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Atmosphere
Special Issues
Carbon Emission and Carbon Neutrality in China
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Carbon Emission and Carbon Neutrality in China

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Pollution Control".

Deadline for manuscript submissions: closed (2 June 2024) | Viewed by 11889

Special Issue Editors

Dr. Ji Zheng

E-Mail Website
Guest Editor
Department of Urban Planning and Design, The University of Hong Kong, Hong Kong 999077, China
Interests: climate change; decarbonization; low-carbon city; traffic emissions
Dr. Yu Li

E-Mail Website
Guest Editor
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: carbon dioxide emissions; low-carbon city; regional development planning
Dr. Yingjie Hu

E-Mail
Guest Editor
College of City Construction, Jiangxi Normal University, Nanchang 330022, China
Interests: carbon footprint; agricultural carbon emission; sustainable development

Special Issue Information

Dear Colleagues,

As the largest CO2 emitter, China has proposed a “Dual Carbon” target, an aim to achieve its carbon peak by 2030 and carbon neutrality by 2060. Carbon emission reduction and carbon sink enhancement are fundamental pathways for achieving carbon neutrality. Uncovering the patterns, process mechanisms, and evolutionary trends of carbon sources and sinks, as well as their interactive mechanisms with the climate system, is significant for achieving carbon neutrality and sustainable development.

The journal Atmosphere is hosting a Special Issue to disseminate the most recent findings related to carbon emissions and carbon neutrality in China. Topics of interest include, but are not limited to, the following:

  • Innovative methods of carbon accounting and calculation;
  • Spatial–temporal patterns of major carbon sources;
  • Spatial–temporal patterns of carbon sinks;
  • Regional carbon cycle process;
  • CO2 flux measurement;
  • Carbon sink potential assessment.

Dr. Ji Zheng
Dr. Yu Li
Dr. Yingjie Hu
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon emission
  • carbon neutrality
  • decarbonization pathway
  • spatiotemporal characteristics
  • driving mechanism

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Published Papers (7 papers)

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Research

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28 pages, 6734 KiB  
Article
Carbon Reduction Pathways for Chinese Provinces: Considering Carbon Intensity Convergence, Regional Development Plans, and Shared Socioeconomic Pathways
by Fanglei Zhong, Yanjie Yin, Jingwen Tian, Daiwei Jiang and Yijun Mao
Atmosphere 2024, 15(8), 918; https://doi.org/10.3390/atmos15080918 - 31 Jul 2024
Viewed by 474
Abstract
The achievement of dual carbon goals varies significantly across Chinese provinces due to the differences in resource endowments and socioeconomic development levels. These variations impose distinct pressures for transitioning along different socioeconomic development paths. Exploration of orderly carbon reduction paths for each province [...] Read more.
The achievement of dual carbon goals varies significantly across Chinese provinces due to the differences in resource endowments and socioeconomic development levels. These variations impose distinct pressures for transitioning along different socioeconomic development paths. Exploration of orderly carbon reduction paths for each province is, thus, crucial, but current predictions have not adequately integrated provincial development plans and carbon emission convergence trends. This study combines the Intergovernmental Panel on Climate Change (IPCC’s) shared socioeconomic pathways (SSPs) with a dual-layer target-setting approach based on trends in carbon emissions and each province’s five-year plans. The scalable stochastic impacts by regression on population, affluence, and technology (STIRPAT) model and ridge regression method were employed to identify the factors influencing carbon emissions. Carbon peak values and timing were then predicted for provinces under different scenarios. The results indicate that total carbon emissions are primarily influenced by provincial economic level and population, with spatial and temporal variations in the driving factors. Carbon emissions are ranked from low to high in the following order: SSP1, SSP2, and SSP5. Provinces were categorized into four tiers based on their peak times: early, on-time, delayed, and significantly delayed peaking. Under SSP1, 24 provinces would achieve carbon peaking as scheduled. Under SSP2, only 17 provinces would achieve carbon peaking on time. Among the first-tier provinces, Beijing and Shanghai would achieve peak carbon five to eight years ahead of schedule; the second-tier provinces of Henan, Fujian, Guangdong, and Inner Mongolia would achieve peak carbon by 2030; the third tier would achieve carbon peak before 2035; and the fourth tier would gradually reach peak carbon before 2050. Policy implications for differentiated carbon peak paths are proposed for different regions based on these findings. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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19 pages, 14004 KiB  
Article
Spatiotemporal Dynamics of CO2 Emissions in China Based on Multivariate Spatial Statistics
by Mengyao Wang, Xiaoyan Dai and Hao Zhang
Atmosphere 2024, 15(5), 538; https://doi.org/10.3390/atmos15050538 - 28 Apr 2024
Viewed by 844
Abstract
With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper [...] Read more.
With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are “Low–Low” at the provincial level, and “Low–Low” and “High–High” at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China’s carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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20 pages, 6374 KiB  
Article
Spatiotemporal Analysis of Urban Carbon Metabolism and Its Response to Land Use Change: A Case Study of Beijing, China
by Yingjie Hu, Jin Sun and Ji Zheng
Atmosphere 2023, 14(8), 1305; https://doi.org/10.3390/atmos14081305 - 17 Aug 2023
Cited by 1 | Viewed by 1362
Abstract
Analyzing the spatial pattern of urban carbon metabolism could provide insights into spatial adjustments to mitigate the greenhouse effect. Using CASA and empirical coefficients, we quantitatively analyzed and mapped the spatial pattern of the urban carbon metabolism of Beijing and its response to [...] Read more.
Analyzing the spatial pattern of urban carbon metabolism could provide insights into spatial adjustments to mitigate the greenhouse effect. Using CASA and empirical coefficients, we quantitatively analyzed and mapped the spatial pattern of the urban carbon metabolism of Beijing and its response to land use change from 2000 to 2020. The results showed that the carbon emission rate of Beijing increased in the first decade and decreased in the next, while the carbon sequestration rate kept rising over the past two decades. The net carbon emission rate of Beijing averaged 1284.52 × 107 kg C yr−1, indicating that the city functioned as a net carbon source throughout the study period. The most harmful carbon transitions were always sourced from the southeastern suburban area, where the natural components were converted to artificial components, while beneficial carbon transitions were in the urban central area, where the artificial component with a higher carbon emission density was converted to the other types of artificial components with relatively a lower carbon emission density, and the northwestern mountainous areas, where land use types transferred out of and into the forest or grass. The spatiotemporal change in urban carbon metabolism was highly correlated with the land use transition, and the land use change from cultivated land to industrial land accounted for 34.87% of the harmful carbon transitions. These results of key carbon flows and hotspots provide insights for policymaking in the effective management of reducing carbon emissions and enhancing carbon sequestration. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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20 pages, 3438 KiB  
Article
NPP and Vegetation Carbon Sink Capacity Estimation of Urban Green Space Using the Optimized CASA Model: A Case Study of Five Chinese Cities
by Fang Xu, Xiangrong Wang and Liang Li
Atmosphere 2023, 14(7), 1161; https://doi.org/10.3390/atmos14071161 - 17 Jul 2023
Cited by 7 | Viewed by 2521
Abstract
Urban area is a major source of CO2 and other greenhouse gases. Urban green space (UGS) is an essential element to increase carbon sequestration directly and reduce emission indirectly. In this study, the net primary production (NPP) and net ecosystem productivity (NEP) [...] Read more.
Urban area is a major source of CO2 and other greenhouse gases. Urban green space (UGS) is an essential element to increase carbon sequestration directly and reduce emission indirectly. In this study, the net primary production (NPP) and net ecosystem productivity (NEP) was monitored in order to enhance the carbon sequestration function of UGS and promote urban low-carbon development. Based on the Sentinel-2 L2A satellite images, meteorological data, and vegetation type data in 2019, we used the optimized Carnegie Ames Stanford Approach (CASA) model to estimate the NPP values of UGS types including attached green space, park green space, protective green space, and regional space in Beijing, Guangzhou, Shanghai, Shenyang, and Xi’an. The NEP values were evaluated based on NPP and soil heterotrophic respiration (RH) to quantify the vegetation carbon sink capacity. The accuracy test shows that the estimated NPP values based on the optimized CASA model are effective. The results indicate that the average NPP values (1008.5 gC·m−2·a−1) and vegetation carbon sink capacity (771.49 gC·m−2·a−1) of UGS in Beijing rank first among the cities, which is followed by the values in Guangzhou. The regional green space and park green space in five cities function as carbon sinks with high NPP values and have vegetation carbon sink capacity, whereas the attached green space in Shanghai and Xi’an as well as the protective green space in Guangzhou and Xi’an function as carbon sources. Moreover, the NEP distribution shows obvious spatial aggregation characteristics, that is, the high NEP values of UGS are clustered in mountainous forest areas in the west and north of Beijing, Northeast Guangzhou, and South Xi’an whereas the low NEP values are mostly concentrated in the urban built-up areas under strong influences of human activities. This research provides a new method for NPP and NEP estimation of UGS at the city scale and the scientific basis for the improvement of the vegetation carbon sink capacity of UGS. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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21 pages, 5632 KiB  
Article
Can Inner Mongolia Learn from Zhejiang’s Low-Carbon Policy?—Comparative Analysis Based on the EPS Model
by Wei Duan, Guilei Lin and Desheng Xu
Atmosphere 2023, 14(1), 169; https://doi.org/10.3390/atmos14010169 - 12 Jan 2023
Cited by 2 | Viewed by 2013
Abstract
Based on the energy policy simulation model (EPS model) and the reality of Zhejiang Province and Inner Mongolia Autonomous Region, the carbon pricing policy scenario and the early retirement policy scenario of coal power generation units were constructed, respectively, and the policy effects [...] Read more.
Based on the energy policy simulation model (EPS model) and the reality of Zhejiang Province and Inner Mongolia Autonomous Region, the carbon pricing policy scenario and the early retirement policy scenario of coal power generation units were constructed, respectively, and the policy effects simulated. The study explored whether Inner Mongolia Autonomous Region can learn from the low-carbon policies that have played a good role in Zhejiang Province in the process of achieving a carbon peak. The research found that: (1) Under the baseline scenario, both Zhejiang Province and Inner Mongolia Autonomous Region failed to achieve a carbon peak by 2030. (2) Under the scenarios of carbon pricing and early retirement of coal power generation units, the peak time of carbon in Zhejiang Province and Inner Mongolia Autonomous Region has been advanced, which shows the effectiveness of carbon pricing and early retirement of coal power generation units. (3) The above two policies have achieved good results in the overall implementation process of Zhejiang Province, but the carbon pricing policy has caused dramatic fluctuations in the power generation in Inner Mongolia Autonomous Region, and the early retirement policy of coal power units has failed to achieve the goal of reaching the peak carbon in Inner Mongolia Autonomous Region on schedule. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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13 pages, 1649 KiB  
Article
Impacts of Urban Rail Transit on On-Road Carbon Emissions: A Structural Equation Modeling Approach
by Yifu Ou, Ji Zheng and Kyung-Min Nam
Atmosphere 2022, 13(11), 1783; https://doi.org/10.3390/atmos13111783 - 28 Oct 2022
Cited by 15 | Viewed by 2373
Abstract
We examine the effects of urban rail transit on on-road carbon emissions in 90 Chinese cities, taking a structural equation modeling approach. Urban rail transit theoretically helps mitigate overall transport-sector emissions by absorbing part of the vehicular traffic demand or by generating traffic-diversion [...] Read more.
We examine the effects of urban rail transit on on-road carbon emissions in 90 Chinese cities, taking a structural equation modeling approach. Urban rail transit theoretically helps mitigate overall transport-sector emissions by absorbing part of the vehicular traffic demand or by generating traffic-diversion effects. However, its net contribution is obscure, given potential traffic-creation effects, since improved rail access can also incentivize new developments and thus induce additional on-road traffic. In contrast to many existing studies that neglect rail transit’s traffic-creation effects, we analyze these opposing effects within a single framework, where primary rail-associated emission channels are explicitly modeled. Our central results show that urban rail density is negatively associated with on-road carbon emissions with a net elasticity of −0.0175, speaking for the dominance of the traffic-diversion effects in China’s context. However, mixed evidence exists on the effects of increased urban rail density on vehicle-kilometers traveled and vehicle ownership, with the two opposing effects being relatively balanced. These findings suggest that transport-sector mitigation needs coordination between urban rail development and planning regulations. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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Review

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17 pages, 1318 KiB  
Review
Carbonyl Sulfide (COS) in Terrestrial Ecosystem: What We Know and What We Do Not
by Jiaxin Li, Lidu Shen, Yuan Zhang, Yage Liu, Jiabing Wu and Anzhi Wang
Atmosphere 2024, 15(7), 778; https://doi.org/10.3390/atmos15070778 - 28 Jun 2024
Viewed by 661
Abstract
Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about [...] Read more.
Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about 1.194–1.721 Tg a−1, with the terrestrial sink induced by plants and soils 0.50–1.20 Tg a−1, accounting for 41%–69% of the total. Hence, the role of plants and soils as COS sinks has been extensively explored. Now we know that factors such as the activity of carbonic anhydrase (CA), leaf structural traits, soil microbial activity, and environmental factors play significant roles in the COS budget. Developments in observational techniques have also made important contributions to the COS budget. This paper provides an overview of the research progress made on COS based on a comprehensive review of the literature. Then, it highlights the current research hotspots and issues requiring further exploration. For instance, it has been demonstrated that there are still significant uncertainties in the estimation of COS sources and sinks, emphasizing the need for further exploration of COS measuring techniques. This review aims to provide comprehensive guidance for COS research in terrestrial ecosystems. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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