the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Carbon dioxide emissions in Northern China based on atmospheric observations from 2005 to 2009
Abstract. China has pledged reduction of carbon dioxide emissions per unit GDP by 60–65 % relative to 2005 levels, and to peak carbon emissions overall by 2030. However, disagreement among available inventories makes it difficult for China to track progress toward these goals and evaluate the efficacy of regional control measures. In this study, we evaluate three anthropogenic CO2 inventories by tracking the fidelity of predicted concentrations of CO2 in the atmosphere to observations, focusing on the key commitment period for the Paris accords (2005) and the Beijing Olympics (2008). One inventory is China-specific and two are spatial subsets of global inventories. The inventories differ in spatial resolution, basis in national or subnational statistics, and reliance on global or China-specific emission factors. We use a unique set of historical atmospheric observations from 2005–2009 to evaluate the three CO2 emissions inventories within China's heavily industrialized and populated Northern region accounting for ~33–41 % of national emissions. Each anthropogenic inventory is combined with estimates of biogenic CO2 within a high-resolution atmospheric transport framework to model the time series of CO2 observations. Model-observation mismatch in concentration units is translated to mass units and used to optimize the original inventories in the measurement influence region, largely corresponding to Northern China. Except for the peak growing season, where assessment of anthropogenic emissions is entangled with the strong vegetation signal, we find the China-specific inventory based on subnational data and domestic field-studies agrees significantly better with observations than the global inventories at all timescales. On average, over the study time period, the China-specific inventory has substantially larger (20 %) emissions for all China than the global inventories. Our analysis uses observations to support and justify increased development of China-specific inventories in tracking China's progress towards reducing emissions. Here we are restricted to a single measurement site; effectively optimizing inventories at relevant spatial scales requires multiple high temporal resolution observations. We emphasize the need for a denser observational network in future efforts to measure and verify CO2 emissions for China both regionally and as a whole.
- Preprint
(2474 KB) - Metadata XML
-
Supplement
(9432 KB) - BibTeX
- EndNote
-
RC1: 'Review of Dayalu et al.', Anonymous Referee #2, 03 Nov 2018
- AC1: 'Reply to RC1', Archana Dayalu, 18 Dec 2018
-
RC2: 'Manuscript Review from Anonymous Referee #1', Anonymous Referee #1, 18 Nov 2018
- AC2: 'Reply to RC2', Archana Dayalu, 18 Dec 2018
- AC3: 'AC1', Archana Dayalu, 18 Dec 2018
- AC4: 'AC4', Archana Dayalu, 18 Dec 2018
-
RC1: 'Review of Dayalu et al.', Anonymous Referee #2, 03 Nov 2018
- AC1: 'Reply to RC1', Archana Dayalu, 18 Dec 2018
-
RC2: 'Manuscript Review from Anonymous Referee #1', Anonymous Referee #1, 18 Nov 2018
- AC2: 'Reply to RC2', Archana Dayalu, 18 Dec 2018
- AC3: 'AC1', Archana Dayalu, 18 Dec 2018
- AC4: 'AC4', Archana Dayalu, 18 Dec 2018
Data sets
Replication Data for: Carbon dioxide emissions in Northern China based on atmospheric observations from 2005 to 2009 A. Dayalu, J. W. Munger, Y. Wang, S. Wofsy, Y. Zhao, T. Nehrkorn, C. Nielsen, M. McElroy, and R. Y.-W. Chang https://doi.org/10.7910/DVN/OJESO0
Model code and software
Replication Data for: Carbon dioxide emissions in Northern China based on atmospheric observations from 2005 to 2009 A. Dayalu, J. W. Munger, Y. Wang, S. Wofsy, Y. Zhao, T. Nehrkorn, C. Nielsen, M. McElroy, and R. Y.-W. Chang https://doi.org/10.7910/DVN/OJESO0
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
1,246 | 294 | 60 | 1,600 | 374 | 69 | 64 |
- HTML: 1,246
- PDF: 294
- XML: 60
- Total: 1,600
- Supplement: 374
- BibTeX: 69
- EndNote: 64
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1