人民黄河

缓解经济发展与节能减排之间的矛盾是黄河流域资源型城市当前亟待解决的问题。为探讨黄河流域资源型城市碳排放的影响因素并进行达峰预测，选取黄河流域资源型城市2000—2020年数据，运用扩展STIRPAT模型分析其碳排放影响因素，基于BP神经网络构建碳排放预测模型分析了不同情景下的碳排放趋势。结果表明：2000—2020年黄河流域资源型城市碳排放量呈波动上升的趋势；人口规模、人均GDP、城镇化率和单位GDP能耗对碳排放量的增加有促进作用，产业结构优化对碳排放量的增加有抑制作用；不同情景下的资源型城市碳排放量差异较大。基于此，提出了黄河流域资源型城市应推动城市转型、加快产业结构优化，大力开发清洁能源、优化能源消费结构，鼓励节能技术创新、提高能源利用效率等建议。

Alleviating the contradiction between economic development and energy conservation and emission reduction is an urgent issue to be solved in resources-based cities in the Yellow River Basin. In order to discuss the influencing factors of carbon emissions of resources-based cities in the Yellow River Basin and make the peak prediction of carbon emission, this paper selected the data of resources-based cities in the Yellow River Basin from 2000 to 2020, used the extended STIRPAT model to analyze the influencing factors of carbon emissions and built a carbon emission prediction model based on BP neural network to analyze the carbon emission trends under different scenarios. The results show that: from 2000 to 2020, the carbon emissions of resources-based cities in the Yellow River Basin show a fluctuating upward trend; population size, per capita GDP, urbanization rate and energy consumption per unit of GDP can promote the increase in carbon emissions, while industrial structure has a inhibitory impact on carbon emissions; the carbon emissions of resources-based cities have bigger differences under different scenarios. Based on this, it is proposed that the resources-based cities in the Yellow River Basin should promote the speed of urban transformation, accelerate the optimization of industrial structure, vigorously develop clean energy, optimize the energy consumption structure, encourage energy conservation technology innovation and improve energy utilization efficiency.