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Niu Z, Zhou W, Huang Y, Wang S, Zhang G, Feng X, Lu X, Lyu M, Turnbull JC. Identification of Urban Carbon Emission Peaks through Tree-Ring 14C. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:17313-17319. [PMID: 39291978 DOI: 10.1021/acs.est.4c06041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Independent identification of carbon emission peaks determined from fuel inventories is a challenging goal. Because of the complete depletion of radiocarbon (14C) in fossil fuel sources, the measurement of atmospheric 14CO2 has proven to offer a means of achieving this goal. Here, we present a study identifying peak carbon emissions from two Chinese cities using urban tree-ring Δ14C time series during 2000-2019. After subtracting background atmospheric Δ14C from urban tree-ring Δ14C to isolate local Δ14C (Δ14Clocal), we find a minimum in 2010 (-51.1 ± 4.5‰) in Beijing and in 2013 in Xi'an (-52.5 ± 0.5‰). These levels correspond to an urban carbon emission peak in 2010 and in 2013 in the two respective cities. The urban carbon emission peaks are further identified by the declines of the mean absolute interannual rate of decrease of tree-ring Δ14C during a period, with the respective values of 3.6 and 6.4 ‰/yr after and before a turning point in Beijing and 3.0 and 6.0 ‰/yr after and before a turning point in Xi'an. This study provides an observation method to identify carbon emission peaks in basin cities.
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Affiliation(s)
- Zhenchuan Niu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
- Institute of Global Environmental Change, Xi'an Jiaotong University, Xi'an 710049, China
- National Observation and Research Station of Regional Ecological Environment Change and Comprehensive Management in the Guanzhong Plain, Xi'an 710061, China
| | - Weijian Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
- Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Joint Xi'an AMS Center Between IEECAS and Xi'an Jiaotong University, Xi'an 710061, China
- Interdisciplinary Research Center of Earth Science Frontier, Beijing Normal University, Beijing 100875, China
| | - Yunfei Huang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
- Interdisciplinary Research Center of Earth Science Frontier, Beijing Normal University, Beijing 100875, China
| | - Sen Wang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China
| | - Guiqian Zhang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China
| | - Xue Feng
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Xuefeng Lu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
- Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Joint Xi'an AMS Center Between IEECAS and Xi'an Jiaotong University, Xi'an 710061, China
| | - Mengni Lyu
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Jocelyn C Turnbull
- National Isotope Center, GNS Science, Lower Hutt 5040, New Zealand
- CIRES, University of Colorado, Boulder, Colorado 80305, United States
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Sharma R, Kunchala RK, Ojha S, Kumar P, Gargari S, Chopra S. Spatial distribution of fossil fuel derived CO 2 over India using radiocarbon measurements in crop plants. J Environ Sci (China) 2023; 124:19-30. [PMID: 36182130 DOI: 10.1016/j.jes.2021.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/23/2021] [Accepted: 11/02/2021] [Indexed: 06/16/2023]
Abstract
Examining the contribution of fossil fuel CO2 to the total CO2 changes in the atmosphere is of primary concern due to its alarming levels of fossil fuel emissions over the globe, specifically developing countries. Atmospheric radiocarbon represents an important observational constraint and utilized to trace fossil fuel derived CO2 (CO2ff) in the atmosphere. For the first time, we have presented a detailed analysis on the spatial distribution of fossil fuel derived CO2 (CO2ff) over India using radiocarbon (Δ14C) measurements during three-year period. Analysis shows that the Δ14C values are varying between 29.33‰ to -34.06‰ across India in the year 2017, where highest value belongs to a location from Gujarat while lowest value belongs to a location from Chhattisgarh. Based on the Δ14C patterns, spatial distributions of CO2ff mole fractions have been determined over India and the calculated values of CO2ff mole fractions are varying between 4.85 ppm to 26.59 ppm across India. It is also noticed that the highest CO2ff mole fraction is observed as 26.59 ppm from a site in Chhattisgarh. CO2ff mole fraction values from four high altitude sites are found to be varied between 4.85 ppm to 14.87 ppm. Effect of sampling different crop plants from the same growing season and different crop plant organs (grains, leaves, stems) on the Δ14C and CO2ff have been studied. Annual and intra seasonal variations in the Δ14C and CO2ff mole fractions have also been analyzed from a rural location (Dholpur, Rajasthan).
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Affiliation(s)
- Rajveer Sharma
- Inter University Accelerator Centre, New Delhi 110067, India; Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi 110016, India.
| | - Ravi Kumar Kunchala
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi 110016, India.
| | - Sunil Ojha
- Inter University Accelerator Centre, New Delhi 110067, India
| | - Pankaj Kumar
- Inter University Accelerator Centre, New Delhi 110067, India
| | | | - Sundeep Chopra
- Inter University Accelerator Centre, New Delhi 110067, India
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Turnbull JC, Domingues LG, Turton N. Dramatic Lockdown Fossil Fuel CO 2 Decrease Detected by Citizen Science-Supported Atmospheric Radiocarbon Observations. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:9882-9890. [PMID: 35759540 PMCID: PMC9301917 DOI: 10.1021/acs.est.1c07994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
COVID-19 lockdowns resulted in dramatic changes to fossil fuel CO2 emissions around the world, most prominently in the transportation sector. Yet travel restrictions also hampered observational data collection, making it difficult to evaluate emission changes as they occurred. To overcome this, we used a novel citizen science campaign to detect emission changes during lockdown and engage youth in climate science. Citizen scientists collected grass samples from their garden or local park, from which we analyzed the radiocarbon content to infer the recently added atmospheric fossil fuel CO2 mole fraction at each sampling location. The local fossil fuel CO2 mole fractions during lockdown were compared with a "normal" nonlockdown period. Our results from 17 sites in five cities around New Zealand demonstrate dramatic reductions in traffic emissions of 75 ± 3% during the most severe lockdown restriction period. This is consistent with sparse local traffic count information and a much larger decrease in traffic emissions than reported in global aggregate estimates of emission changes. Our results demonstrate that despite nationally consistent rules on travel during lockdown, emission changes varied by location, with inner-city sites typically dominated by bus traffic showing smaller decreases in emissions than elsewhere.
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Affiliation(s)
- Jocelyn C. Turnbull
- Rafter
Radiocarbon Laboratory, GNS Science, Lower Hutt 5010, New Zealand
- CIRES, University
of Colorado at Boulder, Boulder, Colorado 80309, United States
| | | | - Nikita Turton
- Rafter
Radiocarbon Laboratory, GNS Science, Lower Hutt 5010, New Zealand
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Radiocarbon isotope technique as a powerful tool in tracking anthropogenic emissions of carbonaceous air pollutants and greenhouse gases: A review. FUNDAMENTAL RESEARCH 2021. [DOI: 10.1016/j.fmre.2021.03.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
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Kolb MJ, Loffreda D, Sautet P, Calle-Vallejo F. Structure-sensitive scaling relations among carbon-containing species and their possible impact on CO2 electroreduction. J Catal 2021. [DOI: 10.1016/j.jcat.2020.12.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Lespinas F, Wang Y, Broquet G, Bréon FM, Buchwitz M, Reuter M, Meijer Y, Loescher A, Janssens-Maenhout G, Zheng B, Ciais P. The potential of a constellation of low earth orbit satellite imagers to monitor worldwide fossil fuel CO 2 emissions from large cities and point sources. CARBON BALANCE AND MANAGEMENT 2020; 15:18. [PMID: 32886217 PMCID: PMC7650226 DOI: 10.1186/s13021-020-00153-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 08/26/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Satellite imagery will offer unparalleled global spatial coverage at high-resolution for long term cost-effective monitoring of CO2 concentration plumes generated by emission hotspots. CO2 emissions can then be estimated from the magnitude of these plumes. In this paper, we assimilate pseudo-observations in a global atmospheric inversion system to assess the performance of a constellation of one to four sun-synchronous low-Earth orbit (LEO) imagers to monitor anthropogenic CO2 emissions. The constellation of imagers follows the specifications from the European Spatial Agency (ESA) for the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) concept for a future operational mission dedicated to the monitoring of anthropogenic CO2 emissions. This study assesses the uncertainties in the inversion estimates of emissions ("posterior uncertainties"). RESULTS The posterior uncertainties of emissions for individual cities and power plants are estimated for the 3 h before satellite overpasses, and extrapolated at annual scale assuming temporal auto-correlations in the uncertainties in the emission products that are used as a prior knowledge on the emissions by the Bayesian framework of the inversion. The results indicate that (i) the number of satellites has a proportional impact on the number of 3 h time windows for which emissions are constrained to better than 20%, but it has a small impact on the posterior uncertainties in annual emissions; (ii) having one satellite with wide swath would provide full images of the XCO2 plumes, and is more beneficial than having two satellites with half the width of reference swath; and (iii) an increase in the precision of XCO2 retrievals from 0.7 ppm to 0.35 ppm has a marginal impact on the emission monitoring performance. CONCLUSIONS For all constellation configurations, only the cities and power plants with an annual emission higher than 0.5 MtC per year can have at least one 8:30-11:30 time window during one year when the emissions can be constrained to better than 20%. The potential of satellite imagers to constrain annual emissions not only depend on the design of the imagers, but also strongly depend on the temporal error structure in the prior uncertainties, which is needed to be objectively assessed in the bottom-up emission maps.
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Affiliation(s)
- Franck Lespinas
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France
- Canadian Centre for Meteorological and Environmental Prediction, 2121 Transcanada Highway, Dorval, QC, H9P 1J3, Canada
| | - Yilong Wang
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France.
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
| | - Grégoire Broquet
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France
| | - François-Marie Bréon
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France
| | - Michael Buchwitz
- Institute of Environmental Physics (IUP), University of Bremen FB1, Otto Hahn Allee 1, 28334, Bremen, Germany
| | - Maximilian Reuter
- Institute of Environmental Physics (IUP), University of Bremen FB1, Otto Hahn Allee 1, 28334, Bremen, Germany
| | | | | | - Greet Janssens-Maenhout
- Joint Research Centre, Directorate Sustainable Resources, European Commission, Transport & Climate, Via Fermi 2749, 21027, Ispra, Italy
| | - Bo Zheng
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de L'Environnement, CEA-CNRS, UVSQ-Université Paris Saclay, Gif-sur-Yvette, France
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Hwang Y, Um JS, Schlüter S. Evaluating the Mutual Relationship between IPAT/Kaya Identity Index and ODIAC-Based GOSAT Fossil-Fuel CO 2 Flux: Potential and Constraints in Utilizing Decomposed Variables. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17165976. [PMID: 32824606 PMCID: PMC7459989 DOI: 10.3390/ijerph17165976] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 08/12/2020] [Accepted: 08/14/2020] [Indexed: 11/21/2022]
Abstract
The IPAT/Kaya identity is the most popular index used to analyze the driving forces of individual factors on CO2 emissions. It represents the CO2 emissions as a product of factors, such as the population, gross domestic product (GDP) per capita, energy intensity of the GDP, and carbon footprint of energy. In this study, we evaluated the mutual relationship of the factors of the IPAT/Kaya identity and their decomposed variables with the fossil-fuel CO2 flux, as measured by the Greenhouse Gases Observing Satellite (GOSAT). We built two regression models to explain this flux; one using the IPAT/Kaya identity factors as the explanatory variables and the other one using their decomposed factors. The factors of the IPAT/Kaya identity have less explanatory power than their decomposed variables and comparably low correlation with the fossil-fuel CO2 flux. However, the model using the decomposed variables shows significant multicollinearity. We performed a multivariate cluster analysis for further investigating the benefits of using the decomposed variables instead of the original factors. The results of the cluster analysis showed that except for the M factor, the IPAT/Kaya identity factors are inadequate for explaining the variations in the fossil-fuel CO2 flux, whereas the decomposed variables produce reasonable clusters that can help identify the relevant drivers of this flux.
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Affiliation(s)
- YoungSeok Hwang
- Department of Climate Change, Kyungpook National University, Daegu 41566, Korea;
| | - Jung-Sup Um
- Department of Geography, Kyungpook National University, Daegu 41566, Korea;
| | - Stephan Schlüter
- Department of Mathematics, Natural and Economic Sciences, Ulm University of Applied Sciences, 89075 Ulm, Germany
- Correspondence:
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Abstract
CO2 emissions are of global concern because of climate change. China has become the largest CO2 emitter in the world and presently accounts for 30% of global emissions. Here, we analyze the major drivers of energy-related CO2 emissions in China from 1978 when the reform and opening-up policy was launched. We find that 1) there has been a 6-fold increase in energy-related CO2 emissions, which was driven primarily (176%) by economic growth followed by population growth (16%), while the effects of energy intensity (−79%) and carbon intensity (−13%) slowed the growth of carbon emissions over most of this period; 2) energy-related CO2 emissions are positively related to per capita gross domestic product (GDP), population growth rate, carbon intensity, and energy intensity; and 3) a portfolio of command-and-control policies affecting the drivers has altered the total emission trend. However, given the major role of China in global climate change mitigation, significant future reductions in China’s CO2 emissions will require transformation toward low-carbon energy systems.
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Niu Z, Zhou W, Feng X, Feng T, Wu S, Cheng P, Lu X, Du H, Xiong X, Fu Y. Atmospheric fossil fuel CO 2 traced by 14CO 2 and air quality index pollutant observations in Beijing and Xiamen, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2018; 25:17109-17117. [PMID: 29644611 DOI: 10.1007/s11356-018-1616-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 02/25/2018] [Indexed: 06/08/2023]
Abstract
Radiocarbon (14C) is the most accurate tracer available for quantifying atmospheric CO2 derived from fossil fuel (CO2ff), but it is expensive and time-consuming to measure. Here, we used common hourly Air Quality Index (AQI) pollutants (AQI, PM2.5, PM10, and CO) to indirectly trace diurnal CO2ff variations during certain days at the urban sites in Beijing and Xiamen, China, based on linear relationships between AQI pollutants and CO2ff traced by 14C ([Formula: see text]) for semimonthly samples obtained in 2014. We validated these indirectly traced CO2ff (CO2ff-in) concentrations against [Formula: see text] concentrations traced by simultaneous diurnal 14CO2 observations. Significant (p < 0.05) strong correlations were observed between each of the separate AQI pollutants and [Formula: see text] for the semimonthly samples. Diurnal variations in CO2ff traced by each of the AQI pollutants generally showed similar trends to those of [Formula: see text], with high agreement at the sampling site in Beijing and relatively poor agreement at the sampling site in Xiamen. AQI pollutant tracers showed high normalized root-mean-square (NRMS) errors for the summer diurnal samples due to low [Formula: see text] concentrations. After the removal of these summer samples, the NRMS errors for AQI pollutant tracers were in the range of 31.6-64.2%. CO generally showed a high agreement and low NRMS errors among these indirect tracers. Based on these linear relationships, monthly CO2ff averages at the sampling sites in Beijing and Xiamen were traced using CO concentration as a tracer. The monthly CO2ff averages at the Beijing site showed a shallow U-type variation. These results indicate that CO can be used to trace CO2ff variations in Chinese cities with CO2ff concentrations above 5 ppm.
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Affiliation(s)
- Zhenchuan Niu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
- Open Studio for Oceanic-Continental Climate and Environment Changes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Weijian Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China.
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China.
- Open Studio for Oceanic-Continental Climate and Environment Changes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
- Joint Center for Global Change Studies, Beijing Normal University, Beijing, China.
| | - Xue Feng
- College of Urban and Environmental Sciences, Northwest University, Xi'an, China
| | - Tian Feng
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Shugang Wu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Peng Cheng
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Xuefeng Lu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Hua Du
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Xiaohu Xiong
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
| | - Yunchong Fu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
- Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, China
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Feng T, Zhou W, Wu S, Niu Z, Cheng P, Xiong X, Li G. Simulations of summertime fossil fuel CO 2 in the Guanzhong basin, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 624:1163-1170. [PMID: 29929228 DOI: 10.1016/j.scitotenv.2017.12.021] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 12/01/2017] [Accepted: 12/03/2017] [Indexed: 06/08/2023]
Abstract
Recent studies on fossil fuel CO2 simulation associated with Δ14CO2 measurements is quite limited, particularly in China. In this study, the fossil fuel CO2 recently added to the atmosphere (δCO2ff) over the Guanzhong basin, central China, during summer 2012 is simulated using a modified WRF-CHEM model constrained by measured CO2 mixing ratio and Δ14CO2. The model well captures the temporal variation of observed CO2 mixing ratio and Δ14CO2, and reasonably reproduces the distribution of observed Δ14CO2. The simulation shows a significant variation of δCO2ff during summertime, ranging from <5ppmv to ~100ppmv and no remarkable trend of δCO2ff is found for June, July, and August. The δCO2ff level is closely associated with atmospheric diffusion conditions. The diurnal cycle of δCO2ff presents a double-peak pattern, a nocturnal one and a rush-hour one, related to the development of planetary boundary layer and CO2 emission from vehicles. The spatial distributions of summertime δCO2ff within the basin is clearly higher than the outside, reaching up to 40ppmv in urban Xi'an and 15ppmv in its surrounding areas, indicative of large local fossil fuel emissions. Furthermore, we find that neglecting the influence of summer heterotrophic respiration in terrestrial biosphere would slightly underestimate the calculated δCO2ff by about 0.38ppmv in the basin.
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Affiliation(s)
- Tian Feng
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China
| | - Weijian Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China.
| | - Shugang Wu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China
| | - Zhenchuan Niu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China
| | - Peng Cheng
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China
| | - Xiaohu Xiong
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Xi'an AMS Center, Xi'an 710061, China
| | - Guohui Li
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
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