随着城市化、工业化的快速推进，我国实现了经济的稳定增长和人民生活水平的持续提升，同时也伴生了收入不平等、资源利用效率低下和环境生态恶化等一系列问题。其中，经济收入水平与能源资源消费结构、环境排放存在着密切关联。为保证社会-经济-生态协调、公平和可持续发展，需要在提高资源利用效率和保护环境生态的同时，提升社会收入分配的公平性。我国目前致力于保障社会收入分配的公平，在这样的经济公平发展模式下，如何厘清收入水平对于能-碳-水耦合的影响传导机制，实现收入平等的社会目标与能源资源高效利用的环境目标高度协同，是促进社会经济复杂系统可持续发展的重要基础。因此，本研究首先辨识能源、碳排放、水资源在社会经济系统中的耦合关联作用机制与关键驱动因子，进而模拟收入不平等水平在能-碳-水耦合模式下的联动传导机制，最终在保障收入公平水平的情景下，提出节能节水减排的协同发展路径。具体如下：

（1）构建中国多区域能-碳耦合网络评价框架。首先，建立能-碳耦合网络：结合31个省市地区的能源消费数据，构建碳排放清单，利用多区域投入产出分析（Multi-Regional Input Output Analysis），核算生产和消费角度的不同产业部门间的碳流，构建包含多省市多部门的能-碳耦合网络模型。进而，基于能-碳耦合网络构建能-碳耦合网络评价体系，评价耦合网络系统整体特征（循环强度、系统共生、系统竞争等），将生态网络分析（Ecological Network Analysis）中的结构分析、控制分析与依赖分析首次应用于碳排放网络模拟，分析了网络中的主要流通路径（主要碳流）和主要节点（地区和产业部门），以及不同组分（地区、部门）间的生态关系（竞争、共生等），进而评价系统整体特征。研究结果显示：1）中国地区53%的碳排放是由东部地区消费东北、西北、西南地区石油天然气以及电力引起。2）基于生态网络控制分析，东部地区碳排放间接受到东北地区的石油天然气及电力部门、西南地区的电力部门、西北地区的石油加工部门和电力部门等主要能源部门控制；东部地区同时也对其他地区的碳排放形成控制关系，且控制强度分布均匀，对南部、西南、中部、北部、西北和东北地区的控制能力均在8%-19%。基于生态网络依赖分析，东北、西南、西北地区碳排放对东部地区的依赖度为40%-50%，且碳流路径与方向较为单一，主要从天然气生产和供应、石油加工和焦化、电力生产和供应等部门流入东部地区。

（2）构建了中国多区域能-水耦合网络核算及评价框架，包括：1）构建能-水耦合网络：结合各省市能源和水资源消费数据，应用多区域投入产出分析，构建水消费矩阵，核算能源生产消费过程中的水消费总量，进而构建省级能-水耦合网络模型。2）建立能-水耦合系统评估体系：构建区域产业链间控制与依赖指标，以及最终需求引起的区域生态关系指标（共生、竞争、中立等）。3）建立中国能-水耦合网络与全球能源贸易的关联网络，探究能源进出口对中国能-水耦合结构和功能的影响。研究结果显示：1）中国单位煤炭、石油、天然气的总水消费量是直接水消费量的近三倍（例如煤炭直接水消费为13 m³/TJ，总水消费为34 m³/TJ）。2）从供应链角度分析得出：北京能源生产过程中隐含的水资源通过供应链流向山东；山东和内蒙古是主要用水地区且面临严重缺水问题，而进口隐含水资源富集的能源产品将缓解该地区的水资源短缺问题；江苏、天津、河北、河南对其他地区能源生产引发的水资源消费具有明显的间接控制效应。3）从消费者角度分析得出：甘肃为最大隐含水输出者，共输出约5400万立方米隐含水至其他地区；河北为最大的隐含水接收者，共接收了约1000万立方米隐含水。

（3）识别中国能-碳耦合系统发展驱动因子。辨识能-碳耦合网络发展的六个主要驱动因子：人口变化、消费量的变化、消费模式的变化、生产结构调整、能源结构、能源强度的变化。通过投入产出结构分解分析（Structural Decomposition Analysis），探究每个驱动因子的贡献率，为进一步的碳排放模拟预测研究提供数据支撑。分析1990年到2014年的碳排放变化，发现固定资产投资是碳排放的主要贡献者（30%-40%），因此近年来对房地产业的调整将对碳减排产生积极的影响。各驱动因子的贡献率中，能源强度对碳减排的贡献超过基准年的200%。因此能源效率的提高仍是减少碳排放最重要的途径。同时，能源结构因子（即单位能源碳排放量）持续提高，其对碳排放增长的影响逐年增大，而人口增长对碳排放的影响不明显。

（4）建立中国能-水耦合系统发展驱动力识别方法，首次将能-水耦合系数作为驱动因子加入水资源消费驱动力研究之中。本研究采用投入产出结构分解分析（SDA）将中国能源相关的水消费分解为六个驱动因子：人口变化、消费量的变化、消费模式的变化、生产结构调整、水能耦合系数变化、能源强度变化。结果发现2000年后，大部分水资源流向两个最终消费者：政府和固定资本投资（各占40%左右）。政府鼓励基础设施建设的总体规划和民间房地产投资将推动政府和固定资本投资这两个部门消耗更多的水资源。因此，减少水资源消费的关键是减少政府在建筑业及相关产业中的消费和以及社会各部门对固定资本的投资。

（5）构建中国能源不平等性评估框架。为揭示收入不平等性的传递机理，本研究收集梳理全球112个国家的多区域投入产出表以及国家内部200个收入群组的消费结构数据；利用多区域投入产出分析消费数据，构建能源在不同国家以及不同收入群组间的传递过程（直接能源流通路径和间接能源流通路径）；提出各个国家用以表征能源消费不平等性的能源GINI系数指标，评估了处于不同经济发展阶段的国家的人均总能源消费（直接和间接能源消费）以及其在全球中的位置。结果显示：中国人均总能源消耗的平均值为28 GJ，远低于全球平均水平39 GJ。在全球范围内，中国的能源不平等状况需要改进，特别是提高低收入人群的能源消费量，达标基本能源需求线（31.5 GJ）。同时，德国作为研究区域中能源消费最平等的发达国家，对我国能源生产与消费可持续发展目标的制定具有借鉴意义。

（6）首次构建模拟收入不平等性在能-碳-水耦合网络中的传导过程的GAINS-IW综合评估模型。本研究将收入不平等性指标引入温室气体和空气污染协同控制综合评估模型（The Greenhouse Gas and Air Pollution Interactions and Synergies Model, GAINS 模型），通过Python编程开发了：1）收入结构子模块：包含中国人口收入矩阵（多级分组），收入人群消费总量矩阵，每个收入群消费结构矩阵（产业部门间消费比例）。结合能源消费不平等性指标，设定中国不同减贫目标和不同收入结构情景，核算目标收入组平均收入、能源消费总量和经济收入与能源消费的耦合系数。2）收入结构子模块与能源活动模块的链接模型：对原有能源模块中的总能源消费量、不同能源消费强度、不同产业部门能源消费总量等数据进行整合，与收入子模块中的能源消费情况进行关联匹配。3）水消费子模块：建立各能源产业部门的直接耗水矩阵，能源产业部门间接耗水矩阵，以及总耗水矩阵。4）水消费子模块与能源活动模块的链接模型：通过部门拆分与合并将水模块中的能源部门与能源模块中的产业部门相匹配，进而对水消费强度、消费总量等系数进行优化。最后，基于收入子模块、收入链接模型、水消费子模块以及水消费链接模型，结合GAINS模型碳排放模块，实现对我国水资源消费和碳排放的预测。结合国家减贫发展要求，设置三种缓解不平等性情景，通过GAINS-IW模型模拟不同收入结构下能源、碳排放和水资源的联动变化。通过情景模拟发现：与基线情景相比，将低收入人群的收入提高到中低收入人群水平将在2020年引起12%碳排放增长，且不影响碳排放在2030年达峰；水资源消耗将在2050年增加28%，仍未超出国家可利用水资源上限。

With the rapid urbanization and industrialization, China has achieved stable increase of economic development and consistent improvement of people's living standards, accompanied with inequal income, low efficient resource utilization and deteriorated eco-environment, of which, there is a strong connection between income level and energy and resource consumption structure, and environmental emissions as well. To pursue the harmonious, fare and sustainable development of social-economic-ecological system, it is necessary to improve the equality of social income distribution when improving the resource utilization efficiency and protecting the environment. China has devoted to improving the equality of income distribution for decades. Under such equal economic development mode, how to clarify the impact transmission mechanism of income inequality on the energy-carbon-water nexus, and how to realize the coordination of social development goals and high efficient energy and resource utilization of environmental goals, are fundamental for the sustainable socio-economic complex system. Thus, this thesis identifies the nexus mechanism and critical driving factors of energy use, carbon emission and water use within the socio-economic system, then simulate the linked transmission process of unequal income level in the energy-carbon-water nexus mode, and finally, propose the collaborative development pathways of energy saving, water saving and emission mitigation, in the context of equal income levels. Concrete results are listed as follows:

(1) Construction of assessment framework on China's multi-regional energy-carbon nexus network. First, the energy-carbon nexus network is established: the carbon emission inventory is set up based on the energy consumption data of 31 provinces and directly governed cities, and the carbon flows among various sectors from both production and consumption aspects are accounted using Multi-Regional Input-Output Analysis, to build the multi-area and multi-sector energy-carbon nexus network model. Furthermore, energy-carbon nexus network assessment framework is established: in order to evaluate the holistic characteristics of the network system (recycling intensity, symbiosis, and competition, etc.), structural analysis, control analysis and reliance analysis of Ecological Network Analysis (ENA) are first applied to the carbon emission network to analyze the major throughflow pathways (major carbon flows) and nodes (regions and sectors) , and ecological relationships (competition, symbiosis, etc.) among various compartments (regions and sectors), and further evaluate the whole system features. The results show that:

1) According to the energy-carbon nexus network model based on MRIO analysis, 53% of the total carbon emissions of China comes from the eastern area’s consumption of oil and natural gas and products from power generation sector produced in northeast, northwest and southwest areas. 2) According to the control analysis, the carbon emissions of the eastern areas will be indirectly controlled by the petroleum and natural gas extraction sector and electricity sector of northeast area, electricity sector of southwest area, and petroleum processing and coking sector and electricity sector of northwest area; The eastern area also exert control on the other areas via consumption-based carbon emissions, and the control intensities are evenly distributed among the south, southwest, central, north, northwest and northeast areas, ranging from 8%-18%. According to the reliance analysis, the reliant degrees of energy industries in northeast, southwest, and northwest areas range from 40%-50%, with the carbon flow pathways and directions being quite similar, flowing from natural gas production and supply, petroleum processing and coking, and electricity sectors to the eastern areas.

(2) Construction of assessment framework on China's multi-regional energy-water nexus network, including: 1) Establishing energy-water nexus network: combined with the energy and water consumption data of concerned provinces and regions, MRIO analysis is conducted to set up the water consumption matrix, account the water consumption of the energy production and consumption process and then construct the province-level energy-water nexus network model. 2) Establishing energy-water nexus system evaluation framework: construct the control and reliance indicators among regional industrial chains, and the ecological relationship indicators (symbiosis, competition, neutral, etc.) caused by final demand. 3) Establishing linkage network between Chinese energy-water nexus network and global energy trade, to investigate the impacts of energy imports and exports on energy-water nexus structure and function of China. Results show that: 1) The total water consumption of unit coal, oil and natural gas are near three times than their direct water consumption (taking coal as an example, the direct water consumption is 13 m³/TJ while the total is 34 m³/TJ). 2) From the aspect of supply chain, the energy-related embodied water flows to Shandong via product supply chain; Shandong and Inner Mongolia are the major end users facing serious water scarcity and imports water-intensive energy products will alleviate the local water resource shortage; Jiangsu, Tianjin, Hebei, and Henan have notable indirect control effects on the water resource consumption caused by energy production in the other areas. 3) From the perspective of consumer, Gansu is the largest exporter, with 54 Mm³ embodied water flowing to the other areas; while Hebei is the largest receiver, receiving 10 Mm³ embodied water from the other areas.

(3) Driving force analysis for energy-carbon nexus system of China. To identify the driving factors of energy-carbon nexus network, this thesis considers six factors: population variation, consumption variation, consumption pattern change, production structure adjustment, energy structure change, energy intensity change. Via the structural decomposition analysis (SDA), the contribution rate of each driving factor to the change of carbon emissions is explored to provide supports for the further simulation and predictions. The analysis of carbon emission changes during 1990-2014 shows that gross fixed capital is the major contributor of carbon emissions (30%-40%). The recent regulation of the estate will pose positive impacts on the carbon emissions. Considering all the driving factors, since the energy intensity contribute rating rate goes beyond 200% of that of the base year, the promotion of energy efficiency will be the most important pathway for carbon emission mitigation. The energy structure factor keeps contributing more to the carbon emissions while the population growth has little impact on the carbon emissions.

(4) Driving force analysis for energy-water nexus system of China. The energy-water nexus coefficient is the first time introduced into the driving force of water consumption. SDA is employed to investigate the energy-related water consumption of China concerning six factors: population variation, consumption variation, consumption pattern change, production structure adjustment, energy-water nexus coefficient change, energy intensity change. Results show that most of the water resources flow to two final consumers: government and gross fixed capital (each 40%). Since the government pushes the global planning for infrastructure construction and estate investment, more water will be consumed by these two sectors. Thus, it is critical to reduce the consumption of the government for construction sector and related sectors and the investment on the gross fixed capital.

(5) Building the energy inequality assessment framework of China. To reveal the income inequality transmission mechanism, this thesis collected the MRIO table of 112 countries, each with more than 200 groups of consumption structure data. Based on MRIO analysis of consumption data, the transmission processes of energy (both direct and indirect energy flow pathways) in different countries and various income groups are investigated; the energy GINI coefficient is proposed to represent the inequality of energy consumption of each country and evaluate the per capita gross energy consumption (both direct and indirect energy consumption) of each country at different economic development stages and its position in the globe. Results show that the average value of energy consumption of China is 28 GJ, which is much lower than the global average value of 39 GJ. Globally, the energy inequality situation of China needs to be improved，especial that of the low-income people, to the basic energy requirement line of 31.5 GJ. Germany has the most favorable equal energy consumption status and could be used as an exemplar for the sustainable development goal of energy production and consumption in China.

(6) Construction of integrated evaluation model, GAINS-IW model, to simulate the inequality transmission process in the energy-carbon-water nexus network. This thesis introduces the inequality issue into the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, and set up via Python: 1) Income structure module: including the Chinese population income matrix with multiple groups, income population gross consumption matrix, and consumption structure matrix of each income group (proportions among sectors). Combined with the energy consumption inequality indicators, scenarios with various income structures and poverty mitigation targets are set up to account the average income level of target groups, total energy consumption, and nexus coefficient of income level and energy consumption. 2) The linkage model concerning income structure module and energy activity module: the total energy consumption, various energy intensities, and energy consumption of various sectors are integrated to match with the energy consumption of the income module. 3) Water consumption module: including the direct water consumption matrix of each energy sector, indirect water consumption matrix of each energy sector, and the gross water consumption matrix. 4) Linkage model of water consumption module and energy activity module: the industrial sectors of energy module are matched with the energy sector of the water module via sector aggregation or disaggregation, to further optimize the water consumption intensity and the total water consumption. Finally, based on the income module, income linkage module, water consumption module, and water consumption linkage module, the water consumption and carbon emissions of China are predicted with the GAINS model. With the poverty alleviation targets of China, three inequality mitigation scenarios are set to simulate the linked variations of energy use, water use and carbon emissions via GAINS-IW model. Results show that, compared to the baseline scenario, improving the income level of low-income people to that of the medium-low income level people will increase 12% carbon emission growth in 2020, but do not delay the peak carbon emissions in 2030. The water consumption will increase by 28% in 2050 but is still under the limit of available water resources of China.