Carbon Emission Prediction Method for Inland Ports Based on an Improved ASIF Model
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摘要: 针对港口碳排放量中长期预测影响因素复杂、预测精度低等问题，提出了基于改进ASIF方法的内河集装箱港口碳排放量核算模型，旨在量化主要因素对港口长期碳排放量的影响，为针对性制定碳中和策略提供依据。将港口集装箱吞吐量、设备结构、能耗强度、排放因子等作为港口碳排放量影响因素，考虑集装箱运输链中“多过程、多设备”的特点，改进了ASIF（activity-modal structure-energy intensity-emission factor）模型，可实现从宏观到微观层面的碳排放量预测。基于改进ASIF模型的解释变量建立情景预测指标体系，并以长江干线某集装箱港口为例，对其基准情景（business-as-usual，BAU）和低碳情景（low-carbon，LC）下的吞吐量、设备构成、运输结构等进行预测和设定，进而核算船舶航行、船舶停泊、岸桥、内集卡、场桥和外集卡的碳排放量。采用单因素实验方法分析不同低碳发展策略下的减排潜力，结果表明：与现有核算模型相比，使用改进的ASIF模型计算案例港口碳排放量，偏差在10%以内；案例港口这2种预测情景下，随着集装箱吞吐量持续增长，基准情景至2060年碳排放尚未达峰，低碳情景下到2055年左右实现碳达峰；船舶排放控制、港机能效提升、港口能源结构优化、集疏运结构优化均为有效的低碳发展策略，但效果依次降低；采用上述方法减排，将在2020—2060年间分别可实现约19万、17万、14.4万及1.1万t的累计碳减排。Abstract: Addressing the complexities and low accuracy of prediction associated with medium-to-long-term forecasting of port carbon emissions, this study proposes a carbon emission prediction (CEP) model for inland container ports based on an improved activity-modal structure-energy intensity-emission factor (ASIF) method. The objective is to quantify the impact of primary factors on long-term port carbon emissions, thereby providing a basis for targeted carbon neutrality strategies. By considering port container throughput, equipment structure, energy consumption intensity, and emission factors as influential factors of port carbon emissions, and accounting for the "multi-process, multi-equipment" characteristics within the container transportation chain, an improved ASIF model is established, which enables CEP from macro to micro levels. A scenario prediction indicator system is developed based on the explanatory variables of the ASIF model. Taking a container port on the Yangtze River as an example, predictions are made for its throughput, equipment composition, and transportation structure under the business-as-usual (BAU) scenario and the low-carbon (LC) scenario. Subsequently, carbon emissions from ship navigation, ship berthing, quay cranes, internal container trucks, yard cranes, and external container trucks are calculated. Lastly, to analyze the emission reduction potential under different low-carbon development strategies, a single-factor experimental approach is employed. The results indicate that: ①compared to existing prediction models, the deviations of carbon emission by the improved ASIF are within 10%. ②Under BAU and LC scenarios for the case port, with the continuous growth of container throughput, carbon emissions have not yet peaked by the year 2060 in the BAU scenario, whereas they are projected to the peak around the year 2055 in the LC scenario. ③Ship emission control, energy efficiency improvement, energy structure optimization, and collection and distribution system optimization are all effective low-carbon development strategies, albeit with decreasing effectiveness. ④Between the year 2020 to 2060, these strategies could achieve cumulative carbon reductions of approximately 190 000, 170 000, 144 000, and 11 000 t, respectively.
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表 2 A港区2010—2021年集装箱吞吐量
Table 2. Container throughput of port A from 2010 to 2021
年份 吞吐量/万TEU 年份 吞吐量/万TEU 2010 40.6 2016 79.6 2011 46.0 2017 84.9 2012 51.3 2018 93.7 2013 60.4 2019 101.2 2014 65.2 2020 107.3 2015 71.5 2021 119.6 
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表 3 设备构成及运输结构
Table 3. Equipment composition and transportation structure
设备名称 占比/% 集疏运方式 占比/% 航行船（油） 100 停泊船（油） 90 公水 51 停泊船（岸电） 10 岸桥（电） 100 水水 45 内集卡（油） 96 内集卡（电） 4 外集卡（油） 100 铁水 4 轨道吊（电） 100
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表 4 装卸设备能耗强度
Table 4. Energy consumption intensity of handling equipment
设备 能耗强度 岸桥/（kWh/TEU） 3.00 轨道式龙门吊/（kWh/TEU） 2.50 电动集卡/（kWh/km） 1.30 柴油集卡/(kg/t·km)* 0.012 注*：设集装箱平均重量为13t/TEU，每车可载2个20 ft标准集装箱或1个40 ft集装箱。
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表 5 船舶能耗强度计算中的参数设置
Table 5. Parameter setting of ship energy consumption intensity calculation
参数 取值 参数 取值 主机额定负载率fM 0.85 泊岸时辅机负载因子LFmaneuverA 0.5 设计速度vd /（km/h） 20 停泊时辅机负载因子LFberthA 0.17 巡航速度vsail /（km/h） 16.425 主机燃油效率RM /（kg/kWh） 0.2 泊岸速度vmaneuver /（km/h） 8.212 5 辅机燃油效率RA /（kg/kWh） 0.2 巡航距离Lsail /km 11.25 泊位利用率Ui /（TEU/h）* 30 or 60 泊岸距离Lmaneuver /km 1 非生产性停泊时间Tw /h 4 巡航时辅机负载因子LFsailA 0.25 船舶箱位利用率η 0.8 注：小于400 TEU的船型取30 TEU/h；大于400 TEU的船型取60 TEU/h。
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表 6 船舶的能耗强度
Table 6. Energy consumption intensity of ship
船型/TEU 航行能耗强度Iisail /（kg/TEU） 停泊能耗强度Iiberth /（kg/TEU） 船型/TEU 航行能耗强度Iisail /（kg/TEU） 停泊能耗强度Iiberth /（kg/TEU） 100 0.643 6 0.421 5 450 0.384 9 0.378 2 150 0.532 7 0.418 7 500 0.377 5 0.395 6 200 0.477 3 0.437 6 600 0.366 5 0.432 0 250 0.444 1 0.465 3 700 0.358 5 0.469 6 300 0.421 9 0.497 4 800 0.352 6 0.508 0 350 0.406 1 0.531 9 900 0.348 0 0.547 0 400 0.394 2 0.567 9 1 000 0.344 3 0.586 3
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表 7 情景预测指标设置
Table 7. Setting of scenario prediction indicators
预测指标 BAU LC 吞吐量 取组合模型预测值 同BAU 集疏运结构 铁水联运：2020—2025年，货运量年均增长15%；2025—2060年，年均增长10%。
水水中转：到2025年，水水中转比例提升至48%，2025年后，水水中转比例每年提升0.2%铁水联运：2020—2025年，货运量年均增长18%，2025—2060年，年均增长12%
水水中转：同BAU集卡电动化率 内集卡：2060年电动化率达到100%
外集卡[28]：2060年电动化率达到20%内集卡：2035年电动化率达到100%
外集卡[29]：2060年电动化率达到40%岸电利用率 2060年岸电利用率达到100% 2035年岸电利用率达到100% 船舶航行碳强度[29] 同基准年 年均下降1.5%* 能耗强度（不含航行） 同基准年 年均下降1%* 电力碳排放因子[30] 到2060年降至0.063 7 kg/kWh 同BAU 注：“*”为以2020年为基准年。
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表 8 港口碳中和实现策略
Table 8. Strategies for carbon neutrality for ports
减排措施 减排效果/万t 对应的碳中和实现策略 航行排放控制 19 近中期推广LNG或混合动力船的应用，并加强电动、氢氨动力等船舶的研发，中远期实现新能源船舶的较大规模应用。 港口设备能效提升 17 推动节能技术研发、自动化港口建设等，从硬件上提高港口能效；通过多资源协同调度、智能优化算法等提高港口运行效率。 港口能源结构优化 14.4 提高岸电使用率，逐步淘汰柴油驱动的港机和集卡，推动电力、氢燃料等在港口的应用。 运输结构优化 1.1 提高铁水、水水联运分担率，形成公路、水路、铁路等多种运输方式有效衔接的综合港口集疏运体系。 政策保障与其他措施 为氢、氨等燃料在船舶上的应用提供政策保障。尝试利用碳税、碳交易等市场机制推动港口碳减排。通过负排放技术实现完全意义上的碳中和。
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