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Growing-season carbon budget of alpine meadow ecosystem in the Qinghai Lake Basin: a continued carbon sink through this century according to the Biome-BGC model 青海湖盆地高寒草甸生态系统生长季碳预算:根据生物-生物-碳汇模型,本世纪碳汇仍将持续
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-12-19 DOI: 10.1186/s13021-023-00244-y
Meng-ya Zhang, Yu-jun Ma, Peng Chen, Fang-zhong Shi, Jun-qi Wei

Background

The alpine meadow is one of the most important ecosystems in the Qinghai-Tibet Plateau (QTP), and critically sensitive to climate change and human activities. Thus, it is crucial to precisely reveal the current state and predict future trends in the carbon budget of the alpine meadow ecosystem. The objective of this study was to explore the applicability of the Biome-BGC model (BBGC) in the Qinghai Lake Basin (QLB), identify the key parameters affecting the variation of net ecosystem exchange (NEE), and further predict the future trends in carbon budget in the QLB.

Results

The alpine meadow mainly acted as carbon sink during the growing season. For the eco-physiological factors, the YEL (Yearday to end litterfall), YSNG (Yearday to start new growth), CLEC (Canopy light extinction coefficient), FRC:LC (New fine root C: new leaf C), SLA (Canopy average specific leaf area), C:Nleaf (C:N of leaves), and FLNR (Fraction of leaf N in Rubisco) were confirmed to be the top seven parameters affecting carbon budget of the alpine meadow. For the meteorological factors, the sensitivity of NEE to precipitation was greater than that to vapor pressure deficit (VPD), and it was greater to radiation than to air temperature. Moreover, the combined effect of two different meteorological factors on NEE was higher than the individual effect of each one. In the future, warming and wetting would enhance the carbon sink capacity of the alpine meadow during the growing season, but extreme warming (over 3.84 ℃) would reduce NEE (about 2.9%) in the SSP5-8.5 scenario.

Conclusion

Overall, the alpine meadow ecosystem in the QLB generally performs as a carbon sink at present and in the future. It is of great significance for the achievement of the goal of carbon neutrality and the management of alpine ecosystems.

背景高寒草甸是青藏高原最重要的生态系统之一,对气候变化和人类活动极为敏感。因此,准确揭示高寒草甸生态系统碳预算的现状并预测其未来趋势至关重要。本研究旨在探索青海湖流域生物群落-生态系统交换模型(BBGC)的适用性,确定影响净生态系统交换(NEE)变化的关键参数,并进一步预测青海湖流域碳收支的未来趋势。在生态生理因子方面,YEL(落叶结束日)、YSNG(开始新生长日)、CLEC(冠层消光系数)、FRC:LC(新细根C:新叶C)、SLA(冠层平均比叶面积)、C:Nleaf(叶片C:N)和FLNR(Rubisco中叶片N的比例)被确认为影响高山草甸碳收支的前七个参数。在气象因子方面,NEE对降水的敏感性大于对水汽压差(VPD)的敏感性,对辐射的敏感性大于对气温的敏感性。此外,两种不同气象因子对 NEE 的综合影响要高于每种因子的单独影响。在未来,增温和湿润将提高高山草甸在生长季节的碳汇能力,但在 SSP5-8.5 情景下,极端增温(超过 3.84 ℃)将降低 NEE(约 2.9%)。这对实现碳中和目标和管理高山生态系统具有重要意义。
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引用次数: 0
The impact of land cover change on the carbon stock of moist afromontane forests in the Majang Forest Biosphere Reserve 马江森林生物圈保护区土地覆被变化对湿润山地森林碳储量的影响
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-12-07 DOI: 10.1186/s13021-023-00243-z
Semegnew Tadese, Teshome Soromessa, Abreham Berta Aneseye, Getaneh Gebeyehu, Tomasz Noszczyk, Mengistie Kindu

Backgorund

Forest plays an important role in the global carbon cycle by sequestering carbon dioxide and thereby mitigating climate change. In this study, an attempt was made to investigate the effects of land use/land cover (LULC) change (1989–2017) on carbon stock and its economic values in tropical moist Afromontane forests of the Majang Forest Biosphere Reserve (MFBR), south-west Ethiopia. Systematic sampling was conducted to collect biomass and soil data from 140 plots in MFBR. The soil data were collected from grassland and farmland. InVEST modelling was employed to investigate the spatial and temporal distribution of carbon stocks. Global Voluntary Market Price (GVMP) and Tropical Economics of Ecosystems and Biodiversity (TEEB) analysis was performed to estimate economic values (EV) of carbon stock dynamics. Correlation and regression analyses were also employed to identify the relationship between environmental and anthropogenic impacts on carbon stocks.

Results

The results indicated that the above-ground carbon and soil organic carbon stocks were higher than the other remaining carbon pools in MFBR. The mean carbon stock (32.59 M tonne) in 2017 was lower than in 1989 (34.76 Mt) of MFBR. Similarly, the EV of carbon stock in 2017 was lower than in 1989. Elevation, slope, and harvesting index are important environmental and disturbance factors resulting in major differences in carbon stock among study sites in MFBR.

Conclusions

Therefore, the gradual reduction of carbon stocks in connection with LULC change calls for urgent attention to implement successful conservation and sustainable use of forest resources in biosphere reserves.

背景:森林通过吸收二氧化碳从而减缓气候变化,在全球碳循环中发挥着重要作用。本研究旨在探讨1989-2017年土地利用/土地覆盖(LULC)变化对埃塞俄比亚西南部马江森林生物圈保护区(MFBR)热带湿润非洲山地森林碳储量及其经济价值的影响。对MFBR试验区140个样地的生物量和土壤进行了系统采样。土壤数据采集自草地和农田。采用InVEST模型对碳储量的时空分布进行了研究。采用全球自愿市场价格(GVMP)和热带生态系统与生物多样性经济学(TEEB)分析估算碳储量动态的经济价值(EV)。利用相关分析和回归分析确定了环境和人为影响对碳储量的影响关系。结果:MFBR地上碳储量和土壤有机碳储量均高于其他剩余碳库。2017年MFBR的平均碳储量(3259万吨)低于1989年的3476万吨。同样,2017年碳储量EV低于1989年。高程、坡度和收获指数是导致不同研究点间碳储量差异的重要环境因子和干扰因子。结论:因此,碳储量的逐渐减少与LULC变化有关,迫切需要关注生物圈保护区森林资源的成功保护和可持续利用。
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引用次数: 0
Enteric methane emission factors of smallholder dairy farming systems across intensification gradients in the central highlands of Ethiopia 埃塞俄比亚中部高地小农奶牛养殖系统跨集约化梯度的肠道甲烷排放因子
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-11-29 DOI: 10.1186/s13021-023-00242-0
Abraham Abera Feyissa, Feyera Senbeta, Adugna Tolera, Dawit Diriba, Kalaya Boonyanuwat

Background

Following global pledges to reduce greenhouse gas (GHG) emissions by 30% by 2030 compared to the baseline level of 2020, improved quantification of GHG emissions from developing countries has become crucial. However, national GHG inventories in most Sub-Saharan African countries use default (Tier I) emission factors (EFS) generated by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric CH4 emissions from animal agriculture. The present study provides an improved enteric CH4 emission estimate (Tier II) based on animal energy requirements derived from animal characteristics and performance data collected from about 2500 cattle in 480 households from three smallholder farming systems to represent the common dairy farming in the central highlands of Ethiopia. Using average seasonal feed digestibility data, we estimated daily methane production by class of animal and farming system and subsequently generated improved EF.

Results

Our findings revealed that the estimated average EF and emission intensities (EI) vary significantly across farming systems. The estimated value of EF for adult dairy cows was 73, 69, and 34 kg CH4/cow/year for urban, peri-urban, and rural farming systems, respectively. Rural dairy farming had significantly higher emission intensity (EI) estimated at 1.78 CO2-eq per kg of fat protein-corrected milk (FPCM) than peri-urban and urban 0.71 and 0.64 CO2-eq kg−1 FPCM dairy farming systems, respectively. The EF estimates in this study are lower than the IPCC's (2019) default value for both stall-fed high-productive and dual-purpose low-productive cows.

Conclusions

The current findings can be used as a baseline for the national emission inventory, which can be used to quantify the effects of future interventions, potentially improving the country's commitment to reducing GHG emissions. Similarly, this study suggests that increased animal productivity through improved feed has a considerable mitigation potential for reducing enteric methane emissions in smallholder dairy farming systems in the study area.

背景:在全球承诺到2030年将温室气体(GHG)排放量在2020年的基准水平上减少30%之后,改进发展中国家温室气体排放的量化变得至关重要。然而,大多数撒哈拉以南非洲国家的国家温室气体清单使用政府间气候变化专门委员会(IPCC)生成的默认(一级)排放因子(EFS)来估计畜牧业的肠道CH4排放量。本研究提供了一个改进的肠道甲烷排放估算(第二级),该估算基于动物能量需求,这些能量需求来自来自埃塞俄比亚中部高地三个小农农业系统的约2500头牛的动物特征和性能数据,这些系统代表了埃塞俄比亚中部高地常见的奶牛养殖。利用平均季节性饲料消化率数据,我们按动物类别和耕作系统估计了每日甲烷产量,并随后产生了改善的饲料能量。结果:我们的研究结果表明,不同的农业系统估计的平均EF和排放强度(EI)差异显著。在城市、城郊和农村耕作系统中,成年奶牛的EF分别为73、69和34 kg CH4/奶牛/年。农村奶牛养殖的排放强度(EI)为1.78 co2当量/ kg,显著高于城市周边和城市的0.71和0.64 co2当量/ kg-1 FPCM奶牛养殖系统。本研究中对高产奶牛和双用途低产量奶牛的EF估计值均低于IPCC(2019)的默认值。结论:目前的研究结果可作为国家排放清单的基线,可用于量化未来干预措施的效果,从而有可能改善该国减少温室气体排放的承诺。同样,本研究表明,通过改善饲料提高动物生产力对于减少研究地区小农奶牛养殖系统的肠道甲烷排放具有相当大的缓解潜力。
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引用次数: 0
Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency 注意差距:协调来自地球观测和国家报告的热带森林碳通量估算需要透明度。
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-11-20 DOI: 10.1186/s13021-023-00240-2
Viola Heinrich, Jo House, David A. Gibbs, Nancy Harris, Martin Herold, Giacomo Grassi, Roberta Cantinho, Thais M. Rosan, Barbara Zimbres, Julia Z. Shimbo, Joana Melo, Tristram Hales, Stephen Sitch, Luiz E. O. C. Aragão

Background

The application of different approaches calculating the anthropogenic carbon net flux from land, leads to estimates that vary considerably. One reason for these variations is the extent to which approaches consider forest land to be “managed” by humans, and thus contributing to the net anthropogenic flux. Global Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent and consistent approach to estimate forest carbon fluxes. These can be compared against results reported in National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely measuring, reporting and verification (MRV). Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare a Global EO-based dataset of forest carbon fluxes to results reported in NGHGIs.

Results

Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (− 0.2 GtCO2yr−1), while Brazil’s NGHGI reported a net carbon source (+ 0.8 GtCO2yr−1). After adjusting the EO estimate to use the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory’s methodology, the EO net flux became a source of + 0.6 GtCO2yr−1, comparable to the NGHGI. Remaining discrepancies are due largely to differing carbon removal factors and forest types applied in the two datasets. In Indonesia, the EO and NGHGI net flux estimates were similar (+ 0.6 GtCO2 yr−1), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO2 yr−1; Global EO: + 0.2 GtCO2 yr−1). Spatially explicit datasets on forest types were not publicly available for analysis from either NGHGI, limiting the possibility of detailed adjustments.

Conclusions

By adjusting the EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences can be explained. Despite limited spatial data available for Indonesia and Malaysia, our comparison indicated specific aspects where differing approaches may explain divergence, including uncertainties and inaccuracies. Our study highlights the importance of enhanced transparency, as set out by the Paris Agreement, to enable alignment between different approaches for independent measuring and verification.

背景:计算陆地人为碳净通量的不同方法导致估算值差异很大。造成这些差异的一个原因是,各种方法认为林地在多大程度上是由人类“管理”的,从而对人为净通量有所贡献。描述土地覆盖和碳储量时空变化特征的全球地球观测数据集为估算森林碳通量提供了一种独立和一致的方法。这些可以与国家温室气体清单(NGHGIs)报告的结果进行比较,以支持准确和及时的测量、报告和核查(MRV)。我们以巴西为主要案例研究,并对印度尼西亚和马来西亚进行了进一步分析,将基于全球生态系统的森林碳通量数据集与全球温室气体地理信息系统报告的结果进行了比较。结果:2001年至2020年期间,由eo得出的所有森林相关排放和清除的估计表明,巴西是碳的净汇(- 0.2亿吨二氧化碳年-1),而巴西的NGHGI报告的净碳源(+ 0.8亿吨二氧化碳年-1)。在使用巴西国家温室气体指数(NGHGI)对管理森林的定义和清单方法中使用的其他假设对估算值进行调整后,估算值的净通量为+ 0.6亿吨二氧化碳年-1,与国家温室气体指数相当。剩下的差异主要是由于两个数据集使用的碳去除因子和森林类型不同。在印度尼西亚,EO和NGHGI净通量估算值相似(+ 0.6 GtCO2年-1),但在马来西亚,它们在量级和符号上都不同(NGHGI: -0.2 GtCO2年-1;全球EO: + 0.2 GtCO2年-1)。关于森林类型的空间明确数据集没有公开提供,供两种全球温室气体指数分析,限制了详细调整的可能性。结论:通过调整EO数据集以提高与巴西NGHGI管理森林碳通量估计值的可比性,最初的分歧估计值在很大程度上得到了调和,其余差异可以解释。尽管印度尼西亚和马来西亚可用的空间数据有限,但我们的比较表明了不同方法可能解释差异的具体方面,包括不确定性和不准确性。我们的研究强调了《巴黎协定》所规定的提高透明度的重要性,以使不同的方法能够协调一致,进行独立的测量和验证。
{"title":"Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency","authors":"Viola Heinrich,&nbsp;Jo House,&nbsp;David A. Gibbs,&nbsp;Nancy Harris,&nbsp;Martin Herold,&nbsp;Giacomo Grassi,&nbsp;Roberta Cantinho,&nbsp;Thais M. Rosan,&nbsp;Barbara Zimbres,&nbsp;Julia Z. Shimbo,&nbsp;Joana Melo,&nbsp;Tristram Hales,&nbsp;Stephen Sitch,&nbsp;Luiz E. O. C. Aragão","doi":"10.1186/s13021-023-00240-2","DOIUrl":"10.1186/s13021-023-00240-2","url":null,"abstract":"<div><h3>Background</h3><p>The application of different approaches calculating the anthropogenic carbon net flux from land, leads to estimates that vary considerably. One reason for these variations is the extent to which approaches consider forest land to be “managed” by humans, and thus contributing to the net anthropogenic flux. Global Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent and consistent approach to estimate forest carbon fluxes. These can be compared against results reported in National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely measuring, reporting and verification (MRV). Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare a Global EO-based dataset of forest carbon fluxes to results reported in NGHGIs.</p><h3>Results</h3><p>Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (− 0.2 GtCO<sub>2</sub>yr<sup>−1</sup>), while Brazil’s NGHGI reported a net carbon source (+ 0.8 GtCO<sub>2</sub>yr<sup>−1</sup>). After adjusting the EO estimate to use the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory’s methodology, the EO net flux became a source of + 0.6 GtCO<sub>2</sub>yr<sup>−1</sup>, comparable to the NGHGI. Remaining discrepancies are due largely to differing carbon removal factors and forest types applied in the two datasets. In Indonesia, the EO and NGHGI net flux estimates were similar (+ 0.6 GtCO<sub>2</sub> yr<sup>−1</sup>), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO<sub>2</sub> yr<sup>−1</sup>; Global EO: + 0.2 GtCO<sub>2</sub> yr<sup>−1</sup>). Spatially explicit datasets on forest types were not publicly available for analysis from either NGHGI, limiting the possibility of detailed adjustments.</p><h3>Conclusions</h3><p>By adjusting the EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences can be explained. Despite limited spatial data available for Indonesia and Malaysia, our comparison indicated specific aspects where differing approaches may explain divergence, including uncertainties and inaccuracies. Our study highlights the importance of enhanced transparency, as set out by the Paris Agreement, to enable alignment between different approaches for independent measuring and verification.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"18 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662451/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138045947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative analysis of soil organic matter fractions, lability, stability ratios, and carbon management index in various land use types within bharatpur catchment, Chitwan District, Nepal 尼泊尔Chitwan区bharatpur流域不同土地利用类型的土壤有机质组分、不稳定性、稳定性比和碳管理指数的比较分析。
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-11-03 DOI: 10.1186/s13021-023-00241-1
Yves Theoneste Murindangabo, Marek Kopecký, Trong Nghia Hoang, Jaroslav Bernas, Tulsi Parajuli, Suman Dhakal, Petr Konvalina, Jean de Dieu Marcel UFITIKIREZI, Gisele Kaneza, Babu Ram Khanal, Shiva Chandra Dhakal, Arjun Kumar Shrestha

Background

Land use and land cover changes have a significant impact on the dynamics of soil organic matter (SOM) and its fractions, as well as on overall soil health. This study conducted in Bharatpur Catchment, Chitwan District, Nepal, aimed to assess and quantify variations in total soil organic matter (TSOMC), labile organic matter fraction (CL), stable organic matter fraction (CS), stability ratio (SR), and carbon management index (CMI) across seven land use types: pastureland, forestland, fruit orchards, small-scale conventional agricultural land, large-scale conventional agricultural land, large-scale alternative fallow and conventional agricultural land, and organic farming agricultural land. The study also explored the potential use of the Carbon Management Index (CMI) and stability ratio (SR) as indicators of soil degradation or improvement in response to land use changes.

Results

The findings revealed significant differences in mean values of TSOMC, CL, and CS among the different land use types. Forestland and organic farming exhibited significantly higher TSOMC (3.24%, 3.12%) compared to fruit orchard lands (2.62%), small scale conventional farming (2.22%), alternative fallow and conventional farming (2.06%), large scale conventional farming (1.84%) and pastureland (1.20%). Organic farming and Forestland also had significantly higher CL (1.85%, 1.84%) and CS (1.27%, 1.39%) compared to all other land use types. Forest and organic farming lands showed higher CMI values, while pastures and forests exhibited higher SR values compared to the rest of the land use types.

Conclusions

This study highlights the influence of various land use types on soil organic matter pools and demonstrates the potential of CMI and SR as indicators for assessing soil degradation or improvement in response to land use and land cover changes.

背景:土地利用和土地覆盖变化对土壤有机质(SOM)及其组分的动态以及整体土壤健康具有重要影响。这项研究在尼泊尔奇特万区巴拉特布尔流域进行,旨在评估和量化七种土地利用类型的土壤总有机质(TSOMC)、不稳定有机质分数(CL)、稳定有机物分数(CS)、稳定性比(SR)和碳管理指数(CMI)的变化:牧场、林地、果园、,大规模常规农业用地、大规模替代休耕和常规农业用土地以及有机农业用地。该研究还探讨了碳管理指数(CMI)和稳定性比(SR)作为土壤退化或改善指标的潜在用途,以应对土地利用变化。结果:不同土地利用类型的TSOMC、CL和CS平均值存在显著差异。与果园地(2.62%)、小规模传统农业(2.22%)、替代休耕和传统农业(2.06%)相比,林地和有机农业表现出显著更高的TSOMC(3.24%,3.12%),与所有其他土地利用类型相比,有机农业和林地的CL(1.85%,1.84%)和CS(1.27%,1.39%)也显著较高。与其他土地利用类型相比,森林和有机农业用地的CMI值更高,而牧场和森林的SR值更高。结论:本研究强调了各种土地利用类型对土壤有机质库的影响,并证明了CMI和SR作为评估土壤退化或改善的指标对土地利用和土地覆盖变化的潜力。
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引用次数: 0
Spatial heterogeneity and scenario simulation of carbon budget on provincial scale in China 中国省级碳预算的空间异质性和情景模拟。
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-09-20 DOI: 10.1186/s13021-023-00237-x
Zhenyue Liu, Jinbing Zhang, Pengyan Zhang, Ling Jiang, Dan Yang, Tianqi Rong

Background

Conducting an extensive study on the spatial heterogeneity of the overall carbon budget and its influencing factors and the decoupling status of carbon emissions from economic development, by undertaking simulation projections under different carbon emission scenarios is crucial for China to achieve its targets to peak carbon emissions by 2030 and to achieve carbon neutrality by 2060. There are large disparities in carbon emissions from energy consumption, the extent of land used for carbon absorption, and the status of decoupling of emissions from economic development, among various regions of China.

Results

Based on night light data and land use data, we investigated carbon budget through model estimation, decoupling analysis, and scenario simulation. The results show that the carbon deficit had a continuous upward trend from 2000 to 2018, and there was a significant positive spatial correlation. The overall status of decoupling first improved and then deteriorated. Altogether, energy consumption intensity, population density of built-up land, and built-up land area influenced the decoupling of carbon emissions from economic development. There are significant scenarios of carbon emissions from energy consumption for the study area during the forecast period, only in the low-carbon scenario will the study area reach the expected carbon emissions peak ahead of schedule in 2027; the peak carbon emissions will be 6479.27 million tons.

Conclusions

China’s provincial-scale carbon emissions show a positive correlation with economic development within the study period. It is necessary to optimize the economic structure, transforming the economic development mode, and formulating policies to control the expansion of built-up land. Efforts must be made to improve technology and promote industrial restructuring, to effectively reduce energy consumption intensity.

背景:对总体碳预算的空间异质性及其影响因素以及碳排放与经济发展的脱钩状况进行了广泛的研究,通过在不同碳排放情景下进行模拟预测,对于中国实现到2030年碳排放峰值和到2060年实现碳中和的目标至关重要。结果:基于夜光数据和土地利用数据,通过模型估计、脱钩分析和情景模拟,对我国各地区能源消费碳排放、碳吸收土地利用程度以及排放与经济发展脱钩状况进行了调查。结果表明,2000-2008年,碳赤字呈持续上升趋势,且存在显著的正空间相关性。脱钩的总体状况先是改善后恶化。综合来看,能源消耗强度、建成区人口密度和建成区面积影响了碳排放与经济发展的脱钩。预测期内,研究区域能源消耗产生的碳排放存在显著情景,只有在低碳情景下,研究区域才会在2027年提前达到预期的碳排放峰值;碳排放峰值为647927万吨。结论:在研究期内,中国省级碳排放量与经济发展呈正相关。要优化经济结构,转变经济发展方式,制定控制建设用地扩张的政策。要着力提高技术水平,推动产业结构调整,切实降低能源消耗强度。
{"title":"Spatial heterogeneity and scenario simulation of carbon budget on provincial scale in China","authors":"Zhenyue Liu,&nbsp;Jinbing Zhang,&nbsp;Pengyan Zhang,&nbsp;Ling Jiang,&nbsp;Dan Yang,&nbsp;Tianqi Rong","doi":"10.1186/s13021-023-00237-x","DOIUrl":"10.1186/s13021-023-00237-x","url":null,"abstract":"<div><h3>Background</h3><p>Conducting an extensive study on the spatial heterogeneity of the overall carbon budget and its influencing factors and the decoupling status of carbon emissions from economic development, by undertaking simulation projections under different carbon emission scenarios is crucial for China to achieve its targets to peak carbon emissions by 2030 and to achieve carbon neutrality by 2060. There are large disparities in carbon emissions from energy consumption, the extent of land used for carbon absorption, and the status of decoupling of emissions from economic development, among various regions of China.</p><h3>Results</h3><p>Based on night light data and land use data, we investigated carbon budget through model estimation, decoupling analysis, and scenario simulation. The results show that the carbon deficit had a continuous upward trend from 2000 to 2018, and there was a significant positive spatial correlation. The overall status of decoupling first improved and then deteriorated. Altogether, energy consumption intensity, population density of built-up land, and built-up land area influenced the decoupling of carbon emissions from economic development. There are significant scenarios of carbon emissions from energy consumption for the study area during the forecast period, only in the low-carbon scenario will the study area reach the expected carbon emissions peak ahead of schedule in 2027; the peak carbon emissions will be 6479.27 million tons.</p><h3>Conclusions</h3><p>China’s provincial-scale carbon emissions show a positive correlation with economic development within the study period. It is necessary to optimize the economic structure, transforming the economic development mode, and formulating policies to control the expansion of built-up land. Efforts must be made to improve technology and promote industrial restructuring, to effectively reduce energy consumption intensity.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"18 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10510156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41104024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The fusion of multiple scale data indicates that the carbon sink function of the Qinghai-Tibet Plateau is substantial 多尺度数据的融合表明,青藏高原的碳汇功能是巨大的
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-09-11 DOI: 10.1186/s13021-023-00239-9
Jingyu Zeng, Tao Zhou, Yixin Xu, Qiaoyu Lin, E. Tan, Yajie Zhang, Xuemei Wu, Jingzhou Zhang, Xia Liu

Background

The Qinghai-Tibet Plateau is the “sensitive area” of climate change, and also the “driver” and “amplifier” of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale.

Results

Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30–70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source).

Conclusions

The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community’s understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve “carbon neutrality” by 2060.

青藏高原是气候变化的“敏感区”,也是全球变化的“驱动器”和“放大器”。其碳动态对气候变化的响应和反馈将显著影响大气中温室气体的含量。然而,由于青藏高原独特的地理环境特征,其碳源和碳汇估算结果仍存在诸多争议。本研究设计了一种基于机器学习的新算法,通过整合来自遥感和地面观测的多尺度碳输入(净初级生产力,NPP)和输出(土壤异养呼吸,Rh)信息,提高碳源和碳汇估算的准确性。然后,我们将多尺度数据融合得到的NPP和Rh的空间格局与其他广泛使用的产品进行了比较,并试图量化区域尺度上碳汇模拟的差异和不确定性。结果全球变暖固然增加了青藏高原的Rh,但也增加了其NPP,目前表现为净碳汇面积(碳汇量为22.3 Tg C/年)。与其他数据产品的对比分析表明,基于遥感的CASA、GLOPEM和MODIS产品低估了青藏高原的碳输入(30-70%),这是青藏高原碳汇水平被严重低估的主要原因。结论青藏高原碳汇的估算对保障其生态屏障功能具有重要意义。它可以加深社区对高原敏感地区气候变化响应的理解。该研究可为评估青藏高原碳源和碳汇的不确定性提供重要依据,也为帮助中国在2060年前实现“碳中和”提供科学参考。
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引用次数: 0
From political pledges to quantitative mapping of climate mitigation plans: Comparison of two European cities 从政治承诺到气候缓解计划的定量制图:两个欧洲城市的比较
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-09-06 DOI: 10.1186/s13021-023-00236-y
Ivonne Albarus, Giorgia Fleischmann, Patrick Aigner, Philippe Ciais, Hugo Denier van der Gon, Rianne Droge, Jinghui Lian, Miguel Andrey Narvaez Rincon, Hervé Utard, Thomas Lauvaux

Background

Urban agglomerates play a crucial role in reaching global climate objectives. Many cities have committed to reducing their greenhouse gas emissions, but current emission trends remain unverifiable. Atmospheric monitoring of greenhouse gases offers an independent and transparent strategy to measure urban emissions. However, careful design of the monitoring network is crucial to be able to monitor the most important sectors as well as adjust to rapidly changing urban landscapes.

Results

Our study of Paris and Munich demonstrates how climate action plans, carbon emission inventories, and urban development plans can help design optimal atmospheric monitoring networks. We show that these two European cities display widely different trajectories in space and time, reflecting different emission reduction strategies and constraints due to administrative boundaries. The projected carbon emissions rely on future actions, hence uncertain, and we demonstrate how emission reductions vary significantly at the sub-city level.

Conclusions

We conclude that quantified individual cities’ climate actions are essential to construct more robust emissions trajectories at the city scale. Also, harmonization and compatibility of plans from various cities are necessary to make inter-comparisons of city climate targets possible. Furthermore, dense atmospheric networks extending beyond the city limits are needed to track emission trends over the coming decades.

城市群在实现全球气候目标方面发挥着至关重要的作用。许多城市已承诺减少温室气体排放,但目前的排放趋势仍无法核实。大气温室气体监测为测量城市排放提供了一种独立和透明的策略。然而,仔细设计监测网络对于能够监测最重要的部门以及适应快速变化的城市景观至关重要。我们对巴黎和慕尼黑的研究表明,气候行动计划、碳排放清单和城市发展计划可以帮助设计最佳的大气监测网络。研究表明,这两个欧洲城市在空间和时间上表现出截然不同的轨迹,反映了不同的减排策略和行政边界限制。预测的碳排放依赖于未来的行动,因此不确定,我们展示了在副城市层面上的减排是如何显著变化的。我们得出结论,量化单个城市的气候行动对于构建更稳健的城市尺度排放轨迹至关重要。此外,各城市规划的协调和兼容性对于实现城市气候目标的相互比较是必要的。此外,需要在城市范围之外建立密集的大气网络来跟踪未来几十年的排放趋势。
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引用次数: 0
Comprehensive evaluation of carbon sequestration potential of landscape tree species and its influencing factors analysis: implications for urban green space management 景观树种固碳潜力综合评价及其影响因素分析:对城市绿地管理的启示
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-09-05 DOI: 10.1186/s13021-023-00238-w
Shanshan Jin, Ershan Zhang, Haotian Guo, Chuanwei Hu, Yaru Zhang, Dongfeng Yan

Background

Continuous increasing carbon dioxide (CO2) has aggravated global warming and promoted urban tree planting projects for many countries. So it’s imperative to select high carbon sequestering landscape tree species while considering their aesthetic values of urban green space.

Results

32 tree species were selected as test objects which were commonly used in landscaping in Zhengzhou, a typical northern city of China. To assess the comprehensive carbon sequestration potential of landscape tree species in different plant configuration types, we simultaneously considered their daily net carbon sequestration per unit leaf area (wCO2), daily net carbon sequestration per unit land area (WCO2) and daily net carbon sequestration of the whole plant (QCO2) through cluster analysis. Besides that, we found out the key factors affecting carbon sequestration potential of landscape tree species by redundancy analysis.

Conclusion

Populus, P Stenoptera, P. acerifolia among large arbors (LA), V odoratissimum, P. Serratifolia, S. oblata among small arbors (SA), and B sinica var. Parvifolia, B. Megistophylla, L quihoui among shrubs (S) were recommended for local urban green space management. Photosynthetic rate (Pn), crown area (CA) and leaf area index (LAI) were the key factors which affected the comprehensive carbon sequestration potential both for LA, SA and S.

二氧化碳(CO2)的持续增加加剧了全球变暖,并促进了许多国家的城市植树项目。因此,在考虑城市绿地审美价值的同时,选择高固碳的景观树种势在必行。结果选取典型北方城市郑州市园林绿化常用树种32种作为试验对象。为了评价不同植物配置类型下景观树种的综合固碳潜力,通过聚类分析同时考虑了其单位叶面积日净固碳量(wCO2)、单位土地面积日净固碳量(wCO2)和全株日净固碳量(QCO2)。通过冗余分析,找出影响景观树种固碳潜力的关键因素。结论大乔木中的杨树、窄翅杨、尖叶杨,小乔木中的臭叶杨、锯齿叶杨、扁叶杨,灌丛中的小叶叶杨、细叶叶杨、大叶杨等是适宜的城市绿地管理树种。光合速率(Pn)、冠面积(CA)和叶面积指数(LAI)是影响林分、林分和林分综合固碳潜力的关键因子。
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引用次数: 1
Spatiotemporal evolution and influencing factors of China’s economic development performance under carbon emission constraints 碳排放约束下中国经济发展绩效时空演化及影响因素
IF 3.8 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2023-08-11 DOI: 10.1186/s13021-023-00235-z
Zhixiang Xie, Rongqin Zhao, Liangang Xiao, Minglei Ding

Background

China’s high-quality economic development depends on achieving sustainable economic development, reaching peak carbon emissions, achieving carbon neutrality, and intensifying the development of an industrial and energy structure that saves resources and protects the environment. This study used the data envelopment analysis (DEA) model and the Malmquist productivity index to measure the economic development performance of mainland China under carbon emission constraints. Then, it described the spatiotemporal evolution of economic development performance and analyzed its influencing factors using the Tobit model.

Results

The results revealed that there were obvious differences in the trends of the static and dynamic performance of economic development. On the one hand, the static performance of economic development exhibited an upward trend from 2008 to 2020. Its distribution characteristics were dominant in the higher and high-level areas. On the other hand, the dynamic performance had a downward trend from 2008 to 2016 and then an upward trend from 2016 to 2020. In most provinces, the dynamic performance was no longer constrained by technological progress but rather by scale efficiency. It was found that the main factors influencing economic development performance were urbanization level, energy efficiency, vegetation coverage, and foreign investment, while other factors had no significant influence.

Conclusions

This study suggests that China should improve its economic development performance by increasing the use of clean energy, promoting human-centered urbanization, increasing carbon absorption capacity, and absorbing more foreign capital in the future.

中国经济的高质量发展取决于实现经济可持续发展,实现碳排放峰值,实现碳中和,加强发展节约资源和保护环境的产业结构和能源结构。本研究采用数据包络分析(DEA)模型和Malmquist生产率指数对碳排放约束下中国大陆经济发展绩效进行测度。在此基础上,利用Tobit模型描述了经济发展绩效的时空演变,并分析了其影响因素。结果研究发现,经济发展的静态绩效和动态绩效趋势存在明显差异。一方面,从2008年到2020年,经济发展的静态绩效呈现上升趋势。其分布特征在高、高层地区占主导地位。另一方面,动态性能在2008 - 2016年呈下降趋势,然后在2016 - 2020年呈上升趋势。大多数省份的动态绩效不再受技术进步的制约,而是受规模效率的制约。研究发现,影响经济发展绩效的主要因素是城市化水平、能源效率、植被覆盖度和外商投资,其他因素对经济发展绩效的影响不显著。结论未来中国应通过增加清洁能源的使用、推进以人为中心的城市化、提高碳吸收能力和吸收更多的外资来提高经济发展绩效。
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引用次数: 0
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Carbon Balance and Management
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