题目：中国城市化及农村人口减少带来的巨大而暂时的碳汇 (发表于Nature Sustainability)
A large but transient carbon sink from urbanization and rural depopulation in China
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会议时间：报告总时长约35分钟, 留言板&语音提问讨论25~40分钟
北京时间 7月8日（周五）晚上9:00 （欧洲专场特别时间）
纽约时间 7月8日（周五）上午9:00
哥本哈根时间 7月8日（周五）下午3:00
报告人简介
Xiaoxin Zhang, PhD student, Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
张晓鑫, 哥本哈根大学
报告摘要
China has experienced unprecedented urbanization and associated rural depopulation during recent decades alongside a massive increase in the total population. By using satellite and demographical datasets, we here test the hypothesis that urbanization and carbon neutrality are not mutually exclusive and that sustainably managed urbanization may even be an integral part of the pathway to reduce atmospheric CO2. We show that, although urban expansion caused an initial aboveground carbon loss of −0.02 PgC during 2002–2010, urban greening compensates these original losses with an overall balance of +0.03 PgC in urban areas during 2002–2019. We further show that a maximum increase in aboveground carbon stocks was observed at intermediate distances to rural settlements (2–4 km), reflecting the decreased pressure on natural resources. Consequently, rural areas experiencing depopulation (−14 million people yr−1) coincided with an extensive aboveground carbon sink of 0.28 ± 0.05 PgC yr−1 during 2002–2019, while at the same time only a slight decline in cropland areas (4%) was observed. However, tree cover growth saturation limits the carbon removal capacity of forests and only a decrease in CO2 emissions from fossil fuel burning will make the aim of carbon neutrality achievable.
近几十年来，中国经历了前所未有的城市化过程以及农村人口外流。利用遥感数据和人口统计数据，本研究检验了一个假设，即城市化和碳中和目标并不相互排斥，可持续管理的城市化有可能是减少大气 CO2 途径的一个组成部分。结果发现，尽管城市化在2002-2010年间导致了0.2亿吨陆地碳汇的丧失，但随后这部分损失被城市绿化所带来的0.3亿吨地上碳汇补偿。此外，在距离农村居民点的中等距离处（2 - 4 km），地上碳储量的增幅最大，反映了自然资源压力的降低。2002-2019年，农村地区人口减少（1400万人/年）的同时地上碳汇增加（0.28±0.05 Pg C/年）。同时总体耕地面积相较于2000年仅略有下降（-4%）。然而，树木覆盖增长的饱和性限制森林的碳汇能力，未来只有减少化石能源燃烧的CO2排放才能实现碳中和的目标。
研究背景
China has announced its plan to achieve carbon neutrality by 2060, which challenges current policies promoting the rapid urbanization of the entire country, as current per capita fossil CO2 emissions rates are four times higher in urban than in rural areas. However, several empirical studies have given evidence that rural outmigration can have a positive effect on vegetation production and carbon storage in rural regions. Several studies have identified China as a hot-spot of global greening and forest cover increase over the past decades, contradicting the perception that a rapid increase in population and urbanization could associate with degradation of vegetation. With this background, we hypothesize that urbanization and the aim of carbon neutrality are not mutually exclusive and that sustainably managed urbanization may even be an integral part of the pathway to reduce net CO2 emissions.
中国宣布了将在2060年实现碳中和的计划，由于目前城市的人均化石燃料二氧化碳排放率是农村地区的四倍，这一目标对整个国家促进快速城市化的政策提出了挑战。然而，一些实证研究表明农村人口外迁会对农村地区的植被生产和碳储量产生积极影响。同时一些研究发现，过去几十年来中国是全球绿化和森林覆盖率增加的热点地区，这与人口和城市化率快速增长导致植被退化的看法相矛盾。在此背景下，研究假设城市化和碳中和的目标并不相互排斥，可持续管理的城市化有可能成为减少二氧化碳净排放途径中的重要部分。
研究结果
A. 农村人口减少及城市区域的绿化
Fig 1 | Population change and urbanization in China. a, Static demographic population. b, Urban areas based on ESA-CCI land cover (urban land cover class). c, Total NTL based on calibrated DMSP/OLS.
Fig 2 | Land use/cover systems and MODiS carbon density change in China. a, Urban–agricultural–forest land systems (urban areas classified by artificial surfaces; Methods): upper inset, example of land use/cover in Shanghai; lower inset, same as upper but for trends in carbon density. b, Mean tree cover change, mean carbon density change and population change for different land use/cover types for 2000–2020. c, Aboveground carbon stocks in urban areas (including urban core, urbanization and suburban, see a). d, Population density (upper map) and carbon density change (lower map) in agricultural land (including ‘high agricultural pressure’ and ‘low agricultural pressure’; Methods). The western part of China with no/sparse vegetation and population (Xinjiang, Qinghai, Tibet) was excluded, shown as hatched areas.
B. 农村人口迁出与地上生物量的变化
Fig. 3 | Population migration and aboveground carbon density change in relation to distance to settlements. a, Population density change for 2000–2020 based on WorldPop. b, Trend in MODIS-based aboveground carbon density for 2002–2019. The western part of China with no/sparse vegetation and population (Xinjiang, Qinghai, Tibet) was excluded, shown as hatched areas. c, Boxplot of aboveground carbon density change and area of depopulation for different distances to settlements. d, Relative change of aboveground carbon density (carbon density change/carbon density in 2002) for different distances to settlements (×, mean value; –, median value). The same pattern remains if only agricultural areas are considered (Extended Data Fig. 5). e, Population migration calculated from mobile phone location data, determined as the difference between the period of spring festival holidays (28 January) and after spring festival (21 February) for eight provinces. f, Rural and urban population change from mobile phone location data in 2017 for eight provinces during spring festival (urban and rural areas from Fig. 2a,b). g, Aboveground carbon density change and rural population migration ratio (population migration/population density after spring festival) from mobile phone location data for different distances to settlements for eight provinces shown in e. In the box plots the lower and upper box limits are the 25th and 75th percentiles, the central line is the median, and the upper (lower) whiskers extend to 1.5 (−1.5) times the interquartile range.
Fig. 4 | Comparison of tree cover, carbon density and NTl for grouped changes of population density in China for different periods. a, Trend of MODIS-based aboveground carbon density change (Methods). b, Trend of tree cover based on VCF5KYR. c, Trend of calibrated NTL. The groups reflect different changes in population density: group 1, <−10; group 2, (−10, 0); group 3, (0, 10); group 4, (10, 150); group 5, ≥150 (units are people km−2). In a–c, ×, mean value; –, median value; significant differences between groups and periods were tested using the Kruskall–Wallis test, ****P < 0.001. The lower and upper box limits are the 25th and 75th percentiles, the central line is the median, and the upper (lower) whiskers extend to 1.5 (−1.5) times the interquartile range.
C. 略有减少的耕地（Fig.5a）
D. 地上碳汇潜力与CO2（Fig.5b）
Fig. 5 | land cover transitions and fossil carbon emissions in China. a, Loss of natural land from expanding areas of artificial surfaces and new forests replacing other land use/cover types based on GlobeLand 30 land cover maps (2000, 2020). b, Annual net carbon change, annual carbon emissions from fossil fuel burning and annual tree cover are shown. The error bars represent the uncertainty of MODIS carbon density data.
References:
Zhang, X., Brandt, M., Tong, X. et al. A large but transient carbon sinkfrom urbanization and rural depopulation in China. Nat Sustain (2022).https://doi.org/10.1038/s41893-021-00843-y.
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