黄河流域生态保护和高质量发展是国家重大发展战略。城市群是黄河流域社会经济发展的重要载体，在黄河流域高质量发展中发挥着重要支撑作用。工业发展推动了黄河流域城市群社会经济的快速繁荣，但同样是大气污染物和CO₂等温室气体排放的主要来源。特别是以能源和重工业为主导产业的呼包鄂榆、关中平原、中原三大城市群，2019年合计贡献了全流域41%以上的工业增加值，工业能源消耗量约占全流域工业能源消费总量的51%，已成为黄河流域工业碳排放与大气污染物排放的重点区域。面对黄河流域城市群生态保护以及“减污降碳，协同增效”的政策目标，本文选择了以呼包鄂榆、关中平原和中原三大城市群开展工业减污降碳研究具有重要的现实意义。

已有研究表明，中国工业碳排放与大气污染物排放具有高度“同源性”。学者们围绕减污降碳开展了大量研究，但主要集中于全国、省级或某一地市的钢铁、电力、交通等重点行业，对于黄河流域城市群工业部门缺乏关注。在减污降碳评估方面，现有研究侧重于评估某项政策/措施对于减污降碳的“协同性”及“累计效益”，但尚未揭示二者减排变动趋势的协同问题。在影响因素的研究中，应用最为广泛的分解分析方法往往受限于恒等关系和经典统计假设，从而导致指标数目较少，影响因子含义弱化。对于减污降碳政策的制定和执行，指标数目过少也会影响其可行性和有效性。

为此，本文首先对黄河流域三大城市群工业发展特征与排放特征进行了回顾分析；基于相对减排量构建了工业减污降碳状态指数，同时结合协同控制效应坐标系，从减污降碳状态和协同控制效应两方面回顾评价了三大城市群工业减污降碳的成效；采用随机森林模型识别了工业减污降碳的关键影响因素及其响应关系；在此基础上设计了五种工业发展情景，模拟预测了不同情景对三大城市群工业减污降碳效果的影响，并对黄河流域三大城市群工业发展提出了分阶段差异化的调控对策。主要研究结论如下：

（1）在产业结构上，呼包鄂榆城市群存在工业结构失衡问题；在工业能源消费上，三大城市群能耗强度远高于全国平均水平，能源消费结构长期呈现“一煤独大”特征。在工业排放压力上，研究区总体工业CO₂排放呈现“强度下降总量上涨”趋势，而呼包鄂榆城市群工业碳排放强度不降反升；尽管工业大气污染物近年来已得到控制，但排放强度仍高于全国平均水平。在排放空间格局上，研究区中部的榆林、鄂尔多斯、长治、晋城等城市是高污染、高碳排放重点城市。

（2）工业减污降碳回顾评价的结果表明：在2005-2010年期间，研究区27个城市实现了工业CO₂与LAP协同控制，但在2010-2015和2015-2019年期间，这一数量下降至24个，工业CO₂排放强度不降反升是阻碍部分城市实现二者协同控制的主要原因。呼包鄂榆城市群的工业减污降碳经历了“LAP协同——非协同——LAP协同”的过程，工业CO₂减排长期落后于工业LAP减排；关中平原城市群的工业减污降碳在2000-2005年期间表现为非协同状态，随后转为CO₂协同状态，在2015-2019年期间已十分接近均衡协同区间，工业CO₂与LAP协同减排的良性促进作用已逐步形成；中原城市群工业减污降碳始终保持正向协同状态，在2000-2005年期间表现为CO₂协同状态，随后始终保持均衡协同状态。

（3）工业减污降碳影响因素的分析结果表明：在影响因素重要性上，三大城市群工业CO₂排放的关键影响因素呈现很强的相似性，工业规模扩张和能耗强度居高不下是三大城市群工业CO₂排放快速增长的共同原因。三大城市群工业LAP的关键影响因素具有明显差异，结构因素是呼包鄂榆城市群的关键影响因素，技术因素是关中平原城市群的关键影响因素，而结构因素和技术因素对中原城市群均有显著影响。在影响因素响应关系分析上，各影响因素与工业CO₂、LAP排放之间均呈现显著的非线性特征。

（4）基于工业协同减排影响因素分析结果，设计了五个工业发展情景，包括基准情景、结构优化情景、技术进步情景、环境治理情景和组合情景。情景模拟预测结果表明：无论在何种优化情景下，三大城市群工业协同减排状态都将转入CO₂协同状态。从协同控制效应及减污降碳综合效益上看，结构优化、技术进步和环境治理在未来推动三大城市群工业减污降碳上各有优势。在组合情景下，由于可以同时考虑结构优化、技术进步和环境治理，并采取相对平衡的分阶段发展策略，能够最大程度上促进工业减污降碳，提高单位综合大气污染物排放所换取的经济效益。基于多情景预测结果及影响因素响应关系，分阶段提出了具有差异性的城市群工业发展对策建议。

本研究创新之处在于，构建了工业减污降碳状态指数，评估了三大城市群近二十年来减污降碳状态及变化趋势；借助机器学习模型开展工业减污降碳的影响因素研究，较好的克服了因素分解分析方法在指标选取上的局限；研究发现黄河流域三大城市群减污降碳影响因素与排放之间存在显著的非线性响应特征，结合影响因素在不同阈值内的作用方式，对三大城市群工业发展提出了分阶段差异化的调控对策。

          Ecological protection and high-quality development in the Yellow River Basin is a major national development strategy. Urban agglomeration has become an important carrier of social and economic development in the Yellow River Basin and plays an important supporting role in the high-quality development of the Yellow River Basin. Industry has promoted the formation and development of urban agglomerations in the Yellow River Basin. It is also the main sector of air pollutants and carbon dioxide emissions. In particular, the three major urban agglomerations of Hohhot-Baotou-Ordos-Yulin urban agglomeration (HBOY), Guanzhong Plain urban agglomeration (GZP) and Central Plains Urban Agglomeration (CP), with energy and heavy industry as the leading industries, contributed more than 41% of the industrial added value of the whole basin in 2019, and the industrial energy consumption accounted for about 51% of the total industrial energy consumption of the whole basin. It has become a key area for industrial carbon emission and air pollutant emission in the Yellow River Basin. Facing the requirements of "synergetic control of environmental pollution and carbon emissions" and ecological protection of urban agglomeration in the Yellow River Basin, this paper selects HBOY, GZP and CP as the case study areas to carry out the study on 

Previous researchs have shown that industrial carbon emissions and air pollutant emissions have a high degree of "homology" in China. At present, the research on synergistic emission reduction of industrial carbon emissions and air pollutants mostly focuses on key industries such as steel, electric power and transportation in the whole country, provincial level or a certain city, but lacks attention to the industry in the Yellow River Basin urban agglomeration. In the aspect of assessment, the existing research focuses on evaluating the "synergy" and "cumulative benefits" of a certain policy or measure for emission reduction, but has not revealed the synergy of emission reduction trends between industrial carbon emissions and air pollutants. In the study of emission influencing factors, decomposition analysis method is the most widely used, but it is often limited by identity relationship and classical statistical assumptions, resulting in a small number of indicators and weakening the meaning of influencing factors. For the formulation and implementation of emission reduction policies, too few indicators will also affect their feasibility and effectiveness.

Therefore, this paper analyzes the industrial development characteristics and emission characteristics of the three urban agglomerations in the Yellow River Basin firstly; Based on the relative emission reduction, this paper constructs the state index of industrial collaborative emission reduction, and carries out the retrospective evaluation of pollution and carbon reduction in the industrial sectors of the three urban agglomerations in combination with the coordinate system of collaborative control effect; The importance and response relationship of influencing factors of industrial synergistic emission reduction are analyzed by using random forest model; On this basis, multi-scenario prediction simulation is carried out, and different countermeasures and suggestions are put forward for the industrial development of the three major urban agglomerations in the Yellow River Basin. The main conclusions are as follows:

(1) In terms of industrial structure, there is an imbalance in industrial structure in HBOY; In terms of industrial energy consumption, the energy consumption intensity of the three major urban agglomerations is much higher than the national average, and raw coal accounts for more than 90% of the energy consumption structure. In terms of industrial emission pressure, the overall industrial carbon emission in the study area shows a trend of "intensity decline and total increase", while the industrial carbon emission intensity of HBOY does not decrease but rises; Although industrial air pollutants have been controlled in recent years, the emission intensity is still higher than the national average. In the spatial pattern of emission, Yulin, Erdos, Changzhi, Jincheng and other cities in the middle of the study area are key cities with high pollution and high carbon emission.

(2) The results of the retrospective evaluation of industrial synergetic control of environmental pollution and carbon emissions show that during 2005-2010, 27 cities in the study area realized the coordinated control of industrial CO₂ and LAP, but this number decreased to 24 during 2010-2015 and 2015-2019. The increase of industrial CO₂ emission intensity is the main reason that hinders some cities from realizing the coordinated control. The industrial synergistic emission reduction status of HBOY has experienced the process of "LAP-synergy—non-synergy—LAP-synergy", and industrial carbon emission reduction lags behind industrial air pollutant emission reduction for a long time; The industrial synergistic emission reduction status of GZP showed a non-synergy state from 2000 to 2005, and then changed to CO₂-synergy state, which was very close to the equilibrium-synergy range from 2015 to 2019, and the benign promotion effect of industrial carbon emission and air pollutant coordinated emission reduction has gradually taken shape; Industrial carbon emissions and air pollutant emission reduction in CP always maintain a positive synergy state, showing a CO₂-synergy state from 2000 to 2005, and then always maintain a equilibrium-synergy state.

(3) The analysis results of influencing factors of co-control of industrial pollutants and carbon emissions show that the key influencing factors of industrial carbon emissions in the three major urban agglomerations are highly similar in terms of the importance of influencing factors, and the common reasons for the rapid growth of industrial carbon emissions in the three major urban agglomerations are the expansion of industrial scale and high energy consumption intensity. There are obvious differences in the key influencing factors of industrial air pollutants in the three major urban agglomerations. Structural factors are the key influencing factors of HBOY, technical factors are the key influencing factors of GZP, and both structural factors and technical factors have significant influences in ZP. In the analysis of the response relationship of influencing factors, there are significant nonlinear characteristics between the influencing factors and industrial carbon emissions and air pollutants.

(4) Based on the analysis results of influencing factors of co-control of industrial pollutants and carbon emissions, five industrial development scenarios are designed, including business as usual scenario, structural optimization scenario, technological progress scenario, environmental governance scenario and combined scenario. Scenario simulation results show that: No matter what kind of optimization scenarios, the three major urban agglomerations of industrial synergistic emission reduction will be transferred to CO₂-synergy state. From the perspective of synergistic control effect and comprehensive benefits of pollution reduction and carbon reduction, structural optimization, technological progress and environmental governance have their own advantages in promoting industrial synergistic emission reduction in the three major urban agglomerations in the future. Under the combined scenario, because the three main influencing factors can be considered at the same time, and a relatively balanced phased development strategy can be adopted, it can promote industrial pollution reduction and carbon reduction to the greatest extent, and improve the economic benefits of unit comprehensive air pollutant emission. Based on the multi-scenario prediction results and the response relationship of influencing factors, this paper puts forward different countermeasures and suggestions for industrial development of urban agglomerations in stages.

  The innovation of this study is that the state index of co-control of industrial pollutants and carbon emissions is constructed, and the co-control state and change trend in the three urban agglomerations in recent 20 years are evaluated; With the help of machine learning model, the influencing factors of co-control are studied, which better overcomes the limitation of factor decomposition analysis method in index selection; It is found that there are significant nonlinear response characteristics between the influencing factors and emissions in the three urban agglomerations of the Yellow River Basin. Combined with the action modes of the influencing factors within different thresholds, the phased and differentiated regulation countermeasures for the industrial development of the three urban agglomerations are put forward.