The relationship between agricultural technologies and carbon emissions in Pakistan

The relationship between agricultural technologies and carbon emissions in Pakistan:Peril and promise

Khalid Zaman a ,?,Muhammad Mushtaq Khan b ,Mehboob Ahmad c ,Bashir Ahmad Khilji d

a

Department of Management Sciences,COMSATS Institute of Information Technology,University Road,Tobe Camp,Abbottabad campus,Pakistan b

Department,Management Sciences,COMSATS Institute of Information Technology,Abbottabad,Pakistan c

Department of Management Sciences,Bahria University,Islamabad,Pakistan d

Department of Economics,Preston University,Islamabad,Pakistan

a b s t r a c t

a r t i c l e i n f o Article history:

Accepted 12May 2012Keywords:

Agricultural technologies Carbon emissions Economic growth Tractors Pakistan

The objective of the study is to investigate the in ?uence of agricultural technologies on carbon emissions in Pakistan by using annual data from 1975to 2010.Data is analyzed by some econometrics techniques includ-ing cointegration theory,Granger causality test,variance decomposition,etc.The results reveal that agricul-tural technologies act as an important driver for increase in carbon emissions in Pakistan.Results indicate that unidirectional causality runs from agriculture machinery to carbon emissions but not vice versa.Agricul-tural technologies are closely associated with economic growth and carbon emissions in Pakistan.Variance decomposition analysis shows that among all the agricultural technologies,granting subsidies to the agricul-ture sector have exerts the largest contribution to changes in carbon emissions.Conversely,agricultural irri-gated land seems relatively the least contributors on changes in carbon emissions due to infertility of total irrigated land available in Pakistan.

?2012Elsevier B.V.All rights reserved.

1.Introduction

In the recent years,attention has been attracted to the deve-lopment of activities i.e.,developing and implementation of stan-dards,directives,regulations,policies etc which are related to the environmental protection and implementation of the principles of sustainable development (Sobotka and Rolak,2010).The impor-tance of information and communication technologies (ICTs)has also given an equal importance to change in agricultural productiv-ity (Michailidis et al.,2011).Liu and Zhang (2011,p.74)opine that

“Agriculture informatization level is an important part of one coun-try's modernization.It is important to construct reasonable agricul-ture informatization evaluation indicator system and propose the evaluation method for promoting the agriculture informatization.”Agriculture and natural environment are closely related to each other.Atmospheric carbon dioxide is a direct factor in agricultural production,involved in crop photosynthesis,and directly affects the primary productivity of crops.Carbon dioxide emissions are the pri-mary source of greenhouse gases which have a huge impact on the

global carbon cycle and agriculture.In the agricultural production process,large amounts of greenhouse gases caused by unreasonable exploitations such as improper land use and chemical fertilizer affect climate change in turn.Agriculture is an important source of green-house gas emissions,especially emissions of a large number of CH 4and N2O.It is estimated that emissions from agricultural sources of CO 2,CH 4and N 2O account for 21%–25%,57%and 65%–80%in the total amount of anthropogenic greenhouse gas emissions.Therefore,the process of agricultural production has a double impact;low-carbon technology in agriculture cannot be ignored (Linda,2001).Low carbon agriculture is the way of development of further agricul-ture through innovation of technology and system,transformation of new energy industry https://www.wendangku.net/doc/379330504.html,ing the methods such as reducing energy consumption and carbon emissions can realize a double win be-tween agricultural production development and ecological environ-ment protection.The direction of achieving low carbon agriculture is to develop low energy consumption agriculture,the circular agricul-tural and the organic agriculture (Kecheng,2010).

Agriculture is the mainstay of the Pakistan economy as it provides employment to 45percent population and provides input for agro-based industry.Agriculture income has created demand for industri-al products.(GoP,2011).The agriculture has lost signi ?cant growth momentum as its growth slowed down to 2.7percent in the decade of 2000s as against 4.4percent in 1990s and 5.4percent in the 1980s.The structural problems and lack of mechanization remained main impediment to growth.The trend in agriculture growth during last three decades is given in Fig.1.

Economic Modelling 29(2012)1632–1639

?Corresponding author at:Department of Management Sciences,Room No:319,Block-A,COMSATS Institute of Information Technology,University Road,Tobe Camp,Abbottabad campus,Pakistan.Tel.:+923348982744(O);fax:+92992383441.

E-mail addresses:khalidzaman@https://www.wendangku.net/doc/379330504.html,.pk ,khalid_zaman786@https://www.wendangku.net/doc/379330504.html, (K.Zaman).

0264-9993/$–see front matter ?2012Elsevier B.V.All rights reserved.doi:10.1016/j.econmod.2012.05.024

Contents lists available at SciVerse ScienceDirect

Economic Modelling

j o u r n a l h o m e p a ge :w w w.e l s e v i e r.c o m/l o c a t e /e c m od

The environmental concerns of Pakistan are associated primarily with the adverse impact of un-sustainable social and economic de-velopment.High population growth rate,lack of public awareness of environmental related education,mismanagement of natural re-sources,widely unplanned urban and industrial expansions are the core hard issues.These are further compounded with the rapid ur-banization.A nation with a population of 177million with an aver-age population density of 222persons per sq km,higher than many other developing countries,whose 37%people live in urban areas and 63%in rural has a high rate of migration to urban centers which has made the cities dysfunctional,overcrowded and very congested.Rapid urbanization is putting the available insuf ?cient infrastructure under enormous pressure and causing environmental debacles of great magnitude.Serious risks of irreversible damages are present due to air and water pollution,mismanagement of solid waste and destruction of fragile ecosystems (GoP,2010).

In this paper an analysis has been carried out to ?nd a statistical relationship between agricultural technologies and carbon emissions in Pakistan by using secondary data from 1975–2010.This paper does not include all dimensions and factors of the technologies-environment problem but limited to the following variables:?Green Technology (GT):The “green technology ”is a broad term for more environmentally friendly solutions.GT for that matter can be used as environmental healing technology that reduces environ-mental damages created by the products and technologies for peo-ples'conveniences.It is believed that GT promises to augment farm pro ?tability while reducing environmental degradation and con-serving natural resources (APCAEM,2010).

?Economic Growth:Economic growth is a necessary –if not suf ?cient –condition to address many of the social and equity concerns faced by societies.Environmental protection not only enhances long-term eco-nomic performance through a more sustainable use of the resource base,but can also contribute to equity:natural resource and envi-ronmental degradation (especially the pollution of fresh water,the mining of soil fertility and depletion of ?sh stocks)impacts most heavily on the poor (OECD,2011).

?Carbon Emissions:The sources of greenhouse gases (GHG)come from various sectors including transportation,industrial processes,power generation for residential consumption,agriculture and de-forestation.According to the United Nations Food and Agriculture Organization (FAO,2006),deforestation accounts for 25to 30per-cent of the release of green house gases.The report states that most people assume that global warming is caused by burning oil and gas.But in fact between 25and 30percent of the greenhouse gases released into the atmosphere each year –1.6billion tonnes —is caused by deforestation.

The objective of this paper is to empirically investigate the in ?u-ence of agricultural technologies on carbon emissions in Pakistan.The more speci ?c objectives are to ?nd out:

i.To estimate whether there is a long-run relationship between agricultural technologies on carbon emissions in Pakistan.ii.To explores the in ?uencing directions between technologies development and carbon emissions.

iii.To compare the in ?uencing magnitude of technologies on

carbon emissions in Pakistan.The paper is organized as follows:after introduction which is pro-vided in Section 1above,literature review is carried out in Section 2.Methodological framework is explained in Section 3.The estimation and interpretation of results is mentioned in Section 4.Section 5con-cludes the paper.

2.Related literature review

The emission of greenhouse gases leads to a range of well docu-mented consequences,such as increases in the average global tem-perature,greater variation in temperatures across time,increased frequency and intensity of extreme weather-related events,and av-erage sea-level rise (IPCC,2007).The potential damages induced by climate change are manifold,in particular for developing countries where climate change is expected to have its most severe repercus-sions.Developing countries depend to a large extent on the agricul-tural sector,which is particularly vulnerable to climatic changes (World Bank,2010).Climate change may also have a negative im-pact on public health in developing countries by for example in-creasing malaria morbidity and mortality (Tol,2008;WHO,2009).Another important consequence is the increased risk of natural di-sasters,mostly in coastal areas of developing countries.Contemplat-ing these risks,climate change may also increase the likelihood of displacement,political unrest and violent con ?ict in developing countries.Developing countries,therefore,have a strong interest in containing climate change and mitigating its consequences through the development and diffusion of green technologies.The develop-ment and diffusion of technology in the context of climate change poses a formidable challenge due to the presence of a ‘double exter-nality ’(Hall and Helmers,2010).Grossman and Helpman (1991,p.16)opines that

“Firms can acquire information created by others without paying for that information in a market transaction,and the creators (or current owners)of the information has no effective recourse,under preva-iling laws,if other ?rms utilize information so acquired ”.

Acemoglu et al.(2009)argument on endogenous growth model that allows for technological change directed either towards carbon-emitting or green technologies.In a setting in which pollut-ing technologies are initially more productive,the authors show that research subsidies are needed to redirect innovation towards cli-mate change-related technologies.However,a tax penalizing carbon emissions is also needed to address the environmental externality.Their analysis suggests that policy intervention in the form of sub-sidies and taxes is needed only temporarily,although delaying the intervention is costly.

Pollution has long been understood to threaten local populations and ecosystems,but there is now a broad awareness that human so-cieties are altering the global climate through the emissions of car-bon dioxide and other “greenhouse ”gasses (Roberts et al,2003).The environment Kuznet curve (EKC)hypothesis was ?rst intro-duced by Grossman and Krueger (1993)for different environmental indicators,including the carbon dioxide emissions as well.The EKC hypothesis stated an inverted U-shape relation between various in-dicators of environmental quality and per capita income.Under

this

Decades

Fig.1.Trends in agriculture growth (%)in Pakistan.Source:GoP (2011).

1633

K.Zaman et al./Economic Modelling 29(2012)1632–1639

hypothesis,carbon dioxide emission was usually explained by linear,quadratic or cubic polynomial functions of income per capita. Grossman and Krueger(1995)further studied the effect of GDP per capita on various local environmental indicators,using a random city-speci?c effect model.They found no evidence that environmen-tal quality deteriorates with economic growth.

Tamazian et al.(2009)brings out the importance of?nancial development indicators on the pollution performance.They argue that increased?nancial development can lead to more investments in environmental projects.Their empirical analysis on BRIC coun-tries(Brazil,Russia,India and China)show that increased foreign direct investment(FDI)in?ows lead to lower levels of CO2per capita emissions.However,there are studies that show that FDI in-?ows lead to environmental degradation(Cole and Elliot,2005). This nexus between FDI and environment could well mean that to attract more FDI investment in certain sectors,developing coun-tries might keep their environmental polices https://www.wendangku.net/doc/379330504.html,x environ-mental policy coupled with cost advantage could provide the ideal ground for participation in a mutually bene?cial arrangement between the host and the source countries.Polluting industries shift base to developing countries,while developed countries focus more on service sector and trade(Lucas et al,1992).This is often cited as a negative and a positive impact of trade between the developing and the developed world,from an environmental perspec-tive.Zaman et al(2011)empirically examined the relationship be-tween energy consumption and development factors i.e.,carbon dioxide emission,industry value added,agriculture value added and population growth,under bivariate cointegration technique in the context of Pakistan over a period of1980–2009.The results reveal that there is a bidirectional relationship between carbon dioxide emis-sion and energy demand,CO2to industrialization&CO2to energy de-mand.While,there is a unidirectional causality relationship between the energy demand and population growth.However,neither agricul-ture value addition nor energy demand affects each other.

Technology strategy is one of the most important aspects of any?rm's strategic posture especially in dynamic environments. Ghazinoory and Farazkish(2010)focused on adjusting a dynamic model of technology strategy development for Iranian nano-composite companies'conditions.They proposed four key environ-mental moderators which affect Chiesa's dynamic model for tech-nology strategy,and investigate these moderators'effects on the dynamic model's indicators.The results show that22indicators of Chiesa's model have changed for this case.Kurlavi?ius(2010) introduces the knowledge based agricultural decision support sys-tem.This system includes database and knowledge base modules which are used for formation of models,optimization,simulation, decision analysis and inferences in the farm model.Decision sup-port system performs the analysis of production ef?ciency,re-source reserves and shortage,and with the help of the Internet in real time provides a farmer with conclusions and suggestions necessary to increase the ef?ciency of production conforming to environmental constraints.Liu and Zhang(2011)construct agricul-ture informatization evaluation indicator system in China and?nds that this system is effective,simple and easy to use.?treimikiene and Esekina(2010)evaluate the impact of EU pollution reduction strategies on atmospheric emissions in Lithuania and to de?ne the role of EU emission reduction policies on shifting environmental Kuznets curves of EU member states and Lithuania.Zaman et al (2012)investigates the casual relationship between energy de-mand and agricultural technology factors in the agricultural sector of Pakistan,over a period of1975–2010.The results reveal that tractor and energy demand has bi-directional relationship;while irrigated agricultural land;share of agriculture and industry value added and subsides have supported the conventional view i.e.,ag-ricultural technology cause energy consumption in Pakistan.On the other hand,neither fertilizer consumption and high technology exports nor energy demand affect each others.

The lack of studies about relationship between CO2emission and agricultural technologies is incentive for writing this paper.In the subsequent sections an effort has been made to empirically?nd out the relationship between technology indicators on carbon emissions in the context of Pakistan.

3.Theoretical framework of the study

The study implies annual observations for the period of 1975–2010.The data is obtained from World Development Indicators published by the World Bank(2010).All the variables in this study and their data de?nitions are shown in Table1.It should be noted that all the data are the annual items and are transformed in to loga-rithmic values for further investigation.

The annual data of carbon emissions,real GDP per capita and ag-ricultural technologies indicators of Pakistan can be seen from Fig.2. We?nd that most variables experience a steady rise across respec-tive sample period,except real GDP per capita;fertilizers consump-tion;subsidies and other transfers and agriculture value added.

The standard hypothesis behind the environmental Kuznets curve is that emissions tend to decrease with successive higher stages of development.However,no explicit determinants of emissions other than income(output)are used in the standard models.In this study,the focus is on the relationship between environmental quality (measured by CO2emissions)and economic growth(measured by real GDP per capita)in the presence of external factors like techno-logical progress which is measured by agriculture machinery,fertil-izers production,cereal productions,agriculture irrigated land;high technology exports,subsidies,agriculture value added and industry value added.The impact of technology on environment should how-ever be more straightforward.Irrespective of developing or devel-oped countries,technological changes across any line of production should lead to lower emissions per unit of output.Since pollutants are often considered as byproducts of production,therefore an

Table1

Variables and data de?nitions.

Variables Measurement Expected sign Data source

CO2CO2represents carbon dioxide emissions(Kt)World Bank(2010) Independent variables

RGDPPC Real GDP per capita(US$)Positive World Bank(2010) TRACTORS Agricultural machinery,tractors per100km2of arable land Positive World Bank(2010) FERTILIZERS Fertilizer consumption(%of fertilizer production)Positive World Bank(2010) CEREALS Land under cereal production(hectares)Positive World Bank(2010) ALAND Agricultural irrigated land(%of total agricultural land)Positive World Bank(2010) HTEXPORTS High-technology exports(current US$)Positive World Bank(2010) SUBSIDIES Subsidies and other transfers(%of expense)Positive World Bank(2010) AVADDED Agriculture,value added(%of GDP)Positive World Bank(2010) IVADDED Industry,value added(%of GDP)Positive World Bank(2010)

Note:Dependent variable in each model is CO2,and all variables are transformed in to the logarithmic items.

1634K.Zaman et al./Economic Modelling29(2012)1632–1639

ef ?cient production process should have limited byproducts in the chain of the production process.

The following Fig.3highlights in schematic fashion the methodo-logical approach adopted in the paper.According to this framework,carbon emissions have been checked on GDP through agricultural technologies indicators.

Following eight equations (Panel A to H)are used to assess carbon emissions as a result of technology indicators in Pakistan i.e.,PanelA :CO 2;TRACTORS ;RGDPPC e1TPanelB :CO 2;FERTILIZERS ;RGDPPC e2TPanelC :CO 2;CEREALS ;RGDPPC e3TPanelD :CO 2;ALAND ;RGDPPC e4TPanelE :CO 2;HTEXPORTS ;RGDPPC e5TPanelF :CO 2;SUBSIDIES ;RGDPPC e6TPanelG :CO 2;AVADDED ;RGDPPC e7TPanelH :CO 2;IVADDED ;RGDPPC

e8T

whereCO 2represents Carbon dioxide Emissions (Kt);RGDPPC represent Real GDP per capita (US $);TRACTORS represent agricultur-al machinery,tractors per 100sq.km of arable land;FERTILIZERS

represent fertilizer consumption (%of fertilizer production);ALAND represent land under cereal production (hectares);ALAND represent agricultural irrigated land (%of total agricultural land);HTEXPORTS represent high-technology exports (current US$);SUBSIDIES repre-sent subsidies and other transfers (%of expense);AVADDED repre-sent agriculture,value added (%of GDP)and IVADDED represent industry,value added (%of GDP).3.1.Econometric framework of the study

The test for co-integration consists of two steps:?rst,the indi-vidual series are tested for a common order of integration.If the se-ries are integrated and are of the same order,it implies co-integration.Dickey and Fuller (1979,1981)devised a procedure to formally test for non-stationarity.The Augmented Dickey Fuller (ADF)test is used to test the stationarity of the series.It analyzes the order of integration of the data series.These statistics are calcu-lated with a constant,and a constant plus time trend,and these tests have a null hypothesis of non-stationarity against an alterna-tive of stationarity.

The study adopts Johansen's Cointegration test to the series of same order to determine the long run relationship between the vari-ables.If series are cointegrated of order 1,trace test (Johansen's Ap-proach)indicates a unique cointegrating vector of order 1and hence indicates the long run relationship.In the multivariate case,if the I (1)variables are linked by more than one co-integrating vector,the Engle and Granger (1987)procedure is not applicable.The test

44

48525660646872765

101520253035

ALAND

20

22242628

3032345

101520253035

AVADDED

9.00E+06

1.00E+071.10E+071.20E+071.30E+071.40E+075

101520253035

CEREALS

0.3

0.40.50.60.70.80.91.05

101520253035

CO2

112

116120124

1281321361405

101520253035

FERTILIZER

0.00E+00

4.00E+078.00E+071.20E+081.60E+082.00E+082.40E+082.80E+085

101520253035

HTEXPORTS

22

232425

26

27285

101520253035

IVADDED

10203040505

101520253035

SUBSIDIES

4080120

1602002405

101520253035

TRACTORS

16

20242832

365101520253035RGDPPC

Fig.2.Data trend for real per capita income (RGDPPC),carbon dioxide emissions (CO2)and agricultural technologies indicators in Pakistan.Source:World Bank (2010).

1635

K.Zaman et al./Economic Modelling 29(2012)1632–1639

for co-integration used here is the likelihood ratio put forward by Johansen and Juselius (1990),indicating that the maximum likeli-hood method is more appropriate in a multivariate system.Therefore,this study has used this method to identify the number of co-integrated vectors in the model.The Johansen and Juselius method has been developed in part by the literature available in the ?eld and reduced rank regression,and the co-integrating vector ‘r ’is de-?ned by Johansen as the maximum Eigen-value and trace test or stat-ic,there is ‘r ’or more co-integrating vectors.Johansen (1988)and Johansen and Juselius (1990)proposed that the multivariate co-integration methodology could be de ?ned as:CO 2eTt ?TECHNOLOGY ;RGDPPC eT

where,TECHNOLOGY represents technology indicators,which is a vector of elements.Considering the following autoregressive rep-resentation:CO 2t ?πB t

X K T ?1

πi CO 2eTt ?1tμt

Johansen's method involves the estimation of the above equation by the maximum likelihood technique,and testing the hypothesis H o ;(π=Ψξ)of “r ”co-integrating relationships,where r is the rank or the matrix π(0∠r ∠Ρ),Ψis the matrix of weights with which the variable enter co-integrating relationships and ξis the matrix of co-integrating vectors.The null hypothesis of non-cointegration among variables is rejected when the estimated likelihood test sta-tistic ?i ??n P p t ?r t1

ln 1?^λi ()exceeds its critical value.Given

estimates of the Eigen-value ^λi

the Eigen-vector (ξi )and the weights (Ψi ),we can ?nd out whether or not the variables in the

vector (CO 2)are co-integrated in one or more long-run relationships among (TECHNOLOGY,RGDPPC).

This paper investigates the in ?uence of Pakistan's agricultural technologies indicators on carbon emissions from two perspectives.One is to conduct the modi ?ed Granger causality (Granger,1988)and Johansen cointegration tests to explore the in ?uencing direc-tions between different technology indicators and carbon emissions,respectively;the other is to compare the in ?uencing magnitude of

Fig.3.Research framework .Source:Self Extract.

1636K.Zaman et al./Economic Modelling 29(2012)1632–1639

different technology indicators on carbon emissions based on the vector error correction model (VECM)and variance decomposi-tion approach.

In order to undertake the modi ?ed version of Granger causality for a VAR model with 3lags (k =2and d max =1),we estimate the follow-ing system of equations:

CO TRACTORS RGDPPC 2

43

5?A 0tA 1CO 2FERTILIZERS RGDPPC 2435tA 2CO 2CEREALS RGDPPC 2435tA 3CO 2

ALAND RGDPPC 2435t

A 4CO 2HTEXPORTS RGDPPC 2435tA 5CO 2SUBSIDIES RGDPPC 2435tA 6CO 2AVADDED RGDPPC 2435tA 7CO 2IVADDED RGDPPC 2435tε1t ε2t ε3t 2

435

e9T

where A 1,A 2….A 7are the 3×3matrices of coef ?cients with A 0being a 3×1identity matrix,and εt are the disturbance terms with zero mean and constant variance.From Eq.(9)we can test the hypothesis that Pakistan's agricultural technologies scale does not Granger cause car-bon emissions with the following hypothesis i.e.,

H 10

?

a 112

?

a 212

?0

where a 12

i

are the coef ?cients of the agricultural technologies scale variable in the ?rst equation of the system presented in Eq.(9).Be-sides,we can test the opposite causality from Pakistan's carbon emis-sions to agricultural technologies scale in the following hypothesis:

H 20?a 121?a 2

21?0

where a 21

i

are the coef ?cients of the carbon emissions variable in the second equation of the system presented in Eq.(9).It should be noted that we incorporate the variable RGDPPC in to Eq.(9)to avoid the omitted variable bias when we examine the Granger causality bias when we examine the Granger causality between agricultural tech-nologies indicators and carbon emissions.

4.Empirical result discussions

4.1.Cointegration among Pakistan's agricultural technologies indicators and carbon emissions

The present study conducts the augmented Dickey –Fuller (ADF)unit root tests for all variables with regard to their stationary proper-ties.The detailed results are shown in Table 2.

The results reveal that all variables in this study are non-stationary at their level but stationary at their ?rst differences,therefore,we say all variables are I (1)series at 1%level over a pe-riod of 1975–2010.Fig.4shows the plots of CO 2;RGDPPC and tech-nology development indicators,in their ?rst difference forms,which sets the analytical framework as regarding the long-term relation-ship between the variables.

After that,we take carbon emissions (CO 2)as the dependent var-iable and each technology indicators and real GDP per capita (RGDPPC)together as the independent variables,and then the Johansen cointegration among them is tested according to Johansen (1988).From the results in Table 3,we ?nd that except high technol-ogy exports (HTEXPORTS),all other technology development indica-tors have at least one cointegration relationship with carbon emissions at 5%level.Therefore,we may say that,for the most part,Pakistan's technology development indicators have signi ?cant long-term equilibrium with carbon emissions.

4.2.Causality among Pakistan's technology development indicators and carbon emissions

Subsequently,we conduct the modi ?ed Granger causality tests by Toda and Yamamoto (1995)for Pakistan's technology development

variables and carbon emissions.The variable RGDPPC is incorporated as an explanatory variable to avoid the omitted variable bias.Results are shown in Table 4.

The results reveal that “TRACTORS does not Granger cause CO 2”are rejected at 1%level but not vice versa.The result shows unidirectional causality runs between them.However,the causality runs between CO 2and FERTILIZER;CO 2and ALAND;CO 2and HTEXPORTS and CO 2and IVADDED does not Granger cause between them via both route;there-fore,we may conclude that both variables are causality independent in nature.“CO 2does not Granger cause CEREALS ”is rejected at 1%level,however,“CEREALS does not Granger cause CO 2”is accepted.The result shows unidirectional causality runs from CO 2to CEREALS.Finally,the causality runs from only SUBSIDIES to CO 2and AVADDED to CO 2shows that both variables have unidirectional causality between them.

The results re ?ect that agricultural technologies are closely asso-ciated with economic growth and carbon emissions.In reality the development of agriculture is closely related to low-carbon develop-ment.Pakistan is an agro-based country,under the premise of large population,energy shortages and serious ecological damage the development of low-carbon agriculture still has long way to go,but it is the trend of agricultural development with great potential.4.3.Variance decomposition analysis

In order to compare the contribution extents of Pakistan's various agricultural technologies development to the change of carbon emis-sions,the variance decomposition approach is adopted over the sam-ple period.First,we take the carbon emissions as the dependent variable and agricultural technologies and RGDPPC together as inde-pendent variables,and conduct the Johansen cointegration test among these variables over a period of 36years.

The results indicate that there exists statistically signi ?cant co-integration among Pakistan's agricultural technologies variables and carbon emissions during 1975–2010.Next,we apply the variance de-composition approach based on the vector error correction model (VECM)to explore the in ?uence of Pakistan's agricultural technolo-gies on carbon emissions,and compare their contribution difference.Results are shown in Fig.5.

The results ?nd that,among all technologies,SUBSIDIES exerts the largest in ?uence,whose steady contribution level for carbon emissions changes approaches to 93.72%;while the in ?uence of HTEXPORTS;TRACTORS;IVADDED;AVADDED;FERTILIZER;and CEREALS follows,with steady contribution level of 83.51%;13.76%;6.93%;6.33%;5.29%;and 4.03%,respectively.It should be noted that the in ?uence of ALAND seems relatively the least;only about 1.92%.The results above have two important implications at least.Firstly,high technology in the core allows polluting industries to shift to the periphery (Roberts et al,2003).Secondly,foreign capital penetration and World-System position

Table 2

ADF tests for variables regarding their stationary properties.Variables Level First difference CO 20.1974(0.9684)?8.8974(0.0000)GDP

1.5024(0.9646)?5.2500(0.0000)TRACTORS 3.7768(0.9999)?3.6008(0.0007)FERTILIZERS ?0.5480(0.4724)?7.4371(0.0000)CEREALS 3.0314(0.9990)?5.2258(0.0000)ALAND

1.2746(0.9980)?6.0936(0.0000)HTEXPORTS 3.2942(0.9998)?5.1365(0.0000)SUBSIDIES ?0.5703(0.4630)?6.6213(0.0000)AVADDED ?1.8603(0.0606)?4.7861(0.0000)IVADDED

0.1861

(0.7343)

?6.6302

(0.0000)

Note:The signi ?cance probabilities for ADF test are reported in parentheses.The null hypothesis is that the series is non-stationary,or contains a unit root.The rejection of the null hypothesis is based on MacKinnon critical values.The lag length are selected based on SIC criteria,this ranges from lag zero to lag one.The statistics signi ?cant at 1%level of signi ?cance.

1637

K.Zaman et al./Economic Modelling 29(2012)1632–1639

appear to be monotonically related to carbon dioxide emissions (Burns,et al.,1997;Grimes and Kentor,2003;Jorgenson,2007).5.Summary and conclusion

The objective of the study is to empirically investigate the in ?u-ence of agricultural technologies on carbon emissions in the context of Pakistan by using the annual data from 1975to 2010.The study ex-plores the in ?uencing directions between different agricultural

technologies and carbon emissions respectively and further is to com-pare the in ?uencing magnitude of different technologies on carbon emissions.Both objectives have been achieved with the sophisticated econometrics techniques including cointegration theory,Granger causality test and variance decomposition,etc.The results reveal that agricultural technologies have signi ?cant long-term equilibrium with carbon emissions except high technology exports.Granger cau-sality runs towards CO 2to agriculture machinery but not vice versa which shows unidirectional causality runs between them.The result of variance decomposition analysis shows that the SUBSIDIES is the only indicator,among all the technologies used in the study has

-.04

-.02.00.02.04.06.085

101520253035

D(CO2)

-0.5

0.00.51.01.52.02.55

101520253035

D(ALAND)

-3

-2-10125

101520253035

D(AVADDED)

-600000

-400000-2000000

200000

4000006000005

101520253035

D(CEREALS)

-20

-15-10-505105

101520253035

D(FERTILIZER)

-6.0E+07

-4.0E+07-2.0E+070.0E+002.0E+074.0E+076.0E+078.0E+071.0E+085

101520253035

D(HTEXPORTS)

-3

-2-1012345

101520253035

D(IVADDED)

-20

-10

01020305

101520253035

D(SUBSIDIES)

-20

-1001020305

101520253035

D(TRACTOR)

16

20242832365

101520253035

D(RGDPPC)

Fig.4.Data trends at their ?rst difference .Source:World Bank (2010).

Table 3

Results of Johansen cointegration tests.

Hypothesized no.of CE (s)Eigenvalue Trace statistic

5%

Critical value Prob.

Panel A:

None ?0.865357.553329.79700.0000Series:CO 2,tractors,RGDPPC At most 10.1106 4.221215.49470.8849At most 20.05680.2339 3.84140.6286Panel B:None ?0.881539.490829.79700.0001Series:CO 2,

FERTILIZERS,RGDPPC At most 10.2106 4.249215.49470.8824At most 20.01770.2630 3.84140.6080Panel C:None ?0.848660.990929.79700.0000Series:CO 2,

CEREALS,RGDPPC At most 10.2683 6.415515.49470.6464At most 20.02420.1464 3.84140.7020Panel D:

None ?

0.895334.498429.79700.0009Series:CO 2,ALAND,RGDPPC At most 1?0.699818.809515.49470.0127At most 20.0356 1.2331 3.84140.2668Panel E:None

0.322018.727129.79700.5127Series:CO 2,

HTEXPORTS,RGDPPC At most 10.1474 5.512515.49470.7522At most 20.00260.0901 3.84140.7639Panel F:

None ?0.942374.325129.79700.0000Series:CO 2,SUBSIDIES,RGDPPC At most 10.3740 2.622715.49470.9813At most 20.01280.0052 3.84140.9415Panel G:

None ?0.872944.484929.79700.0000Series:CO 2,AVADDED,RGDPPC At most 10.2694 2.706115.49470.9786At most 20.01750.2585 3.84140.6111Panel H:

None ?0.864256.324529.79700.0000Series:CO 2,IVADDED,RGDPPC

At most 10.20147.285415.49470.1287At most 2

0.0132

0.2845

3.8414

0.5899

Note:Dependent variable in each Johansen cointegration test is CO 2.

?Denotes rejection of the hypothesis at the 5%level.

Table 4

Causality test results among agricultural technologies indicators and carbon emissions.Null Hypothesis

Chi-square statistic

Prob.CO 2does not Grange cause the changes in TRACTORS 2.125890.3489TRACTORS does not Granger cause the changes in CO 214.77990.0006CO 2does not Grange cause the changes in FERTILIZERS

0.70870.7016FERTILIZERS does not Granger cause the changes

in CO 2

0.67210.7146CO 2does not Grange cause the changes in CEREALS

13.45260.0012CEREALS does not Granger cause the changes in CO 2 2.05470.3579CO 2does not Grange cause the changes in ALAND 3.10710.2115ALAND does not Granger cause the changes in CO 2 2.93380.2306CO 2does not Grange cause the changes in HTEXPORTS

3.62360.1634HTEXPORTS does not Granger cause the changes

in CO 2

3.10060.2122CO 2does not Grange cause the changes in SUBSIDIES

1.94440.3782SUBSIDIES does not Granger cause the changes in CO 2 6.85320.0325CO 2does not Grange cause the changes in AVADDED

2.58380.2747AVADDED does not Granger cause the changes in CO 28.96460.0113CO 2does not Grange cause the changes in IVADDED 4.15680.1251IVADDED does not Granger cause the changes in CO 2 1.0113

0.6031

Note:The modi ?ed Granger causality test approach used in the table is provided by Toda and Yamamoto's (1995).And the causality tests between agricultural technologies indicators and carbon emissions are based on the signi ?cance of Chi-square statistics for Wald tests of VAR models in Eq.(1).

1638K.Zaman et al./Economic Modelling 29(2012)1632–1639

exerts the largest share to in ?uence changes in carbon emissions i.e.,93.72%.Subsequently,HTEXPROTS;TRACTORS;IVADDED;AVADDED;FERTILIZERS and CEREALS follow their in ?uences to changes in car-bon emissions according to their share percentages.The in ?uence of agriculture irrigated land (ALAND)seems relatively the least contri-bution on changes in carbon emissions i.e.,1.92%.

In a word,when Pakistan's future carbon emissions demand is pro-jected,the change of agricultural technologies development should be taken into account;or else,further development in Pakistan's agricul-ture industry may increase emissions in a way that has not been accounted for,which makes it more dif ?cult for Pakistan to meet its planned emissions reductions targets.References

Acemoglu,D.,Aghion,P.,Bursztyn,L.,Hemous,D.,2009.The environment and directed

technical change.NBER Working Paper No.15451.

APCAEM,2010,A Feasibility Study on the Application of green technology for sustainable

agriculture development:Assessing the policy impact in selected member countries of https://www.wendangku.net/doc/379330504.html,n and Paci ?c Centre for Agricultural Engineering and Machin-ery,China.Online available at:https://www.wendangku.net/doc/379330504.html,/doc/67280078/Green-Tech (accessed on 17September,2011).

Burns,T.,Davis,B.,Kick,E.,1997.Position in the World-System and National Emissions

of Greenhouse Gases.Journal of World-Systems Research 3(3),432–466.

Cole,M.A.,Elliot,R.J.R.,2005.FDI and the capital intensity of “dirty ”sectors:a missing

piece of the pollution haven puzzle.Review of Development Economics 9(4),530–548.

Dickey,D.,Fuller,W.,1979.Distribution of the estimators for autoregressive time-series with a unit root.Journal of the American Statistical Association 74,427–431.Dickey,D.,Fuller,W.,1981.Likelihood ratio statistics for autoregressive time series

with a unit root.Econometrica 49(1057),1072.

Engle,R.F.,Granger,C.W.J.,1987.Co-integration and error-correction:representation,

estimation and testing.Econometrica 55,251–276.

FAO,2006.Deforestation causes global warming:key role for developing countries in

?ghting greenhouse gas emissionsonline available at:https://www.wendangku.net/doc/379330504.html,/newsroom/en/news/2006/1000385/index.html 2006accessed on 25th July,2011.Ghazinoory,S.,Farazkish,M.,2010.A model of technology strategy development for

Iranian nano-composite companies.Technological and Economic Development of Economy 16(1),25–42.

GoP,https://www.wendangku.net/doc/379330504.html,ernment of Pakistan,Economic Survey of Pakistan (2009–10.Finance

Division,Economic,Advisor's Wing,Islamabad,Pakistan.

GoP,https://www.wendangku.net/doc/379330504.html,ernment of Pakistan,Economic Survey of Pakistan (2010–11.Finance

Division,Economic,Advisor's Wing,Islamabad,Pakistan.

Granger, C.W.J.,1988.Causality,cointegration and control.Journal of Economic

Dynamics and Control 12,551–559.

Grimes,P.,Kentor,J.,2003.Exporting the greenhouse:foreign capital penetration and

CO2emissions 1980–1996.Journal of World-Systems Research 9(2),261–275.Grossman,G.M.,Helpman,E.,1991.Innovation and Growth in the Global Economy.

MIT Press.

Grossman,M.G.,Krueger,A.B.,1993.Environmental Impacts of a North American Free

Trade Agreement.In:Garber,P.(Ed.),The U.S.-Mexico Free Trade Agreement.MIT Press,Cambridge,MA,pp.165–177.

Grossman,M.G.,Krueger,A.B.,1995.Economic growth and the environment.Quarterly

Journal of Economics 60,353–377.

Hall,B.H.,Helmers,C.,2010.The role of patent protection in (clean/green)technology

transfer:Symposiumretrieved at 25th July,2011from https://www.wendangku.net/doc/379330504.html,/@@bhhall/papers/HallHelmers10_SCHTLJ_techtransfer.pdf 2010.IPCC,2007.Climate Change 2007—Synthesis Report.

Johansen,S.,1988.Statistical analysis of cointegrating vectors.Journal of Economic Dy-namics and Control 12,231–254.

Johansen,S.,Juselius,K.,1990.Maximum likelihood estimation and inference on

cointegration with applications to the demand for money.Oxford Bulletin of Eco-nomics and Statistics 52,169–210.

Jorgenson,A.,2007.The effects of primary sector investment on carbon dioxide emis-sions from agriculture production in less-developed countries,1980–99.Interna-tional Journal of Comparative Sociology 48(11),29–42.

Kecheng,Q.,2010.Construction of Low-Carbon Agriculture,M &D Forumretrieved

online at 19th July,2011from https://www.wendangku.net/doc/379330504.html,/upload/product/201010/2010jjfzh01a82010.

Kurlavi ?ius,A.,2010.Sustainable agricultural development:knowledge-based decision

support.Technological and Economic Development of Economy 15(2),294–309.Linda,J.,2001.Climate Change and Agricultural Sustainable Development.Beijing

Press,Beijing,p.35(in Chinese).

Liu,P.,Zhang,X.,2011.Investigation into evaluation of agriculture informatization

level based on two-tuple.Technological and Economic Development of Economy 17(1),74–86.

Lucas,R.,Wheeler,P.,Hettige,H.,1992.Economic development,environmental regula-tion and international migration of toxic pollution 1960–1988.In:Low,P.(Ed.),In-ternational Trade and the Environment.:World Bank Discussion Paper,159.World Bank,Washington DC.

Michailidis,A.,Chatzitheodoridis,F.,Theodosiou,G.,2011.Evaluation of innovative

agricultural extension projects using novel investment tools.Technological and Economic Development of Economy 16(4),703–716.

OECD,2011.A Green Growth Strategy for Food and Agriculture:Preliminary

ReportOnline available at:https://www.wendangku.net/doc/379330504.html,/dataoecd/38/10/48224529.pdf 2011Accessed on 23rd July,2011.

Roberts,T.,Grimes,P.E.,Manale,J.L.,2003.Globalization and the environment.Journal

of World-Systems Research IX (2),277–315summer,Special Issue,https://www.wendangku.net/doc/379330504.html,/.

Sobotka,A.,Rolak,Z.,2010.Multi-attribute analysis for the eco-energetic assessment

of the building life cycle.Technological and Economic Development of Economy 15(4),593–611.

?treimikiene,D.,Esekina,B.,2010.EU pollution reduction strategies and their impact

on atmospheric emissions in Lithuania.Technological and Economic Development of Economy 14(2),162–170.

Tamazian,A.,Chousa,J.P.,Vadlamannati,K.C.,2009.Does higher economic and ?nan-cial development lead to environmental degradation:evidence from BRIC coun-tries.Energy Policy 37,246–253.

Toda,H.Y.,Yamamoto,T.,1995.Statistical inference in vector auto-regressions with

possibly integrated processes.Journal of Econometrics 66,225–250.

Tol,R.S.,2008.Climate,development,and malaria:an application of FUND.Climatic

Change 88,21–34.

WHO,2009.Protecting Health from Climate Change:Global Research Priorities.Geneva.World Bank,2010.World Development Indicators —2010.World Bank,Washington

D.C.

Zaman,K.,Khan,M.M.,Saleem,Z.,2011.Bivariate cointegration between energy con-sumption and development factors:a case study of Pakistan.International Journal of Green Energy 8(8),820–833.

Zaman,K.,Khan,M.M.,Ahmad,M.,Rustam,R.,2012.The relationship between agri-cultural technology and energy demand in Pakistan.Energy Policy 44(5),268–279.

Variance Decomposition of CO2 (%)

Fig.5.Variance decomposition result of agricultural technologies development on carbon emissions.

1639

K.Zaman et al./Economic Modelling 29(2012)1632–1639

amongbetween的区别用法全

among between为近义词，皆可表示“在……之间”，但用法大不相同，现归纳比较如下： 一、among一般用于三者或三者以上的“在……中间”，其宾语通常是一个表示笼统数量或具有复数意义的名词或代词。 His house is hidden among the trees． 他的房子隐藏在树林之中。 She sat among the children． 她坐在孩子们中间。 二、between一般指两者之间，其宾语往往是一个具体数目的人(物)，或者是由and连接的两个具体的人(物)。 There was a fight between the two boys． 这两个男孩间发生了一场格斗。 I am sitting between my parents． 我正坐在我父母中间。 三、把两者以上的为数不多的人或事物单独地看待，用and连接时，要用between；把两者以上的人或事物看成一群、一堆或一组而不是个体时，要用among。 Switzerland lies between France,Italy,Austria and Germany． 瑞士位于法国、意大利、奥地利和德国之间。 The old man’s cottage lies among the trees． 老人的小木屋在树林中。 四、between也可用于三者以上的事物之间，强调一物与数物之间的关系。 The small village lies between the three mountains．

小村庄位于三座大山之间。 I saw something lying between the wheels of the train． 我看见火车轮子之间有什么东西。 五、涉及人或事物之间的区别以及人或事物之间的关系时，一般要用between。 We must find out the difference between the three companies. 我们必须查清这三家公司之间的区别。 The relations between various countries are very important. 各国之间的关系是很重要的。 六、表示“由于……合作的结果”时，要用between。 Between them they landed the fish． 他们协力把鱼拖上了岸。 Between the five companies the project was soon completed． 在五家公司的齐心协力下，这项工程不久就完成了。 七、当and连接三者或三者以上的人(物)而仍然强调两者的并列时，常用between。 The hospital lies between a river and hills． 医院坐落在一条河与群山之间。 The park lies between a road and the woods． 公园位于一条马路与树林之间。 八、在divide,share等表示“分享”之类的动词之后。若接一个表示三者或三者以上的复数名词时，用among或between均可。 The father divided his money among/between his three sons。

四年级一件难忘的事400字作文【五篇】

四年级一件难忘的事400字作文【五篇】 四年级一件难忘的事400字精选作文篇一 在童年里有许许多多的事情就像在海滩上捡贝壳，有绚烂的笑，是开心的往事；有黯淡的，像是勾起一段伤心的往事，都使我非常难忘。 早晨，风和日丽，我去帮妈妈和爸爸买早餐，等我去到早餐店，我发现早餐店旁有一大群人，我带着好奇心走去，让我大吃一惊，我发现那有一位老奶奶绊倒在地上。 我心想：为什么一位老奶奶搬绊倒在地上，但每一个人都无动于衷，还围观老奶奶，真是不尊重老人！我气得暴跳如雷，我就问我旁边的大人：“你们为什么不扶老奶奶”那人就说：“因为最近在新闻里，有很多老人成心绊倒在地上让路人扶起她。”谁知老人就说：扶起他的人是推他的人。老人还说：赔我钱。我听完就有一点不敢拉老奶奶了。 这时，一位青年人走过来，马上扶起老奶奶，旁边的人说，那个青年人真笨，青年人就说：“难道金钱比生活还重要吗？”青年人问奶奶要紧吗？奶奶说，不要紧，谢谢你，小伙子。青年人就说不用谢，说完就走了，我看到青年人的身影，我觉得很惭愧。 这一件事使我非常难忘，假如社会的人都献出一点爱心，那么社会就是充满爱心的。

四年级一件难忘的事400字精选作文篇二 每一个人都有自己最难忘的事，我最难忘的事就是三年级那次集体打连响儿。 记得那一次我们拿着漂亮的连响儿，排着整齐的队伍，伴随着美好的音乐，踏着坚决的步伐，熟练地打了起来。 看到这样整齐划一的队伍，我不由心生骄傲：看来我的努力还是没有白费呀！但放眼又一望，我们四周可以说是人山人海，有无数双眼睛正盯着我们，我心里不知从哪里来了一种莫名的紧张，我头上冒着冷汗，腿不由的发着抖。就在这一霎时，我做错了一个动作，登时，我感觉所有人的目光都投向了我一个人，我这颗本来就不平静的心，现在显得更加紧张了、更加不安了，我一下子都不知该干什么了，我真想有一个洞，让我钻到洞里去，我以前打的是那么灵敏，可现在却有气无力，仿佛有一个小精灵把我这活泼的精神给夺走了，经过漫长的煎熬，我好不容易才等到了结束的那一刻。 我回家把这件事告诉我妈妈，妈妈说：想做好一件事就要加倍的努力，不要认为自己会做了就可以了，妈妈的这次教导，将使我一生受益。 四年级一件难忘的事400字精选作文篇三 我家有各种各样的陶瓷器皿，比如：碗，花瓶，勺子，水杯等。它们形态各异，五彩缤纷。它们站在一起，仿佛都在展示自己曼妙的

人教版四年级(上册)数学专项训练

人 教 版 四年级（上册） 数 学 基 础 知 识 专 项 训 练

人教版四年级上册数学基础知识填空题专项训练 １、由5个千万、4个万、8个十和9个一组成的数是（），读作（），取近似值到万位约是（）。 2、406000000读作（），这个数中的6在（）位上，表示（），改写成用万作单位是（）。 3、一周角=（）平角=（）直角。 4、367÷23把23看作（）来试商比较方便。 5、下午3：00时针和分针夹成的最小角是（）度。 6、在数位顺序表中，从右起第四位是（）位，这个数的计数单位是（），如果这个数位上的数字是8，8表示（）。 7、5个一百万、4个十万、2个千和4个一组成的数是（）。读作（），它有（）个计数单位。 8、在9、8中间添（）个0，这个数才是九千万零八。 9、一个数加上2的和比最小的五位数多1，这个数减2是（ 10、在数位顺序表中，从右起第四位是（）位，这个数的计数单位是（），如果这个数位上的数字是8，8表示（）。 11、5个一百万、4个十万、2个千和4个一组成的数是（）。读作（），它有（）个计数单位。 12、在9、8中间添（）个0，这个数才是九千万零八。 13、一个数加上2的和比最小的五位数多1，这个数减2是（） 14、120分米=（）米 540秒=（）分 72小时=（）天 132个月=（）年 15、计量角的单位是（）。（）是量角的工具。 16、角的大小要看两边（），（）越大，角越大。 17、线段有（）个端点。把线段的一端无限延长，就得到一条（），把线段的两端无限延长，就得到一条（），它（）端点。 18、过一个点可以画（）条直线，过两点可以画（）条直线。 19、按照从大到小的顺序排列下面各数 88000 80800 80008 80080 ________________________________________________ 20、把锐角、平角、钝角、直角、周角按下列顺序排列。 （）＞（）＞（）＞（）＞（） 21、4293÷4口，要使商是二位数，口可以填（）

雅思口语素材汇总之端午节

雅思口语素材汇总之端午节 雅思口语素材:Dragon Boat Festival(端午节) Qu Yuan The Dragon Boat Festival, also called the Duanwu Festival, is celebrated on the fifth day of the fifth month according to the Chinese calendar. For thousands of years, the festival has been marked by eating zong zi (glutinous rice(糯米)wrapped to form a pyramid using bamboo or reed leaves) and racing dragon boats. The festival is best known for its dragon-boat races, especially in the southern provinces where there are many rivers and lakes. This regatta(赛舟会)commemorates the death of Qu Yuan , an honest minister who is said to have committed suicide by drowning himself in a river. Qu was a minister of the State of Chu situated in present-day Hunan and Hubei provinces, during the Warring States Period (475-221BC)(战国时期). He was upright, loyal and highly esteemed for his wise counsel that brought peace and prosperity to the state. However, when a dishonest and corrupt prince vilified Qu, he was disgraced and dismissed from office. Realizing that the country was now in the hands of evil and corrupt officials, Qu grabbed a large stone and leapt into the Miluo River on the fifth day of the fifth month. Nearby fishermen rushed over to try and save him but were unable to even recover his body. Thereafter, the state declined and was eventually conquered by the State of Qin. The people of Chu who mourned the death of Qu threw rice into the river to feed his ghost every year on the fifth day of the fifth month. But one year, the spirit of Qu appeared and told the mourners that a huge reptile(爬行动物)in the river had stolen the rice. The spirit then advised them to wrap the rice in silk and bind it with five different-colored threads before tossing it into the river. During the Duanwu Festival, a glutinous rice pudding called zong zi is eaten to symbolize the rice offerings to Qu. Ingredients such as beans, lotus seeds(莲子), chestnuts(栗子), pork fat and the golden yolk of a salted duck egg are often

2018初中英语词汇之among与between的用法区别

2018初中英语词汇之among与between的用法区别 一般说来，among 用于三者或三者以上的在中间，其宾语通常是一个表示笼统数量或具有复数(或集合)意义的名词或代词；而between 主要指两者之间，其宾语往往是表示两者的名词或代词，或者是由and 连接的两个人或物： They hid themselves among the trees. 他们躲在树林中。 There was a fight between the two boys. 这两个孩子打过一次架。 Im usually free between Tuesday and Thursday. 我通常在星期二与星期四之间有空。 在下列情况，between 可用于三者： (1) 当两个以上的人或物用and 连接时： between A, B and C 在A、B和C 之间 (2) 涉及事物之间的区别或各国之间的关系时： the difference between the three of them 他们三者之间的区别 the relations between various countries 各国之间的关系 (3) 表示由于合作的结果时： Between them they landed the fish. 他们协力把鱼拖上了岸。

(4) 在divide, share 等表示分享之类的动词之后，若接一个表示三者或三者以上的复数名词时，用among 和between 均可：He divided his money among [between] his five sons. 他把钱分给了5 个儿子。

关于难忘的一件事四年级作文3篇

关于难忘的一件事四年级作文3篇 【导语】每个人都有难忘的事，我当然也不会例外。下面是小编为大家整理的关于难忘的一件事四年级作文，仅供参考，欢迎大家阅读。 关于难忘的一件事四年级作文一 六岁那年，发生了一件令我难忘的事情——在商场里我差点儿走丢了！ 那天，天气很冷，我们一家人去商场买东西。买完后，我们在一楼闲逛。走着走着，我松开了妈妈的手，跑去看一款造型独特的吸尘器，当回过头时，爸爸妈妈已经走得无影无踪了。商场里人很多，我非常害怕，心想：“妈妈也一定急坏了！怎么办？” 我在商场里转了一圈，越来越害怕、恐惧，忽然，我想起爸爸的车在路边停着，干脆就“守株待兔”吧！所以就跑去爸爸的车旁边等。过了一会儿，爸爸妈妈终于找到我了，妈妈冲过来，一把把我紧紧地搂进怀中，口里不停的说：“吓死妈妈了，妈妈腿都软了！”然后又语无伦次的夸我聪明，没瞎跑，唉！我心里就像打翻了五味瓶一样，说不出的'滋味儿！ 从那以后，我再也不敢轻易放开妈妈的手了。 关于难忘的一件事四年级作文二

一个美丽的晚霞中，那七元五角的事使我永刻不能忘怀。 我背着书包回了家，对妈妈和蔼地说：“妈咪，我回来了！哦，对了妈咪，老师吩咐我们要买一支黑笔，您可不可以给我两块半。”说完，妈咪点了点头，从黑纹色的包里拿出了两块半，我拿起了钱就往商店里奔驰去。 从商店里拿起了一支晶亮的黑笔，到收银台付了钱，就发现了里头还藏了个五元，我的贪婪之心有苏醒了。付了钱后就在半路上犹豫到底要不要把这五元给妈咪呢？在犹豫时就看见了一个小妹妹，她看见前面的叔叔掉了十元钱，就还给了那个叔叔，我就在想，连一个比我还小的妹妹都那么听话，我不能落后，就跑回了家，把五元还给了妈咪。 做人要道德，道德只是个简单的是与非的问题，实践起来却很难，把五元还给妈咪，一个人要是从小就受到这样的教育的话，就会获得道德实践的勇气和力量。 关于难忘的一件事四年级作文三 在我的脑海里发生过许多难忘的事情，但是有一件事令我记忆犹新，那是发生在去年的一件事。 那是一天下午我在我在学校上学的时候，我借了刘利娜的语文作业抄，下课了，我抄完了。就和女同学玩橡皮筋。正在这时候周老师来了，我们吓得腿都软了。 在回家得路上我心里忐忑不安，心想这样做对不对呢？

2020年四年级数学上册解决问题专项综合练习

2020年四年级数学上册解决问题专项综合练习 1. 某小学学生向汶川地震灾区踊跃捐款，请根据下图填空． （1）______年级的捐资金额最多，是______元． （2）六个年级捐资金额这组数据的中位数是______元． （3）二年级捐资金额是四年级捐资金额的______%． （4）四年级捐资金额比五年级少______%． 2. 特快列车每小时行170千米,普通列车每小时行107千米 （1）特快列车40小时行多少千米？ （2）普通列车40小时行多少千米？ 3. 2010年第六次全国人口普查显示，我国人口总数大约是1339720000 人，读横线的数。 4. 如图是广本汽车销售店2013年一月至五月的销售情况统计图．

请你根据上图，完成以下的填空： （1）______月的销售量最少． （2）二月份的销售量比一月份多______台． （3）五月份的汽车销售量是三月份的______%． （4）四月份的汽车销售量比二月份增加了______%． 5. 下图显示的是某班20人在“献爱心”活动中捐图书的情况，该班级人均捐了多少册书？ 6. 小强拆了甲、乙两架纸飞机，下面是这两架飞机前5次试飞情况的统计图． （1）估一估，前5次试飞，哪一驾纸飞机飞行的距离远一些？ （2）第6次试飞，甲飞机的飞行距离是21米，乙飞机的飞行距离是10米．在图中画出表示这架纸飞机第6次试飞飞行距离的直条，并计算这架纸飞机6次飞行距离的平均数各是多少．

7. 早餐店炸油饼，油锅一次最多能炸2张饼，炸熟一张饼要4分钟（正反面各2分钟）．如果一个客人要9张饼，早餐店老板最快多少分钟可以把油饼给他？ 8. 某机床厂各车间男、女工人统计图． 看上面的统计图回答下面的问题． （1）三个车间共有工人______人，其中女工共______，男工共______人．（2）三个车间平均每车间有______人． （3）第三车间男工人数比第二车间男工人数多______ %． 9. 学校进行团体操表演，每行站20人，正好站24排．如果要站成16排，那么每行需要站多少人？ 10. 50枚棋子围成圆圈，编上号码1、2、3、4、…50，每隔一枚棋子取出一枚，要求最后留下的枚棋子的号码是42号，那么该从几号棋子开始取呢？ 11. 估一估，哪个算式的商最接近圈中的数，画上“√”。 先估算出每个圆中的四个算式的商是多少，再比较一下，看哪个算式的商最接近圈中的数。 12. 小红在计算一个数乘2.5时，忽略了2.5的小数点，得到的结果是75，正确的结果是多少？

雅思口语常用背诵素材

口语常用背诵素材 一，喜好和厌恶： 1.（释放压力）I guess most young people enjoy listening to music. It’s a perfect way to reduce stress/relieve stress. (*It’s a perfect stress-buster.) 2.（休闲）I think the best way to relax and kill time (kick back and relax) is to be with friends. Chatting with them helps me unwind/wind down (* Chatting with them is very therapeutic). 3.（放松）I found it pretty relaxing to flick through a magazine before going to bed (*before hitting the sack/hitting the hay). 4.（运动）Jogging on sunny days and simply basking in the sun(bathing in the sun) is super enjoyable(pleasurable). /Jogging is my favorite workout. It can always cheer me up after I’ve been down and depressed. And it can help me shed some unwanted weight. 5.（喜欢，提升心情）I’m quite into watching sitcom (I’m fascinated by, I’m crazy about, I adore, I’m very fond of...). Spending 20 minutes in front of the screen and having a good laugh after dinner really puts me in a better mood/ switch my mood/ lift my spirits. 6.（天气）I fancy spring most compared to the other three. Summer is simply too hot and stuffy (*muggy), and you can’t stay out for two minutes without getting sweaty and smelly. Autumn is too dry and winter too freezing cold. 7.（电影）I’m a movie buff (Movies are my biggest pastime), and I would either catch one on my couch or go to the movie theatre when they have the one I like on the big screen./ It's a great form of relaxation for me to while away the hours of a long flight, to keep my family together on the sofa, and to give me a bit of a thrill. 8.（无聊困难）I’m terrible at what I study now./(History is never my forte/ my strong suit). The classes are kind of a drag (It’s super dull/ *It’s mind-numbing), and there’s always loads of (tons of) homework to do. Memorizing those facts and years is a lot of effort (is tricky; is no picnic; is challenging for me). 9.（不能忍）I can’t stand (I hate, I totally dislike) the busy traffic in my city. I’m sick and tired of always getting stuck in traffic for a long time during rush hours. It really bothers me (It drives me crazy, *It drives me up the wall). 10. （受欢迎）Hip-hop is really trendy (is catching on, is all the rage) among young people these days. 二，时间和地点 11. （优点）What’s great about my home town is that there are plenty of shopping malls, coz I’m a shopaholic and I can shop for hours. 12. （远）The stadium is quite far away from where I live, and every time I want to do there, it takes me roughly 40 minutes by bus to arrive. (It’s one-hour drive from the city center.) 13. （方便）My apartment is in the center/heart of the city, a handy location where I can find supermarkets and clubs right on my doorstep. It’s a bit noisy though. 14. （近）I’m a movie-goer and and there’s a movie theater pretty close to my home, so I go there quite often (frequently). (close to my home= *within walking distance of my home , *in close proximity to my home) 15. （经常）I have a heavy workload at school, so I have to go to the library to study pretty much

英语地点介词的正确使用方法

英语地点介词的正确使用方法 地点介词主要有at ，in，on，to，above，over，below，under，beside，behind ，between。它们的用法具体如下： 1、at （1）at通常指小地方：In the afternoon，he finally arrived at home。到下午他终于到家了。 （2）at通常所指范围不太明显，表示“在……附近，旁边”：The ball is at the corner。球搁在角落里。 2、in （1）in通常指大地方：When I was young，I lived in Beijing。我小时候住在北京。 （2）在内部：There is a ball in in the box。盒子里有只球。 （3）表示“在…范围之内”（是从属关系）： Guangdong lies in the south of China。深圳在中国的南部。 3、on

（1）on主要指“在……之上”，强调和表面接触： There is a book on the table。桌上有一本书。 （2）表示毗邻，接壤（是相邻关系）： Canada lies on the north of America 加拿大在美国的北边（与美国接壤）。 4、to 主要表示“在……范围外”，强调不接壤，不相邻。 Japan is to the east of China。日本在中国的东面。 注意： （1）at 强调“点”，on 强调“面”，in 强调“在里面”，to 表示“范围外”。 （2）on the tree：表示树上本身所长着的叶子、花、果实等 in the tree：表示某物或某人在树上 on the wall：表示在墙的表面，如图画、黑板等 in the wall：表示在墙的内部中，如门窗、钉子、洞、孔 5、above

四年级难忘的一件事作文400字

每个人的每一天都充满着快乐、伤心、害怕或者难过，并且会有一些难忘的事情。你难忘的一件事是什么呢？下面是小编和大家分享的“四年级难忘的一件事作文400字”，一起来看看吧，希望大家喜欢。 四年级难忘的一件事作文400字（一） 虽然我才上四年级，但是我的生活里也有很多难忘的事。我就给大家讲一件让我难忘的事吧。有一次爸爸让我做大米饭，给我留下了深刻的印象。 那天中午，爸爸对我说：“今天中午你来帮妈妈做大米饭吧，正好也锻炼锻炼。”我听了以后高兴地说：“好啊，小菜一碟。”说完以后我就开始动手了。我先把大米放在盆里淘干净，再倒进锅里，放在炉子上就到客厅去看我喜欢看的电视去了。在我看得正高兴的时候，忽然就闻到厨房里传出来一股烧糊的味儿来。我一看表，已经过去了半个小时了，我马上跑进厨房，把锅端下来。打开锅盖，就看见了变黑的锅底。可我没有放弃，又做了一次。 我又把米淘干净倒进锅里以后，我又去写作业去了。过了一会儿，我又闻到了那股烧糊的味道。我跑到厨房一看，锅底又黑了。这一看，我的眼泪都快掉下来了，这可怎么办啊？这时候，爸爸来了，对我说：“不用哭，做什事都要专心，再来一次。”我点了点头。第三次，我终于把大米饭做熟了，看见自己的成果，我感到很高兴。 这件事让我明白了：做什么事都要专心致志，不能三心二意。 四年级难忘的一件事作文400字（二） 今天，是我和姐姐第一次去买菜。 妈妈给了我们钱，说：＂要注意安全哦。＂我们说：＂知道了。＂ 一路上，我的心在扑通扑通地跳。来到菜市场，我都目瞪口呆了，各种各样的蔬菜放在我面前，有西兰花、芫茜、冬瓜……还有许多嘈杂声呢！ 我回忆起妈妈要我买的菜，哦！要买鱼。我走进市场左看看，右望望，嘿，找到了！我走过去，正准备对卖鱼的叔叔说话，一位阿姨便先说了一步。阿姨买完了鱼，我又准备说，谁知，又有一位阿姨要买。5分钟过去了，我还没买到，我着急了，对着叔叔大声说：＂叔叔，请给我一块鲜鱼肉！＂叔叔笑眯眯地说：＂你要多少呀？＂＂4元。＂我回答说。叔叔弄好了鱼，用袋子好了给我，我付了钱并说了一声＂谢谢＂就走了。 我又想到要买菜，对了，还有芫茜！我找到了买我所需要的地方，就跟那位婆婆要了一点。当我走出市场时，天空下起了牛毛似的雨，我跟姐姐说：＂我们快走吧！＂接着，我们骑着自行车，飞快地奔回家。 骑到半路，雨就更大了，我们到了一棵树下遮雨，但是好久都不见天空好转。为不拖延时间，我和姐姐顶着风冒着雨冲回家。

四年级上册数学专项练习

薄弱环节专项全练全测(一) 数与代数【薄弱点一】大数读、写的准确性 一、读出或写出下列各数。(8分) 30050082 读作：______________________ 3960400090 读作：______________________ 一千零四十万四千零二十写作：________________ 七千零三亿零二十万零五写作：________________ 二、求近似数。(8分) 1．省略万位后面的尾数。 16493560≈9528641≈ 2．省略亿位后面的尾数。 2709546312≈9953364778≈ 三、选择。(6分) 1．下面三个数中，一个0也不读出来的是( )。 A．50000800 B．50080 C．5008000 2．下面各数中，用9，8，7，5，0这五个数字组成的最接近8万的数是( )。 A．89750 B．80579 C．85079 3．74□7600000≈75亿，□里最大能填( )。 A．8 B．9 C．7 【薄弱点二】乘、除法计算的准确性 四、改错。(12分)

五、笔算下面各题，带※号的要验算。(24分) 240×38＝207×40＝※360×50＝ 380÷70＝ 694÷72＝※633÷21＝ 【薄弱点三】用乘、除法知识解决问题的正确性 六、解决问题。(34分) 1．一块长方形草坪的面积是120平方米，改建后，长扩大到原来的4倍，宽扩大到原来的3倍，改建 后草坪的面积是多少？(8分) 2．某花店在教师节到来之际，搞促销活动：每盆月季花16元，买3盆送1盆。 照这样计算，买4盆花，每盆比原来便宜多少钱？(8分) 3．一根木头长15米，把它平均分成5段，每锯一段需8分钟，锯完一共要花多少分钟？(8分) 4．一辆长途客车6小时行了348千米。照这样的速度，它12小时可以行多少千米？(10分) 解法1：先求客车1小时行驶多少千米，再求12小时可以行驶多少千米。 解法2： 先求12小时中有几个6小时，再求几个348千米是多少。 【薄弱点四】合理安排时间 七、小红家来了客人，她要沏茶招待客人。(8分) 找茶叶：1分钟沏茶：3分钟接水：1分钟洗杯子：2分钟洗水壶：2分钟烧水：10分钟 应该怎样安排时间才能使所用时间最短？至少要多长时间？

雅思口语素材

雅思口语素材 Document serial number【LGGKGB-LGG98YT-LGGT8CB-LGUT-

Useful Expressions: Words and phrases Friends and communication: solidify/ strengthen/ enhance/ promote communication / connection with mutual understanding relationship network/circle of f r i e n d s cultivate/develop friendship with s b . keep steady relationship with sb. establish interpersonal networksac build up the social circle spur message transmission Knowledge and experience widen one’s outlook broaden one’s vision/horizon acquire knowledge and skills comprehensive/overall quality

expand/enlarge one’s scope of knowledge knowledge reserve/base/storage theoretical knowledge practical skills social experience broaden one’s knowledge base promote one’s overall/ comprehensive competence accumulate experiences learn lessons from past experiences Work and experience the scarcity of employment o p p o r t u n i t i lay the foundations for career p r o s p e r i t y

四年级作文 一件难忘的事

大年三十，踩气球 白雪皑皑的夜晚，从一间小屋里传出了阵阵欢快的笑声。那是大年三十，人们正忙着发压岁钱。只见家人们从裤兜里掏出一张比一张大的钱，塞到满怀欣喜的孩子们的手里。我们拿着钱就去买了许许多多的气球。 我们一家人开始给气球打气。我们不知疲惫地打了一个又一个。不一会儿，整整地堆满了一间大房子。气球的颜色和形状各不相同，有大的、有小的、红的、绿的、白的……在灯光的照耀下，非常漂亮。 我挑了一些漂亮点儿的气球，挂了起来，把客厅装扮得像春节联欢晚会现场一样光彩亮丽。时钟刚好走到12点时，我便急得像上锅的蚂蚁一样，立即跳向气球堆。“啪啪……”气球发出响亮的爆炸声。这清脆的爆炸声吸引了爸爸妈妈和弟弟的围观。他们被我那热乎劲儿感染了，也过来跟我一起踩气球。“噼噼啪啪……”一阵响，就像放鞭炮一样，既吓人又好玩。清脆的爆炸声给热闹的夜晚增添了一份别具一格的色彩。 不一会儿，整整一屋的气球就只踩剩一个了。我上前去一踩，没想到它竟然跑了，气得我张牙舞爪直瞪眼，恨不得一脚把它踩扁。我那滑稽的举动惹得爸妈们突地大笑起来。我不服气，气鼓鼓的又跑上去，对着气球狠狠地一踩，心想这回肯定能踩扁它。可谁知，我一个不小心，脚下一滑，便跌坐在气球上。“啪……”完了，气球在我的屁股上炸开了花。这下子，可把我的爸妈们逗得更乐了。 欢快的笑声在小屋的四周回荡，也回荡在我生命的旋律中…

捉螃蟹 记得去年冬天的一个早晨，天气晴朗，阳光明媚，我和表妹一起到河边的沙滩上捉螃蟹。 河里的水非常的少，到处都是石头。螃蟹，就藏在这些奇形怪状的石头下面。我们一边沿着岸边走，一边翻着旁边的石头。突然，表妹发现了一只螃蟹，激动万分地对我说：“哥哥，这块石头下面好像藏了一只螃蟹。”我们连忙轻轻地走过去，慢慢地蹲下去，小心翼翼地把石头搬开，快速伸过手去捉它，没想到螃蟹用两只大钳子把我的手狠狠地夹住了，痛得我脸都涨红了。我赶紧用力的把手往外一甩，才摆脱掉这该死的螃蟹。“呀！流血了！”表妹惊呼道。我低头一看，才发现是自己的手被螃蟹夹了一条大口子，直流血。我淡然地擦擦手说没事，可怎知表妹被我那流血直流的手吓得大哭起来。忍者疼痛，我迅速一抓，就把螃蟹扔进了瓶子里，表妹立即破涕为笑。 我们终于捉了一只螃蟹，心里有说不出的高兴，我那鲜红的手指和表妹那还挂着晶莹泪珠的脸，在阳光下，闪闪发光……

四年级数学上册专项练习

填空题 1、当除数是34时，试商时可以把除数看作( )，这样初商容易偏( )。 2、（）个26相加的和是468；（）比12个15多20。 334＝21），这时被除数是（）。 4、在括号里填上合适的数。 480秒=（）分540厘米=（）分米624时＝（）日 5、我们戴的红领巾上有一个（）角，两个（）角。 6、钟面上，分针转动360度，相应地时针转动（）度。 从3：00走到3：15，分针转动了（）度。 6点时，时针和分针所组成的角是（）度，是（）角， 3点时，时针和分针所组成的角是（）度，是（）角。 7、把“78÷26=3，26+3=29”合并成一个综合算式是（）。 8、在5○1÷58中，如果商的最高位在十位上，○中最小填（），还可以填（）。如果3□2÷36的商是一位数，□里的数最大可以填（），最小可以填（）。在算式□17÷53中，要使商是两位数，□最小填（）；要使商是一位数，□最大填（）。 9、在公路上有三条小路通往小明家，它们的长度分别是125米、207米、112米，其中 有一条小路与公路是垂直的，那么这条小路的长度是（）米。 10、李阳从1楼到3楼用了12秒，她从一楼到六楼需要（）秒。 11．二百零六亿八千万写作（），改写成用“万”作单位的数是（）万，用“亿”作单位这个数的近似数是（）亿。 12．2个千万、7个万、8个百和5个十组成的数是（），这个数读作（）。 13．由6、7、5、1、0组成的最大数是（），最小数是（）。14、计算除法时，错将除数36看成63，结果得到商12。请你帮他算一算，正确的商应该是（）。

15．一个边长24厘米的正方形面积是（）平方厘米。 16、把两道算式组成综合算式，再用递等式计算。 14×2=28 21×4=84 10×5=50 28-15=13 200-84=116 30＋50=80 （）（）（） 选择、判断题 1、30度的角被投影仪投到屏幕上时角就变大了。（） 2、570÷40＝14……1。（） 3、在方向板上，北和西南之间夹角是135°。（） 4、在同一平面内，两条直线不是相交就是平行。（） 5、在同一平面内，两条直线不是平行就是垂直。（） 6、4个同样大的正方体可以拼成一个较大的正方体。（） 7、在10倍的放大镜下看15度的角就变成了150度。（） 8、六位数一定比七位数小。（） 9、平角就是一条直线，周角就是一条射线。（） 10、三位数除以两位数，商不可能是三位数。（） 11、三位数除以两位数，商最多是两位数。（） 12、过一点能画无数条直线。（）13．两条直线相交成直角时，这两条直线就互相垂直。（）14．观察物体时，在同一位置看到相同的形状可能有不同的摆法。（）15、两条不相交的直线叫做平行线。（） 1、在4□7÷46的商是两位数，□中的数最小是（）。 ①7 ② 6 ③5 2、想使物体从斜面上向下滚动时尽可能地快，下面的选项中，木板与地面的夹 角是（）度最符合要求。 ①20 ②38 ③10 ④80

雅思口语素材

U s e f u l E x p r e s s i o n s: Words and phrases Friends and communication: mutual understanding solidify/ strengthen/ enhance/ promote communication / connection with relationship network/circle of friends cultivate/develop friendship with sb. keep steady relationship with sb. establish interpersonal networksac build up the social circle spur message transmission Knowledge and experience widen one’s outlook broaden one’s vision/horizon acquire knowledge and skills comprehensive/overall quality expand/enlarge one’s scope of knowledge knowledge reserve/base/storage theoretical knowledge practical skills social experience broaden one’s knowledge base promote one’s overall/ comprehensive accumulate experiences competence learn lessons from past experiences Work and experience the scarcity of employment opportunities lay the foundations for career prosperity immerse oneself in endless job tasks boost/augment/enhance efficiency be adept in boost one’s c ompetitiveness Health and pressure diminish individuals' leisure time drive away lassitude lighten one’s burden homework/workforce overload

难忘的一件事作文400字四年级_1

难忘的一件事作文400字四年级 难忘的一件事作文400字四年级 最令我难忘的一件事，就是偷吃四色小辣椒了，那四色辣椒的滋味，真是难以形容，令人难忘。在我家楼下有一个小菜园，那里是爷爷的乐园，他每天都会去那，乐呵呵地给他种的蔬菜浇水。在这个菜园里，有白菜、罗卜和辣椒。最引起我主意的就是辣椒了。爷爷种的不是一般的辣椒，是四色小辣椒。四色小辣椒是一种能变色的小辣椒，在每个季节变一种色，春天是绿色、夏天是黄色、秋天是紫色、冬天是红色，非常神奇。一天我在楼下散步，当时正是秋天的一个。我走到菜园时，看见里面的小辣椒，紫紫的，看起来很好吃。心想：着么紫的小辣椒难道还会辣吗？肯定能好吃，心中便有了一种想法，摘一个尝一尝，反正爷爷也不在。我以飞一般的速度跑了过去。用手一拽，边摘了下来。我像得了一件宝贝似的，小心翼翼地捧着四色小辣椒，向家跑去。到了家，见没人，才放了心。跑进厨房把四色小辣椒洗干净，然后把放四色小辣椒放进嘴里嚼，不嚼不要紧，一嚼可坏了。顿时，舌头、喉喽就像要喷火一样，辣的我说不出话来。我跑到水

龙头前大口大口的喝起水来。这才好点，没想到这四色小辣椒比别的辣椒辣上十倍。这件事一直刻在我的心头，甩也甩不掉呢。 四年级:戴恋佳 难忘的一件事作文400字四年级 最令我难忘的一件事，就是偷吃四色小辣椒了，那四色辣椒的滋味，真是难以形容，令人难忘。在我家楼下有一个小菜园，那里是爷爷的乐园，他每天都会去那，乐呵呵地给他种的蔬菜浇水。在这个菜园里，有白菜、罗卜和辣椒。最引起我主意的就是辣椒了。爷爷种的不是一般的辣椒，是四色小辣椒。四色小辣椒是一种能变色的小辣椒，在每个季节变一种色，春天是绿色、夏天是黄色、秋天是紫色、冬天是红色，非常神奇。一天我在楼下散步，当时正是秋天的一个。我走到菜园时，看见里面的小辣椒，紫紫的，看起来很好吃。心想：着么紫的小辣椒难道还会辣吗？肯定能好吃，心中便有了一种想法，摘一个尝一尝，反正爷爷也不在。我以飞一般的速度跑了过去。用手一拽，边摘了下来。我像得了一件宝贝似的，小心翼翼地捧着四色小辣椒，