北京市居民家庭水—能消费活动碳核算及影响因素分析

Analysis of Carbon Emissions Accounting and Influencing Factors of Water-Energy Consumption Behaviors in Beijing Residents

中文关键词:  居民家庭  消费行为  水—能耦合  碳排放

英文关键词:residential household  consumption behavior  water-energy nexus  carbon emission

中文摘要:

      本研究以北京市海淀区和通州区1320份居民家庭水—能消费行为调查问卷为样本，采用参数估算方法，核算了家庭洗澡、做饭、清洁、制冷供暖四类主要水—能消费行为的人均用水量、用电量、用气量和碳排放量，运用统计检验识别了不同人群的主要消费行为、碳排放特征，利用回归分析方法分析了不同人群的各种消费行为碳排放量的影响因素。研究结果显示，北京市居民家庭水—能耦合行为相关的人均用水量为26.9 m³/a、电耗为254.1 kW·h/a、燃气消耗量为27.8 m³/a，分别约占家庭全年消耗/排放总量的65.6%、31.8%和50.4%。水—能耦合行为相关总碳排放量包括居民家庭能耗直接碳排放量和水耗的水资源生产和处理过程间接碳排放量。案例地区居民家庭水—能耦合相关总碳排放量为376.7 kgCO₂/a，占家庭总量的40.1%，其中间接碳排放量为36.1kgCO₂/a，远低于直接碳排放量。这一结果说明城市水、能资源和碳排放协同管理需要重点关注消费端。从消费行为来看，家庭用水量中洗澡和做饭占比最高；用电量中不同季节行为差异较大，冬季洗澡用电占比最高，夏季制冷用电占比最高；各个行为的碳排放量在不同季节也有显著差异，其中冬季和春秋季洗澡碳排放量较高，夏季制冷碳排放量较高；高用水量人群洗澡和做饭行为的用水量绝对量和占比均较高，高碳排放人群的洗澡碳排放绝对量和占比均较高。从影响因素来看，洗澡行为变量对总碳排放量的影响作用高于做饭和清洁行为。研究表明，关注不同类型居民家庭的水—能耦合关系及相应的碳排放，尤其是洗澡和制冷行为，是家庭碳减排高关注度的优先领域。

英文摘要:

      In this study, 1320 questionnaires investigating the residential water and energy consumption behaviors in Haidian District and Tongzhou District of Beijing were used as samples. The per capita water consumption, electricity consumption, gas consumption, and carbon emission of four primary consumption behaviors (i.e., bathing, cooking, cleaning, and cooling/heating) were estimated using parameter estimation method. We identified the characteristics of carbon emission and associated influencing factors of the four consumption behaviors among different residents groups using the regression analysis. The results showed that the water consumption per capita was 26.9m³/a, electricity consumption was 254.1(kw·h)/a, and gas consumption was 27.8 m³/a, accounting for 65.6%, 31.8%, and 50.4% of the total annual residential water consumption, energy consumption, and CO₂ emission, respectively. The water-energy nexus-related carbon emissions in the case study were 376.7 kgCO₂/a, accounting for 40.1% of the carbon emissions, of which the indirect carbon emissions (carbon emissions from the production and treatment of residential consumed water resources) were 36.1 kgCO₂/a. The indirect carbon emissions were far less than direct carbon emissions (carbon emissions from residential energy consumption). This result implied that the collaborative management of urban water, energy, and carbon emissions needs to focus on the consumption side. Bathing and cooking accounted for the highest proportion of residential water consumption. Seasonal variations were significantly different in terms of behavioral level electricity and carbon emissions. The electricity consumption of bathing in winter was with the highest proportion while the electricity consumption of cooling in summer was the highest. The carbon emissions of bathing in winter and spring/autumn were higher, while the carbon emissions of cooling in summer were higher. For residents from the high water consumption group, their water consumption of bathing and cooking was higher (absolute amount and proportion). For residents from the high carbon emission group, their carbon emissions of bathing were higher. The bathing behaviors had larger impacts on the residential total carbon emissions than cooking and cleaning behaviors. Our study indicated that the behavioral level water-energy nexus and carbon emissions among different residents, especially the bathing and cooling behaviors, should be prioritized for residential resource consumption and carbon emission reduction.