Long-term carbon emission reduction potential of building retrofits with dynamically changing electricity emission factors
Long-term carbon emission reduction potential of building retrofits with dynamically changing electricity emission factors
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DOI：
10.1016/j.buildenv.2021.108683
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发表时间：
2022-01-02
影响因子：
7.4
通讯作者：
Zuo, Wangda
中科院分区：
文献类型：
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作者：
Lou, Yingli;Ye, Yunyang;Zuo, Wangda
建筑物约占美国总碳排放量的36%，建筑物改造具有减少碳排放的巨大潜力。目前的研究采用了一个恒定的电力排放系数，虽然它随着时间的推移，由于可再生能源发电的增加而变化。为了准确预测建筑改造的减排潜力，本研究开发了一种新的方法，利用动态变化的电力排放因子。以中型办公楼为例，我们预测了2020年至2050年美国五个气候和可再生能源采用率不同的地区的八项建筑改造措施的减排量。为了评估减排潜力对发电组成的敏感性，研究了可再生能源采用的五种情景。结果揭示了美国中型办公室建筑改造减排潜力的几个新现象：(1)从2026年到2050年，它会下降;（2）它与煤炭使用量有相同的趋势;（3）它在高可再生成本情景下达到最大值。根据研究结果，建议建筑改造应侧重于1）提高照明和设备效率; 2）煤炭使用率较高的地点; 3）高可再生能源成本情景下的建筑。新方法也可用于预测美国建筑行业的减排潜力，并可应用于其他建筑类型和地区。
Buildings account for approximately 36% of the United States' total carbon emissions and building retrofits have great potential to reduce carbon emissions. Current research adopts a constant electricity emission factor although it changes over time due to the increase of renewable energy generation. To accurately predict emission reduction potential of building retrofits, this study develops a novel method by using dynamically changing electricity emission factors. Using medium office buildings as an example, we predicted emission reduction of eight building retrofit measures from 2020 to 2050 in five locations in the U.S. with distinct climates and renewable adoption rates. To evaluate emission reduction potential sensitivity to the compositions of electricity generation, five scenarios for renewable energy adoptions are investigated. The results reveal several new phenomena on emission reduction potential of building retrofits for medium offices in the U.S.: (1) it decreases from 2026 to 2050; (2) it has the same trend with coal usage; and (3) it reaches the maximum under the high renewable cost scenario. Based on the results, it is recommended that building retrofits should focus on 1) improving lighting and equipment efficiency; 2) locations with higher coal usage rate, and 3) buildings under the high renewable cost scenario. The new method can also be used for predicting emission reduction potential of the building sector in the U.S. by applying to other building types and regions.