How will the emission trading scheme save cost for achieving China's 2020

How will the emissions trading scheme save cost for achieving China’s 2020carbon intensity reduction target?

Lian-Biao Cui a ,b ,Ying Fan b ,?,Lei Zhu b ,Qing-Hua Bi b

a School of Management,University of Science and Technology of China,Hefei 230026,China

Center for Energy and Environmental Policy Research,Institute of Policy and Management,Chinese Academy of Sciences,Beijing 100190,China

h i g h l i g h t s

Establish an inter-provincial emissions trading model of China.

The economic performance of carbon emission trading in China is modelled.

Total abatement cost could be reduced by 23.67%with the uni?ed emissions trading market. The emissions trading market may result in a carbon price of 53yuan/tCO 2for the 2020target.

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

Received 31October 2013

Received in revised form 10April 2014Accepted 14May 2014Available online xxxx

Keywords:

Carbon emissions trading Abatement cost Cost-saving effects

Computable general equilibrium model China

a b s t r a c t

Chinese government has committed to reduce its carbon intensity by 40–45%over the period 2005–2020at the 2009Copenhagen Summit.To achieve the target in a cost-effective way,China is signaling strong intentions to establish emissions trading scheme,and presently seven pilots have been established.This paper focuses on the cost-saving effects of carbon emissions trading in China for the 2020target.First,an interprovincial emissions trading model is constructed.Then,three kinds of policy scenarios,including no carbon emissions trading among provinces (NETS),the carbon emissions trading only covering the pilots (PETS),and the uni?ed carbon emissions trading market (CETS),have been designed.The results show that China needs to reduce its emissions by 819MtCO 2for achieving the 42.5%reduction in carbon inten-sity over the period 2005–2020.The PETS and the CETS,which may result in a carbon price of 99yuan/tCO 2and 53yuan/tCO 2,could reduce the total abatement costs by 4.50%and 23.67%,respectively.This paper also ?nds that the carbon emissions trading could yield different impacts on different provinces,and the cost-saving effects of the eastern and western provinces are more pronounced than the central provinces.Necessary sensitivity analysis is also provided at the end of the research.These ?ndings may be useful for promoting the development of carbon emissions trading in China.

1.Introduction

Chinese government has announced the reduction of its carbon emissions per unit of GDP (also called carbon intensity)by 40–45%from the 2005levels by 2020at the 2009Copenhagen Summit.To achieve the commitment,China’s Twelfth Five-Year Plan (2011–2015),which adopts a master plan for its economic and social development each ?ve years,has put forward a national target for reducing the nation’s carbon intensity by 17%.This national target has been disaggregated at the provincial level,assigning the responsibility for different levels of carbon intensity reduction to 31provinces,and is a mandatory constraint of the provincial economic development [1].However,China has a vast territory,and different provinces in China usually have different resource endowments and economic development levels.It implies that the marginal abatement cost (MAC)in the different provinces could also be different.Therefore,how to reduce the total costs by enhancing cooperation between provinces is an important issue.

The emissions trading scheme (ETS)is one of the two main cost-effective mechanisms for controlling carbon emissions,and the other one is carbon tax.As for ETS,the right to emit carbon is a tradable commodity,and the participants with high abatement costs will spend money on buying emission rights to emit more,while the participants with low abatement costs are being rewarded for their more emissions reduction.As a cost-effective mechanism,ETS has received increasing attention in different

?Corresponding author.Tel./fax:+861062542627.

E-mail address:yfan@https://www.360docs.net/doc/b02685570.html, (Y.Fan).

countries and regions,especially from the European Union [2,3].Most recently,China also signals strong intentions to establish a national carbon trading system.As a ?rst step,the National Devel-opment and Reform Commission of China declares that seven pilots including the cities of Beijing,Chongqing,Shanghai,Shenz-hen,Tianjin,and the provinces of Guangdong and Hubei have been approved to establish carbon emissions trading projects during the Twelfth Five-Year Plan.With experience from these pilots,China will promote to establish a uni?ed emissions trading market by 2020[4].It can be seen that the ETS will play an important role in reducing carbon emissions for China in the near future.

The research on the ETS has a magni?cent foundation in theory.For example,Coase ?rst proposes the use of property rights to solve externality issues [5].Dales introduces the concept of property rights into the ?eld of contamination control,and ?rst proposes the concept of emissions trading scheme [6].Montgom-ery points out that the ef?cient equilibrium of ETS is independent of initial allocation if the market is in perfect competition [7].Tie-tenberg holds on the view that the emissions trading will result in all ?rms bearing the same marginal abatement costs,and the soci-ety will achieve Pareto optimality in the case of no transaction costs [8].Rose points out that the ETS is not only cost-effective,but also embodies the spirits of equity [9].Sterner argues that the ETS is more effective than administrative commands,but the environmental issues cannot be solved without government regulation because of its particularity [10].

In addition to theoretical analysis,some researches focused on the application aspects of the ETS.For example,Grubb evaluates the economic implications of achieving the Kyoto Protocol targets,the results show that the cost-saving effect is obvious if the global emissions trading market could be quickly and effectively implemented [11].Rose et al.study the cost-saving effects of the inter-regional emissions trading markets in the United States,and found that the overall cost-savings increases with increasing geographic scope [12].Massetti and Tavoni propose a fragmented cap-and-trade scheme with a speci?c regional market in mind for developing Asia,and argue that creating two large trading markets would result in small ef?ciency losses,while generating more reasonable regional incentives and transfers [13].

As for the ETS in China,the scienti?c research is still at an initial stage.For example,Zhou et al.evaluates the economic perfor-mance of an interprovincial emissions trading scheme in China.They adopt ?ve equity criteria to conduct the initial quote alloca-tion,and the results indicate that the total abatement cost could decrease by over 40%[14].Zhang et al.discuss the economic impacts of emissions trading scheme in China for achieving the 17%reduction in carbon intensity during the Twelfth Five-Year Plan,and they argue that the uni?ed emissions trading market could result in 25%lower welfare loss relative to the no emissions trading case [1].Cui et al.study the cost-saving effects of emissions trading scheme in achieving the reduction targets in the Twelfth Five-Year Plan,the results show that the national abatement cost could decrease more than 20%through implementing the uni?ed emissions trading market [15].So far,it seems that limited research focuses on the evaluation of emissions trading markets in China for the 2020target.

The Twelfth Five-Year Plan will pass soon,and the prospect for a uni?ed emissions trading market in China appears distant at present.As things are,China will most likely establish a uni?ed emissions trading market in the Thirteenth Five-Year Plan.Against this background,this paper focuses on the cost-saving effects of emissions trading scheme of China in achieving the 2020target (i.e.40–45%reduction in carbon intensity relative to the 2005lev-els by 2020).First,an interprovincial emissions trading model is constructed.Then,three kinds of policy scenarios,including no emissions trading scheme (NETS),the coverage of emissions trad-

ing scheme that only contains the pilots (PETS),and the uni?ed emissions trading market (CETS),have been designed.The rest of this paper is organised as follows.Section 2develops an interpro-vincial emissions trading model.Section 3introduces the data preparation.Section 4details the results of different policy scenar-ios.Section 5provides a sensitive analysis.The conclusions and the discussion are presented in Section 6.

2.Interprovincial carbon emissions trading model

To establish an interprovincial emissions trading model in China,we need ?rst estimate the marginal abatement cost (MAC)for each province.In this paper,we adopt the coordinate transla-tion technique (CTT)to obtain the provincial MACs on the basis of the national MAC.MAC re?ects the additional costs of reducing the last unit of CO 2and is upward-sloping,in other words,the marginal abatement cost will increase when more abatement is undertaken [16–19].

2.1.National marginal abatement cost

There are two main methods to derive MAC curves.The ?rst method is the top-down modelling approach,which uses macroeconomic models to control carbon emissions through the imposition of carbon tax [20,21].The other method is the bottom-up modelling approach.With the detailed technical infor-mation of emissions reduction,as well as the availability of various energy technologies and their economic costs,the MAC is esti-mated with an optimisation model [22–25].In this research,the former method will be used.The CHINAGEM model,which is a dynamic version of computable general equilibrium (CGE)model of China,is used to calculate the national MAC.The bottom-up modelling approach will be discussed in the sensitive analysis.CHINAGEM is a large system of equations describing the behav-iour of economic agents,the linkages between sectors of the econ-omy,and between China and the rest of the world.It applies a nested structure to represent production technology,and energy can be substituted by capital and labour,which is a reasonable assumption for Chinese industrial sectors [26].The core part of CHINAGEM contains widely accepted economic theories,such as consumer and producer optimisation behaviours.CHINAGEM sim-ulations begin from a base year (i.e.2002),for which a detailed input–output table is available.The input–output table is used to construct a model database that portrays a picture of the Chinese economy for that year,and the model database provides an initial solution for the CHINAGEM equation system [27].The construction of the baseline in this paper can be divided into two parts:the his-torical calibration and the forecast simulations.As for the historical period (2002–2010),we will calibrate the model with latest data,and then the policy simulation will be conducted in the forecasting period (2011–2020).

2.1.1.The baseline construction

Regarding the historical simulation,the CHINAGEM model is calibrated to data from a variety of economic and energy sources.In sum,three kinds of indicators are used in our research.The ?rst one is macroeconomic indicators,including the real GDP,invest-ment,private consumption and population,and the annual growth rates of these indicators have been used in our calibration.For the data sources,we refer to the China Statistical Yearbook 2013[28].The second one is environmental indicator such as CO 2emissions,and we adopt the latest information provided by the International Energy Agency (IEA)to calibrate the national emissions of China over the period 2002–2010[29].The third one is energy indicators,which consist of coal,crude oil,natural gas,re?ned oil and

2L.-B.Cui et al./Applied Energy xxx (2014)

xxx–xxx

electricity.The annual output changes of these energy commodi-ties will be used for the calibration.For the data sources,we refer to the China Energy Statistical Yearbook 2013[30].

For the forecasting period,this paper keeps the extrapolations of trends in the historical calibration and assumes that the annual GDP growth rate of China maintains 7.5%over the period 2011–2015.As China may experience a slowdown of economics in the Thirteenth Five-Year Plan,we assume that the national annual GDP growth rate is 5.5%over the period 2016–2020.The annual carbon emissions results from fossil fuels in the forecasting period are endogenous.For the GDP assumptions,this paper refers to sev-eral papers [31,32].More GDP growth scenarios will be discussed in the sensitive analysis.

2.1.2.The baseline simulation

The baseline scenario of China’s economic over the period 2002–2020is displayed in Fig.1,which shows that the national GDP increases from 29.19trillion yuan (the constant price in 2002,the same hereinafter)in 2010to 54.76trillion yuan in 2020,and mean-while,the carbon emissions increase from 7.20GtCO 2(Giga tons of CO 2,the same hereinafter)to 10.26GtCO 2,thus the carbon inten-sity decreases from 2.47tCO 2/10,000yuan to 1.87tCO 2/10,000yuan,and a decline of 24.07%has been achieved,with an average of 2.72%.The national carbon intensity will decrease by 37.51%relative to the 2005levels by 2020,which is smaller than the 40–45%target.It implies that more additional measures are needed for China to achieve the proposed intensity target.

The natural decline of carbon intensity in the baseline is reason-able for two reasons.Firstly,the national carbon intensity has reduced by 17.46%during the Eleventh Five-Year Plan,this is because China has adopted many mandatory measures,including an industrial energy ef?ciency mandate,targets for the deploy-ment of renewable and nuclear electricity generation,and reduced subsidies to China’s energy-intensive,export-oriented sectors [1].The reduction becomes more dif?cult when more abatement is undertaken,therefore,the 10.73%reduction in carbon intensity during the Twelfth Five-Year Plan should be less than that in the Eleventh Five-Year Plan.Secondly,IEA shows that the average annual decline of carbon intensity over the period 1995–2005

where the national carbon emissions in 2020are assumed to be exogenous,and the associated carbon tax is set to be endogenous.In each simulation,we shock the national emissions reduction with a ?xed level,and the corresponding carbon tax will be calculated with the CHINAGEM model.The simulation results are presented in Table 1.Assuming zero intercept,the functions are,

MAC 2020eR T?à679:63?ln e1àR Te2T

where MAC is the national marginal cost (yuan per ton CO 2)and R is the ratio of emissions reductions.2.2.Provincial MACs curves

To get the provincial MACs curves,this paper adopts the CTT approach [34].Based on the estimation by Nordhaus,Bohm and Larsen derive the MACs for other countries by modifying that of the United States,taking the difference of the national carbon intensities into account [34].With the same approach,Okada investigates the international environmental agreements in a game-theory framework,and Li et al.discuss how to allocate emissions allowance among provinces in China with the minimum total cost,and Cui et al.study the cost-saving effects of emissions trading scheme in achieving the reduction targets in the Twelfth Five-Year Plan [15,35,36].

To simplify the research,several assumptions have been made.Firstly,this paper assumes that all the reduction behaviour will only occur in 2020.It can be used for avoiding discussing the dis-tribution burdens in various years.Secondly,it is assumed that the relative relationship between provincial CO 2intensities remain unchanged with different carbon intensity targets,which may be reasonable in a short period.Thirdly,we assume that the interpro-vincial emissions trading are in perfect competition and complete information,and transaction costs will not be involved.

Fig.2illustrates the national MAC curve,and the abscissa is the ratio of carbon intensity reduction,while the ordinate represents the marginal cost.Let e denotes the national carbon intensity,which can be regarded as the weighted average of provincial car-bon intensities.Provinces with lower carbon intensities are Fig.1.GDP,CO 2emission and carbon intensity in the baseline.

L.-B.Cui et al./Applied Energy xxx (2014)xxx–xxx 3

if it were to reach the steepness of the MAC curve of province l .Hence,

r l ?1à

e l e

e3T

Then,for province i (no matter low carbon intensity or high car-bon intensity),the marginal abatement cost MC i is computed as,

MC i eR i T?MAC eR i tr i TàMAC er i T?b ln 1à

R i 1àr i

e4T

where R i is the ratio of emissions reduction,MAC is the national marginal abatement cost.Formula (4)can be written in another form,

MC i eA i T?b ln 1à

A i

E i e1àr i T

e5T

where A i is the quanti?ed emissions reduction,E i is carbon emis-sions in the benchmark.Therefore,the total abatement cost C i satis?es,

C i eA i T?

A i

b ln 1à

E i e1àr i T

dx ?àb E i e1àr i TàA i ? ln 1àA i

E i e1àr i T

àb A i

e6T

2.3.Carbon emissions trading model

The total costs for province i in ETS include two parts.The ?rst one is the abatement cost of emissions reduction A i .The other one is the expenditure to buy emission rights through emissions trad-ing market.The objective function is,

p i ?C i eA i Ttt ?eq i àA i T

e7T

where q i is the initial reduction quota,and t is the carbon price.

Regarding the ?rst order conditions,@p i

?0,we have,A i ?E i e1àr i T?1àexp et =b T

e8T

With the constraint condition P

i A i

i q i ,

the equilibrium car-

bon price t ?satis?es,

t ?

?b ln 1àP i q i

i E i e1àr i T

e9T

To summarise,the problem can be simpli?ed to,

A ?i ?E i e1àr i TP k q k P k E k e1àr k Tp i ?àb E i e1àr i TP k q k P k E k e1àr k Tàb E i e1àr i Tln 1àP k q k P k E k e1àr k T

tb q i ln 1àP k

q k P k E k

e1àr k

>>>>>>><>>>>>>>:e10T

3.Data preparation

3.1.The calculation of provincial shift distances

In Section 2.2,we detail how to derive the provincial MACs by modifying that of the nationwide.The shift distance is an important parameter need to be estimated.As illustrates in For-mula (3),the shift distance for each province is determined by the difference between its carbon intensity and the national carbon intensity.The national carbon intensity in 2020can be obtained from the baseline simulation.To estimate the provincial carbon intensity,this paper simply assumes the provincial CO 2emissions in 2020equal to the national emissions in 2020multiplied by their emissions shares in 2010,and similarly the provincial GDP in 2020in baseline can be estimated as the national GDP in 2020multi-plied by their GDP shares in 2010.

3.2.Provincial CO 2reduction targets allocation

To allocate the national carbon intensity reduction targets ratio-nally across Chinese provinces,many studies have been conducted while there are still debates on this issue [36–38].For example,Li et al.adopt a nonlinear programming model to obtain the optimal CO 2abatement allocation among provinces in China with a mini-mum total abatement cost [36].Wei et al.develops a CO 2abate-ment capacity index (ACI)based on weighted equity and ef?ciency indexes,and they ?nd that there exists a large gap in potential reduction capability and marginal abatement cost among the eastern,middle and western regions [37].Yu et al.propose a PSO–FCM–Shapley approach to allocate carbon emission reduction target among 30provinces,and the results indicate that provinces with high cardinality of emissions have to shoulder the largest reduction,whereas provinces with low emission intensity met the minimum requirements for emission in 2010[38].In sum,assigning targets at the provincial level is a very complicated problem.The reasonable allocation may need a wide variety of considerations—marginal cost of abatement,equity,perceptions of fairness,sector structure,and level of development,and so on.This research assumes that the approach to allocate carbon emissions reduction target among provinces in the Twelfth Five-Year Plan will be employed to 2020as well.Actually,to achieve the 17%reduction in the carbon intensity over the period 2010–2015effectively,the Chinese government has assigned different levels of reduction targets to 31provinces with negotiation among stakeholders (see Table A1),taking the difference of the provincial development stages into account,which is intended to ease the pressure on less af?uent regions or regions targeted for accelerated development.Therefore,this allocation partial embodies the principal of fairness.However,the provincial targets are intensity

Table 1

Fig.2.Derivation of provincial MACs [15,35,36].

4L.-B.Cui et al./Applied Energy xxx (2014)xxx–xxx

targets,and it is necessary to transform them into quanti?ed emission reduction volume.Cui et al.addressed this issue and transformed the intensity targets into quanti?ed targets for all 31provinces in the Twelfth Five Year Plan(see Table A1)[15]. We assumed that the provincial reduction targets in2020are pro-portional to their reduction burdens in the Twelfth Five-Year Plan.

4.Empirical results and analysis

4.1.Policy scenarios

In this paper,the target of42.5%reduction in national carbon intensity relative to the2005level by2020,which is the average of the40–45%commitment of China at the2009Copenhagen Summit,is assumed the emission reduction target.Three policy scenarios of no emissions trading scheme among provinces(NETS), emissions trading scheme only containing the pilots(PETS),and the uni?ed national emissions trading market(CETS),is designed and analysis.It should be noticed that in PETS,Shenzhen was inte-grated into Guangdong for data availability.More details about the policy scenarios please refer to Table2.

4.2.Simulation results

4.2.1.The cost-saving effects

Table3illustrates the cost-saving effects of the emissions trad-ing scheme in China.To achieve the42.5%reduction in carbon intensity over the period2005–2020,the national emissions need to be reduced by about819MtCO2,accounting for7.98%of the total emissions in2020.If there is no emissions trading among provinces(NETS),the total abatement cost is about28153million yuan,accounting for0.05%of national GDP in2020.In the case of PETS,the total abatement cost is26886million yuan,which implies that a4.50%cost-saving is achieved,and the equilibrium carbon price is about99yuan/tCO2.If the uni?ed emissions trading market could be implemented(CETS),the total abatement cost would be21486million yuan,which suggests that a23.67% cost-saving is achieved,and the equilibrium carbon price is 53.17yuan/tCO2.

4.2.2.Provincial behaviours in ETS

In this section,the effect of the carbon emissions trading on provincial behaviours will be discussed.

(1)In NETS scenario,provinces achieve their reduction targets

on their own.Fig.3shows that different provinces have dif-ferent reduction burdens and different abatement costs.

More specially,the?ve provinces with the largest reduction in CO2emissions are Shandong(82MtCO2),Jiangsu(71 MtCO2),Hebei(68MtCO2),Guangdong(63MtCO2),and Lia-oning(54MtCO2),while some western provinces such as Xinjiang and Tibet experience zero burdens.The reason for the results is that the reduction burdens for some western provinces are relatively small that they are able to achieve by relying on the technology progress.

In NETS,the marginal abatement costs of the eastern coastal provinces(with higher per-capita GDP,higher emissions share, but lower emission intensity)are much higher than those of the western provinces.For example,the marginal abatement costs of Beijing and Guangdong are almost155yuan/tCO2,while Qinghai and Tibet have zero abatement costs.The huge differences in mar-ginal abatement costs among provinces imply a high level of national abatement cost,which indicates the necessity of the emis-sions trading market in China.

(2)In PETS,six pilot provinces can reduce their cost by partici-

pating in the ETS.As Table4shows,the cost-savings of Guangdong is572million yuan,which is the largest of all.

This is followed by Hubei with406million yuan.The cost-saving effects of Chongqing and Beijing are151and 119million yuan.In PETS,the cost-saving effects of Shang-hai and Tianjin are not obvious.The reason is that the mar-ginal abatement costs for the two cities are not very far off from the equilibrium carbon price.

Fig.4with details in PETS shows that,Guangdong,Beijing and Shanghai are the emissions rights buyers,while Guangdong takes over75%of the market share.To the contrary,Tianjin,Chongqing, and Hubei will sell emission rights to bene?t from PETS,and almost68%of the certi?ed emission reductions will be provided by Hubei.Overall,the carbon trading volume among pilot prov-inces in PETS is about28MtCO2,and accounts for17%of the total CO2reduction in the pilots.The cost-saving is1268million yuan, accounting for14%of total abatement costs of the pilots.

(3)In CETS,all provinces could buy(or sell)emission rights in

the national market.However,different provinces experience different cost-saving effects,as they have differ-ent marginal abatement costs.As shown in Table5,the cost-saving effects of the eastern and western provinces are more pronounced than the central provinces of China.For exam-ple,the cost-saving effects of the eastern provinces such as Guangdong and Jiangsu are1945and831million yuan, and the cost-saving effects of the western provinces such as Xinjiang and Guizhou are560and187million yuan,while the middle provinces such as Anhui and Henan have limited cost-saving effects,almost approaching zero.

For the emissions trading,the eastern provinces will buy emis-sion rights to reduce their abatement costs,while the western provinces may earn bene?ts by reducing more.When the market

Table2

Policy scenarios.

Reduction target Denotes Policy description

42.5%reduction in carbon intensity relative to2005levels

by2020

NETS No emissions trading market,the reference case

PETS The coverage of emissions trading market contains Beijing,Chongqing,Shanghai,Tianjin, Guangdong and Hubei

CETS All provinces involve in trading market,and a uni?ed national emissions trading market has been achieved

Table3

The cost-saving effects of trading markets with different reduction targets.

NETS PETS CETS

Total emissions reduction(MtCO2)819.01819.01819.01

Abatement cost(million yuan)28,15326,88621,489

Cost-saving(%)0 4.5023.67

Carbon price(yuan/tCO2)–98.8753.17

Emissions trading(MtCO2)–27.76147.55 L.-B.Cui et al./Applied Energy xxx(2014)xxx–xxx

reaches equilibrium,Guangdong (40MtCO 2),Jiangsu (33MtCO 2)and Zhejiang (22MtCO 2)are the three largest buyers,and more than 60%of emission rights will be purchased by these three prov-inces.To the contrary,the three largest emission right sellers are Inner Mongolia (36MtCO 2),Shanxi (23MtCO 2)and Xinjiang (21MtCO 2),sponsoring more than 50%of the selling market.4.2.3.The cost-saving effects of CETS with more ambitious targets The previous study has shown how China could reduce the total abatement costs by establishing emissions trading scheme,espe-cially in the case of CETS.In this section,several more ambitious targets will be investigated.It is assumed that the uni?ed carbon emissions trading could be established in 2020,and the initial pro-vincial emissions reduction shares maintain unchanged with above analysis.

Five cases have been considered for the simulation,and we assume 40%,45%,50%,55%,and 60%reduction in carbon intensity relative to the 2005levels by 2020for each case.As Table 6shows,with the intensity targets increase from 40%to 60%,the quanti?ed emissions reduction increases from 408MtCO

2to 3692MtCO 2.

Meanwhile,the total abatement costs increase from 6602million yuan to 680655million yuan.

Fig.5illustrates the cost-saving effects of the uni?ed emissions trading scheme with different intensity targets.It shows that along with the increasing of intensity targets,the cost-saving effects become more obvious.More speci?cally,with the carbon intensity reduction increases from 40%to 60%,the cost-saving effects increase from 23%to 32%,and the equilibrium carbon price increases from 25yuan/tCO 2to 269yuan/tCO 2.In particular,for the 45%target,the total abatement cost will be reduced by 24%if the uni?ed emissions trading market could be established,and the carbon price is almost 78yuan/tCO 2.5.Sensitive analyses

5.1.Changes in annual GDP growth

The previous analysis assumes that the annual GDP growth rate is 7.5%over the period 2011–2015and then decreases to 5.5%over the period 2016–2020.To analyse the sensitivity effect of the

Fig.3.provincial reduction in the case of no emissions trading among provinces.

Table 4

provincial reduction in the case of PETS.

CO 2reduction (MtCO 2)

Emissions trading a (MtCO 2)Abatement cost (Million yuan)Total cost

(Million yuan)Cost-savings (Million yuan)8.33 4.2540282319.30à1.4393178925.29 2.621220147845.10à18.74217532241.6520.892009407419.92à7.58961211159.60

0.00

7698

buying emission rights,the negative stands for selling emission rights.

Fig.4.Carbon emissions trading in PETS.

annual GDP growth rate,four GDP growth scenarios are designed.In particular,we assume that the annual GDP growth rate increases from 6.5%to 9%(see Table 7)during the Twelfth Five-Year Plan,and the corresponding annual GDP growth rate increases from 4%to 6.5%over the period 2016–2020.Table 7presents the natural decline of carbon intensity with different scenarios.As we can see,with the GDP growth rate varies from S1to S4,the natural decline

S4,while carbon prices show some decrease from

58yuan/tCO 2to 48yuan/tCO 2,with a modest change.5.2.The shape of the national MAC

The national MAC curve is a key input to derive the provincial MAC curves.Different MACs may result in different carbon prices.To investigate the effects of the shapes of national MAC on the

Table 5

Provincial reduction in the case of CETS.

CO 2reduction (MtCO 2)

Emissions trading a (MtCO 2)Abatement cost (Million yuan)Total cost (Million yuan)Cost-savings (Million yuan)Guangdong 23.1539.516076471945Jiangsu 37.7833.399911025831Zhejiang 19.5722.34513536724Shanghai 14.0613.89369383388Shandong 70.8211.221858186949Beijing 4.637.98122130397Tianjin 10.737.16281289134Fujian 12.587.01330337109Sichuan 19.73 6.7551852464Hunan 21.61 2.9256757011Hubei

25.07 1.296586592Chongqing 11.07 1.272912924Jiangxi 13.88 1.213643653Shaanxi 17.94à0.194714700Guangxi 12.75à0.853343342Anhui 23.55à1.066186171Hainan 1.55à1.55413942Tibet 1.60à1.61424043Jilin 22.97à4.0160359919Qinghai 4.33à4.35114109117Gansu

13.03à4.8134233748Heilongjiang 21.20à5.2055655135Liaoning 60.04à5.801575157015Henan 51.62à5.841354134918Ningxia 13.06à6.5834333690Yunnan 25.57à8.3367166374Hebei 79.32à11.802081206948Guizhou 29.41à14.23772757187Xinjiang 20.79à20.86546525560Shanxi

60.89à22.7315981575231Inner Mongolia 74.70à36.1719601924475Total

819.00

0.00

21,489

6664

Note:the positive stands for emission rights buyer,the negative stands for emission rights seller.

Table 6

Fig.5.The cost-saving effects with ambition reduction target.

L.-B.Cui et al./Applied Energy xxx (2014)xxx–xxx

results,we introduce two more curves.The?rst one is McKinsey

MAC curve,which is a kind of bottom-up approaches that depend on the marginal cost and emissions reduction potential of all available technical options[22,24].The other one is MIT Emissions Prediction and Policy Analysis(EPPA)MAC curve,which is a kind of top-down approaches that generate MAC curves by recording the emission reductions achieved at different marginal costs[21].

The MAC curves for the above two approaches are measured in 2002price of Chinese currency Yuan for consistency.Following the McKinsey approach,the national MAC of China in2020was estimated as MAC McKinsey

2020

eRT?à2884:73?lne1àRTà720:06.The simulation data is from the research provided by Hanaoka and

Kainuma[39].On the other hand,we have MAC EPPA

2020

eRT?à303:82?lne1àRTà16:70by?tting the data from the analysis of Morris et al.[21].This calculation shows that the MAC in the McKinsey approach is much larger than that in the EPPA approach.The rea-son is that China has maximum technically feasible abatement potential in the former method.For example,as stated by Hanaoka and Kainuma,China’s carbon emissions could not reduce more than3.4GtCO2in2020[40].

Fig.7illustrates the cost-saving effects of the carbon emissions trading with different national MACs.It should be mentioned that the CTT approach is used in these three curves to derive provincial MACs.The cost-saving effect changes little,while carbon prices vary substantially across different national MACs.More specially, the McKinsey approach will result in a carbon price of225yuan/ tCO2,which is nearly4times of that in the base case,while EPPA model achieves a carbon price of24yuan/tCO2,which is less than the period2010–2020.

It should be noted that the emission reduction targets for some provinces are zero under the above approaches.Actually,the neg-ative targets imply that these provinces are allowed to emit more than their baseline emission levels in2020.To avoid this,we follow [40]to set the emission reduction targets for these provinces at zero and the emission reduction targets for other provinces are then proportionally adjusted[14].

Fig.8shows that the cost-saving effects are sensitive to the initial allocation methods.More specially,if the provincial emission allowances are allocated based on the population approach,the total abatement costs could decrease by48%,which is the largest of all.In the case of the equal intensity reduction approach,China could reduce its total cost by11%,which is the smallest of all.The cost-savings in the Grandfathering approach is about12%,which is almost half of that in the base case.This comparison implies the complexity of the allocation of initial emis-sion permits,while the approach China adopted for the Twelfth Five Year Plan is somehow not bad.

5.4.The provincial MACs

We have no reliable alternative but to use CTT approach to derive provincial MACs on the basis of the national MAC.Although some scholars estimated the cost-saving effects of the interprovin-cial emissions trading scheme of China,the provincial MACs are not presented in their papers[1,15,41].One exception is the analysis provided by Zhou et al.,which gives an interesting estima-tion of provincial MACs in China[14].However,different from the concept of MAC,the independent variable of the provincial MACs in Zhou et al.’s analysis was de?ned as the amount of cumulative

Fig. 6.The cost-saving effects of the CETS with different annual GDP growth

assumptions.

Fig.7.The cost-saving effects of the CETS with different national MACs.Fig.8.The cost-saving effects of the CETS with different allocation approaches.

the partial emissions trading (PETS)may result in a carbon price of 70.55yuan/tCO 2.Most recently,6pilots of China have started their carbon emissions trading projects,and the released trading infor-mation may be useful to evaluate the validity of modelling results.The carbon prices in Table 8are from the of?cial websites of 6pilots.It shows that carbon prices vary substantially across differ-ent pilots.More specially,the city of Shenzhen is the ?rst pilot in China to introduce ETS,and the carbon prices range from 28.00yuan/tCO 2to 130.90yuan/tCO 2,with an average of 75.31yuan/tCO 2,which is the largest of all.The carbon prices in Guangzhou range from 60.00yuan/tCO 2to 66.00yuan/tCO 2,and the average level is 62.54yuan/tCO 2.Hubei starts its emissions trading project on April 2014and the carbon prices vary around 22.60yuan/tCO 2.We are happy to ?nd that the modelling result 70.55yuan/tCO 2falls in the price interval of these pilots.The inter-esting ?nding may support the validity of the provincial MACs from CTT approach.

6.Conclusion and discussion

The emission trading scheme is regarded as a cost-effective way for mitigating CO 2emissions,and presently China signals strong intentions to establish a national emissions trading market.This research explores on the cost-saving effect of carbon emissions trading in China for achieving its 2020intensity reduction target.Firstly,an interprovincial emissions trading model is constructed.Then,three kinds of policy scenarios,including no carbon emis-sions trading among provinces,an emission trading scheme only covering the pilots,and a uni?ed national emissions trading scheme,have been analysed followed by a few sensitivity analysis.With the simulation,this paper ?nds some interesting results.Firstly,to achieve 42.5%reduction in carbon intensity over the per-iod 2005–2020,the national emissions need to be reduced by

about 819MtCO 2,accounting for 7.98%of the total emissions in 2020.Secondly,the partial emissions trading market (PETS)and the uni?ed national trading market (CETS),which may result in a carbon price of 99yuan/tCO 2and 53yuan/tCO 2,could reduce the total abatement costs by 4.50%and 23.67%,respectively.Thirdly,the emissions trading scheme could yield different cost-saving effects for different provinces,and the cost-saving effects of the eastern and western provinces are more pronounced than the cen-tral provinces of China.

This paper provides a preliminary evaluation of the cost-saving effects of carbon emissions trading in China,and the results show that the emissions trading scheme will play an important role in promoting China to reduce CO 2emissions in a cost-effective way.In fact,the proposed 17%intensity target during Twelfth Five-Year Plan is just the ?rst try for China to take quanti?ed reduction mea-sures.With more stringent targets and the increase in marginal abatement cost,the carbon trading volume will be enlarged.The emissions trading scheme will play an increasing important role in helping China to reduce CO 2emissions cost effectively in the future.

This research employs a single-region CGE model,CHINAGEM,to simulate the effects,and the climate policies of other countries have not been involved.In fact,the emissions reduction measures adopted in other countries will change China’s MAC through trade effects.However,Ellerman and Decaux indicate that the EPPA-based curves are very stable and thus robust to other countries’behaviours [42],and this ?nding based on a multi-region CGE model may be useful to reduce the concerns of climate targets abroad on China’s emissions trading market.This paper does not consider the possible in?uence of Clean Development Mechanism (CDM)on local ETS due to data availability.In fact,although China used to be a dominant provider of the CDM credits,the EU has adjusted its CDM policy in the third phase,which stipulates that only Least Developed Countries (LDCs)as sources of post-2012new project credits [43,44].It implies that the CDM credits from the new projects registered in China can’t be sold in the EU-ETS anymore from 2013.

There are other limitations in our research.Firstly,this paper focuses on the cost-saving effects of interprovincial carbon emissions trading,and do not consider the potential for emissions trading among industries or enterprises.Secondly,referring to other research,this paper estimates the provincial MACs on the basis of national levels with CTT approach,and more accurate mea-sures about provincial MACs in 2020will result in more convincing results.Thirdly,transaction costs haven’t been considered in this research.As a matter of fact,transaction costs do decrease the

Table 8

The carbon prices for the pilots in the observation period.Pilots

Product

Observation period

Carbon price (yuan/tCO 2)Min

Max Average Beijing BEA 2013.11.28–2014.4.350.0057.0052.75Tianjin TJEA 2013.12.26–2014.4.325.4850.1130.88Shanghai SHEA132013.11.26–2014.4.327.0050.9033.94Guangzhou GDEA 2013.12.19–2014.4.360.0066.0062.54Shenzhen SZA 2013.6.18–2014.4.328.00130.9075.31Hubei

HBEA

2014.4.2–2014.4.3

21.00

24.20

22.60

Note:Chongqing was not included because its carbon trading project has not been implemented.

Table A1

The provincial reduction targets in the Twelfth Five-Year Plan.Province Intensity reduction (%)Quanti?ed reduction a (MtCO 2)Province Intensity reduction (%)Quanti?ed reduction a (MtCO 2)Beijing 189.83Hubei 1720.57Tianjin 1913.95Hunan

1719.14Hebei 1852.73Guangdong 19.548.82Shanxi

1729.84Guangxi 169.29Inner Mongolia 1630.17Hainan 110.00Liaoning 1842.35Chongqing 179.63Jilin

1714.81Sichuan 17.520.66Heilongjiang 1612.51Guizhou 1611.88Shanghai 1921.78Yunan 16.513.48Jiangsu 1955.47Tibet 100.00Zhejiang 1932.66Shannxi 1713.86Anhui 1717.56Gansu 16 6.43Fujian 17.515.27Qinghai 100.00Jiangxi 1711.78Ningxia 16 5.08Shandong 1864.01Xinjiang

0.00

Henan

33.75

Note:the provincial quanti?ed emissions reduction targets are from Cui et al.’s estimation [15].

L.-B.Cui et al./Applied Energy xxx (2014)xxx–xxx

cost-saving effects of emissions trading scheme.All of these limita-tions need to be addressed in the future.Acknowledgements

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PEP六年级上册英语教案全册

Unit 1How can I get there? 第一课时一、教学内容 Part A Let's try & Let's talk 二、教学目标 1．能够听、说、读、写句子：“Where is the museum shop？”“It's near the door.”。 2．能够听、说、认读单词ask、sir和句型“Is there a…？”“I want to…”“What a great museum！”。三、教学重难点 1．学习句子“Where is the museum shop？”“It's near the door.”。 2．正确使用方位介词。四、教学准备单词卡、录音机、磁带。五、教学过程 Step 1 热身(Warming－up) Let's do Go to the bookstore.Buy some books. Go to the post office.Send a letter. Go to the hospital.See the doctor. Go to the cinema.See a film.

Go to the museum.See some robots. Step 2 新课呈现(Presentation) 1．学习Let's try (1)打开课本读一读Let's try中呈现的问题和选项。 (2)播放录音，让学生听完后勾出正确的选项。 (3)全班核对答案。 2．学习Let's talk (1)播放Let's talk的录音，学生带着问题听录音：Where is the museum shop？Where is the post office？听完录音后让学生回答这两个问题，教师板书：It's near the door.It's next to the museum.教师讲解：near表示“在附近”，next to表示“与……相邻”，它的范围比near小。最后让学生用near和next to来讲述学校周围的建筑物。 (2)讲解“A talking robot！What a great museum！”，让学生说说这两个感叹句的意思。 (3)再次播放录音，学生一边听一边跟读。 (4)分角色朗读课文。 Step 3 巩固与拓展(Consolidation and extension) 1．三人一组分角色练习Let's talk的对话，然后请一些同学到台前表演。 2．教学Part A：Talk about the places in your city/town/village.

(完整版)小学英语语法专项练习-一般将来时1will

语法专项练习-----------一般将来时will 一、一般将来时的定义：一般将来时表示在将来时间将要发生的动作或存在的状态，与表示将来的时间连用。 tomorrow, next day(week, month, year…),soon, the day after tomorrow（后天）等如：She will visit Shanghai tomorrow. 二、一般将来时的构成主语+shall/will do ★ shall与will的区别 shall：常用于第一人称否定式: shall not=shan’t will: 常用于第二、第三人称，但在口语中各种人常都可以用will 否定式：will not=won’t 三、一般将来时的用法主语+shall/will+do这种结构不是表示自己的打算、意图或计划，而是表示未来的事实或对将来的预测等如： No one will do heavy work. Roberts will do everything for us. 一般将来时的构成肯定句：主语+shall/will+do 否定句：主语+shall/will+not+do（will not 可缩写成won’t）一般疑问句：shall/will+主语+ do 特殊疑问句：疑问词+ shall/will+主语+do？选择题 1.We ________ good grade(取得好分数) next time. A. get B. will get C. going to get D. will gets 2.They ________ models the day after tomorrow. A. will be going to make B. will going to make C. are going to make D. will made 3.Mother ________ me a nice present（好的礼物） on my next birthday. A. will gives B. will give C. gives D. give 4.He ________ go to the park tomorrow morning. A. will B. is C. will be D. be 5.The dogs will _______ at the garden. A. play B. plays C. playing D. playing 6.My mother _______ shopping tomorrow. A. will goes B. will going C. willn’t go D. won’t go 7.The next time you see Niko, he _____sixteen years old. A. will be B. is C. was D. will 8.In ten years, John_______ an astronaut.

【语法精讲】：will表示的一般将来时的用法

【语法精讲】：will表示的一般将来时的用法 will是助动词，意为“将；将要；将会”，其后要接动词原形，即“will+动词原形”构成一般将来时，描述从现在来看将要发生的事情或表达对未来的预测等。助动词will可用于各种人称，无人称和数的变化。句子中往往有表示将来的时间状语，如tomorrow, next week, the day after tomorrow等。注意：第一人称的一般将来时，一般用助动词shall。 What shall I wear to the party? Shall we order some coffee? 一、will的用法 1. 表示说话人说话时所作的决定。例：—It’s cold in here. ―OK, I will close the window. I’ll have the salad, please. 给我来点儿色拉吧。 2. 表示说话人知道或认为将会发生的事（但并非说话人自己的意图或计划）。例：Her mother will be ninety next week. Will he pass the exam, do you think? 你认为他考试能及格吗？ This job won’t take long.这工作花不了多长时间。 3. 表示请求、承诺和主动提议。例：Will you buy some bread on your way home? We’ll be back early. Will you send this letter for me, please? 二、will的句式结构 1. 肯定句结构：主语+will+动词原形+其他。 I will arrive in Shanghai tomorrow. She will go there next week. 2. 否定句结构：主语+will+not+动词原形+其他。由于will是助动词，因此否定句直接在will后加not即可。Will not可缩略为won’t,即will not=won’t. I won’t be able to come to dinner today. We won’t be busy this evening. 3. 一般疑问句结构：Will+主语+动词原形+其他？ will为助动词，变一般疑问句时，直接提到句首。 She will be our English teacher next term.

人教版六年级上册英语知识点总结

人教版六年级英语上册各单元知识点汇总 Unit 1 How do you go to school？一、重点短语： by plane 坐飞机 by ship 坐轮船 on foot 步行 by bike 骑自行车 by bus 坐公共汽车 by train 坐火车 traffic lights 交通灯 traffic rules 交通规则 go to school 去上学 get to 到达 get on 上车 get off 下车Stop at a red light. 红灯停Wait at a yellow light. 黄灯等Go at a green light. 绿灯行二、重点句型： 1.How do you go to school？你怎么去上学？ https://www.360docs.net/doc/b02685570.html,ually I go to school on foot. Sometimes I go by bus. 通常我步行去上学。有时候骑自行车去。 3.How can I get to Zhongshan Park ？我怎么到达中山公园？ 4.You can go by the No. 15 bus. 你可以坐 15 路公共汽车去。三、重点语法： 1、There are many ways to go somewhere.到一个地方去有许多方法。这里的 ways 一定要用复数。因为 there are 是There be 句型的复数形式。 2、on foot 步行乘坐其他交通工具大都可以用介词by…，但是步行只能用介词 on 。 4、go to school 的前面绝对不能加 the，这里是固定搭配。 5、USA 和 US 都是美国的意思。另外America 也是美国的意思。 6、go to the park 前面一定要加the. 如果要去的地方有具体的名字，就不能再加 the ，如果要去的地方没有具体名字，都要在前面加 the. （ go to school 除外。） 7、How do you go to …？你怎样到达某个地方？如果要问的是第三人称单数，则要用： How does he/she…go to …？ 8、反义词： get on（上车）---get off（下车） near（近的）—far（远的） fast（快的）—slow（慢的） because（因为）—why（为什么） same（相同的）—different（不同的） 9、近义词： see you---goodbye sure---certainly---of course 10、频度副词： always 总是，一直 usually 通常 often 经常 sometimes 有时候 never 从来不 Unit 2 Where is the science museum？一、重点短语： library 图书馆 post office 邮局 hospital 医院 cinema 电影院

语法一般将来时will讲解与练习图文稿

语法一般将来时w i l l讲解与练习集团文件发布号：（9816-UATWW-MWUB-WUNN-INNUL-DQQTY-

Shall/Will+主语+V原形肯定回答：Yes, I/we + shall. / Yes. 主语+will. 否定回答：No, I/we shan’t./No, 主语+ won’t. — Will she arrive tomorrow 她明天会到吗—Yes,she will. / No, she won’t. will/shall的特殊用法 (1) 主语是第一人称I,we时，常用助动词shall+V原形 I shall write you a letter next month. 我下礼拜将会给你写信。 (2) 在问对方是否愿意，或者表示客气的邀请时，常用will. Will you go to the zoo with me 你能和我一起去动物园吗 (3 ) 在表示建议或者征求对方意见时，用shall. Shall we go at ten 我们可以十点钟走吗 be going to 与 will的区别： (1) be going to 表示近期、眼下就要发生的事情，will 表示的将来时间则较远一些， ① He is going to write a letter tonight.② He will write a book one day.

新版pep六年级上册英语-各单元知识点总结

Unit 1 How can I get there? 一：重点单词和短语 Science科学, museum博物馆, post office, bookstore, cinema, hospital ，tasty, buy, London Eye伦敦银, stomach胃,crossing十字路口, turn left, turn right, go straight=walk straight直走.next to紧挨着/与。。。相邻, far from(离。。。远), near在。。。附近,behind（在。。。后面）, in front of（在。。。前面）, between…and…（在。。。和。。。之间）二：按要求写单词： hot(反义词)cold , cool(反义词)warm，too（同音词）to/two can not(缩写)can’t right(反义词)left/wrong buy(同音词)by/bye sea(同音词)see first（基数词）one four(序数词)fourth did (原形)do /does three(序数词)third give(过去式)gave 三：重点句型分析 1. Where is the museum shop? 此问句是由特殊疑问词where 引导的一个特殊疑问句，where意为“在哪里，到哪里”，用来询问地点，放在句子的开头。询问“某人或某物在哪里”的基本句型是：“ Where +is/are+ 主语？”，where is 后接名词或代词的单数形式，where are 后接名词或代词的复数形式。表示地点的词：museum博物馆, post office邮局, bookstore书店, cinema电影院, hospital医院restaurant餐馆bank银行bus stop 公交车站lake湖library图书馆zoo动物园school学校park公园garden花园hotel旅馆 2. It’s nea r the door. 此句中near是表示位置的介词，意为“旁边，附近” ，其同义句是：It’s next to the door.它在门的旁边。表示位置的短语：next to the bookstore挨着书店near the hospital在医院附近near the post office在邮局附近over there 在那边on Dongfang Street在东方大街上in front of the school在学校前面 3. How can we get there? 此句用来询问“怎样去某地”，后面直接跟地点。回答时，可以用“ Turn left, turn right, go straight.”等句来回答。同义句：1.Can you tell me the way to+地点？ 2.Where is the +地点？ 3.Which is the way to +地点 4. Turn left at the bookstore. Then turn right at the hospital. 此句是指路的句型。常用到的句型有：turn left, 向左转turn right, 向右转go straight直着走。同时表示在某处的介词用at. 5.Is the Thames far from here? No, it isn’t. 此句是个be动词开头的一般疑问句，其回答要用Yes或No. 句中的far from意为“离……远”。反义词组为next to.

PEP小学英语六年级上册各单元知识点复习资料

六年级上复习资料 Unit1 How Do You Go There? (你怎样去那里？) 重点单词： on foot= walk走路by bike骑自行车by bus坐公车by train坐火车by plane坐飞机by ship坐轮船by subway坐地铁near近的far远的usually通常sometimes有时候easy简单的the fifth floor第五层楼traffic lights交通灯traffic rules交通规则stop停止wait等待get to到达same相同的mean意思是driver司机right 右边left左边must必须know知道重点句子： 1. How do you go to school? 你是怎样去上学的？ 2. I go to school by bus.我是坐公交车去上学的。 3. Usually I go to school on foot. 我通常走路去上学。 4. Sometimes I go by bike. 有时候我骑自行车去。、 5. My home is near/ far. 我的家是近的。/ 远的。 6. Look at the traffic lights, remember the traffic rules. 看着交通灯，记住交通规则。 7. Stop at a red light. Wait at a yellow light. Go at a green light. 红灯停。黄灯等一等。绿灯行。 8. Red means stop, yellow means wait, green means go. 红色的意思是停止，黄色的意思是等待，绿色的意思是通行。 9. How can I get to the park? 我该怎样到达公园呢？ 10. You can go by the No. 15 bus. 你可以坐15路公交车去。重点知识： 1.坐某种交通工具用by，例如：by bike, by train。而走路用“on”例如on foot. 2.国家名字，地方名字第一个字母要大些：例如：Canada加拿大, China中国, America美国，England英国，Australia澳大利亚 3.国家名缩写前面加the，缩写字母都要大写。例如：the USA=the US美国，the UK英国，the CAN加拿大，the PRC中国。 4.频度副词是表示做的次数多少的词语。从多到少依次排列为：always总是，usually通常，often经常，sometimes有时候，never从不。频度副词可以放在句首，也可以放在人称后面。例如：Usually I go to school by bus. = I usually go to school by bus. 5.near近的，far远的。这两个词是一对反义词。注意：not near= far, not far = near. 6.时间前面用at. 例如：在三点钟：at 3 o’ clock. 一段时间前面用for 7.表达第几层楼的时候我们要用序数词，前面还要有the。例如：第一、二、三、四、五层楼分别是：the first floor. the second floor. the third floor. the fourth floor. the fifth floor. 8.交通灯traffic lights，交通规则：traffic rules。这两个词后面都一定要加s, 绝对不能少。因为交通灯有红黄绿三盏，一定是复数，交通规则不可能只有一条，所以都一定要加s，考试的时候千万别忘了加s哦！ 9.大部分的国家都是靠右行驶的：drivers drive on the right side of the road. 记住England and Australia, drivers drive on the left side of the road.英国和澳大利亚，司机是靠左行驶的。

六年级上册英语知识点总结归纳(PEP新版)

PEP新版六年级上册英语知识点归纳总结目录 Unit1How can I get there? (2) Unit2Ways to go to school (3) Unit3My weekend plan (4) Unit4I have a pen pal (5) Unit5What does he do? (6) Unit6How do you feel? (7)

Unit1How can I get there? library图书馆north(北) post office邮局 hospital医院turn left左转turn right右转places:cinema电影院 (地点)bookstore书店(东)east west(西) science museum科学博物馆 pet hospital宠物医院crossing十字路口 school学校south(南) shoe store/shop鞋店 supermarket超市go straight直行一、问路 1．Where is the cinema,please?请问电影院在哪儿？ next to the hospital.在医院的旁边。 in front of the school.在学校的前面. behind the park在公园的后面 It’s near the zoo.在动物园的附近. on the right/left of the bookstore.在书店的左/右边. east of the bank.在银行的东边. far from here.离这儿很远. 2.Excuse me,is there a cinema near here请问这附近有电影院吗？ Yes,there is./No,there isn’t.有./没有。 3.How can I get to the hospital?我该怎样到达医院呢？ Take the No.57bus.乘坐57路公汽。二、指引路 1．You can take the No.312bus.你可乘坐312路公交车去那儿. 2.Go straight for three minutes.向前直走3分钟. 3.Turn right/left at the…在…地方向右/左转. 4.Walk east/west/south/north for…minutes.朝东/西/南/北/走…分钟. 三、Is it far from here?离这儿远吗? Yes,it is./No,it isn’t.是的，很远/不是，很远。

“一般将来时”的几种语法形式

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pep最新六年级上册单元英语课文翻译

PEP7最新六年级下册Unit4-Unit6英语课文翻译 Unit4 I have a pen pal.单词表：学习的三单形式，迷，远足，笔友，业余爱好，茉莉，想法主意，堪培拉，令人惊奇的，表示征求意见，射门，加入，俱乐部，分享 P38Let’s talk奥利弗：彼得的爱好是什么？张鹏：他喜欢读故事。他住在一个农场上，所以有时他读给那些奶牛！奥利弗：那是有趣的。张鹏：他喜欢练功夫和游泳。奥利弗：真的吗？我也是。张鹏：他也喜欢唱歌。奥利弗：哦，你也喜欢唱歌。张鹏：是的。我打算教他中国歌曲《茉莉花》！奥利弗：好主意！P39Let’s learn彼得：嘿，张鹏，你的爱好是什么？张鹏：我喜欢读故事。我也喜欢唱歌和练功夫。跳舞唱歌读故事踢足球练功夫 P40Let’s talk约翰：嘿，一。你正在干什么？（现在进行时）吴一凡：我正在写一份电子邮件给我的朋友在澳大利亚。约翰：他住在悉尼吗？吴一凡：不，他不是。他住在堪培拉。他的名字是约翰，也。约翰：真的吗？他喜欢猜字谜和去远足吗？吴一凡:是的，他是。约翰：太神奇了！我也喜欢这些。我也能成为他的笔友吗？吴一凡：当然。为什么不呢？约翰：酷！ P41Let’s learn约翰：过来并且看看我的新的笔友。他的名字也是约翰！兄弟：真的吗？他也住在中国吗？约翰：不，他不在。他住在澳大利亚，但是他学语文。烧中国食物学语文猜字谜去远足 P42let’s read布告栏：我们能跳舞吗？有一个跳舞课在星期天在下午一点。我喜欢跳舞,兵器我需要一个搭档。打电话给艾米：3345567射门！射门！射门让我们一起读。你的爱好是什么？你喜欢阅读吗？我有很棒的书。我们能分享！打电话给迈克：4435678 科学俱乐部，你的俱乐部。你想学习关于机器人吗？来到科学房间。见见罗宾。他教学生制作机器人。robin Unit 5 What does he do?单词表：工厂，工人，邮递员，商人企业家，警察，渔民科学家，飞行员，教练，国家，校长，大海，保持，大学，体育馆，如果，记者，使用，打字，快速地，秘书 P48Let’s talk莎拉：你的爸爸是在这里今天吗？奥利弗：不，他在澳大利亚。莎拉：他是干什么的？奥利弗：他是一个商人。他经常去其它的城市。莎拉：并且你的妈妈是干什么的？奥利弗：她是一个班主任。莎拉：那是好的。奥利弗：是的，她将要是在这里今天。莎拉：你想成为一个班主任吗？奥利弗：不，我想成为一个出租车司机。 P49Let’s learn职业日工厂工人邮递员商人警察张鹏：你的爸爸是一个邮递员吗？奥利弗：不，他不是。张鹏：他是干什么的？：奥利弗：他是一个商人。 P50Let’s talk迈克：我的叔叔是一个渔夫。小雨：他在哪里工作？迈克：他工作在海上。他看到很多鱼每天。小雨：我知道了。他怎么去工作的？乘小船？迈克：不，他工作在小船上。他骑自行车去工作。小雨：他有一个很健康的生活。迈克：是的。他工作非常努力并且保持健康。小雨：我们也应该努力学习并且保持健康。 P51Let’s learn渔民科学家飞行员教练奥利弗：我的叔叔是科学家。吴一凡：他在哪里工作？奥利弗：他工作在一个大学。 P52let’s read胡斌喜欢运动。他擅长足球，乒乓球和篮球。他经常去跑步放学后。他想工作在一个体育馆。提示：

人教版六年级英语上册教案完整版

Unit 1How can I get there？单元整体分析本单元是人教版英语六年级上册的第一单元，单元的话题是“How can I get there?” 本单元通过不同的场景，提供了表达地点、问路的句型结构。教学中三个版块:A 部分，B部分和C 部分。A部分包括重点词汇和情景对话，共两个课时。第一课时呈现了吴一凡和Robin的谈话，引出表示地点的词汇。.第二课时吴一凡和Robin的谈话，引出句型Where is the...? It?s…A 部分重点掌握词汇和询问地点并回答的句型。B部分包括重点词汇、情景对话和读和写，共三个课时。第一课时呈现Mike问路的对话，引出关于路线的一些词汇。第二课时吴一凡和Mike 看完电影讨论吃饭地点在哪，呈现了问路并回答的句型How can we get there? Turn left/right....,并进一步表达句型Where is the ...? It?s next to...第三课时通过图片了解辨别方位的方法。通过吴一凡、Mike和Robin寻找意大利餐馆，拓展本单元所学句型。B部分重点是掌握词汇和问路及回答的句型How can we get there? Turn left/right... C 部分包括听力测试、介词词组的总结和故事，共一课时。重点是复习巩固本单元所学重点词汇和句型。在课堂教学中，首先要整体把握本单元教学内容，教学重点和教学难点，了解学生学情。然后围绕本单元主题“How can I get there?”展开教学设计。本单元的教学内容与学生的生活相关，在组织语言教学时要注意设计生活化，充分利用教材已经设定的情境展开教学，引导学生在合作学习中表达和语用所学句型。鼓励学生自编对话巩固所学知识。同时还要引导学生自己归纳介词词组，启发学生的思维。本单元所需要掌握的词汇中science, post office 中的office,在四年级、五年级的教材中已经学过。本单元所需要掌握的询问地点并回答的句型在Where is the ...?It’s in/on/under/near/in front of/behind....在四年级、五年级的教材中已经学过。这个句型的表达为本单元的教学奠定了一定的基础。单元教学目标 1. 知识目标（1）能够听、说、读、写单词和词组：science museum, post office, bookstore, cinema, crossing, turn left, go straight, turn right （2）能够听、说、认读单词：ask, sir, interesting, Italian, restaurant, pizza, street, get, GPS, street, gave, feature, follow, far, tell （3）能够听、说、读、写句型： —Where is the...? —It?s near the door.. —How can we get there? —Turn left at the bookstore. （4）能够掌握句式： Where+系动词+地点名词？ It+系动词+表示地点的介词短语。 How can I/we + get to +地点？（5）知道英语句子有升降调。 2. 能力目标（1）能够正确使用science museum, post office, bookstore, cinema, crossing, turn left, go straight, turn right这些单词和词组描述城市设施及其位置。（2）能够在情景中运用句型询问地点并作答： —Where is the....? —It?s ... （3）能够在情景中运用句型问路并描述路线。

一般将来时：will

第八单元一般将来时will 用法定义：一般将来时表示在未来某个时间点或时间段内将要发生的动作或存在的状态，以及将来反复发生的动作，也可以表示未来倾向、习惯或很可能发生的事等。具体用法如下：1.“will +动词原形”常见用法（当主语为第一人称时还可以用shall表示将来）： 1）表示将要发生的动作或存在的状态。如： There will be a big party in our school on Friday. 周五我们学校将有一个大派对。 I will/shall arrive tomorrow. 我将明天到。 2）没有时间状语，但可以从意思上判断指未来的动作或情况。如： The meeting won't last long. 这个会开不了多久。 3）用于“祈使句+and+陈述句（谓语为will do形式）”中。如： Work hard and you will succeed. 努力吧，你会成功的。 4）在时间和条件状语从句中往往使用一般现在时表将来，而主句用一般将来时。如： I will leave now if he comes here. 如果他来，我现在就走。一般将来时will 结构：肯定句否定句一般疑问句 “will + 动词原形”可用来描述将来的事情或表达对未来的预测。肯定句结构：主语+will+动词原形(+其他). 否定句结构：主语+will not/won't+动词原形(+其他). 一般疑问句结构：Will+主语+动词原形(+其他)? （肯定回答：Yes, 主语+will. 否定回答：No, 主语+won't.）例： We will ask Miss Chen for help. 我们会向陈小姐寻求帮助。 He will not accept your suggestion. 他不会接受你的建议。 Will she be back in two days? 她将在两天之后回来吗？ Yes, she will. 是的，她会。/ No, she won't. 不，她不会。一般将来时will 结构：特殊疑问句特殊疑问句结构：1. 特殊疑问词（作其他成分）+ will +主语+动词原形(+其他)? ；2. 特殊疑问词（作主语）+ will +动词原形(+其他)? ；3. 特殊疑问词（作主语的定语）+主语+will +动词原形(+其他)? 例： When will Mary get here tomorrow? Mary明天什么时候到这儿？ Who will do the job when you leave? 你走了谁来做这个工作？

一般将来时will

英语初一专题一般将来时 -will 知识点精讲透析 Will 是助动词，意为“将；将要；将会” ,其后要接动词原形，即”will+ 动词原形”构成一般将来时，描述从现在来看将要发生的事情或表达对未来的预测等。助动词will 可用于各种人称，无人称和数的变化。句子中往往有表示将来的时间状语，如tomorrow ，next week, the day after tomorrow 等。注意：第一人称的一般将来时，一般用助动词shall. What shall I wear to the party? Shall we order some coffee? 一、will 的用法 1. 表示说话人说话时所作的决定。例：—“It 's cold in here. ”—“OK,I will close the window. ” I 'll have the salad, please. 给我来点儿色拉吧。 2. 表示说话人知道或认为将会发生的事（但并非说话人自己的意图或计划）。例：Her mother will be ninety next week. Will he pass the exam,do you think? 你认为他考试能及格吗？ This job won 't take long. 这工作花不了多长时间。 3. 表示请求、承诺和主动提议。例：Will you buy some bread on your way home? We 'llbe back early. Will you send this letter for me,please? 二、will 的句式结构 1. 肯定句结构：主语+will+ 动词原形+ 其他。 I will arrive in Shanghai tomorrow. She will go there next week. 2. 否定句结构：主语+will+not+ 动词原形+ 其他。由于will是助动词，因此否定句直接在will后加not即可。Will not可缩略为won ',即 will no t=w on ' I won 'tbe able to come to dinner today.

语法一般将来时will讲解与练习

Grammar语法:simple future tense‘will’一般将来时 1) 表示将来某个时间要发生的动作或者存在的状态。 We shall go to see him tomorrow. 我们明天去看他。 2) 表示将来经常或者反复发生的动作。 From now on I will come everyday. 从现在起，我将每天来。 will表将来时态，其后常跟的时间状语：tomorrow 明天, the day after tomorrow后天, next week下周, this Sunday这个星期天, in+以后的时间，in the future在将来。肯定句结构主语+ shall / will +V原形 She will arrive tomorrow. 她明天到。 shall与will的区别 shall：常用于第一人称否定式: shall not=shan’t will: 常用于第二、第三人称，但在口语中各种人常都可以用will 否定式：will not=won’t 否定句结构主语+ shall / will+ not +V原形 She will not arrive tomorrow. 他明天不会到。一般疑问句结构 Shall/Will+主语+V原形肯定回答：Yes, I/we + shall. / Yes. 主语+will. 否定回答：No, I/we shan’t./No, 主语+ won’t. —Will she arrive tomorrow? 她明天会到吗？—Yes,she will. / No, she wo n’t. will/shall的特殊用法 (1) 主语是第一人称I,we时，常用助动词shall+V原形 I shall write you a letter next month. 我下礼拜将会给你写信。 (2) 在问对方是否愿意，或者表示客气的邀请时，常用will. Will you go to the zoo with me? 你能和我一起去动物园吗？ (3 ) 在表示建议或者征求对方意见时，用shall. Shall we go at ten? 我们可以十点钟走吗？ be going to 与will的区别： (1) be going to 表示近期、眼下就要发生的事情，will 表示的将来时间则较远一些， ①He is going to write a letter tonight.②He will write a book one day. (2) be going to表示根据主观判断将来肯定发生的事情,will表示客观上将来势必发生的事情。①He is seriously ill. He is going to die. ②He will be twenty years old. (3 ) be going to 含有“计划，准备”的意思，而will 则没有这个意思， ①She is going to lend us her book. ②He will be here in half an hour. (4) 在有条件从句的主句中，一般不用be going to, 而多用will, If any beasts comes at you, I'll help you. 如果野兽攻击你，我会帮助你。

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