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2018-2022 年湾区 CO 排放量持续减少。

Sustained Reductions of Bay Area CO Emissions 2018-2022.

机构信息

Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, California 94720, United States.

College of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States.

出版信息

Environ Sci Technol. 2024 Apr 16;58(15):6586-6594. doi: 10.1021/acs.est.3c09642. Epub 2024 Apr 4.

Abstract

Cities represent a significant and growing portion of global carbon dioxide (CO) emissions. Quantifying urban emissions and trends over time is needed to evaluate the efficacy of policy targeting emission reductions as well as to understand more fundamental questions about the urban biosphere. A number of approaches have been proposed to measure, report, and verify (MRV) changes in urban CO emissions. Here we show that a modest capital cost, spatially dense network of sensors, the Berkeley Environmental Air Quality and CO Network (BEACON), in combination with Bayesian inversions, result in a synthesis of measured CO concentrations and meteorology to yield an improved estimate of CO emissions and provide a cost-effective and accurate assessment of CO emissions trends over time. We describe nearly 5 years of continuous CO observations (2018-2022) in a midsized urban region (the San Francisco Bay Area). These observed concentrations constrain a Bayesian inversion that indicates the interannual trend in urban CO emissions in the region has been a modest decrease at a rate of 1.8 ± 0.3%/year. We interpret this decrease as primarily due to passenger vehicle electrification, reducing on-road emissions at a rate of 2.6 ± 0.7%/year.

摘要

城市代表了全球二氧化碳(CO)排放的重要且不断增长的部分。为了评估针对减排的政策的效果,以及更深入地了解有关城市生物圈的基本问题,需要对城市排放和随时间变化的趋势进行量化。已经提出了许多方法来衡量、报告和核实(MRV)城市 CO 排放的变化。在这里,我们表明,适度的资本成本、空间密集的传感器网络,即伯克利环境空气质量和 CO 网络(BEACON),与贝叶斯反演相结合,可将测量的 CO 浓度和气象数据综合起来,从而更好地估算 CO 排放,并对 CO 排放随时间变化的趋势进行经济有效的准确评估。我们描述了近 5 年来(2018-2022 年)在中等城市地区(旧金山湾区)进行的连续 CO 观测。这些观测到的浓度约束了贝叶斯反演,表明该地区的城市 CO 排放的年际趋势是适度减少,年减少率为 1.8±0.3%/年。我们将这种减少主要归因于乘用车的电气化,从而将道路排放量减少了 2.6±0.7%/年。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af27/11025126/efb2e77a3f3d/es3c09642_0001.jpg

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