Dataset Information

County-level CO₂ emissions and sequestration in China during 1997-2017.

ABSTRACT: With the implementation of China's top-down CO₂ emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO₂ emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO₂ emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO₂ emissions in 2,735 Chinese counties during 1997-2017. Moreover, as vegetation has a significant ability to sequester and reduce CO₂ emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO₂ emissions in China.

SUBMITTER: Chen J

PROVIDER: S-EPMC7665019 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

County-level CO2 emissions and sequestration in China during 1997-2017.

Chen Jiandong J Gao Ming M Cheng Shulei S Hou Wenxuan W Song Malin M Liu Xin X Liu Yu Y Shan Yuli Y

Scientific data 20201112 1

With the implementation of China's top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focus ...[more]

PMID: 33184289

Similar Datasets

Project description:Energy consumption dominates annual CO2 emissions in China. It is essential to significantly reduce CO2 emissions from energy consumption to reach national carbon neutrality by 2060, while the role of terrestrial carbon sequestration in offsetting energy-related CO2 emissions cannot be underestimated. Natural climate solutions (NCS), including improvements in terrestrial carbon sequestration, represent readily deployable options to offset anthropogenic greenhouse gas emissions. However, the extent to which China's terrestrial carbon sequestration in the future, especially when target-oriented managements (TOMs) are implemented, can help to mitigate energy-related CO2 emissions is far from certain. By synthesizing available findings and using several parameter-sparse empirical models that have been calibrated and/or fitted against contemporary measurements, we assessed China's terrestrial carbon sequestration over 2010-2060 and its contribution to offsetting national energy-related CO2 emissions. We show that terrestrial C sequestration in China will increase from 0.375 ± 0.056 (mean ± standard deviation) Pg C yr-1 in the 2010s to 0.458 ± 0.100 Pg C yr-1 under RCP2.6 and 0.493 ± 0.108 Pg C yr-1 under the RCP4.5 scenario in the 2050s, when TOMs are implemented. The majority of carbon sequestration comes from forest, accounting for 67.8-71.4% of the total amount. China's terrestrial ecosystems can offset 12.2-15.0% and 13.4-17.8% of energy-related peak CO2 emissions in 2030 and 2060, respectively. The implementation of TOMs contributes 11.9% of the overall terrestrial carbon sequestration in the 2020s and 23.7% in the 2050s. The most likely strategy to maximize future NCS effectiveness is a full implementation of all applicable cost-effective NCS pathways in China. Our findings highlight the role of terrestrial carbon sequestration in offsetting energy-related CO2 emissions and put forward future needs in the context of carbon neutrality.

Project description:Background:The prognostic relevance of gastric tumor location has been reported and debated. Our study was conducted to examine the differences in clinicopathological features, prognostic factors, and overall survival (OS) between patients with proximal gastric cancer (PGC) and distal gastric cancer (DGC). Patients and Methods:Patients with PGC or DGC were identified from the China National Cancer Center Gastric Cancer Database (NCCGCDB) during 1997-2017. Survival analysis was performed via Kaplan-Meier estimates and Cox proportional hazards models. Results:We reviewed 16,119 cases of gastric cancer patients, including 6,479 of PGC and 9,640 of DGC. PGC patients presented as older patients (61.5 versus 56.4 years, P<0.001) and more males (82.9% versus 68.2%, P<0.001). Compared with DGC, PGC was more likely to be in later pT stage (pT3 and pT4, 65.0% versus 52.8%, P<0.001) and lymph node metastasis (54.8% versus 50.9%, P<0.001). In univariate analysis, PGC patients had a worse survival outcome in stage I (Hazard ratio [HR] = 2.04, 95% CI: 1.42-2.94) but a better prognosis in stage IV (HR = 0.85, 95% CI: 0.73-0.98) when compared to DGC patients. However, multivariate analysis demonstrated that PGC was not an independent predictor for poor survival (HR = 1.07, 95% CI: 1.00-1.14). Results from multivariate analysis also revealed that pT4, lymph node metastasis, distant metastasis, no gastrectomy, and Borrmann IV were independent predictors associated with poor survival for both PGC and DGC patients. Additional prognostic factors for PGC patients included underweight (BMI < 18.5) (HR = 1.29, 95% CI: 1.06-1.58), linitis plastica (HR = 2.13, 95% CI: 1.25-3.65), and overweight (23 ? BMI <27.5) (HR = 0.80, 95% CI: 0.71-0.90). During the 20-year study period, the 5-year OS increased significantly for both PGC and DGC, with the increase rate of 91.7% and 67.7%, respectively. Conclusion:In China, PGC significantly differed from DGC in clinicopathological characteristics and prognostic factors. However, there was no significant relationship between survival outcome and gastric tumor location.

Dataset Information

County-level CO₂ emissions and sequestration in China during 1997-2017.

Publications

County-level CO<sub>2</sub> emissions and sequestration in China during 1997-2017.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets