Long-term manure application has the potential to alleviate soil acidification, and increase carbon sequestration and nutrient availability, thus improving cropland fertility. However, the mechanisms behind greenhouse...Long-term manure application has the potential to alleviate soil acidification, and increase carbon sequestration and nutrient availability, thus improving cropland fertility. However, the mechanisms behind greenhouse gas N_(2)O emissions from acidic soil mediated by long-term manure application remain poorly understood. Herein, we investigated N_(2)O emission and its linkage with gross N mineralization and nitrification rates, as well as nitrifying and denitrifying microbes in an acidic upland soil subjected to 36-year fertilization treatments, including an unfertilized control(CK), inorganic fertilizer(F), 2× rate of inorganic fertilizer(2F), manure(M), and the combination of inorganic fertilizer and manure(FM) treatments. Compared to the CK treatment(1.34 μg N kg^(-1) d^(-1)), fertilization strongly increased N_(2)O emissions by 34-fold on average, with more pronounced increases in the manure-amendment(10.6-169 μg N kg^(-1) d^(-1)) than those in the inorganic fertilizer treatments(3.26-5.51 μg N kg^(-1) d^(-1)). The manure amendment-stimulated N_(2)O emissions were highly associated with increased soil pH, mean weight diameter of soil aggregates, substrate availability(e.g., particulate organic carbon, NO_(3)^(-)and available phosphorus), gross N mineralization rates, denitrifier abundances and the(nirK+nirS)/nosZ ratio. These findings suggest that the increased N_(2)O emissions primarily resulted from alleviated acidification, increased substrate availability and improved soil structure, thus enhancing microbial N mineralization and favoring N_(2)O^(-)producing denitrifiers over N_(2)O consumers. Moreover, ammonia-oxidizing bacteria(AOB) rather than ammonia-oxidizing archaea(AOA) positively correlated with soil NO_(3)^(-)concentration and N_(2)O emissions, indicating that nitrification indirectly contributed to N_(2)O production by supplying NO_(3)^(-)for denitrification. Collectively, manure amendment potentially stimulates N_(2)O emissions, primarily resulting from alleviated soil acidification and increased substrate availability, thus enhancing N mineralization and denitrifier-mediated N_(2)O production. Our findings suggest that consideration should be given to the greenhouse gas budgets of agricultural ecosystems when applying manure for managing the pH and fertility of acidic soils.展开更多
This experiment was conducted in Xinxiang, Henan from June 2013 to June 2014. Total four treatments were designed including farmers ’ common practice （F, 250 kg/hm^2）, 80% F （LF, 200 kg/hm^2）, 80% F＋biochar （LF...This experiment was conducted in Xinxiang, Henan from June 2013 to June 2014. Total four treatments were designed including farmers ’ common practice （F, 250 kg/hm^2）, 80% F （LF, 200 kg/hm^2）, 80% F＋biochar （LFC） and no fertilizer （CK） to measure the dynamic emissions of CO2 and N2O from a summer maize-winter wheat field by static chamber-gas chromatography method. The results showed that the soil CO2 emission was 21.8-1 022.7 mg/（m^2·h）, and was mainly influenced by soil temperature and moisture content. During the growth of summer maize, the soil CO2 emission was more significantly affected by soil moisture con-tent; and in winter wheat growing season, it was more significantly affected by soil temperature in the top 5 cm. The LF and LFC treatments significantly reduced the soil cumulative CO2 emission, especial y during the growth of winter wheat. Fertiliza-tion and irrigation were the main factors influencing the soil N2O emission. The soil N2O emission during the fertilization period accounted for 73.9%-74.5% and 40.5%-43.6% of the soil cumulative N2O emission during the summer maize-and winter wheat-growing season, respectively. The peak of emission fluxes was determined by fertilization amount, while the occurrence time of emission peak and emission re-duction effect were influenced by irrigation. The LF treatment reduced the soil cu-mulative N2O emission by 15.7%-16.8% and 18.1%-18.5% during the growth period of summer maize and winter wheat, respectively. Reduced nitrogen fertilization is an effective way for reducing N2O emission in intensive high-yielding farmland. Under a suitable nitrogen level （200 kg/hm^2）, the application of biochar showed no significant effect on the soil N2O emission in a short term. The N2O emission factors of the L and LF treatments were 0.60% and 0.56%, respectively. ln the intensive high-yield-ing farmland of North China, reducing the nitrogen application amount is an appro-priate measure to mitigate greenhouse gas emissions without crop yield loss.展开更多
How to achieve the objective of reducing CO2 emissions has been an academic focus in China recently. The factors influencing CO2 emissions are the vital issue to accomplish the arduous target. Firstly, three influenti...How to achieve the objective of reducing CO2 emissions has been an academic focus in China recently. The factors influencing CO2 emissions are the vital issue to accomplish the arduous target. Firstly, three influential factors, the energy consumption, the proportion of tertiary industry in gross domestic product （GDP）, and the degree of dependence on foreign trade, are carefully selected, since all of them have closer grey relation with China＇s COz emissions compared with others when the grey relational analysis （GRA） method is applied. The study highlights co-integration relation of these four variables using the co-integration analysis method. And then a long-term co-integration equation and a short-term error correction model of China＇s CO2 emissions are devel- oped. Finally, the comparison is exerted between the forecast value and the actual value of China＇s CO2 emissions based on error correction model. The results and the relevant statistics tests show that the pro- posed model has better explanation capability and credibility.展开更多
Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial het...Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial heterogeneity in regional CO_(2) patterns.This study investigated the spatiotemporal distribution of atmospheric CO_(2) in Pucheng and Nanping industrial parks,Nanping City,by conducting field experiments using two coherent differential absorption lidars from 1 August to 31 October 2024.Results showed that the spatial distributions of CO_(2) emis-sions within a 3 km radius were mapped,and the local diffusion processes were clarified.CO_(2) patterns varied differently in two industrial parks over the three-month period:Average CO_(2) concentrations in non-emission areas were 422.4 ppm in Pucheng and 408.7 ppm in Nanping,with the former experiencing higher and more variable carbon emissions;Correlation analysis indicated that synthetic leather factories in Pucheng contributed more to SO_(2) and NO_(x) levels compared to the chemical plant in Nanping;In Pucheng,CO_(2) concentrations were transported from the north at ground-level wind speeds exceeding 4 m/s,while in Nanping,the concentrations dispersed gradually with increasing wind speeds;Forward trajectory simulations revealed that the peak-emission from Pucheng primarily affected southern Fujian,northeastern Jiangxi,and southern Anhui,while the peak-emission from Nanping influenced central and western Fujian and northeastern Jiangxi.Besides,emissions in both industrial parks were higher on weekdays and lower on weekends,reflecting changes in industrial activi-ties.The study underscores the potential of lidar technology for providing detailed insights into CO_(2) distribution and the interactions between emissions,wind patterns,and carbon transport.展开更多
Transitioning real estate development toward low-carbon operations is a critical strategy for China to achieve its carbon peaking and neutrality targets.Accurately calculating CO_(2) emissions from real estate develop...Transitioning real estate development toward low-carbon operations is a critical strategy for China to achieve its carbon peaking and neutrality targets.Accurately calculating CO_(2) emissions from real estate development is essential for effective implementation of low-carbon strategies.However,research that specifically addresses CO_(2) emissions from real estate development is lacking.To fill this knowledge gap,this study examined CO_(2) emissions from China's real estate development between 2000 and 2020,presenting a comprehensive analysis of the production and consumption aspects of emissions,and inter-provincial transfers of emissions driven by the sector.Our findings reveal a significant increase in embodied CO_(2) emissions fromChina's real estate development,escalating from 145.5Mt in 2000 to 477.3Mt in 2020.The proportion of emissions attributable to real estate development among China's total CO_(2) emissions ranged from5%to 6%between 2000 and 2020,underscoring the sector's non-negligible impact on the country's overall CO_(2) emissions.Our analysis demonstrated that building material production,especially steel and cement,contributed significantly to the sector's emissions,underscoring the need for decarbonization and the adoption of green building materials.Additionally,a marginal increase in CO_(2) emissions per constructed area requires enhanced sustainable construction practices.Furthermore,our study revealed that the ongoing rise in inter-provincial CO_(2) emissions transfer due to real estate development intensifies carbon inequality across provinces.These findings are instrumental for policymakers and stakeholders to develop targeted interventions to mitigate CO_(2) emissions and promote sustainable growth in China's real estate sector.展开更多
Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nit...Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nitrogen addition in a Larix gmelinii forest was carried out to study the effects on soil carbon,nitrogen,and CO_(2)flux during the thawing,growing,and freezing periods.Our study found that warming(0-2.0℃)increased soil organic carbon(SOC)and total nitrogen(STN),dissolved organic carbon(DOC)and dissolved organic nitrogen(DON),and microbial biomass carbon(MBC)and microbial biomass nitrogen(MBN).Warming played a direct role in regulating soil CO_(2)emissions,stimulated microbial and plant root respiration and soil CO_(2)flux rapidly increased.Rainfall increase initially increased soil carbon and nitrogen,but a 30%increase in mean annual rainfall caused losses of SOC,STN,DOC,and DON,while MBC and MBN accumulated.Soil CO_(2)emissions were regulated by MBC after an increase in rainfall,excess moisture inhibited microbial activity,and soil CO_(2)flux showed a trend of R2(20%rainfall increase)>R1(10%rainfall increase)>CK(control)>R3(30%rainfall increase).The addition of nitrogen increased SOC,STN,DOC,DON,MBC and MBN.Soil CO_(2)flux progressively decreased with nitrogen inputs(2.5,5.0 and 10.0 g m^(-2)a^(-1)),as more N intensified plant-microbe competition.Nitrogen addition indirectly regulated soil CO_(2)emissions by altering SOC and STN,with MBC and MBN acting as secondary regulators.The results highlight the role of cold-temperate coniferous forest soils in predicting carbon-climate feedback in high-latitude forest permafrost regions.展开更多
The emission of heavy-duty vehicles has raised great concerns worldwide.The complex working and loading conditions,which may differ a lot from PEMS tests,raised new challenges to the supervision and control of emissio...The emission of heavy-duty vehicles has raised great concerns worldwide.The complex working and loading conditions,which may differ a lot from PEMS tests,raised new challenges to the supervision and control of emissions,especially during real-world applications.On-board diagnostics(OBD)technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles.This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals.Real-world NO_(x)and CO_(2)emissions of China-6 heavy-duty vehicles have been examined.The results showed that city heavy-duty vehicles had higher NO_(x)emission levels,which was mostly due to longer time of low SCR temperatures below 180°C.The application of novel methods based on 3BMAWalso found that heavy-duty diesel vehicles tended to have high NO_(x)emissions at idle.Also,little difference had been found in work-based CO_(2)emissions,and this may be due to no major difference were found in occupancies of hot running.展开更多
The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels...The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels and background variability,particularly owing to the influence of terrestrial biospheric fluxes.This necessitates the development of a regional inversion methodology based on atmospheric CO_(2)observations to verify bottom-up estimations independently.This study presents a promising approach for estimating China's FFCO_(2)emissions by incorporating the model residual errors(MREs)of the column-averaged dry-air mole fractions of CO_(2)(XCO_(2))from FFCO_(2)emissions(MREff)retained in the analysis of natural flux optimization.China's FFCO_(2)emissions during the COVID-19 lockdown in 2020 are estimated using the GEOS-Chem adjoint model.The relationship between the MREff and FFCO_(2)is determined using the model based on a regional FFCO_(2)anomaly suggested by posterior NOx emissions from air-quality data assimilation.The MREff is typically one-tenth in magnitude,but some positively skewed outliers exceed 1 ppm because the prior emissions lack lockdown impacts,thereby exerting considerable observation forcing given the satellite retrieval uncertainties.We initialize the FFCO_(2)with posterior NOx emissions and optimize the colinear emission ratio.Synthetic data experiments demonstrate that this approach reduces the FFCO_(2)bias to less than 10%.The real-data experiments estimate 19%lower FFCO_(2)with GOSAT XCO_(2)and 26%lower with OCO-2 XCO_(2)than the bottom-up estimations.This study proves the feasibility of our regional FFCO_(2)inversion,highlighting the importance of addressing the outlier behaviors observed in satellite XCO_(2)retrievals.展开更多
This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and car...This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.展开更多
Global climate change is the most serious challenge that modern society faces.Soil-biochar carbon sequestration is a promising natural solution for capturing carbon.This study monitored the CO_(2) emissions of five bi...Global climate change is the most serious challenge that modern society faces.Soil-biochar carbon sequestration is a promising natural solution for capturing carbon.This study monitored the CO_(2) emissions of five biochar incubated Malaysian Tropical soils(MT-Soil).The recalcitrance index of palm kernel shell biochar(PKS)was higher than that of wood chip biochar(WCB),bamboo biochar(BB),coconut shell biochar(CHB)and rice husk biochar(RHB),and was different from the observed CO_(2) emission characteristics(WCB>CHB>RHB>BB>PKS).Thus,the carbon sequestration potential of biochar could not be evaluated solely by the recalcitrance index.This CO_(2) emission is linked not only to the total organic carbon(TOC)and total carbon(TC)of the biochar but also associated with mobile matter(MM),water holding capacity(WHC),available phosphorus(AP),exchangeable potassium(AK),and nitrogen content.The multiple linear regression analysis(MLRA)shows that the weights of these factors on CO_(2) emissions are as follows:TC>pH>MM>WHC>AP>AK.The results show that in addition to biochar stability,pore structure and available phosphorus release also affect carbon dynamics through indirect effects on microbial activity.This means that to minimize CO_(2) emissions during application of biochar,it is necessary to use soil that is rich in phosphorus and biochar that has undeveloped pore structure and high stable carbon.Finally,this study provides valuable theoretical underpinnings biochar application in MT-Soil.展开更多
As the largest energy consuming manufacturing sector and one of the most important sources of carhon dioxide （CO2） emissions, the China＇s iron and steel industry has paid attention to the study of changing trend an...As the largest energy consuming manufacturing sector and one of the most important sources of carhon dioxide （CO2） emissions, the China＇s iron and steel industry has paid attention to the study of changing trend and influencing factors of CO2 emissions from energy use. The logarithmic mean Divisia index （LMD1） technique is used to decompose total change in CO2 emissions into four factors： emission factor effect, energy structure effect, energy consumption effect, and steel production effect. The results show that the steel production effect is the major factor which is responsible for the rise in CO2 emissions; whereas the energy consumption effect contributes most to the reduction in CO2 emissions. And the emission factor effect makes a weak negative contribution to the increase of CO2 emis- sions. To find out the detailed relationship between change in energy consumption or steel production and change in CO2 emissions, the correlation equations are also proposed.展开更多
In 2009, nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspec...In 2009, nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspects such as the change of LUCC and the use of energy and its associated impacts had been recognized. Recently, the impact of tourism on environment and climate attracts the attention of international organizations and societies in pace with rapid development of tourism industry. Energy consumption and CO2 emissions in tourism sector are becoming a hot spot of international tourism research in recent five years. The use of energy for tourism can be divided according to transport-related purposes （travel to, from and at the destination） and destination-related purposes excluding transports （accommodation, food, tourist activities, etc.）. In addition, the transports, accommodation and foods are related to many other industries which are dependent on energy. Thus, the estimations of energy consumption and CO2 emissions in tourism sector have become a worldwide concern. Tourism in China grows rapidly, and the number of domestic tourists was 1902 million in 2009. Energy use and its impact on the environment increase synchronously with China’s tourism. It is necessary to examine the relationship between energy use and CO2 emissions. In this article, a preliminary attempt was applied to estimate the energy consumption and CO2 emissions from China’s tourism sector in 2008. Bottom-up approach, literature research and mathematical statistics technology were also adopted. According to the calculations, Chinese tourism-related may have consumed approximately 428.30 PJ of energy in 2008, or about 0.51% of the total energy consumptions in China. It is estimated that CO2 emissions from tourism sector amounted to 51.34 Mt, accounting for 0.86% of the total in China. The results show that tourism is a low-carbon industry and also a pillar industry coping with global climate change, energy-saving and CO2 emission reduction. Based on this, the authors suggested that tourism should become an important field in low-carbon economic development.展开更多
CO_(2) emissions(CEs)pose a growing threat to environmental changes and global warming,attracting extensive attention.Here,we leveraged near-real-time monitoring data spanning 2019 to 2022 to investigate spatiotempora...CO_(2) emissions(CEs)pose a growing threat to environmental changes and global warming,attracting extensive attention.Here,we leveraged near-real-time monitoring data spanning 2019 to 2022 to investigate spatiotemporal heterogeneity,sectoral contributions,provincial spatial correlation,and driving factors influencing CEs at the provincial level in China.Our analysis,integrating Moran’s Index analysis,Spearman correlation analysis,and the Geographically Weighted Regression model,unveiled China’s consistent world-leading CEs,surpassing 10,000 Mt over the study period.Spatially,CEs exhibited a heterogeneous distribution,with markedly higher emissions in eastern and northern regions compared to western and southern areas.Temporally,CEs displayed significant fluctuations,peaking in the fourth quarter before declining in subsequent quarters.Chinese NewYear and COVID-19 had the biggest effects on CEs,with average daily reductions of-20.8%and-18.9%,respectively,compared to the four-year average and the same period in 2019.Sectoral analysis highlighted the power and industry sectors as primary contributors to CEs in China,jointly accounting for 37.9%-40.2%and 43.5%-46.4%of total CEs,respectively.Spatial clustering analysis identified a distinct High-High agglomeration region,predominantly encompassing provinces such as Inner Mongolia,Shandong and Jiangsu.Furthermore,total energy consumption and electricity consumption emerged as significant drivers of CEs,exhibiting correlation coefficients exceeding 0.9,followed by exhaust emissions,population size,and gross domestic product.Moreover,the influence of drivers on provincial CEs exhibited notable spatial heterogeneity,with regression coefficients displaying a decreasing gradient from north to south.These findings provide scientific and technological support to realize the provincial dual-carbon goals in China.展开更多
The response of N_(2)O emissions to nitrogen(N)addition is usually positive,but its response to phosphorus(P)addition varies,and the underlying mechanisms for the changes in N_(2)O emissions remain unclear.We conducte...The response of N_(2)O emissions to nitrogen(N)addition is usually positive,but its response to phosphorus(P)addition varies,and the underlying mechanisms for the changes in N_(2)O emissions remain unclear.We conducted field studies to examine the response of N_(2)O emissions to N and P addition over two years in three typical alpine grasslands,alpine meadow(AM),alpine steppe(AS),and alpine cultivated grassland(CG)on the Qinghai-Tibet Plateau(QTP).Our results showed consistent increases in N_(2)O emissions under N addition alone or with P addition,and insignificant change in N_(2)O emissions under P addition alone in all three grasslands.N addition increased N_(2)O emissions directly in AM,by lowering soil pH in AS,and by lowering abundance of denitrification genes in CG.N and P co-addition increased N_(2)O emissions in AM and AS but only showed an interactive effect in AM.P addition enhanced the increase in N_(2)O emissions caused by N addition mainly by promoting plant growth in AM.Overall,our results illustrate that short-term P addition cannot alleviate the stimulation of N_(2)O emissions by N deposition in alpine grassland ecosystems,and may even further stimulate N_(2)O emissions.展开更多
This study analyzes the influence of green bonds on carbon neutrality.It examines the daily data of sectoral CO_(2) emissions of the top five CO_(2)-emitting nations from January 2,2019 to December 30,2022 using wavel...This study analyzes the influence of green bonds on carbon neutrality.It examines the daily data of sectoral CO_(2) emissions of the top five CO_(2)-emitting nations from January 2,2019 to December 30,2022 using wavelet transform coherence,quantile-onquantile regression,Granger causality in quantiles,and quantile regression approaches.The results revealed that(i)green bonds are strongly related to sectoral CO_(2) emissions;(ii)green bonds reduce transport sector CO_(2) emissions in China,the US,and Japan while causing an upsurge in India and Russia;(iii)green bonds reduce industrial sector CO_(2) emissions only in the US;(iv)green bonds have a declining influence in energy sector CO_(2) emissions at lower quantiles in India,China,and the US,whereas the impact increases at higher quantiles;and(v)green bonds decrease residential sector CO_(2) emissions in the US,Russia,and Japan.The study revealed that green bonds help reduce CO_(2) emissions in the residential sector in various quantiles.Therefore,the US,Russia,and Japan should raise household awareness of green energy utilization by promoting them with green bonds.In addition,green bonds can effectively reduce transportation sector CO_(2) emissions in China and the US.Therefore,the policymakers of the two global powers should contribute to global CO_(2) reduction by promoting green transportation and clean energy transition in the transportation sector through green bonds.Thus,green bonds can play an effective role in the fight against global warming.展开更多
The energy sector is pivotal in Vietnam’s commitment to achieving net-zero emissions by 2050.This study employs a combination of Structural Decomposition Analysis(SDA)and decoupling approaches based on data from Viet...The energy sector is pivotal in Vietnam’s commitment to achieving net-zero emissions by 2050.This study employs a combination of Structural Decomposition Analysis(SDA)and decoupling approaches based on data from Vietnam’s energy statistics and the Vietnam Living Standards Survey(VHLSS)for 2016,2018,and 2020.The primary aim is to elucidate the effects of direct energy consumption by household groups on CO_(2)emissions,examine factors affecting emissions,and clarify the relationship between CO_(2)emissions from household energy consumption and economic growth in Vietnam.Research results underscore that household groups make considerable use of electricity and Liquefied Petroleum Gas(LPG),simultaneously reducing the proportion of firewood,rice husk,sawdust,agricultural by-products and other fuels.The decrease in energy intensity emerges as the primary factor in lowering household emissions,while population growth and economic efficiency exert the opposite effect.Additionally,the research reveals disparities in emissions between urban and rural areas,similarly among household groups within the given location.Despite maintaining a robust decoupling status between emissions from household consumption and economic growth,unsustainable risks persist,particularly with the increase in electricity demand.The study also highlights the uneven impact of the COVID-19 epidemic on CO_(2)emissions across household groups.Drawing upon these findings,several recommendations are proposed to control CO_(2)emissions from direct energy household consumption to facilitate the most effective household decarbonisation process while ensuring sustainable economic growth in Vietnam.展开更多
The marginal abatement cost(MAC)of CO_(2)emissions is one of the most critical indicators used to assess energy conservation and emission reduction.Although extensively measured,few studies have incorporated the influ...The marginal abatement cost(MAC)of CO_(2)emissions is one of the most critical indicators used to assess energy conservation and emission reduction.Although extensively measured,few studies have incorporated the influence of policy constraints when evaluating MAC.To address this gap,this paper proposes a nonparametric directional distance function approach under policy regulations to estimate the CO_(2)shadow price in the construction industry across 30 Chinese provinces from 2010 to 2017.Based on this enhanced method,four key findings emerge:①the annual CO_(2)shadow price exhibits an overall upward trend during the observation period;②regional shadow prices display marked variation across provinces;③regional heterogeneity in shadow prices has increased steadily over time;and④both urbanization rate and energy consumption per unit of gross domestic product are significantly negatively correlated with the CO_(2)shadow price.Finally,the paper offers several policy recommendations for CO_(2)emissions reduction in the Chinese construction industry at the national,industry,and enterprise levels.展开更多
Despite countries having signed agreements and developed policy to reduce CO_(2)emissions,there is disproportionate compliance with the agreements,with developed countries continuing to be the largest emitters.The obj...Despite countries having signed agreements and developed policy to reduce CO_(2)emissions,there is disproportionate compliance with the agreements,with developed countries continuing to be the largest emitters.The objective of this study was to compare the impact of South Africa’s population growth,economic growth,and fertilizer consumption on CO_(2)emissions,with those of the US,China,and other BRICS countries.The study used panel data sourced from the World Bank’s World Development Indicators ranging from 1960 to 2023.Results of the fixed effects panel regression show that the coefficient of change for China’s population size(β=9.156,p<0.01)is the highest among the six countries.It is followed by the USA(β=9.156,p<0.05)and South Africa(β=1.474,p<0.01).The effects of GDP for China(β=1.128,p<0.01)on CO_(2)emissions are the largest,followed by South Africa(β=1.098,p<0.01)and the USA in third place(β=0.614,p<0.05).These results show that South Africa is highly reliant on coal-based energy resources.As a policy recommendation,South Africa needs to diversify its energy mix and invest more in renewable energy resources.展开更多
To address the global issue of climate change and create focused mitigation plans,accurate CO_(2)emissions forecasting is essential.Using CO_(2)emissions data from 1990 to 2023,this study assesses the predicting perfo...To address the global issue of climate change and create focused mitigation plans,accurate CO_(2)emissions forecasting is essential.Using CO_(2)emissions data from 1990 to 2023,this study assesses the predicting performance of five sophisticated models:Random Forest(RF),XGBoost,Support Vector Regression(SVR),Long Short-Term Memory networks(LSTM),and ARIMA To give a thorough evaluation of the models’performance,measures including Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and Mean Absolute Percentage Error(MAPE)are used.To guarantee dependable model implementation,preprocessing procedures are carried out,such as feature engineering and stationarity tests.Machine learning models outperform ARIMA in identifying complex patterns and long-term associations,but ARIMA does better with data that exhibits strong linear trends.These results provide important information about how well the model fits various forecasting scenarios,which helps develop data-driven carbon reduction programs.Predictive modeling should be incorporated into sustainable climate policy to encourage the adoption of low-carbon technologies and proactive decisionmaking.Achieving long-term environmental sustainability requires strengthening carbon trading systems,encouraging clean energy investments,and enacting stronger emission laws.In line with international climate goals,suggestions for lowering CO_(2)emissions include switching to renewable energy,increasing energy efficiency,and putting afforestation initiatives into action.展开更多
Establishing positive and urgent targets for CO_2 reduction and emission peak,and promoting energy conservation and energy structure adjustment are among the strategies to address global climate change and CO_2 emissi...Establishing positive and urgent targets for CO_2 reduction and emission peak,and promoting energy conservation and energy structure adjustment are among the strategies to address global climate change and CO_2 emissions reduction.They are also means to break through the constraints of domestic resources and environment,and internal needs,to achieve sustainable development.Generally speaking,a country's CO_2 emission peak appears after achieving urbanization and industrialization.By then,connotative economic growth will appear,GDP will grow slowly,energy consumption elasticity will decrease,and energy consumption growth will slow down-dependent mainly on new and renewable energies.Fossil fuel consumption will not increase further.When CO_2 emission reaches its peak,the annual reduction rate of CO_2 intensity of GDP is greater than GDP annual growth rate;and the annual reduction rate of CO_2 intensity of energy use is greater than the annual growth rate of energy consumption.Therefore,three important approaches to promotion of CO_2 emission peak can be concluded:maintaining reasonable control of GDP growth,strengthening energy conservation to significantly reduce the GDP energy intensity,and optimizing the energy mix to reduce the CO_2 intensity of energy use.By around 2030,China will basically have completed its rapid development phase of industrialization and urbanization.Connotative economic growth will appear with the acceleration of industrial structure adjustment The target of GDP energy intensity will still be to maintain an average annual reduction of 3%or higher.The proportion of non-fossil fuels will reach 20-25%,and the aim will be to maintain an average annual growth rate of 6-8%.The total annual energy demand growth of 1.5%will be satisfied by the newly increased supply of non-fossil fuels.The annual decline in CO_2 intensity of GDP will reach 4.5%or higher,which is compatible with an average annual GDP growth rate of approximately 4.5%in order to reach CO_2 emission peak.This corresponds to the level of China's potential economic growth.Achieving CO_2 emission peak will not impose a rigid constraint on economic development,but rather promote economic development and accelerate the transformation of green,low-carbon development.The CO_2 emission peak can be controlled with a cap of 11 billion tons,which means that CO_2 emission will increase by less than 50%compared with 2010.The per capita emission peak will be controlled at a level of less than 8 tons,which is lower than the 9.5 tons in the EU and Japan and much lower than the 20 tons in the US,future economic and social development faces many uncertainties in achieving the CO_2 emission peak discussed above.It depends on current and future strategies and policies,as well as the pace and strength of economic transformation,innovation,and new energy technologies.If the economic transformation pattern fails to meet expectations,the time required to reach CO_2emission peak would be delayed and the peak level would be higher than expected.Therefore,we need to coordinate thoughts and ideas and deploy these in advance;to highlight the strategic position of low-carbon development and its priorities;to enact mid-to long-term energy development strategies;and to establish and improve a system of laws,regulations,and policies as well as an implementation mechanism for green,low-carbon development Oriented by positive and urgent CO_2 reduction and peak targets,the government would form a reversed mechanism to promote economic transformation and embark on the path of green,low-carbon development as soon as possible.展开更多
基金financially supported by the National Science & Technology Fundamental Resources Investigation Project of China (2021FY100501)the Youth Innovation of Chinese Academy of Agricultural Sciences (Y2023QC16)。
文摘Long-term manure application has the potential to alleviate soil acidification, and increase carbon sequestration and nutrient availability, thus improving cropland fertility. However, the mechanisms behind greenhouse gas N_(2)O emissions from acidic soil mediated by long-term manure application remain poorly understood. Herein, we investigated N_(2)O emission and its linkage with gross N mineralization and nitrification rates, as well as nitrifying and denitrifying microbes in an acidic upland soil subjected to 36-year fertilization treatments, including an unfertilized control(CK), inorganic fertilizer(F), 2× rate of inorganic fertilizer(2F), manure(M), and the combination of inorganic fertilizer and manure(FM) treatments. Compared to the CK treatment(1.34 μg N kg^(-1) d^(-1)), fertilization strongly increased N_(2)O emissions by 34-fold on average, with more pronounced increases in the manure-amendment(10.6-169 μg N kg^(-1) d^(-1)) than those in the inorganic fertilizer treatments(3.26-5.51 μg N kg^(-1) d^(-1)). The manure amendment-stimulated N_(2)O emissions were highly associated with increased soil pH, mean weight diameter of soil aggregates, substrate availability(e.g., particulate organic carbon, NO_(3)^(-)and available phosphorus), gross N mineralization rates, denitrifier abundances and the(nirK+nirS)/nosZ ratio. These findings suggest that the increased N_(2)O emissions primarily resulted from alleviated acidification, increased substrate availability and improved soil structure, thus enhancing microbial N mineralization and favoring N_(2)O^(-)producing denitrifiers over N_(2)O consumers. Moreover, ammonia-oxidizing bacteria(AOB) rather than ammonia-oxidizing archaea(AOA) positively correlated with soil NO_(3)^(-)concentration and N_(2)O emissions, indicating that nitrification indirectly contributed to N_(2)O production by supplying NO_(3)^(-)for denitrification. Collectively, manure amendment potentially stimulates N_(2)O emissions, primarily resulting from alleviated soil acidification and increased substrate availability, thus enhancing N mineralization and denitrifier-mediated N_(2)O production. Our findings suggest that consideration should be given to the greenhouse gas budgets of agricultural ecosystems when applying manure for managing the pH and fertility of acidic soils.
基金Supported by National Key Technology Research and Development Program(2013BAD11B03)National Natural Science Foundation(31272249,31071865,41505100)~~
文摘This experiment was conducted in Xinxiang, Henan from June 2013 to June 2014. Total four treatments were designed including farmers ’ common practice （F, 250 kg/hm^2）, 80% F （LF, 200 kg/hm^2）, 80% F＋biochar （LFC） and no fertilizer （CK） to measure the dynamic emissions of CO2 and N2O from a summer maize-winter wheat field by static chamber-gas chromatography method. The results showed that the soil CO2 emission was 21.8-1 022.7 mg/（m^2·h）, and was mainly influenced by soil temperature and moisture content. During the growth of summer maize, the soil CO2 emission was more significantly affected by soil moisture con-tent; and in winter wheat growing season, it was more significantly affected by soil temperature in the top 5 cm. The LF and LFC treatments significantly reduced the soil cumulative CO2 emission, especial y during the growth of winter wheat. Fertiliza-tion and irrigation were the main factors influencing the soil N2O emission. The soil N2O emission during the fertilization period accounted for 73.9%-74.5% and 40.5%-43.6% of the soil cumulative N2O emission during the summer maize-and winter wheat-growing season, respectively. The peak of emission fluxes was determined by fertilization amount, while the occurrence time of emission peak and emission re-duction effect were influenced by irrigation. The LF treatment reduced the soil cu-mulative N2O emission by 15.7%-16.8% and 18.1%-18.5% during the growth period of summer maize and winter wheat, respectively. Reduced nitrogen fertilization is an effective way for reducing N2O emission in intensive high-yielding farmland. Under a suitable nitrogen level （200 kg/hm^2）, the application of biochar showed no significant effect on the soil N2O emission in a short term. The N2O emission factors of the L and LF treatments were 0.60% and 0.56%, respectively. ln the intensive high-yield-ing farmland of North China, reducing the nitrogen application amount is an appro-priate measure to mitigate greenhouse gas emissions without crop yield loss.
基金Supported by the National Natural Science Foundation of China(41101569)the China Postdoctoral Science Foundation Funded Project(2011M500965)+5 种基金the Jiangsu Funds of Social Science(11EYC023)the Doctoral Discipline New Teachers Fund(20110095120002)the Jiangsu Postdoctoral Science Foundation Funded Project(1102088C)the Fundamental Research Funds for the Central Universities(JGJ110763)the Talent Introduction Funds of China University of Mining and Technologythe Sail Plan Funds for Young Teachers of China University of Mining and Technology~~
文摘How to achieve the objective of reducing CO2 emissions has been an academic focus in China recently. The factors influencing CO2 emissions are the vital issue to accomplish the arduous target. Firstly, three influential factors, the energy consumption, the proportion of tertiary industry in gross domestic product （GDP）, and the degree of dependence on foreign trade, are carefully selected, since all of them have closer grey relation with China＇s COz emissions compared with others when the grey relational analysis （GRA） method is applied. The study highlights co-integration relation of these four variables using the co-integration analysis method. And then a long-term co-integration equation and a short-term error correction model of China＇s CO2 emissions are devel- oped. Finally, the comparison is exerted between the forecast value and the actual value of China＇s CO2 emissions based on error correction model. The results and the relevant statistics tests show that the pro- posed model has better explanation capability and credibility.
基金supported by the National Natural Science Foundation of China(Nos.42305147 and 42405138)the Natural Science Foundation of Jiangsu Province(No.BK20230428).
文摘Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial heterogeneity in regional CO_(2) patterns.This study investigated the spatiotemporal distribution of atmospheric CO_(2) in Pucheng and Nanping industrial parks,Nanping City,by conducting field experiments using two coherent differential absorption lidars from 1 August to 31 October 2024.Results showed that the spatial distributions of CO_(2) emis-sions within a 3 km radius were mapped,and the local diffusion processes were clarified.CO_(2) patterns varied differently in two industrial parks over the three-month period:Average CO_(2) concentrations in non-emission areas were 422.4 ppm in Pucheng and 408.7 ppm in Nanping,with the former experiencing higher and more variable carbon emissions;Correlation analysis indicated that synthetic leather factories in Pucheng contributed more to SO_(2) and NO_(x) levels compared to the chemical plant in Nanping;In Pucheng,CO_(2) concentrations were transported from the north at ground-level wind speeds exceeding 4 m/s,while in Nanping,the concentrations dispersed gradually with increasing wind speeds;Forward trajectory simulations revealed that the peak-emission from Pucheng primarily affected southern Fujian,northeastern Jiangxi,and southern Anhui,while the peak-emission from Nanping influenced central and western Fujian and northeastern Jiangxi.Besides,emissions in both industrial parks were higher on weekdays and lower on weekends,reflecting changes in industrial activi-ties.The study underscores the potential of lidar technology for providing detailed insights into CO_(2) distribution and the interactions between emissions,wind patterns,and carbon transport.
文摘Transitioning real estate development toward low-carbon operations is a critical strategy for China to achieve its carbon peaking and neutrality targets.Accurately calculating CO_(2) emissions from real estate development is essential for effective implementation of low-carbon strategies.However,research that specifically addresses CO_(2) emissions from real estate development is lacking.To fill this knowledge gap,this study examined CO_(2) emissions from China's real estate development between 2000 and 2020,presenting a comprehensive analysis of the production and consumption aspects of emissions,and inter-provincial transfers of emissions driven by the sector.Our findings reveal a significant increase in embodied CO_(2) emissions fromChina's real estate development,escalating from 145.5Mt in 2000 to 477.3Mt in 2020.The proportion of emissions attributable to real estate development among China's total CO_(2) emissions ranged from5%to 6%between 2000 and 2020,underscoring the sector's non-negligible impact on the country's overall CO_(2) emissions.Our analysis demonstrated that building material production,especially steel and cement,contributed significantly to the sector's emissions,underscoring the need for decarbonization and the adoption of green building materials.Additionally,a marginal increase in CO_(2) emissions per constructed area requires enhanced sustainable construction practices.Furthermore,our study revealed that the ongoing rise in inter-provincial CO_(2) emissions transfer due to real estate development intensifies carbon inequality across provinces.These findings are instrumental for policymakers and stakeholders to develop targeted interventions to mitigate CO_(2) emissions and promote sustainable growth in China's real estate sector.
基金funded by the Science and Technology Programme of Inner Mongolia Autonomous Region(Grant No.:2023YFDZ0026 and 2024KYPT0003)the 2024 Postgraduate Research and Innovation Programme of Inner Mongolia Agricultural University。
文摘Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nitrogen addition in a Larix gmelinii forest was carried out to study the effects on soil carbon,nitrogen,and CO_(2)flux during the thawing,growing,and freezing periods.Our study found that warming(0-2.0℃)increased soil organic carbon(SOC)and total nitrogen(STN),dissolved organic carbon(DOC)and dissolved organic nitrogen(DON),and microbial biomass carbon(MBC)and microbial biomass nitrogen(MBN).Warming played a direct role in regulating soil CO_(2)emissions,stimulated microbial and plant root respiration and soil CO_(2)flux rapidly increased.Rainfall increase initially increased soil carbon and nitrogen,but a 30%increase in mean annual rainfall caused losses of SOC,STN,DOC,and DON,while MBC and MBN accumulated.Soil CO_(2)emissions were regulated by MBC after an increase in rainfall,excess moisture inhibited microbial activity,and soil CO_(2)flux showed a trend of R2(20%rainfall increase)>R1(10%rainfall increase)>CK(control)>R3(30%rainfall increase).The addition of nitrogen increased SOC,STN,DOC,DON,MBC and MBN.Soil CO_(2)flux progressively decreased with nitrogen inputs(2.5,5.0 and 10.0 g m^(-2)a^(-1)),as more N intensified plant-microbe competition.Nitrogen addition indirectly regulated soil CO_(2)emissions by altering SOC and STN,with MBC and MBN acting as secondary regulators.The results highlight the role of cold-temperate coniferous forest soils in predicting carbon-climate feedback in high-latitude forest permafrost regions.
基金supported by the National Key Research and Development Project of China(No.2022YFC3701802)the National Natural Science Foundation of China(No.52272342)the Major Science and Technology Projects of Qinghai Province(No.2019-GX-A6).
文摘The emission of heavy-duty vehicles has raised great concerns worldwide.The complex working and loading conditions,which may differ a lot from PEMS tests,raised new challenges to the supervision and control of emissions,especially during real-world applications.On-board diagnostics(OBD)technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles.This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals.Real-world NO_(x)and CO_(2)emissions of China-6 heavy-duty vehicles have been examined.The results showed that city heavy-duty vehicles had higher NO_(x)emission levels,which was mostly due to longer time of low SCR temperatures below 180°C.The application of novel methods based on 3BMAWalso found that heavy-duty diesel vehicles tended to have high NO_(x)emissions at idle.Also,little difference had been found in work-based CO_(2)emissions,and this may be due to no major difference were found in occupancies of hot running.
基金jointly supported by the National Key Research and Development Plan(Grant No.2023YFB3907405)the National Natural Science Foundation of China(Grant No.42175132)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-037)。
文摘The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels and background variability,particularly owing to the influence of terrestrial biospheric fluxes.This necessitates the development of a regional inversion methodology based on atmospheric CO_(2)observations to verify bottom-up estimations independently.This study presents a promising approach for estimating China's FFCO_(2)emissions by incorporating the model residual errors(MREs)of the column-averaged dry-air mole fractions of CO_(2)(XCO_(2))from FFCO_(2)emissions(MREff)retained in the analysis of natural flux optimization.China's FFCO_(2)emissions during the COVID-19 lockdown in 2020 are estimated using the GEOS-Chem adjoint model.The relationship between the MREff and FFCO_(2)is determined using the model based on a regional FFCO_(2)anomaly suggested by posterior NOx emissions from air-quality data assimilation.The MREff is typically one-tenth in magnitude,but some positively skewed outliers exceed 1 ppm because the prior emissions lack lockdown impacts,thereby exerting considerable observation forcing given the satellite retrieval uncertainties.We initialize the FFCO_(2)with posterior NOx emissions and optimize the colinear emission ratio.Synthetic data experiments demonstrate that this approach reduces the FFCO_(2)bias to less than 10%.The real-data experiments estimate 19%lower FFCO_(2)with GOSAT XCO_(2)and 26%lower with OCO-2 XCO_(2)than the bottom-up estimations.This study proves the feasibility of our regional FFCO_(2)inversion,highlighting the importance of addressing the outlier behaviors observed in satellite XCO_(2)retrievals.
基金supported by the top-level design of the National Natural Science Foundation of China(NSFC)Major Project“Realization of optimal carbon neutral pathway and coupling of multi-scale interaction patterns of natural-social systems in China”(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.
基金the support of the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme(FRGS)(No.FRGS/1/2022/TK01/UM/02/2)the Young Innovative Talent Project-Guangdong Scientific Research Platform and Projects for the Higher-educational Institution&Education Science Planning Scheme(No.KY2022036401)+3 种基金University-level scientific research institution project(No.KY2023000401)Characteristic innovation project of colleges and universities in Guangdong Province(No.2021KTSCX191)Science and Technology developing Project of Dongguan City(No.20211800904572)the Instrument of Dongguan city college and Universiti Malaya for technical support。
文摘Global climate change is the most serious challenge that modern society faces.Soil-biochar carbon sequestration is a promising natural solution for capturing carbon.This study monitored the CO_(2) emissions of five biochar incubated Malaysian Tropical soils(MT-Soil).The recalcitrance index of palm kernel shell biochar(PKS)was higher than that of wood chip biochar(WCB),bamboo biochar(BB),coconut shell biochar(CHB)and rice husk biochar(RHB),and was different from the observed CO_(2) emission characteristics(WCB>CHB>RHB>BB>PKS).Thus,the carbon sequestration potential of biochar could not be evaluated solely by the recalcitrance index.This CO_(2) emission is linked not only to the total organic carbon(TOC)and total carbon(TC)of the biochar but also associated with mobile matter(MM),water holding capacity(WHC),available phosphorus(AP),exchangeable potassium(AK),and nitrogen content.The multiple linear regression analysis(MLRA)shows that the weights of these factors on CO_(2) emissions are as follows:TC>pH>MM>WHC>AP>AK.The results show that in addition to biochar stability,pore structure and available phosphorus release also affect carbon dynamics through indirect effects on microbial activity.This means that to minimize CO_(2) emissions during application of biochar,it is necessary to use soil that is rich in phosphorus and biochar that has undeveloped pore structure and high stable carbon.Finally,this study provides valuable theoretical underpinnings biochar application in MT-Soil.
基金Item Sponsored by the Fundamental Research Funds for the Central Universities of China(N090602007)
文摘As the largest energy consuming manufacturing sector and one of the most important sources of carhon dioxide （CO2） emissions, the China＇s iron and steel industry has paid attention to the study of changing trend and influencing factors of CO2 emissions from energy use. The logarithmic mean Divisia index （LMD1） technique is used to decompose total change in CO2 emissions into four factors： emission factor effect, energy structure effect, energy consumption effect, and steel production effect. The results show that the steel production effect is the major factor which is responsible for the rise in CO2 emissions; whereas the energy consumption effect contributes most to the reduction in CO2 emissions. And the emission factor effect makes a weak negative contribution to the increase of CO2 emis- sions. To find out the detailed relationship between change in energy consumption or steel production and change in CO2 emissions, the correlation equations are also proposed.
基金The Key Project of China National Tourism Administration, No.10TAAK007
文摘In 2009, nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspects such as the change of LUCC and the use of energy and its associated impacts had been recognized. Recently, the impact of tourism on environment and climate attracts the attention of international organizations and societies in pace with rapid development of tourism industry. Energy consumption and CO2 emissions in tourism sector are becoming a hot spot of international tourism research in recent five years. The use of energy for tourism can be divided according to transport-related purposes （travel to, from and at the destination） and destination-related purposes excluding transports （accommodation, food, tourist activities, etc.）. In addition, the transports, accommodation and foods are related to many other industries which are dependent on energy. Thus, the estimations of energy consumption and CO2 emissions in tourism sector have become a worldwide concern. Tourism in China grows rapidly, and the number of domestic tourists was 1902 million in 2009. Energy use and its impact on the environment increase synchronously with China’s tourism. It is necessary to examine the relationship between energy use and CO2 emissions. In this article, a preliminary attempt was applied to estimate the energy consumption and CO2 emissions from China’s tourism sector in 2008. Bottom-up approach, literature research and mathematical statistics technology were also adopted. According to the calculations, Chinese tourism-related may have consumed approximately 428.30 PJ of energy in 2008, or about 0.51% of the total energy consumptions in China. It is estimated that CO2 emissions from tourism sector amounted to 51.34 Mt, accounting for 0.86% of the total in China. The results show that tourism is a low-carbon industry and also a pillar industry coping with global climate change, energy-saving and CO2 emission reduction. Based on this, the authors suggested that tourism should become an important field in low-carbon economic development.
基金supported by the National Natural Science Foundation of China(No.52200120)the R&D Program of Beijing Municipal Education Commission(No.KM202310011003).
文摘CO_(2) emissions(CEs)pose a growing threat to environmental changes and global warming,attracting extensive attention.Here,we leveraged near-real-time monitoring data spanning 2019 to 2022 to investigate spatiotemporal heterogeneity,sectoral contributions,provincial spatial correlation,and driving factors influencing CEs at the provincial level in China.Our analysis,integrating Moran’s Index analysis,Spearman correlation analysis,and the Geographically Weighted Regression model,unveiled China’s consistent world-leading CEs,surpassing 10,000 Mt over the study period.Spatially,CEs exhibited a heterogeneous distribution,with markedly higher emissions in eastern and northern regions compared to western and southern areas.Temporally,CEs displayed significant fluctuations,peaking in the fourth quarter before declining in subsequent quarters.Chinese NewYear and COVID-19 had the biggest effects on CEs,with average daily reductions of-20.8%and-18.9%,respectively,compared to the four-year average and the same period in 2019.Sectoral analysis highlighted the power and industry sectors as primary contributors to CEs in China,jointly accounting for 37.9%-40.2%and 43.5%-46.4%of total CEs,respectively.Spatial clustering analysis identified a distinct High-High agglomeration region,predominantly encompassing provinces such as Inner Mongolia,Shandong and Jiangsu.Furthermore,total energy consumption and electricity consumption emerged as significant drivers of CEs,exhibiting correlation coefficients exceeding 0.9,followed by exhaust emissions,population size,and gross domestic product.Moreover,the influence of drivers on provincial CEs exhibited notable spatial heterogeneity,with regression coefficients displaying a decreasing gradient from north to south.These findings provide scientific and technological support to realize the provincial dual-carbon goals in China.
基金funded by the National Key R&D Program of China(2021YFE0112400 and 2023YFF1304303)the National Natural Science Foundation of China(32361143870 and 32101315)。
文摘The response of N_(2)O emissions to nitrogen(N)addition is usually positive,but its response to phosphorus(P)addition varies,and the underlying mechanisms for the changes in N_(2)O emissions remain unclear.We conducted field studies to examine the response of N_(2)O emissions to N and P addition over two years in three typical alpine grasslands,alpine meadow(AM),alpine steppe(AS),and alpine cultivated grassland(CG)on the Qinghai-Tibet Plateau(QTP).Our results showed consistent increases in N_(2)O emissions under N addition alone or with P addition,and insignificant change in N_(2)O emissions under P addition alone in all three grasslands.N addition increased N_(2)O emissions directly in AM,by lowering soil pH in AS,and by lowering abundance of denitrification genes in CG.N and P co-addition increased N_(2)O emissions in AM and AS but only showed an interactive effect in AM.P addition enhanced the increase in N_(2)O emissions caused by N addition mainly by promoting plant growth in AM.Overall,our results illustrate that short-term P addition cannot alleviate the stimulation of N_(2)O emissions by N deposition in alpine grassland ecosystems,and may even further stimulate N_(2)O emissions.
文摘This study analyzes the influence of green bonds on carbon neutrality.It examines the daily data of sectoral CO_(2) emissions of the top five CO_(2)-emitting nations from January 2,2019 to December 30,2022 using wavelet transform coherence,quantile-onquantile regression,Granger causality in quantiles,and quantile regression approaches.The results revealed that(i)green bonds are strongly related to sectoral CO_(2) emissions;(ii)green bonds reduce transport sector CO_(2) emissions in China,the US,and Japan while causing an upsurge in India and Russia;(iii)green bonds reduce industrial sector CO_(2) emissions only in the US;(iv)green bonds have a declining influence in energy sector CO_(2) emissions at lower quantiles in India,China,and the US,whereas the impact increases at higher quantiles;and(v)green bonds decrease residential sector CO_(2) emissions in the US,Russia,and Japan.The study revealed that green bonds help reduce CO_(2) emissions in the residential sector in various quantiles.Therefore,the US,Russia,and Japan should raise household awareness of green energy utilization by promoting them with green bonds.In addition,green bonds can effectively reduce transportation sector CO_(2) emissions in China and the US.Therefore,the policymakers of the two global powers should contribute to global CO_(2) reduction by promoting green transportation and clean energy transition in the transportation sector through green bonds.Thus,green bonds can play an effective role in the fight against global warming.
基金the Funds for Science and Technology Development of the Ministry of Education and Training,Vietnam(grant number B2023-DNA-21).
文摘The energy sector is pivotal in Vietnam’s commitment to achieving net-zero emissions by 2050.This study employs a combination of Structural Decomposition Analysis(SDA)and decoupling approaches based on data from Vietnam’s energy statistics and the Vietnam Living Standards Survey(VHLSS)for 2016,2018,and 2020.The primary aim is to elucidate the effects of direct energy consumption by household groups on CO_(2)emissions,examine factors affecting emissions,and clarify the relationship between CO_(2)emissions from household energy consumption and economic growth in Vietnam.Research results underscore that household groups make considerable use of electricity and Liquefied Petroleum Gas(LPG),simultaneously reducing the proportion of firewood,rice husk,sawdust,agricultural by-products and other fuels.The decrease in energy intensity emerges as the primary factor in lowering household emissions,while population growth and economic efficiency exert the opposite effect.Additionally,the research reveals disparities in emissions between urban and rural areas,similarly among household groups within the given location.Despite maintaining a robust decoupling status between emissions from household consumption and economic growth,unsustainable risks persist,particularly with the increase in electricity demand.The study also highlights the uneven impact of the COVID-19 epidemic on CO_(2)emissions across household groups.Drawing upon these findings,several recommendations are proposed to control CO_(2)emissions from direct energy household consumption to facilitate the most effective household decarbonisation process while ensuring sustainable economic growth in Vietnam.
基金support of Dean Fund Project of the China National Institute of Standardization[Grant No.572025Y-12477]National Natural Science Foundation of China[Grant No.72204247].
文摘The marginal abatement cost(MAC)of CO_(2)emissions is one of the most critical indicators used to assess energy conservation and emission reduction.Although extensively measured,few studies have incorporated the influence of policy constraints when evaluating MAC.To address this gap,this paper proposes a nonparametric directional distance function approach under policy regulations to estimate the CO_(2)shadow price in the construction industry across 30 Chinese provinces from 2010 to 2017.Based on this enhanced method,four key findings emerge:①the annual CO_(2)shadow price exhibits an overall upward trend during the observation period;②regional shadow prices display marked variation across provinces;③regional heterogeneity in shadow prices has increased steadily over time;and④both urbanization rate and energy consumption per unit of gross domestic product are significantly negatively correlated with the CO_(2)shadow price.Finally,the paper offers several policy recommendations for CO_(2)emissions reduction in the Chinese construction industry at the national,industry,and enterprise levels.
文摘Despite countries having signed agreements and developed policy to reduce CO_(2)emissions,there is disproportionate compliance with the agreements,with developed countries continuing to be the largest emitters.The objective of this study was to compare the impact of South Africa’s population growth,economic growth,and fertilizer consumption on CO_(2)emissions,with those of the US,China,and other BRICS countries.The study used panel data sourced from the World Bank’s World Development Indicators ranging from 1960 to 2023.Results of the fixed effects panel regression show that the coefficient of change for China’s population size(β=9.156,p<0.01)is the highest among the six countries.It is followed by the USA(β=9.156,p<0.05)and South Africa(β=1.474,p<0.01).The effects of GDP for China(β=1.128,p<0.01)on CO_(2)emissions are the largest,followed by South Africa(β=1.098,p<0.01)and the USA in third place(β=0.614,p<0.05).These results show that South Africa is highly reliant on coal-based energy resources.As a policy recommendation,South Africa needs to diversify its energy mix and invest more in renewable energy resources.
文摘To address the global issue of climate change and create focused mitigation plans,accurate CO_(2)emissions forecasting is essential.Using CO_(2)emissions data from 1990 to 2023,this study assesses the predicting performance of five sophisticated models:Random Forest(RF),XGBoost,Support Vector Regression(SVR),Long Short-Term Memory networks(LSTM),and ARIMA To give a thorough evaluation of the models’performance,measures including Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and Mean Absolute Percentage Error(MAPE)are used.To guarantee dependable model implementation,preprocessing procedures are carried out,such as feature engineering and stationarity tests.Machine learning models outperform ARIMA in identifying complex patterns and long-term associations,but ARIMA does better with data that exhibits strong linear trends.These results provide important information about how well the model fits various forecasting scenarios,which helps develop data-driven carbon reduction programs.Predictive modeling should be incorporated into sustainable climate policy to encourage the adoption of low-carbon technologies and proactive decisionmaking.Achieving long-term environmental sustainability requires strengthening carbon trading systems,encouraging clean energy investments,and enacting stronger emission laws.In line with international climate goals,suggestions for lowering CO_(2)emissions include switching to renewable energy,increasing energy efficiency,and putting afforestation initiatives into action.
基金supported by Major programs of humanities and social science base,Ministry of Education[grant number10JJD630011]
文摘Establishing positive and urgent targets for CO_2 reduction and emission peak,and promoting energy conservation and energy structure adjustment are among the strategies to address global climate change and CO_2 emissions reduction.They are also means to break through the constraints of domestic resources and environment,and internal needs,to achieve sustainable development.Generally speaking,a country's CO_2 emission peak appears after achieving urbanization and industrialization.By then,connotative economic growth will appear,GDP will grow slowly,energy consumption elasticity will decrease,and energy consumption growth will slow down-dependent mainly on new and renewable energies.Fossil fuel consumption will not increase further.When CO_2 emission reaches its peak,the annual reduction rate of CO_2 intensity of GDP is greater than GDP annual growth rate;and the annual reduction rate of CO_2 intensity of energy use is greater than the annual growth rate of energy consumption.Therefore,three important approaches to promotion of CO_2 emission peak can be concluded:maintaining reasonable control of GDP growth,strengthening energy conservation to significantly reduce the GDP energy intensity,and optimizing the energy mix to reduce the CO_2 intensity of energy use.By around 2030,China will basically have completed its rapid development phase of industrialization and urbanization.Connotative economic growth will appear with the acceleration of industrial structure adjustment The target of GDP energy intensity will still be to maintain an average annual reduction of 3%or higher.The proportion of non-fossil fuels will reach 20-25%,and the aim will be to maintain an average annual growth rate of 6-8%.The total annual energy demand growth of 1.5%will be satisfied by the newly increased supply of non-fossil fuels.The annual decline in CO_2 intensity of GDP will reach 4.5%or higher,which is compatible with an average annual GDP growth rate of approximately 4.5%in order to reach CO_2 emission peak.This corresponds to the level of China's potential economic growth.Achieving CO_2 emission peak will not impose a rigid constraint on economic development,but rather promote economic development and accelerate the transformation of green,low-carbon development.The CO_2 emission peak can be controlled with a cap of 11 billion tons,which means that CO_2 emission will increase by less than 50%compared with 2010.The per capita emission peak will be controlled at a level of less than 8 tons,which is lower than the 9.5 tons in the EU and Japan and much lower than the 20 tons in the US,future economic and social development faces many uncertainties in achieving the CO_2 emission peak discussed above.It depends on current and future strategies and policies,as well as the pace and strength of economic transformation,innovation,and new energy technologies.If the economic transformation pattern fails to meet expectations,the time required to reach CO_2emission peak would be delayed and the peak level would be higher than expected.Therefore,we need to coordinate thoughts and ideas and deploy these in advance;to highlight the strategic position of low-carbon development and its priorities;to enact mid-to long-term energy development strategies;and to establish and improve a system of laws,regulations,and policies as well as an implementation mechanism for green,low-carbon development Oriented by positive and urgent CO_2 reduction and peak targets,the government would form a reversed mechanism to promote economic transformation and embark on the path of green,low-carbon development as soon as possible.
