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>A city-level comparison of fossil-fuel and industry processes-induced CO 2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories
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A city-level comparison of fossil-fuel and industry processes-induced CO 2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories
Abstract Background Quantifying CO 2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO 2 emissions. As the largest urbanized megalopolis region in northern China, the Beijing-Tianjin-Hebei (Jing-Jin-Ji, JJJ) region (population: 112.7 million) is under considerable pressure to reduce carbon emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the CO 2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies. Results Here, we collected and analyzed 8 published emission inventories to assess the emissions and uncertainty at the JJJ city level. The results showed that a large discrepancy existed in the JJJ emissions among downscaled country-level emission inventories, with total emissions ranging from 657 to 1132 Mt CO 2 (or 849?±?214 for mean?±?standard deviation (SD)) in 2012, while emission estimates based on provincial-level data estimated emissions to be 1038 and 1056 Mt. Compared to the mean emissions of city-data-based inventories (989 Mt), provincial-data-based inventories were 6% higher, and national-data-based inventories were 14% lower. Emissions from national-data-based inventories were 53–75% lower in the high-emitting industrial cities of Tangshan and Handan, while they were 47–160% higher in Beijing and Tianjin than those from city-data-based inventories. Spatially, the emissions pattern was consistent with the distribution of urban areas, and urban emissions in Beijing contributed 50–70% of the total emissions. Higher emissions from Beijing and Tianjin resulted in lower estimates of prefectural cities in Hebei for some national inventories. Conclusions National-level data-based emission inventories produce large differences in JJJ prefectural city-level emission estimates. The city-level statistics data-based inventories produced more consistent estimates. The consistent spatial distribution patterns recognized by these inventories (such as high emissions in southern Beijing, central Tianjin and Tangshan) potentially indicate areas with robust emission estimates. This result could be useful in the efficient deployment of monitoring instruments, and if proven by such measurements, it will increase our confidence in inventories and provide support for policy makers trying to reduce emissions in key regions.
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机译：摘要背景从城市量化CO 2排放是非常重要的，因为城市贡献了全球总共二氧化碳排放量的70％以上。作为中国北方最大的城市化的甲型大都市，京津冀（京锦吉，JJJ）地区（人口：112.7百万人）受到相当大的压力，以减少碳排放。尽管涵盖了JJJ地区的几种排放库存，但JJJ县城规模的二氧化碳排放综合评价仍然有限，而且该信息对实施缓解策略至关重要。结果在此，我们收集和分析了8个公布的排放库存，以评估JJJ市级的排放和不确定性。结果表明，在较低的国家级排放库存中的JJJ排放中存在大的差异，总排放量为657至1132 MT CO 2（或849？±214，用于平均值？标准偏差（SD）） 2012年，虽然基于省级数据估计排放的排放估计为1038和1056吨。与城市数据库存（989吨）的平均排放相比，基于省级数据的库存增加了6％，国家 - 基于数据的库存降低了14％。在唐山和邯郸的高散发工业城市中，基于国家数据的库存的排放量降低了53-75％，而北京和天津的高度较高47-160％，而不是城市数据库库存。在空间上，排放模式与城市地区的分布一致，北京的城市排放占总排放量的50-70％。北京和天津较高的排放导致河北省河北省县城的估算率较低。结论国家级数据的排放库存产生了JJJ县级排放估计的巨大差异。城市级别的基于数据的库存产生了更一致的估计。这些库存（如北京南部，北京市南部，中央和唐山的高排放）所识别的一贯的空间分布模式可能表明具有稳健的排放估计的地区。该结果可用于有效部署监测仪器，如果通过此类测量证明，它将增加我们对库存的信心，并为决策者提供支持减少关键区域排放的支持。
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