shows scatter plots of the observed versus CMAQ-predicted seasonal mean concentrations of sulfur compounds from April 2004to March 2005.The CMAQ-predicted concentra-tions in EB were generally higher and agreed better with the observations than those in EJ,indicating that the model well simulated the transboundary air pollution.While CMAQ tended to underpredict the concentrations in the winter,most of the predicted seasonal values in EB were approximately within a factor of 2of the observations.The CMAQ performance for predictions of
SO 42àconcentrations in fog at Mt.Rokko was comparable to that in precipitation in Japan.
Table 2summarizes CMAQ-predicted seasonal and annual mean concentrations of sulfur compounds in the land areas in EB-D4and
Table 3
Model-predicted seasonal and annual fog frequency,liquid water content of fog,fog water deposition and precipitation in the land areas in D4from April 2004to March 2005.
Elevation
Spring Summer Fall Winter Annual Fog frequency (%)500m < 2.2 1.80.7 3.5 2.1!500m 13.512.410.120.914.2Liquid water
content (g m à3)500m <0.140.130.090.130.15!500m 0.180.210.170.110.16Fog water
deposition (mm)500m <33118!500m 35502916129Precipitation (mm)
500m <5223867234822113!500m
784
833
1085
832
3533
Fig.7.Spatial distributions of model-predicted (a)fog frequency,(b)mean liquid water content of fog,(c)annual fog water deposition and (d)annual precipitation in D4from April 2004to March 2005.The results of liquid water content are not shown in grid cells with fog frequencies <2%.
H.Shimadera et al./Atmospheric Environment 45(2011)6299e 6308
6305
corresponding contribution rates of the transboundary air pollution from April2004to March2005.Fig.6shows spatial distributions of the CMAQ-predicted annual mean concentrations of sulfur compounds for EB,EB-D4and EJ-D4.The spatial distribution of mean SO2concentration in EB-D4was similar to that in EJ-D4,particularly in and around the high SO2emission areas(Fig.2).In the CMAQ prediction,transport of an air mass from East China to the Kinki Region of Japan generally took2days or more,which was equivalent to or longer than the atmospheric lifetime of SO2suggested in other studies(e.g.,Restad et al.,1998;Tsai et al.,2010).These?ndings indicate the large contribution of local emissions and small contri-bution of the transboundary air pollution to SO2concentration in the Kinki https://www.doczj.com/doc/ae2556451.html,rge amounts of aerosol SO42à,which were primarily produced through the oxidation of SO2,were transported from the Asian Continent to Japan.Consequently,the transboundary air pollution contributed signi?cantly to not only aerosol SO42àconcentration but also SO42àconcentration in precipitation and fog, particularly in the spring,in D4.The mean SO42àconcentration in fog was approximately6times higher than that in precipitation in the land areas in EB-D4.Aikawa et al.(2001)reported that the observed concentration of chemical species in fog was approximately7times higher than that in precipitation at the Mt.Rokko fog sampling site. The?nding indicates that the result of this study is reasonable.
4.Fog water deposition in the Kinki Region
Table3summarizes model-predicted seasonal and annual fog frequency,liquid water content of fog,fog water deposition and precipitation in the land areas in D4from April2004to March2005. In order to show the importance of fog in high elevation areas, the land areas in D4were classi?ed into two zones:the land areas with elevation<500m and the mountainous areas with elevation !500m,which respectively accounted for57and15%of D4.Fig.7 shows spatial distributions of the model-predicted annual frequency of fog occurrence,liquid water content of fog,fog water deposition and precipitation in D4.Fog frequency,fog water depo-sition and precipitation generally increased with increasing eleva-tion,with mean values of annual fog frequency,fog water deposition and precipitation in the mountainous areas with elevation!500m being6.9,17and1.7times larger than those in the land areas with elevation<500m.The results indicate that effects of fog are much more variable from region to region than those of precipitation.
The values of fog frequency in wide areas of high mountains were comparable to or higher than those in Mt.Rokko,which is charac-terized by its high frequency of fog(Aikawa et al.,2001).In Kii Mts., Chugoku Mts.and Suzuka Mts.(Fig.1),annual fog frequencies at individual3-km grid cells reached up to52,49and43%,respectively.
Among the four seasons,the amounts of fog deposition was the largest in the summer due to large liquid water content and thick vegetation cover,and the smallest in the winter due to small liquid water content and thin vegetation cover.Seasonal mean fog water deposition velocities in the mountainous areas with elevation !500m were14,15,14and8.4cm sà1in the spring,summer,fall and winter.Impaction and gravitational settling of fog droplet respectively accounted for94and6%of the total fog water deposi-tion in D4,indicating that mountain fog events with relatively high wind speed dominantly contributed to fog water deposition.Annual ratio of fog water deposition to precipitation was only1.1%in the entire D4,but was3.7%in the mountainous areas with elevation !500m.Moreover,in Mt.Rokko,Kii Mts.,Chugoku Mts.and Suzuka Mts,annual ratios of fog water deposition to precipitation at indi-vidual3-km grid cells reached up to6.0,16,10and11%,respectively.
In other studies conducted in the temperate zone,observed turbulent fog water deposition velocities generally ranged from0to 10cm sà1at Speulderbos in the Netherlands(Vermeulen et al.,1997). Observed fog water deposition velocities generally ranged from0to 30cm sà1at the Waldstein research site in Germany(Klemm and Wrzesinsky,2007).Model-predicted seasonal mean fog water deposition velocities ranged from18to27cm sà1at Whiteface Mountain in the United States(Miller et al.,1993).Ratios of fog water deposition to precipitation in mountainous forests were3.4%at the L?geren research site in Switzerland(Burkard et al.,2003),4.4%in Vosges Mts.in France(Herckes et al.,2002a),9.4%at the Waldstein research site in Germany(Klemm and Wrzesinsky,2007),13e25%in the Southern Appalachian Region of the United States(Shubzda et al., 1995),and22%at Whiteface Mountain in the United States(Miller et al.,1993),respectively.Although a direct comparison may not be appropriate given the differences in regions and methods,the results in this study are in the range of reported values in other studies. 5.Sulfur deposition in the Kinki Region
Table4summarizes the model-predicted seasonal and annual sulfur deposition through dry,wet and fog deposition in the
land Fig.8.Spatial distributions of model-predicted annual sulfur deposition through(a)dry,(b)wet and(c)fog deposition in EB-D4from April2004to March2005.
Table4
Model-predicted seasonal and annual sulfur deposition through dry,wet and fog
deposition in the land areas in EB-D4from April2004to March2005.
Elevation Spring Summer Fall Winter Annual
Dry(mmol m)500m< 5.5(21) 4.1(1) 3.8(10) 3.9(23)17.3(14)
!500m 6.1(28) 3.6(0) 4.4(13) 3.3(29)17.3(18)
Wet(mmol mà2)500m<10.7(37)7.7(16)9.2(20) 6.3(35)33.9(27)
!500m16.8(42)15.9(16)14.0(20)11.0(39)57.6(29)
Fog(mmol mà2)500m<0.5(42)0.5(34)0.1(28)0.0(26) 1.1(37)
!500m 4.2(41) 4.7(26) 2.3(29)0.4(38)11.6(32)
Total(mmol mà2)500m<16.6(32)12.3(12)13.1(17)10.3(31)52.3(23)
!500m27.0(39)24.2(15)20.6(19)14.8(36)86.5(27)
Parenthetical values are corresponding contribution rates of transboundary air
pollution(%).
H.Shimadera et al./Atmospheric Environment45(2011)6299e6308
6306
areas in EB-D4and corresponding contribution rates of the transboundary air pollution from April 2004to March 2005.Fig.8and Fig.9show spatial distributions of the model-predicted annual sulfur deposition through dry,wet and fog deposition in EB-D4and those of corresponding contribution rate of the trans-boundary air pollution,respectively.The amount of dry deposition of SO 2accounted for 75%of the total dry sulfur deposition in the land areas in EB-D4.Therefore,the amount of sulfur deposition through dry deposition was large in the high SO 2emission areas (Fig.2),and corresponding contribution of the transboundary air pollution was relatively small.
The contribution rates of the transboundary air pollution varied considerably from region to region,and were large in northern areas in D4.The transboundary air pollution contributed 6e 57%of the total sulfur deposition at individual 3-km grid cells,and 24%in the entire D4.Ichikawa et al.(1998)and Lin et al.(2008)estimated that the transboundary air pollution contributed 42and 31%of sulfur deposition in Japan in 1990and 2001,respectively.The contribution rate in D4in this study was smaller than those in Japan in these studies.The difference can be attributed to various reasons,such as differences in study years and regions,meteorology ?elds,emission data and model structures.
The amount of sulfur deposition through wet deposition was large in the mountainous areas since the amount of precipitation was also large in the mountainous areas (Fig.7d).The sulfur deposition through wet deposition contributed the most to the total sulfur deposition among the three deposition processes,accounting for 64%the total sulfur deposition in the entire area in EB-D4.
The sulfur deposition through fog water deposition accounted for only 4.3%the total sulfur deposition in the entire area in EB-D4.In some mountainous areas,however,the amount of sulfur depo-sition through fog water deposition was larger than that through dry deposition and comparable to that through wet deposition.In Mt.Rokko,Kii Mts.,Chugoku Mts.and Suzuka Mts,ratios of the sulfur deposition through fog to the total sulfur deposition at individual 3-km grid cells reached up to 24,36,31and 31%,respectively.The results indicate that fog water deposition is an important atmospheric deposition process in mountainous forest areas in the Kinki Region of Japan.6.Conclusions
The present study estimated annual sulfur deposition through fog,wet and dry deposition in the Kinki Region of Japan for the period from April 2004to March 2005.The meteorology and air quality predictions were performed with the WRF/CMAQ modeling system in the 4nested modeling domains from D1covering a wide area of Asia to D4covering most of the Kinki Region.WRF
successfully simulated the meteorology near the ground surface in the Kinki Region and the upper air meteorology in Japan,and approximately captured mountain fog at the Mt.Rokko fog sampling site.CMAQ well predicted the long-range atmospheric
transport of aerosol SO 42à
from the Asian Continent to Japan,which
strongly affected SO 42à
concentrations in precipitation and fog in
the Kinki Region.Mean SO 42à
concentration in fog was approxi-mately 6times higher than that in precipitation in the Kinki Region.
The fog water deposition and corresponding sulfur deposition were estimated with the two-dimensional fog deposition model and the results of the WRF/CMAQ modeling system in the Kinki Region.Annual ratio of fog water deposition to precipitation was only 1.1%in the entire D4,but reached up to more than 10%in some mountainous areas with high fog frequencies,such as Kii Mts.,Chugoku Mts.and Suzuka Mts.
The amount of sulfur deposition through dry deposition was large in the high SO 2emission areas,and that through wet deposition was large in the mountainous areas due to the large amount of precipitation.The sulfur deposition through wet depo-sition contributed the most to the total sulfur deposition among the three deposition processes in the Kinki Region.The sulfur deposition through fog accounted for only 4.3%the total sulfur deposition in the entire D4.However,annual ratio of the sulfur deposition through fog to the total sulfur deposition reached up to more than 30%in some mountainous areas.The results indicate that fog water deposition is an important atmospheric deposition process in mountainous forest areas in the Kinki Region of Japan.Acknowledgments
We are grateful to the Hyogo Prefectural Governments and MOE of Japan for providing the observation data associated with the WRF/CMAQ evaluations and to Dr.Werner Eugster for providing the observation data on fog water deposition by Burkard et al.(2003)and Eugster et al.(2006).
This work was supported by Grant-in-Aid for JSPS Fellows.References
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页脚.
. . 教学过程 一、课堂导入 本堂知识是初中最常见的介词by的一个整理与总结，让学生对这个词的用法有一个系统的认识。页脚.
. . 二、复习预习 复习上一单元的知识点之后，以达到复习的效果。然后给学生一些相关的单选或其他类型题目，再老师没有讲解的情况下，让学生独立思考，给出答案与解释，促进学生发现问题，同时老师也能发现学生的盲点，并能有针对性地进行后面的讲课。 页脚.
. . 三、知识讲解 知识点1： by + v.-ing结构是一个重点，该结构意思是“通过……，以……的方式”，后面常接v.-ing形式，表示“通过某种方式得到某种结果”，即表示行为的方式或手段。 I practice speaking English by joining an English-language club. 我通过加入一个英语语言俱乐部来练习讲英语。 Mr Li makes a living by driving taxis.先生靠开出租车为生。 页脚.
. . 页脚. 介词by + v.-ing 结构常用来回答How do you...?或How can I...?之类的问题。 —How do you learn English? 你怎样学习英语呢？ —I learn English by reading aloud. 我通过大声朗读来学英语。 —How can I turn on the computer? 我怎样才能打开电脑呢？ —By pressing this button. 按这个按钮。 知识点2：by 是个常用介词，其他用法还有： 1【考查点】表示位置，意思是“在……旁边”，“靠近……”，有时可与beside互换。 The girls are playing by (beside) the lake. 女孩们正在湖边玩。 此时要注意它与介词near有所不同，即by 表示的距离更“近”。比较： He lives by the sea. 他住在海滨。 He lives near the sea. 他住在离海不远处。
Through 的用法 （一）作介词 (1) 从…中通过;贯穿,穿过(强调丛物体内部或一定范围内),透过 We started to push our way through crowds of children、 The River Thames flows through London、On our way we had to pass through Hudson Street、 The sunlight was coming in through the window、The sound echoed through the hall、(2)通过,凭借(方法手段),经由 He became rich through hard work and ability、 We learn to speak through speaking、He got the job through his uncle、 (3)由于,因为…的关系 He failed through lack of experience、 (4)自始至终;从头到尾/底 The children are too young to sit through a long concert、 We worked through the night、 (5)经受;经历 That was a small matter after the Cultural Revolution they had been through、辨析:through ,across ,over (复习) The Great Wall winds its way from west to east, _______ deserts, _______ mountains, ______ valleys, till at last it reaches the sea、 Go _______ the bridge _______ the river, and you will find the shop、 I have made friends right ________ the world、 The crowd of people walked past the City Hall to the Center Square、 Through & by 表示“通过”时,through 后常加名词表示手段媒介,而by 后常加工具具 体名词以及-ing 形式。 He got that job through his uncle、 You can succeed by working hard、I sent the letter by airmail、 (二) 作副词 (1) 通过,过去(可与许多动词连用) The flood is too deep to drive through、 (2) 彻底地;接通电话 Don’t tell me how it ends---I haven’t read it through、 You’re through to London, sir! (三) 常见搭配 Get through ①通过;度过 He got through his examinations、 ②做完;吃完;饮完 We managed to get through the work in four hours、
By 与through 的区别 1．by （1）表示方法，手段。即“用...，通过...以…方式 ”相当于by means of 如： All work had to be done by hand 所有的工作都是手工进行的。 He makes a living by teaching 他以教书为生。 It happened through no fault of mine.这件事的发生, 并非由于我的任何过错。 He saluted her by raising his hat.他举起帽子向她致意。 She earned money by writing.她靠写作挣钱。 根据；按照to play by the rules按规则比赛 相差His horse won by a nose.他的马以一鼻之差取胜。 （2）表示传达、传递的方式或煤介。如： How did you send the letter, by airmail or by ordinary mail？ 你是怎么发送的这信，是通过航天邮件还是普通邮件？ （3）表示用交通工具、通讯工具后接名词单数，不加冠词。如： He came by train, but his wife came by bus. 他是乘火车来的，可是他老婆是坐公共汽车来的。 注意下面两句的区别： Did you come by train =Did you come in his car / on my bike？ “by +抽象名词”构成的词组有： by accident / by chance / by diligence / by effort / by force / by heart / by luck / by mistake / by hard work. （4）指数量增加或减少到的程度，相差。 We lost the match by one goal 我们仅以一球之差输了比赛。 （5）根据，按照 pay sb by the hour /day/week Sell sth by the pound /meter/ dozen sell sth by weight/length As a rule，domestic servants doing odd jobs are paid by the hour 通常，家政服务是按照小时计酬的。 They marched by night.他们夜里进军。 2. through （1）表示“以；通过；经由”。如：
一、介词的分类介词可分为三类： 1.简单介词：由一个单词构成的介词。如：about, after, but, for, from, below等。 2.复合介词：由两个或两个以上单词合成的介词，如：into, throughout，onto，within，without, nearby 等。 3.短语介词：一个或两个简单介词和一个或几个其他词类组合成一个短语，相当于一个介词，叫做短语介词，这类介词的末尾总是一个简单介词。如：according to, because of, out of, in front of, instead of, along with等。 二、介词短语的用法：介词短语作为一个成分在句中可用作定语、状语、表语、宾语补足语等。 1.作定语：介词短语作定语时，一般放在被修饰词的后面，作后置定语。 The book on the desk is very interesting. 书桌上的那本书很有趣。 China is a great country with a long history. 中国是一个具有悠久历史的国家。 2.作状语：介词短语作状语时，一般放在动词后面或句末、句首。用来表示时间、地点、目的、方式和原因等。 The basketball match will start at nine. 篮球比赛将在9点开始。（表示时间）He likes to swim in the river. 他喜欢去河里游泳。（表示地点）I went there to get my book back. 我去那里取回我的书。（表示目的）I came here by bike. 我骑自行车来到这里。（表示方式）She was trembling with fear. 她吓得直发抖。（表示原因）3.作表语：介词短语作表语时，一般放在be动词和连系动词之后。 I'm on duty today. 今天我值日。My English teacher is from Australia. 我的英语老师来自澳大利亚。(4)作宾语补足语：介词短语作宾语补足语时，一般放在宾语之后。 Help yourself to some fish. 请吃鱼。I found everything ill good condition. 我发现一切状况良好。 We all think of him as an honest man. 我们都认为他是一个诚实的人。 三、常用介词的意义及用法 （一）表示时间的介词：英语中表示时间的介词很多，主要有以下这些：at, on，in, after，for，since, by，till，until等。 1. at的用法时间介词at表示时刻或时间的某一点。如：at 4: 30 (noon, dawn, midnight... )在4: 30（中午、黎明、午夜） 2.on的用法：时间介词on表示日期及某天的上午、下午、晚上等。如：on Sunday (Oct. 1... )在星期日（10月1日……）on Sunday afternoon星期日下午，另也可说：in the afternoon on Sunday 特别提示：关于“在周末”的几种表示法： at (on) the weekend （在周末——特指）at (on) weekends （在周末——泛指）over the weekend （在整个周末）during the weekend （在周末期间）。在圣诞节，应说"at Christmas", 而不说"on Christmas"。 3.in的用法 (1)时间介词in表示“时段，时期”，在多数情况下可以和during互换，前者强调对比，后者强调持续。如： in (during) 1987在1987年in (during) the 21st century在21世纪 但是如果表示“在某项活动的期间”，则只能用during。如：during the trip...在旅行期间…… (2)时间介词in表示以说话时间为基点的“若干时间以后”，常用于谓语是将来时的时间状语。如要表示“若干时间内”，则常用within。试比较：The meeting will end in 30 minutes. 会议30分钟以后结束。Can you finish it within 30 minutes? 你能在30分钟之内完成这件事吗？ 但是在过去时态中，in和within的意思一样，并都可用于表示“在若干时间以内”，这时不要误用during。如： The job was done during a week. (x) The job was done in a week. (√) 4.after的用法 时间介词after表示“在（某具体时间）以后”，注意不要和in混淆。如：after supper (5 o'clock, the war,
AT The ball is at the edge of the table. WITH The black brick is with the ball. FROM The ball is going from the hand. AGAINST The black brick is against the white b rick. TO The ball is going to the hand. ACROSS The black rod is across the white rod. AFTER3is after2. AMONG The ball is among the bricks. BEFORE1is before2. ABOUT The bricks are about the ball. THROUGH The rod is through the board. DOWN The ball is down. BETWEEN The ball is between the bricks. UP The ball is up. UNDER The ball is under the arch. ON The ball is on the table. OVER The arch is over the ball. OFF The ball is off the table. BY The ball is by the arch. IN The ball is in the bucket. OUT The ball is out of the basket.
介词（preposition） 又称前置词，是一种虚词。介词不能单独做句子成分。介词后须接宾语，介词与其宾语构成介词短语。 一、介词从其构成来看可以分为： 1、简单介词（Simple prepositions）如：at ,by, for, in, from, since, through等； 2、复合介词（Compound prepositions）如：onto, out of, without, towards等； 3、短语介词（phrasal prepositions）如；because of, instead of, on account of, in spite of, in front of等； 4、二重介词（double prepositions）如：from behind, from under, till after等； 5、分词介词（participial prepositions），又可称动词介词（verbal prepositions）如：during, concerning, excepting, considering, past等。 二、常见介词的基本用法 1、 about 关于 Do you know something about Tom？ What about this coat？（……怎么样） 2、 after 在……之后 I’m going to see you after supper. Tom looked after his sick mother yesterday.（照看） 3、 across 横过 Can you swim across the river. 4、 against 反对 Are you for or against me? Nothing could make me turn against my country.（背叛） 5、 along 沿着 We walked along the river bank. 6、 before 在……之前 I hope to get there before seven o’clock. It looks as though it will snow before long.（不久） 7、behind 在……后面 The sun is hidden behind the clouds. 8、by 到……时 We had learned ten English songs by the end of last term. 9、during 在……期间 Where are you going during the holiday. 10、except 除了 Everyone except you answered the question correctly. 11、for 为了 The students are studying hard for the people. 12、from 从 I come from Shanghai. 13、in 在……里 on 在……上面 under在……下面 There are two balls in/on/under the desk. 14、near 在……附近 We live near the park. 15、of ……的 Do you know the name of the winner. 16、over 在……正上方 There is a bridge over the river. Tom goes over his English every day.（复习） 17、round/around 围绕 The students stand around the teacher. 18、to 朝……方向 Can you tell me the way to the cinema. 19、towards朝着 The car is traveling towards Beijing.
七个经过” pass, cross, through, by…… 怎么过（有何区别） 这7个表”经过“的词中，除pass, cross是动词外，其它都是介词（副词）。首先，我们从词性上去区别它们。 充当谓语动词时用pass, cross, 不充当谓语动词时用past, across, through, over, by从旁边“经过”“绕过” “路过”用pass （介词形式为past）, 从表面“越过”用cross（介词形式为across）img src=https://www.doczj.com/doc/ae2556451.html,/large/pgc-image/15251329904161dc24 05d4e img_width=474 img_height=266 alt=七个经过”= pass,= cross,= through,= by……怎么过（有何区别）= inline=0 style=box-sizing: border-box; -webkit-tap-highlight-color: transparent; border-style: none; max-width: 100%; display: block; margin: 10px auto; Light goes through the window 不充当谓语时，几个介词“经过”的区别 past从旁边“经过”“路过”“绕过”by从旁边“经过”“绕过”“绕过”（此时by=pst）across 从表面“经过” , 空中“越过”（比如把东西从房间的一边扔到另一边）over 1. 从上方“经过”“飞过” “跨过”；2.从表面“经过”“越过”（此时over=across）through从内部“穿过”为何以上单词用法孩子们不容易分得清，而“man和child却不可能弄错？因为前者的汉语意思相
介词的用法 1.表示地点位置的介词 1)at ,in, on, to，for at (1)表示在小地方; (2)表示“在……附近，旁边” in (1)表示在大地方; (2)表示“在…范围之内”。 on 表示毗邻，接壤，“在……上面”。 to 表示在……范围外，不强调是否接壤；或“到……” 2)above, over, on 在……上 above 指在……上方,不强调是否垂直，与below相对； over指垂直的上方,与under相对,但over与物体有一定的空间，不直接接触。 on表示某物体上面并与之接触。 The bird is flying above my head. There is a bridge over the river. He put his watch on the desk. 3)below, under 在……下面 under表示在…正下方 below表示在……下，不一定在正下方 There is a cat under the table. Please write your name below the line. 4)in front [frant]of, in the front of在……前面 in front of…意思是“在……前面”，指甲物在乙物之前，两者互不包括；其反义词是behind（在……的后面）。 There are some flowers in front of the house.(房子前面有些花卉。) in the front of 意思是“在…..的前部”，即甲物在乙物的内部.反义词是at the back of…（在……范围内的后部）。 There is a blackboard in the front of our classroom. 我们的教室前边有一块黑板。 Our teacher stands in the front of the classroom. 我们的老师站在教室前.(老师在教室里) 5）beside，behind beside 表示在……旁边 behind 表示在……后面 2.表示时间的介词 1)in , on，at 在……时 in表示较长时间，如世纪、朝代、时代、年、季节、月及一般（非特指）的早、中、晚等。 如in the 20th century, in the 1950s, in 1989, in summer, in January, in the morning, in one?s life , in one?s thirties等。 on表示具体某一天及其早、中、晚。 如on May 1st, on Monday, on New Year?s Day, on a cold night in January, on a fine morning, on Sunday afternoon等。 at表示某一时刻或较短暂的时间，或泛指圣诞节，复活节等。 如at 3:20, at this time of year, at the beginning of, at the end of …, at the age of …, at Christmas，at night, at noon, at this moment等。 注意：在last, next, this, that, some, every 等词之前一律不用介词。如：We meet every day.
介词 介词是一种用来表示词与词、词与句之间的关系的虚词，在句中不能单独作句子成分。介词后面一般有名词代词或相当于名词的其他词类，短语或从句作它的宾语。介词和它的宾语构成介词词组，在句中作状语，表语，补语或介词宾语。介词可以分为时间介词、地点介词、方式介词、原因介词和其他介词， 1.表示地点位置的介词 1)at ,in, on, to at (1)表示在小地方; (2)表示“在……附近，旁边” in (1)表示在大地方; (2)表示“在…围之”。 on 表示毗邻，接壤，“在……上面”。 to 表示在……围外，不接壤；或“到……” eg: in the east of China(在中国的东部) on the east of China(在与中国的东部接壤的地方) to the east of China(在中国以东) 2)above, over, on 在……上 above 表示一个物体高过另一个物体,不强调是否垂直，与below相对； over一个物体在另一个物体的垂直上方,与under相对,但over与物体有一定的空间，不直接接触。 on表示一个物体在另一个物体表面上，并且两个物体互相接触与beneath相对。 The bird is flying above my head.（这只鸟飞在我的头上） There is a bridge over the river.（河上有一座桥） He puts his watch on the desk.（他把他的手表放在桌子上） 3)below, under 在……下面 under表示在…正下方 below表示在……下，不一定在正下方 There is a cat under the table.（有一只猫在桌子底下） Please write your name below the line.（请把你的名字写在线下） 4)in front [frant]of, in the front of在……前面 in front of…意思是“在……前面”，指甲物在乙物之前，两者互不包括；其反义词是behind（在……的后面）。 There are some flowers in front of the house.(房子前面有些花卉。) in the front of 意思是“在…..的前部”，即甲物在乙物的部.反义词是at the back of…（在……围的后部）。 There is a blackboard in the front of our classroom. 我们的教室前边有一块黑板。 Our teacher stands in the front of the classroom. 我们的老师站在教室前.(老师在教室里) 5）beside，behind , between beside 表示在……旁边 behind 表示在……后面 between表示在两者之间 6) on the tree, in the tree on the tree 长在树上 in the tree 外来落在树上
教学过程 一、课堂导入 本堂知识是初中最常见的介词by的一个整理与总结，让学生对这个词的用法有一个系统的认识。
二、复习预习 复习上一单元的知识点之后，以达到复习的效果。然后给学生一些相关的单选或其他类型题目，再老师没有讲解的情况下，让学生独立思考，给出答案与解释，促进学生发现问题，同时老师也能发现学生的盲点，并能有针对性地进行后面的讲课。
三、知识讲解 知识点1：by + v.-ing结构是一个重点，该结构意思是“通过……，以……的方式”，后面常接v.-ing 形式，表示“通过某种方式得到某种结果”，即表示行为的方式或手段。 I practice speaking English by joining an English-language club. 我通过加入一个英语语言俱乐部来练习讲英语。 Mr Li makes a living by driving taxis.李先生靠开出租车为生。 介词by + v.-ing 结构常用来回答How do you...?或How can I...?之类的问题。 —How do you learn English? 你怎样学习英语呢？ —I learn English by reading aloud. 我通过大声朗读来学英语。 —How can I turn on the computer? 我怎样才能打开电脑呢？ —By pressing this button. 按这个按钮。
知识点2：by 是个常用介词，其他用法还有： 1【考查点】表示位置，意思是“在……旁边”，“靠近……”，有时可与beside互换。The girls are playing by (beside) the lake. 女孩们正在湖边玩。 此时要注意它与介词near有所不同，即by 表示的距离更“近”。比较： He lives by the sea. 他住在海滨。He lives near the sea. 他住在离海不远处。
By和Through的方式方法区别 一、by的用法 （1）表示方法，手段。即“用……；通过……”相当于by means of。 e.g. ①All work had to be done by hand. 所有的工作都是手工进行的。 e.g. ②He makes a living by teaching. 他以教书为生。 （2）表示传达、传递的方式或煤介。 e.g. How did you send the letter, by airmail or by ordinary mail? 你是怎么发送的这信，是通过航天邮件还是普通邮件？ （3）表示用交通工具、通讯工具后接名词单数，不加冠词。 e.g. He came by train, but his wife came by bus. 他是乘火车来的，可是他老婆是坐公共汽车来的。 （4）指数量增加或减少了的程度，相差。 e.g. ①We lost the match by one goal. 我们仅以一球之差输了比赛。 e.g. ②The output of steel went up by 20 percent．钢产量增长了20％。 （5）根据，按照，以……计 固定搭配： pay sb by the hour /day/week sell sth by the pound /meter/ dozen sell sth by weight/length e.g. As a rule，domestic servants doing odd jobs are paid by the hour. 通常，家政服务是按照小时计酬的。（do odd jobs做零工；打零工） 二、through的用法 （1）表示“以；通过；经由”。 e.g. He succeeded through hard work. 他通过努力获得成功。 （2）空间上通过，透过，经过 e.g. Light comes in through the window。光线从窗户进来。 （3）时间上通过，自始至终，从头到尾经过 e.g. He often works through the night. 他常常通宵工作。
介词through的用法 1.表示“从...中穿过”“透过” Go though the forest 穿过森林 A river goes through the city. 一条小河穿过这座城市 Walk through the aisle. 通过走廊 The sunshine comes in through the window. 阳光透过窗户照进来。 2.表示“通过，凭借（某种方法，方式） He became rich through hard work 通过辛劳的工作 He got the job through his uncle. We learn to speak though listening. 3.自始至终；从头到尾 We worked through the night. 我们通宵的工作。 4.带有through的固定短语 Go through/come through 经历 Look through 浏览 Get through to sb接某人通电话，打通某人电话
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across和through的区别 悬赏分：0 - 解决时间：2007-5-25 18:14 提问者：斯航 - 千总四级最佳答案 1、首先是词性的区别：across为介词，而cross为动词。 （动词为“穿过，横穿”，名词为“十字，十字路口”） 2、当然across必须与through 区别开来。across为“横穿”，与“道路”交叉形成“十字”。而through为在立体空间中的“穿过”。如：go through the forest“穿过森林”，go across the street “穿过大街” ------ through表示“贯通、直穿、透过、穿过”的意思，即是从一头（边）贯穿到另一头（边）。 例The river runs through our city.这条河流经我们市。 He passed through the hall. 他穿过大厅 across表示“横穿、横过、横渡、横跨” 例：I swam across the Changjiang River 20 years ago. 20年前我横渡了长江。 Look left and right before you go across the street. 过马路时要左右看。 ---------- through, across和over的区别 ①、through：穿过 I threw it through the window. Is it quicker to drive round the town, or straight though the centre? ②、across: from one side to the other （在平面上）越过，在/到……对/面，横过。 I can’t swim across the river. 我不能游到河对岸。 He went across the hall to the door. 他越过大厅到门口。 ③、over: 翻越过 across和over两者都表示从一侧向另一侧的运动： She drove over /across the bridge. 但如果越过的是一个高的物体，则用over: He climbed over the wall. 如果越过的是一个平面，则宜用across： He went across the hall to the door. across和through都表示“穿过”，“通过”的意思，across表示从物体表面“穿过”、“通过”;而through则表示从内部“穿过”、“通过”。 by 的用法 介词，表示通过…方法或途径的意思，译成“靠，通过”，后面可加名词或名词短语。
by, through和via之间的区别 by, through, via这三个词都有“通过”的含义，但是区别很大，以下我会详细分析这三个词各自的用法和区别： 1by，我们通常会见到以下六种用法： 1. 表示附近，例如nearby，pass by，go by，sit by the window等； 2. 表示由某人做某事，例如The name of the Company is “XXX” or such other name or names as may be designated by Management Board; 3. 表示截止到……为止，例如by the year of......； 4. 表示乘坐某种交通工具，例如by train/plane/sea/ship/air等； 5.表示通过某种方式，例如by means of, by email等； 6.表示原因，例如by reason of。 2through的含义是穿过、通过，合同中常见的表达： 1. Section(a) through Section(e) 从(a)款至(e)款，这里有”贯穿“的含义 2. The Fund may invest directly and/or indirectly through a XXX Fund to achieve the foregoing goals. 基金可通过XXX基金直接和/或间接进行投资，以实现前述目标。 3.through friendly negotiation 通过友好协商 3via表达的意思是“经由某个人、某个区域、某个工具达到某个目的”，这里的“人/区域/工具”都是中间媒介，它们起着传递、连接等作用。其含义主要有两层：(1)经由......中转；(2)通过；凭借，常见句型： 1. I sent a message to Mary via her friend. 通过Mary的朋友带信给她； 2. He flew to New York via Hong Kong. 他经由香港飞往纽约； 3. broadcast via satellite 通过卫星广播。 区别： by侧重通过某种方式；through侧重穿过、透过；via侧重通过某种媒介达到目的。 以上仅代表旗渡观点，欢迎批评指正或讨论交流。
初中英语介词的使用口诀表 以下是一些介词的使用口诀,希望对大家有用： 上午、晚要用in，at黎明、午夜、点与分。年、月、年月、季节、周，、灯、影、衣、冒in。 将来时态in...以后，小处at大处in。有形with无形by，语言、单位、材料in。 特征、方面与方式，心情成语惯用in。介词at和to 表方向，攻击、位置、恶、善分。 日子、日期、年月日，星期加上早、午、晚，收音、农场、值日on，关于、基础、靠、著论。 着、罢、出售、偷、公、假，故意、支付、相反，准。特定时日和"一……就"，on后常接动名词。 年、月、日加早、午、晚，of之前on代in。步行、驴、马、玩笑on，cab，carriage则用in。 at山脚、门口、在当前，速、温、日落、价、核心。 工具、和、同随with，具有、独立、就、原因。 就……来说宾译主，对、有、方状、表细分。 海、陆、空、车、偶、被by，单数、人类know to man。 this、that、tomorrow，yesterday，next、last、one。 接年、月、季、星期、周，介词省略已习惯。 over、under正上下，above、below则不然，
若与数量词连用，混合使用亦无关。 beyond超出、无、不能，against靠着，对与反。 besides，except分外，among之along沿。 同类比较except，加for异类记心间。 原状because of,、owing to、due to表语形容词 under后接修、建中，of、from物、化分。 before、after表一点, ago、later表一段。 before能接完成时，ago过去极有限。 since以来during间，since时态多变换。 与之相比beside，除了last but one。 复不定for、找、价、原，对、给、段、去、为、作、赞。 快到、对、向towards，工、学、军、城、北、上、南。 but for否定用虚拟，复合介词待后言。 ing型由于鉴，除了除外与包合。 之后、关于、在......方面，有关介词须记全。 into外，表位置，山、水、国界to在前。 1.表示时间，注意以下用法： (1) 表示时间的某一点、某一时刻或年龄等用at。如： I get up at six in the morning. 我早上六点钟起床。He got married at the age of 25. 他25 岁结婚。
介词是一种用来表示词词, 词与句之间的关系的词。在句中不能单独作句字成分。介词后面一般有名词代词或相当于名词的其他词类，短语或从句作它的宾语。介词和它的宾语构成介词词组，在句中作状语，表语，补语或介词宾语。 介词分类及用法 一、表示时间的介词 时间介词有in , on，at， after， since， during,by,before,after,until等，前三个介词用法有个口诀： at午夜、点与分，上午、下午、晚用in。 年、月、年月、季节、周，之前加上介词in。 将来时态多久后，这些情形亦用in。 日子、日期、年月日，星期之前要用on。 其余几组常见的时间介词辨析如下辨析如下： 1、时间介词in与after 的用法辨析 介词 in + 一段时间用于一般将来时。如：We’ll go to school in two weeks. 介词after + 一段时间用于一般过去时。如：My mother came home after half an hour. 介词after + 时间点常用于一般将来时。如：We’ll go out for a walk after supper. 2、时间介词for与since的用法辨析 介词for 表示一段时间如：I have been living here for 10 years. 介词since 表示从过去某一时间以来如：I have been living here since 2000. 3、时间介词before与by的用法辨析 介词before表示“在…之前”如：He won’t come back before five . 介词by表示“到…时为止，不迟于…”如：The work must be finished by Friday. 4、时间介词during与for的用法辨析 当所指的时间起止分明时用介词during如：He swims every day during the summer. 如果一段时间不明确则用介词for如：I haven’t seen her for years. 5、时间介词till与until用法的异同 till和until用在肯定句中，均可表示“直到…为止”，如：I will wait till（until）seven o'clock． till和until用在否定句中，均可表示“在…以前”或“直到…才”。 如：Tom didn't come back till（until）midnight． till多用于普通文体，而 until则用于多种文体，并且在句子开头时，用