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In order to explore whether China-Africa exchange will influence on the African environment. This paper selects four paths of China-Africa exchanges and explores the impact of each path on the African environment under the influence of different factors. We found that construction income and Africa's exports to China will increase Africa's carbon emissions. Foreign direct investment and China's exports to Africa will lead to a reduction in carbon emissions in Africa. The resource moderation will reduce the significance of the environmental impact of each path on Africa. Based on the above conclusions, several suggestions are made on the policies and actual operations in the path of China-Africa exchanges., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper constructs a theoretical model of biased production decisions due to the import of environmental intermediate goods. Additionally, it analyzes the influence of these imports on CO2 emissions based on the trade and CO2 emission data of Chinese prefecture-level cities from 2000 to 2016. Furthermore, it empirically explores how environmental intermediate imports affect CO2 emissions. The study found the following: first, the import of environmental intermediate goods can effectively reduce CO2 emissions; this conclusion still holds under robustness and endogeneity tests. Second, the carbon emission reduction effect related to the import of environmental intermediate goods is affected by differences in geographical location, environmental pollution, sustainable development ability and government efficiency. Third, the mechanism test found that the import of environmental intermediate goods exerts emission reduction effects through the green technological innovation and industrial structure upgrading mechanisms. The conclusions of the research in this article provide a reference for coordinating trade development and environmental protection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

This paper constructs a matching index model to research the matching degree of embodied carbon trade and value-added trade among eight regions and 31 provinces in China in 2012 and 2015. The study finds that (1) At the regional level, a mismatch is shown between embodied carbon trade and value-added trade among regions, for example, in 2015, the northwest region has output embodied carbon to the north coast, while input the value-added trades from the north coast. (2) At the provincial level, a mismatch is displayed between embodied carbon transaction and value-added trade, for example, Beijing had a net shift of embodied carbon from Xinjiang in 2015, but Xinjiang had a net transfer of added value from Beijing. Therefore, the Chinese government needs to establish an ecological compensation mechanism to improve the mismatch between embodied carbon trade and value-added trade among Chinese regions (provinces)., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As the largest carbon dioxide emitter, China is working towards the direction of a green economy. As an irreplaceable part of establishing a green economy, the low-carbon city pilot (LCCP) policy is implemented in many large cities in China, and the scope of implementation will be further expanded. However, to date, there has been an absence of empirical studies basing on prefecture-level cities about the evaluation of China's LCCP policy. Evaluating and optimizing the LCCP policy is constructive to achieve the goal of China's green economic transition. In this paper, we evaluated the effect of the LCCP policy on China's low-carbon economic transition by using the difference-in-difference (DID) approach which can effectively alleviate endogenous problems and better evaluate this effect and the panel data of 210 prefecture-level cities in China from 2008 to 2016. The empirical analysis revealed that the LCCP policy inhibited China's low-carbon economic transition in general. Specifically, the policy worked well in the eastern region but failed in the central region and western region by studying the regional heterogeneity and influence mechanism. The reason is that the LCCP policy can stimulate low-carbon innovation with the help of innovation offset effects in the eastern region, but it failed to do so in the central region and western region. In addition, this paper analyzed the performance of three types of policy tools adopted by local governments to implement the policy, we found that market-economic tools are valuable to improving the low-carbon economic transition in pilot areas, but command-mandatory tools and voluntary tools have failed to achieve the expected objectives. The research results of this article can provide policy recommendations for optimizing the low-carbon policy and provide a reference for countries that are determined to develop a green economy. [ABSTRACT FROM AUTHOR]

In the context of China's commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060, as well as its strategy to build a strong transportation country, it is of foremost importance to study the carbon emission reduction effect of the opening of high-speed rail (HSR). This paper innovatively introduces the frequency of HSR stops as an indicator of HSR operation, and uses a time-varying difference-in-difference (DID) model, a mediating effect model and a spatial DID model to assess the direct and indirect impact, transmission mechanism, and spatial spillover effects of the opening and operation of HSR on carbon emission reduction based on a panel of 279 prefecture-level cities from 2003 to 2017. We found that the opening and operation of HSR significantly reduced urban carbon emissions. The direct transmission mechanism analysis shows that the opening of HSR can reduce carbon emissions by replacing highway passenger traffic. Indirect mechanism analysis shows that the opening of HSR can reduce carbon emissions through technological effect, structural effect and opening effect. The test of spatial spillover effect shows that the opening of HSR can promote carbon emission reduction not only in node cities, but also in neighboring cities., Competing Interests: The authors have declared that no competing interests exist.

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO2 emissions in China from spatial perspective. The results indicate: firstly, in China, CO2 emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO2 emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by "warning effect", CO2 emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO2 emissions is not a simple linear relationship, but shows an "inverted N-shaped" curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies., Competing Interests: The authors have declared that no competing interests exist.

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency., Competing Interests: NO authors have competing interests.

The development of globalization has separated the production and consumption of products spatially, and the international trade of products has become a carrier of embodied carbon trade. This paper adopted the perspective of value-added trade to calculate the amount of embodied carbon trade of China from 2006 to 2015 and perform a structural decomposition analysis of the changes in China's embodied carbon trade. This study found that: (1) China's embodied carbon exports are much larger than its embodied carbon imports, and there are differences between countries. China imported the largest amount of embodied carbon from South Korea, and it exported the largest amount of embodied carbon to the United States. (2) The structural decomposition analysis shows that changes in the value-added carbon emission coefficient during the study period would have caused China's embodied carbon trade to decrease, and changes in value-added trade would have caused China's embodied carbon trade to increase. Therefore, countries trading with China need to strengthen their cooperation with China in energy conservation, emission reduction, and product trade. In order to accurately reflect China's embodied carbon trade, it is necessary to calculate embodied carbon trade from the perspective of value-added trade., Competing Interests: The authors have declared that no competing interests exist.

China's announcement of its goal of carbon neutrality has increased the practical significance of research on carbon dioxide (CO2) emissions that result from urbanization. With a comprehensive consideration of population migration in China, this study examines the impact of urbanization on CO2 emissions based on provincial panel data from 2000 to 2012. Two indicators (resident population and household registration population) are used to measure urbanization rate. The results reveal that the impact of urbanization on CO2 emissions in China is closely correlated with the structure of urban resident population and interregional population migration. The estimation results are still robust by using generalized method of moments (GMM) estimator and two-stage least squares (2SLS) estimator. The proportion of temporary residents is introduced as a proxy variable for population migration. The panel threshold model regression results show that the proportion of temporary residents has a marginal effect on the relationship between urbanization and CO2 emissions. In regions with a higher proportion of temporary residents, the positive effects of resident population urbanization on CO2 emissions tend to be weaker. These findings are consistent with the theories of ecological modernization and urban environmental transition. This paper makes suggestions on China's urbanization development model and countermeasures are proposed to minimize the CO2 emissions caused by urbanization., Competing Interests: The authors have declared that no competing interests exist.

With the change of social economic system and the rapid growth of agricultural economy in China, the amount of agricultural energy consumption and carbon dioxide emissions has increased dramatically. Based on the estimation of agricultural carbon dioxide emissions from 1991 to 2018 in China, this paper uses EKC model to analyze economic growth and agricultural carbon dioxide emissions. The Kaya method is used to decompose the factors affecting agricultural carbon dioxide emissions. The experimental results show that there is a co-integration relationship between economic growth and the total intensity of agricultural carbon emissions, and between economic growth and the intensity of carbon emissions caused by five types of carbon sources: fertilizer, pesticide, agricultural film, agricultural diesel oil and tillage. Economic growth is the main driving factor of agricultural carbon dioxide emissions. In addition, technological progress has a strong role in promoting carbon emission reduction, but it has a certain randomness. However, the impact of energy consumption structure and population size on carbon emissions is not obvious., Competing Interests: The authors have declared that no competing interests exist.

The credible sources of fossil energy efficiently are a vital cause of economic growth and considerable influence on adequate security. Whereas radiant energy positively enhances or ostensibly promotes socio-economic stability and the controlled environment. The fossil energy sources supply has become progressively stern in China and reconnoitering the beta decoupling relationships between CO2 emissions, GDP, energy consumption, electricity consumption, value-added industries, and population. The results will be favorable for illustrative the security of the valuable resources. This study adopts the extended stochastic model (STIRPAT) with Beta Decoupling Techniques (BDT). This modern technique merely employs the decoupling situation by the alpha and beta effects from 1989 to 2018 and calculates the % change in CO2 emissions by GDP growth and energy consumption. The estimated results represent negative and economic growth depends on coal and natural gas. First, CO2 emissions annually increasing cause of rapid growth, energy consumption, and electricity production, and the structural contradiction of energy remained static. Second, the Value-added industries estimated that CO2 emissions reduce by primary industries. Third, the decoupling states of CO2 emissions and population show an inverse relationship. This paper tentatively suggests China is sustainable, naturally strengthens energy output, transmutes the energy consumption structure, and advances development policies under environmental circumstances., Competing Interests: We have no conflicts of interest to disclose.

This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS). [ABSTRACT FROM AUTHOR]

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China's energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future., Competing Interests: NO authors have competing interests.

China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO2 emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO2 emission. This paper builds a spatial auto regression (SAR) model with provincial panel data from 2011 to 2017 to calculate the spatial spillover effect of China's LCTI on regional CO2 emission. The results show that regional LCTI can reduce the local CO2 emission, but will increase the CO2 emission of adjacent regions due to spatial spillover effect. This produces the uncertainty of the promotion effect of LCTI on China's low-carbon transformation. Therefore, this paper suggests innovation resources should be appropriately and evenly distributed among regions to avoid their agglomeration in few regions., Competing Interests: The authors have declared that no competing interests exist.

Carbon emissions are the primary reason that contributes to global warming. The gradient has a significant impact on the carbon dioxide (CO2) emissions produced by trucks. The aim of the current paper is to propose a carbon emission quantification model for diesel trucks on longitudinal slope sections and investigate the influence of gradient on the carbon emissions of trucks for use in the low-carbon highway design. The law of conservation of mechanical energy, the first law of thermodynamics, and the vehicle longitudinal dynamics theory were adopted for deriving the carbon emission model of the trucks on the flat, uphill, downhill and round-trip longitudinal slope segments. Three kinds of common trucks were chosen to conduct the field test. Following the test data, the model demonstrates a high accuracy. The minimum gradient which is expected to impact carbon emissions of trucks on the round-trip longitudinal slope sections was the balance gradient as revealed. The gradient of the longitudinal slope is required to be avoided to be greater in comparison with the balance gradient for the achievement of the two-way traffic low carbon operation on a highway. The results of this study are valuable to researchers interested in low carbon road design and low carbon transportation control., Competing Interests: The authors have declared that no competing interests exist.

Environmentally extended input-output analysis (EEIOA) has long been used to quantify global and regional environmental impacts and to clarify emission transfers. Structural path analysis (SPA), a technique based on EEIOA, is especially useful for measuring significant flows in this environmental-economic system. This paper constructs an imports-adjusted single-region input-output (SRIO) model considering only domestic final use elements, and it uses the SPA technique to highlight crucial routes along the production chain in both final use and sectoral perspectives. The results indicate that future mitigation policies on household consumption should change direct energy use structures in rural areas, cut unreasonable demand for power and chemical products, and focus on urban areas due to their consistently higher magnitudes than rural areas in the structural routes. Impacts originating from government spending should be tackled by managing onsite energy use in 3 major service sectors and promoting cleaner fuels and energy-saving techniques in the transport sector. Policies on investment should concentrate on sectoral interrelationships along the production chain by setting up standards to regulate upstream industries, especially for the services, construction and equipment manufacturing sectors, which have high demand pulling effects. Apart from the similar methods above, mitigating policies in exports should also consider improving embodied technology and quality in manufactured products to achieve sustainable development. Additionally, detailed sectoral results in the coal extraction industry highlight the onsite energy use management in large domestic companies, emphasize energy structure rearrangement, and indicate resources and energy safety issues. Conclusions based on the construction and public administration sectors reveal that future mitigation in secondary and tertiary industries should be combined with upstream emission intensive industries in a systematic viewpoint to achieve sustainable development. Overall, SPA is a useful tool in empirical studies, and it can be used to analyze national environmental impacts and guide future mitigation policies. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

Maintaining crop outputs to feed its large population with limited resources while simultaneously mitigating carbon emissions are great challenges for China. Improving the efficiency of resource use in crop production is important in reducing carbon emissions. This paper constructs a methodological framework combining emergy-based indicator accounting and a nonseparable undesirable output slack-based measurement (SBM) data envelopment analysis (DEA) model. This framework is used to explore the efficiency of inputs and outputs and the greenhouse gas (GHG) emissions reduction potential for crop production systems, using Zhejiang province, China, as a case study. It is found that an emergy synthesis and a nonseparable undesirable output SBM-DEA framework is compatible with the case study. Crop production in Zhejiang province has relied heavily on an increase in agrochemical inputs to maintain agricultural output. Energy and chemical fertilizer use are determined as the province’s major carbon emissions sources. Although carbon emissions per unit of monetary output has decreased sharply, the carbon emissions per unit emergy output has increased, demonstrating a high carbon intensity reality. The DEA highlighted the differences in crop production efficiency, resource factor redundancy and carbon mitigation potential in the different prefectures of the province. To conclude this research, policies to support low carbon agriculture development, including subsidizing low carbon agriculture technology development and expansion and the cancellation of subsidies to high carbon production factors, such as chemical fertilizer production and sales, are discussed to conclude the research. [ABSTRACT FROM AUTHOR]

This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China's CO2 emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995-2011 into consideration. The results indicated that CO2 emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO2 emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO2 emissions. Conversely, energy intensity was identified as having a negative influence on CO2 emissions. In addition, the significance of the relationship between CO2 emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO2 emissions.

Environmentally extended input-output analysis (EEIOA) has long been used to quantify global and regional environmental impacts and to clarify emission transfers. Structural path analysis (SPA), a technique based on EEIOA, is especially useful for measuring significant flows in this environmental-economic system. This paper constructs an imports-adjusted single-region input-output (SRIO) model considering only domestic final use elements, and it uses the SPA technique to highlight crucial routes along the production chain in both final use and sectoral perspectives. The results indicate that future mitigation policies on household consumption should change direct energy use structures in rural areas, cut unreasonable demand for power and chemical products, and focus on urban areas due to their consistently higher magnitudes than rural areas in the structural routes. Impacts originating from government spending should be tackled by managing onsite energy use in 3 major service sectors and promoting cleaner fuels and energy-saving techniques in the transport sector. Policies on investment should concentrate on sectoral interrelationships along the production chain by setting up standards to regulate upstream industries, especially for the services, construction and equipment manufacturing sectors, which have high demand pulling effects. Apart from the similar methods above, mitigating policies in exports should also consider improving embodied technology and quality in manufactured products to achieve sustainable development. Additionally, detailed sectoral results in the coal extraction industry highlight the onsite energy use management in large domestic companies, emphasize energy structure rearrangement, and indicate resources and energy safety issues. Conclusions based on the construction and public administration sectors reveal that future mitigation in secondary and tertiary industries should be combined with upstream emission intensive industries in a systematic viewpoint to achieve sustainable development. Overall, SPA is a useful tool in empirical studies, and it can be used to analyze national environmental impacts and guide future mitigation policies.

Global management of wetlands to suppress greenhouse gas (GHG) emissions, facilitate carbon (C) sequestration, and reduce atmospheric CO2 concentrations while simultaneously promoting agricultural gains is paramount. However, studies that relate variability in CO2 and CH4 emissions at large spatial scales are limited. We investigated three-year emissions of soil CO2 and CH4 from the primary wetland types of the Liaohe Delta, China, by focusing on a total wetland area of 3287 km2. One percent is Suaeda salsa, 24% is Phragmites australis, and 75% is rice. While S. salsa wetlands are under somewhat natural tidal influence, P. australis and rice are managed hydrologically for paper and food, respectively. Total C emissions from CO2 and CH4 from these wetland soils were 2.9 Tg C/year, ranging from 2.5 to 3.3 Tg C/year depending on the year assessed. Primary emissions were from CO2 (~98%). Photosynthetic uptake of CO2 would mitigate most of the soil CO2 emissions, but CH4 emissions would persist. Overall, CH4 fluxes were high when soil temperatures were >18°C and pore water salinity <18 PSU. CH4 emissions from rice habitat alone in the Liaohe Delta represent 0.2% of CH4 carbon emissions globally from rice. With such a large area and interannual sensitivity in soil GHG fluxes, management practices in the Delta and similar wetlands around the world have the potential not only to influence local C budgeting, but also to influence global biogeochemical cycling. [ABSTRACT FROM AUTHOR]

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40-45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China's low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.

Based on carbon spot prices selected from seven carbon pilots, we assess the financial performances related to carbon volatility in China on the overall perspective. According to the results, the Chinese carbon market fluctuated severely at the beginning of carbon trading, but has stabilised in general, despite several dramatic changes related to ‘yearly compliance events’. Long-term memory exists in the volatility series. Moreover, asymmetry exists in the Chinese carbon market, and volatility reacts more severely to good news than to bad news. Finally, we discuss our empirical results, and make certain suggestions regarding firms’ awareness, international cooperation and individual investors not only for policy makers in China but also for other developing countries who are contemplating either commencing carbon trading or improving the current market. [ABSTRACT FROM AUTHOR]

The Sanjiang Plain has been experienced significant wetland loss due to expanded agricultural activities, and will be potentially restored by the China National Wetland Conservation Action Plan (NWCP) in future. The objective of this study is to evaluate the impact of future climate warming and wetland restoration on wetland CH4 emissions in northeast China. We used an atmosphere-vegetation interaction model (AVIM2) to drive a modified biogeophysical model (CH4MODwetland), and projected CH4 flux variations from the Sanjiang Plain wetlands under different Representative Concentration Pathway scenarios throughout the 21st century. Model validation showed that the regressions between the observed and simulated CH4 fluxes by the modified model produced an R2 of 0.49 with a slope of 0.87 (p<0.001, n = 237). According to the AVIM2 simulation, the net primary productivity of the Sanjiang Plain wetlands will increase by 38.2 g m-2 yr-1, 116.6 g m-2 yr-1 and 250.4 g m-2 yr-1 under RCP 2.6, RCP 4.5 and RCP 8.5, respectively, by the end of this century. For RCP 2.6, 4.5 and 8.5 scenarios, the CH4 fluxes will increase by 5.7 g m-2 yr-1, 57.5 g m-2 yr-1 and 112.2 g m-2 yr-1. Combined with the wetland restoration, the regional emissions will increase by 0.18‒1.52 Tg. The CH4 emissions will be stimulated by climate change and wetland restoration. Regional wetland restoration planning should be directed against different climate scenarios in order to suppress methane emissions. [ABSTRACT FROM AUTHOR]

Soil respiration, a major component of the global carbon cycle, is significantly influenced by land management practices. Grasslands are potentially a major sink for carbon, but can also be a source. Here, we investigated the potential effect of land management (grazing, clipping, and ungrazed enclosures) on soil respiration in the semiarid grassland of northern China. Our results showed the mean soil respiration was significantly higher under enclosures (2.17μmol.m−2.s−1) and clipping (2.06μmol.m−2.s−1) than under grazing (1.65μmol.m−2.s−1) over the three growing seasons. The high rates of soil respiration under enclosure and clipping were associated with the higher belowground net primary productivity (BNPP). Our analyses indicated that soil respiration was primarily related to BNPP under grazing, to soil water content under clipping. Using structural equation models, we found that soil water content, aboveground net primary productivity (ANPP) and BNPP regulated soil respiration, with soil water content as the predominant factor. Our findings highlight that management-induced changes in abiotic (soil temperature and soil water content) and biotic (ANPP and BNPP) factors regulate soil respiration in the semiarid temperate grassland of northern China. [ABSTRACT FROM AUTHOR]

Global changes such as increasing CO2, rising temperature, and land-use change are likely to drive shifts in litter inputs to forest floors, but the effects of such changes on litter decomposition remain largely unknown. We initiated a litter manipulation experiment to test the response of litter decomposition to litter removal/addition in three successional forests in southern China, namely masson pine forest (MPF), mixed coniferous and broadleaved forest (MF) and monsoon evergreen broadleaved forest (MEBF). Results showed that litter removal decreased litter decomposition rates by 27%, 10% and 8% and litter addition increased litter decomposition rates by 55%, 36% and 14% in MEBF, MF and MPF, respectively. The magnitudes of changes in litter decomposition were more significant in MEBF forest and less significant in MF, but not significant in MPF. Our results suggest that change in litter quantity can affect litter decomposition, and this impact may become stronger with forest succession in tropical forest ecosystem. [ABSTRACT FROM AUTHOR]

The production and consumption of the greenhouse gases (GHGs) methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O) in soil profile are poorly understood. This work sought to quantify the GHG production and consumption at seven depths (0–30, 30–60, 60–90, 90–150, 150–200, 200–250 and 250–300 cm) in a long-term field experiment with a winter wheat-summer maize rotation system, and four N application rates (0; 200; 400 and 600 kg N ha−1 year−1) in the North China Plain. The gas samples were taken twice a week and analyzed by gas chromatography. GHG production and consumption in soil layers were inferred using Fick’s law. Results showed nitrogen application significantly increased N2O fluxes in soil down to 90 cm but did not affect CH4 and CO2 fluxes. Soil moisture played an important role in soil profile GHG fluxes; both CH4 consumption and CO2 fluxes in and from soil tended to decrease with increasing soil water filled pore space (WFPS). The top 0–60 cm of soil was a sink of atmospheric CH4, and a source of both CO2 and N2O, more than 90% of the annual cumulative GHG fluxes originated at depths shallower than 90 cm; the subsoil (>90 cm) was not a major source or sink of GHG, rather it acted as a ‘reservoir’. This study provides quantitative evidence for the production and consumption of CH4, CO2 and N2O in the soil profile. [ABSTRACT FROM AUTHOR]

Winter soil respiration is a very important component of the annual soil carbon flux in some ecosystems. We hypothesized that, with all other factors being equal, shorter winter SR result in reduced contribution to annual soil C flux. In this study, the contribution of winter soil respiration to annual soil respiration was measured for three sites (grassland: dominated by Artemisia sacrorum, Bothriochloa ischaemum and Themeda japonica; shrubland: dominated by Vitex negundo var. heterophylla; plantation: dominated by Populus tomatosa) in a mountainous area of north China. Diurnal and intra-annual soil CO2 flux patterns were consistent among different sites, with the maximum soil respiration rates at 12∶00 or 14∶00, and in July or August. The lowest respiration rates were seen in February. Mean soil respiration rates ranged from 0.26 to 0.45 µmol m−2 s−1 in the winter (December to February), and between 2.38 to 3.16 µmol m−2 s−1 during the growing season (May-September). The winter soil carbon flux was 24.6 to 42.8 g C m−2, which contributed 4.8 to 7.1% of the annual soil carbon flux. Based on exponential functions, soil temperature explained 73.8 to 91.8% of the within year variability in soil respiration rates. The Q10 values of SR against ST at 10 cm ranged from 3.60 to 4.90 among different sites. In addition, the equation between soil respiration and soil temperature for the growing season was used to calculate the “modeled” annual soil carbon flux based on the actual measured soil temperature. The “measured” annual value was significantly higher than the “modeled” annual value. Our results suggest that winter soil respiration plays a significant role in annual soil carbon balance, and should not be neglected when soil ecosystems are assessed as either sinks or sources of atmospheric CO2. [ABSTRACT FROM AUTHOR]

Soil carbon dioxide (CO2) emission is one of the largest fluxes in the global carbon cycle. Therefore small changes in the size of this flux can have a large effect on atmospheric CO2 concentrations and potentially constitute a powerful positive feedback to the climate system. Soil CO2 fluxes in the alpine steppe ecosystem of Northern Tibet and their responses to short-term experimental warming were investigated during the growing season in 2011. The results showed that the total soil CO2 emission fluxes during the entire growing season were 55.82 and 104.31 g C m-2 for the control and warming plots, respectively. Thus, the soil CO2 emission fluxes increased 86.86% with the air temperature increasing 3.74°C. Moreover, the temperature sensitivity coefficient (Q10) of the control and warming plots were 2.10 and 1.41, respectively. The soil temperature and soil moisture could partially explain the temporal variations of soil CO2 fluxes. The relationship between the temporal variation of soil CO2 fluxes and the soil temperature can be described by exponential equation. These results suggest that warming significantly promoted soil CO2 emission in the alpine steppe ecosystem of Northern Tibet and indicate that this alpine ecosystem is very vulnerable to climate change. In addition, soil temperature and soil moisture are the key factors that controls soil organic matter decomposition and soil CO2 emission, but temperature sensitivity significantly decreases due to the rise in temperature. [ABSTRACT FROM AUTHOR]