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Forest sector is divided into managed forests and no-managed forests. The primary forest products are supplied from managed forests <ref>Petr Havlík, Hugo Valin, Mario Herrero, Michael Obersteiner, Erwin Schmid, Mariana C Rufino, Aline Mosnier, Philip K Thornton, Hannes Böttcher, Richard T Conant, 2014. Climate change mitigation through livestock system transitions. ''proceedings of the National Academy of Sciences'' 111, 3709-3714.</ref>. The built-up, water and ice areas are assumed constant during the study period.

 
=== References ===
<references />

Forestry - C3IAM

2021-08-05T12:08:19Z

Qiao-Mei Liang:

Agriculture - C3IAM

2021-08-05T12:07:54Z

Qiao-Mei Liang:

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Primary agricultural products considered in the model are listed in the following Table 1. The livestock activities are connected with the feed requirement per animal product. Following Alcamo’s work <ref>Rüdiger Schaldach, Joseph Alcamo, Jennifer Koch, Christina Kölking, David M Lapola, Jan Schüngel, Jörg A Priess, 2011. An integrated approach to modelling land-use change on continental and global scales. ''Environmental Modelling & Software'' 26, 1041-1051.</ref>, the model currently considers ruminants for livestock activities such as cattle and sheep, but non-ruminants are not included. The total forage demand is calculated by multiplying livestock unit with average forage consumption per livestock unit during one year.

For the reference land use area distribution used in the base year 2011, croplands are produced by eight crop categories which contain 149 crop types (see Table 1). According to Food and Agriculture Organization (FAO) definition, grass is from permanent pastures and can be used to graze <ref>François Souty, Thierry Brunelle, Patrice Dumas, Bruno Dorin, Philippe Ciais, Renaud Crassous, Chistoph Müller, Alberte Bondeau, 2012. The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. ''Geoscientific Model Development'' 5, 1297-1322.</ref>.

{| class="wikitable"
|+'''Table 1''' Product types in C3IAM/EcoLa model.
|'''Crop types'''
|'''Concrete products'''
|-
|Rice
|rice
|-
|Wheat
|wheat
|-
|CerealCrop
|barley, buckwheat, canary seed, cereals, maize, millet, mixed grain, quinoa, rye, sorghum, triticale
|-
|VegCrop
|almonds, apples, arecanuts, avocados, bambara beans, bananas, beans, berries, blueberries, brazil nuts, broad beans, horse beans, cabbages and other brassicas, carrots and turnips, cashew nuts, cashewapple, cassava, cauliflowers and broccoli, cherries, chestnuts, chick peas, chicory roots, chillies and peppers, citrus fruit, coconuts, cow peas, cranberries, cucumbers and gherkins, currants, dates, eggplants, figs, tropical fruit, garlic, gooseberries, grapefruit, grapes, hazelnuts, kiwi fruit, leeks, leguminous vegetables, lemons and limes, lentils, lettuce and chicory, lupins, mangoes, mushrooms and truffles, nuts, oats, okra, olives, onions, oranges, other melons, papayas, peaches and nectarines, pears, persimmons, pigeon peas, pineapples, pistachios, plantains, plums and sloes, pome fruit, potatoes, pulses, pumpkins, quinces, raspberries, roots and tubers, spinach, stone fruit, strawberries, string beans, sweet potatoes, tangerines, mandarins, taro, tomatoes, walnuts, watermelons, yams, yautia
|-
|OilCrop
|castor oil seed, groundnuts, hempseed, jojoba seeds, kapokseed, karate nuts, linseed, melonseed, mustard seed, oilpalm, oilseeds, poppy seed, rapeseed, safflower seed, sesame, soybeans, sunflower, tallowtree Seeds, tung nuts
|-
|SugarCrop
|sugar beet, sugar beet
|-
|FiberCrop
|agave, fibrenes, hemp tow waste, jute, manila fibre, other bastfibres, ramie, sisal
|-
|OtherCrop
|anise, apricots, artichokes, asparagus, carobs, cinnamon, cloves, cocoa, coffee, fonio, ginger, hops, kola nuts, maté, nutmeg, pepper, peppermint, pyrethrum, spices, tea, tobacco, vanilla, vetches
|-
|Livestock
|cattle, goats, horses, sheep
|}
 
=== References ===
<references />

Land-use - C3IAM

2021-08-05T12:07:11Z

Qiao-Mei Liang:

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The future patterns of land use have direct influence on GHG emissions and mitigation potential for land use sector and food supply. The C3IAM/EcoLa model is a global multi-regional land use allocation optimization model, which covers the agricultural and forestry sectors (see the following Figure 1). It can be used to analyze land use change in a long-term period. The primary objective of the model is to minimize the total cost of production under consideration of agricultural demand in 12 regions.

Major types of cost in C3IAM/EcoLa are:

(1) Production costs of crop and livestock production, which are obtained by a total sum of the costs of labor, capital and intermediate inputs divided by the land area obtained from C3IAM/GEEPA;

(2) Land conversion costs which are exogenously determined by the cost of new additional land and investment into infrastructure;

(3) Carbon emissions costs which consider the carbon costs caused by land use change in mitigation scenarios.
[[File:7.png|left|900px|thumb|Figure 1. The framework of C3IAM/EcoLa]]

Industrial sector - C3IAM

2021-08-05T12:06:05Z

Qiao-Mei Liang:

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C3IAM/NET-industrial sectors include steel, cement, nonferrous metals, chemical, paper and other industries. First, on the basis of considering economic development, industrial upgrading, acceleration of urbanization, intelligentization, electrification and other social and economic changes, the demand for products of each industrial sector is forecasted separately. Secondly, by incorporating factors such as technological progress, raw material substitution, fuel substitution, process adjustment, etc., the production process of each industrial sector is simulated to obtain the corresponding energy flow and material flow under the optimal production cost.

The path optimization part in industrial sectors is based on the technical perspective, considering more than 200 energy-saving technologies (such as non-blast furnace steelmaking, hydrogen steelmaking, new dry kiln, waste heat power generation technology, biological conversion technology, electrolytic water hydrogen production, etc.). By setting a series of technology, energy and emission parameters such as technology investment cost, energy conversion efficiency, energy emission factor, etc., the industrial sectors are modeled. With the goal of minimizing the total annual cost, the model chooses the optimal technological development path for the industrial sector of each region or the country under multiple constraints such as backward production capacity phase-out, technology substitution, fuel conversion, and technological progress. The model of the industrial sectors reflects the characteristics of the industrial production process with a wide variety of products, production processes, and diverse energy-saving technologies. The biggest advantage lies in the bottom-up view of actual production, making the simulation process and results practical. The results show the future potential of electric arc furnaces in the iron and steel industry <ref>Runying An, Biying Yu, Ru Li, Yi-Ming Wei, 2018. Potential of energy savings and CO2 emission reduction in China’s iron and steel industry. ''Applied energy'' 226, 862-880.</ref>, the emission reduction potential of raw material substitution in the cement industry <ref>Cheng-Yao Zhang, Biying Yu, Jing-Ming Chen, Yi-Ming Wei, 2021. Green transition pathways for cement industry in China. ''Resources, Conservation and Recycling'' 166, 105355.</ref>, and the emission reduction path of multiple products in the chemical industry <ref>Jing-Ming Chen, Biying Yu, Yi-Ming Wei, 2018. Energy technology roadmap for ethylene industry in China. ''Applied Energy'' 224, 160-174.</ref>, which can provide the government and enterprises with detailed and feasible technical investment guidance.

 
=== References ===
<references />

Transport - C3IAM

2021-08-05T12:05:16Z

Qiao-Mei Liang:

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C3IAM/NET-Transport model divides the transport sector into three parts, including intercity passenger transport, urban passenger transport and freight transport. Urban passenger transport is divided into public transport (bus and rail transit), taxi, and private vehicles (cars and electric bikes). Intercity passenger transport is divided into private vehicles and four main business intercity passenger transport (road transport, railway transport, aviation and waterway transport). Freight transport is divided into five main types: road transport, railway transport, aviation transport, waterway and pipeline transport. The main fuel includes gasoline, diesel, LNG, electricity, jet fuel, biofuel, fuel oil, hydrogen and so on.

By considering the economic development, the trend of population growth, the development of service industry and the level of transportation infrastructure in the future, combined with the change of travel behavior and the popularization of shared mobility, the multi-factor regression method is used to predict the intercity passenger travel demand <ref>Bao-Jun Tang, Xiao-Yi Li, Biying Yu, Yi-Ming Wei, 2019. Sustainable development pathway for intercity passenger transport: A case study of China. ''Applied Energy'' 254, 113632.</ref>. By considering the increase of urbanization and per capita income, the urban passenger travel demand is predicted <ref>Xi Li, Biying Yu, 2019. Peaking CO2 emissions for China's urban passenger transport sector. ''Energy Policy'' 133, 110913.</ref>. By considering the future growth rate of GDP, the change of industrial structure, the development of e-commerce and other factors, the freight transport demand is predicted.

With the goal of minimizing the annualized cost during the planning period, the model can directly describe the competition and substitution process of different technologies in the transport sector and describe the evolution of the transport structure. The model can effectively simulate the possible technological progress, efficiency improvement, cost reduction and technological breakthrough in the development of the medium and long term transport sector. In combination with current transport policies and future emission-reduction targets in the transportation sector, the energy consumption and CO2 emission-reduction potential under diﬀerent scenarios will be analyzed. A detailed and operable development path for China’s transport sector can then be provided.
 
=== References ===
<references />

2021-08-05T11:56:38Z

Qiao-Mei Liang:

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C3IAM framework includes three macro-economy modules: the Global Multi-regional Economic Optimum Growth model (C3IAM/EcOp), the Global Energy and Environmental Policy Analysis model (C3IAM/GEEPA) and the Multi-Regional China Energy and Environmental Policy Analysis model (C3IAM/MR.CEEPA).

The C3IAM/EcOp is established based on the theory of optimal economic growth and consists of two modules (economic and climate modules) (as shown in Figure 1). The economic module describes the optimal economic growth path and investment decisions under the balance of long-term emission reduction costs and climate losses<ref>Yi-Ming Wei, Rong Han, Ce Wang, Biying Yu, Qiao-Mei Liang, Xiao-Chen Yuan, Junjie Chang, Qingyu Zhao, Hua Liao, Baojun Tang, Jinyue Yan, Lijing Cheng, Zili Yang, 2020. Self-preservation strategy for approaching global warming targets in the post-Paris Agreement era. ''Nature Communications'' 11, 1624.</ref>.

While the climate module, which is a simplified model by upscaling C3IAM/Climate, presents the greenhouse gas concentration growth, radiative forcing and temperature change thereafter. The mitigation, adaptation and loss module is simplified based on upscaling C3IAM/Loss. To maximize global welfare, the model optimizes regional consumption and investment. Therefore, national optimal mitigation and adaptation decisions could be provided.

The assumptions, model structure and mathematical formulae between C3IAM/GEEPA and C3IAM/MR.CEEPA are similar. Both are composed of five basic modules, i.e., production, income, expenditure, investment and foreign trade module. The production module describes the production structure in different regions, in which the input in each sector assumes to follow a nested constant elasticity of substitute (CES) function. The household income mainly comes from labor income and capital returns. We assume that after paying household income tax, households spend disposable income on saving and on the consumption of various goods. Household saving is obtained by multiplying household disposable income with saving rate. The consumption, production and trade of goods and services are fundamentally determined by market prices. Capital and labor allocation is determined by wages and return of capital. The basic frameworks for C3IAM/GEEPA and C3IAM/MR.CEEPA are shown in Figure 2 and Figure 3, respectively.
[[File:3.png|left|900px|thumb|Figure 1. The framework of C3IAM/EcOp]]
[[File:4.png|left|900px|thumb|Figure 2. The framework of C3IAM/GEEPA<ref>Kun Zhang, Qiao-Mei Liang, Li-Jing Liu, Mei-Mei Xue, Bi-Ying Yu, Ce Wang, Rong Han, Yun-Fei Du, Yun-Fei Yao, Jun-Jie Chang, 2020. Impacts of mechanisms to promote participation in climate mitigation: border carbon adjustments versus uniform tariff measures. ''Climate Change Economics'' 11, 2041007.</ref><ref>Li-Jing Liu, Felix Creutzig, Yun-Fei Yao, Yi-Ming Wei, Qiao-Mei Liang, 2020. Environmental and economic impacts of trade barriers: The example of China–US trade friction. ''Resource and Energy Economics'' 59, 101144.</ref>|left|frame]]
[[File:5.png|left|900px|thumb|Figure 3. The framework of C3IAM/MR.GEEPA<ref>Kun Zhang, Qiao-Mei Liang, Li-Jing Liu, Mei-Mei Xue, Bi-Ying Yu, Ce Wang, Rong Han, Yun-Fei Du, Yun-Fei Yao, Jun-Jie Chang, 2020. Impacts of mechanisms to promote participation in climate mitigation: border carbon adjustments versus uniform tariff measures. ''Climate Change Economics'' 11, 2041007.</ref>|left]]

 
 
 
 

=== References ===
<references />

Macro-economy - C3IAM

2021-08-05T11:56:18Z

Qiao-Mei Liang:

Macro-economy - C3IAM

2021-08-05T11:55:56Z

Qiao-Mei Liang:

2021-08-05T11:27:19Z

Qiao-Mei Liang:

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C3IAM consists of various analytical models developed to analyze policy issues within a specific set of sectors as shown in Figure 1<ref>Yi-Ming Wei, Rong Han, Qiao-Mei Liang, Bi-Ying Yu, Yun-Fei Yao, Mei-Mei Xue, Kun Zhang, Li-Jing Liu, Juan Peng, Pu Yang, Zhi-Fu Mi, Yun-Fei Du, Ce Wang, Jun-Jie Chang, Qian-Ru Yang, Zili Yang, Xueli Shi, Wei Xie, Changyi Liu, Zhongyu Ma, Jinxiao Tan, Weizheng Wang, Bao-Jun Tang, Yun-Fei Cao, Mingquan Wang, Jin-Wei Wang, Jia-Ning Kang, Ke Wang, Hua Liao, 2018. An integrated assessment of INDCs under Shared Socioeconomic Pathways: an implementation of C3IAM. ''Natural Hazards'' 92, 585-618.</ref>. These models are interlinked to provide an integrated system for assessing the impact of climate change. C3IAM considers factors such as global multi-regional, multi-sectoral economic development, greenhouse gas emissions, emission reduction costs, climate change losses module, etc. It can not only depict the social economic system in detail, but also realize a long-term balanced growth path.

To apply C3IAM, all model settings are adjusted so that the model reproduces the state-of-the-world in 2011 and cover the period 2011–2100.

C3IAM pays more attention to clarify the comprehensive impacts of climate change and it has a better performance in the following various aspects:

1. More in-depth depiction of China: to refine the emissions pathway from the perspective of regional and sectoral, the Multi-Regional CGE Model (C3IAM/MR.CEEPA) that covers 31 provinces and the multi-sector technology model (C3IAM/NET) that covers eight energy-intensive industries are developed;

2. Extension of economic model: to capture the long-term optimal economic growth and climate change mitigation dynamically, C3IAM integrates the global CGE model (C3IAM/GEEPA) and the global economic optimum growth model (C3IAM/EcOp);

3. Realizing the hard link between the earth and socioeconomic systems: the economic models are integrated with earth system model, and the two-way feedbacks could be achieved.

<figure id="fig:The general structure of C3IA">
[[File:The general structure of C3IAM.png|left|900px|thumb|Figure 1. The general structure of C3IAM]]
</figure>

=== References ===
<references />

Spatial dimension - C3IAM

2021-08-05T11:23:41Z

Qiao-Mei Liang:

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C3IAM framework has global coverage and divides the world into 12 regions, which are USA, China, Japan, Russian Federation, India, Other Branches of Umbrella Group, European Union, Other West European Developed Countries, Eastern European CIS excluding Russian Federation, Asia excluding China, India and Japan, Middle East and Africa and Latin America (See Figure 1 and Table 1 below).
<figure id="Figure 1. The classification of regions in C3IAM">
[[File:Figure 1. The classification of regions in C3IAM.png|left|900px|thumb||Figure 1. The classification of regions in C3IAM]]
</figure>

{| class="wikitable"
|+Table 1. Classification of 175 members in 12 regions in C3IAM.
|'''Region'''
|'''Involved members'''
|-
|'''USA'''
|United States of America
|-
|'''CHN'''
|China
|-
|'''JPN'''
|Japan
|-
|'''RUS'''
|Russian Federation
|-
|'''IDN'''
|India
|-
|'''OBU'''

'''(Other Branches of Umbrella Group)'''
|Canada, Australia, New Zealand
|-
|'''EU'''

'''(European Union)'''
|Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom, Cyprus, Czech Republic, Estonia, Hungary, Malta, Poland, Slovakia, Slovenia, Bulgaria, Latvia, Lithuania, Romania, Croatia
|-
|'''OWE'''

'''(Other West European Developed Countries)'''
|Albania, Montenegro, Serbia, The former Yugoslav Republic of Macedonia, Turkey, Bosnia and Herzegovina, Guam, Iceland, Liechtnstein, Norway, Puerto Rico, Switzerland,
|-
|'''EES'''

'''(Eastern European CIS excluding Russian Federation)'''
|Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Republic of Moldova, Tajikistan, Turkmenistan, Ukraine, Uzbekistan
|-
|'''ASIA'''

'''(Asia excluding China, India, Japan)'''
|Afghanistan, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, Democratic People's Republic of Korea, Fiji, French Polynesia, Indonesia, Lao People's Democratic Republic, Malaysia, Maldives, Micronesia (Fed. States of), Mongolia, Myanmar, Nepal, New Caledonia, Pakistan, Papua New Guinea, Philippines, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Taiwan (Province of China), Thailand, Timor-Leste, Vanuatu, Viet Nam
|-
|'''MAF'''

'''(Middle East and Africa)'''
|Algeria, Angola, Bahrain, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo, Côte d`Ivoire, Democratic Republic of the Congo, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Iran (Islamic Republic of), Iraq, Israel, Jordan, Kenya, Kuwait, Lebanon, Lesotho, Liberia, Libyan Arab Jamahiriya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Occupied Palestinian Territory, Oman, Qatar, Rwanda, Réunion, Saudi Arabia, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Swaziland, Syrian Arab Republic, Togo, Tunisia, Uganda, United Arab Emirates, United Republic of Tanzania, Western Sahara, Yemen, Zambia, Zimbabwe
|-
|'''LAM'''

'''(Latin America)'''
|Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Suriname, Trinidad and Tobago, United States Virgin Islands, Uruguay, Venezuela (Bolivarian Republic of)
|}