Abstract Understanding the risks posed to humankind, the environment, and overall growth requires a deep exploration of the profound impact of greenhouse gas (GHG) emissions, especially carbon dioxide (CO 2 ), on global climate change. This study explores the complex relationships among economic extension, energy utilization, financial progress, natural resource rents, and CO 2 emissions in Bangladesh. By analyzing annual data from 1974 to 2022, our analysis reveals a long-term connection between the variables, as evidenced by the autoregressive distributed lag (ARDL) bounds test. We found that for every 1% rise in economic growth, energy use, financial progress, and natural resource rents, CO 2 emissions rise by 0.13%, 1.50%, 0.39%, and 0.04%, respectively. This is based on the dynamic ordinary least squares (DOLS) method. The outcomes are further supported by the canonical cointegrating regression (CCR), followed by fully modified ordinary least squares (FMOLS). By illuminating the causes of Bangladesh's environmental degradation, this study offers actionable policy suggestions aimed at fostering sustainable growth and enforcing strict regulations that effectively mitigate environmental harm. Graphical Abstract

Asif Raihan

Junaid Rahman

Tipon Tanchangya

Mohammad Ridwan

A. B. M. Mainul Bari

Carbon Research

Influences of economy, energy, finance, and natural resources on carbon emissions in Bangladesh

经济、能源、金融和自然资源对孟加拉国碳排放的影响

Abstract Forest ecosystems play a crucial role in regulating greenhouse gas (GHG) emissions and mitigating climate change. This research aimed to evaluate the GHG emissions of various sources within forested ecosystems and assess their respective contributions to global warming potential (GWP), vital for developing more targeted strategies to mitigate climate change, shaping climate policies, carbon accounting, sustainable forest management, and advancing scientific comprehension of ecosystem-climate dynamics. The study comprehensively analysed carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) emissions EDGAR data of deforestation, fires, and natural processes such as organic soil decomposition within forested ecosystems. The assessment quantified the CO 2 equivalent emissions for each category from 1990 to 2022 and forecasted till 2030. Our forecast shows that CO 2 emissions from deforestation could reach between 3,990 and 4,529 metric ton (Mt) by 2030, with forest fires contributing an additional 750 Mt. Forestland CO 2 absorption is expected to decline to -5134.80 Mt by 2030. There is uncertainty surrounding the forecasts for Organic soil CO 2 (829.78 Mt) and Other land CO 2 (-764.53 Mt). In addition, deforestation was a significant contributor to CO 2 emissions, with a GWP ranging from 4000 to 4500, highlighting the complex interplay between natural processes and human activities in shaping atmospheric warming patterns. Additionally, forest fires emit a complex mix of GHGs. The potency of these gases in warming the planet varies considerably, with CH 4 exhibiting a GWP range of 500 to 700 Mt CO 2 equivalent, and CO 2 ranging from 900 and 1350 Mt. These variations depend on fire intensity and its overall impact on the climate system. Forestland acts as powerful carbon sink, capturing atmospheric CO 2 with negative GWP values between -7000 and -6000. Researchers suggest a multifaceted strategy such as stricter enforcement of sustainable forestry regulations, investing in projects that promote carbon sequestration, and reforestation. Additionally, advancements in drone technology, satellite imagery, remote sensing and advanced data analytics can aid in detecting and mitigating climate change impacts, ultimately paving the way for carbon neutrality. Graphical Abstract

Mohammad Fazle Rabbi

Sándor Kovács

Quantifying global warming potential variations from greenhouse gas emission sources in forest ecosystems

量化森林生态系统中温室气体排放源的全球变暖潜力变化

Abstract Carbon dioxide (CO 2 ), whose atmospheric volume has been increasing, is the principal greenhouse gas (GHG) that causes global warming and climate change. Climate change from increasing greenhouse gases (GHGs) has broad health and environmental influences. Human-emitted GHGs constitute a significant cause of global warming. The main objective of this article is to assess the influence of technological innovation, economic growth, fossil energy use, renewable energy consumption, and globalisation on CO 2 emissions (CO 2 Es) in South Africa over the observation period 1990–2020. The Dynamic Ordinary Least Squares (DOLS) estimator was implemented to examine the relationship between the constituents. The study results indicate that economic growth, fossil energy use, technological innovation, and globalisation boost CO 2 Es, whereas renewable energy consumption reduces CO 2 Es. The output of the canonical cointegrating regression and fully modified least squares estimators also supports the output of the DOLS estimator. We concluded that, in South Africa, a rise in economic growth, fossil energy use, technological innovation, and globalisation results in an upsurge in CO 2 Es. In contrast, an increase in renewable energy consumption leads to a reduction in CO 2 Es. This research work contributes to the discourse on CO 2 Es in the South African context. The study recommends that policymakers in South Africa should design policies that foster the formation of a low-carbon country, the consumption of renewable energy, and the implementation of environment-friendly technological innovations that reduce the use of fossil energy. Graphical Abstract

Frank Ranganai Matenda

Helper Zhou

Mabutho Sibanda

The influence of economic growth, fossil and renewable energy, technological innovation, and globalisation on carbon dioxide emissions in South Africa

经济增长、化石和可再生能源、技术创新及全球化对南非二氧化碳排放的影响

Abstract Biochar application to soil is a potential climate change mitigation strategy. In addition to long-term sequestration of the carbon content of the biochar itself, its application may reduce the emissions of other greenhouse gases (GHGs) from the soil. However, the reported effects of biochar application on soil GHG fluxes exhibit inconsistent results. Prediction of such effects is an important gap that needs to be addressed in biochar research. In this study, rule-based machine learning models were developed based on rough-set theory. Data from the literature were used to generate the rules for predicting the effects of biochar application on soil GHG (CO 2 , N 2 O, and CH 4 ) fluxes. Four rule-based models for CO 2 fluxes, two rule-based models for N 2 O fluxes, and three rule-based models for CH 4 fluxes were developed. The validity of these models was assessed based on both statistical measures and mechanistic plausibility. The final rule-based models can guide the prediction of changes in soil GHG fluxes due to biochar application, and thus serve as a decision-support tool to maximize the benefits of biochar application as a negative emission technology (NET). In particular, mechanistically plausible rules were identified that predict triggers for GHG fluxes that can offset carbon sequestration gains. This knowledge allows biochar application to be calibrated to local conditions for maximum efficacy. Graphical Abstract

Beatriz A. Belmonte

Jesus Gabriel A. Flores

Cristine L. Mestizo

Patricia Nicole B. Rafer

Michael Francis D. Benjamin

Kathleen B. Aviso

Raymond R. Tan

A rough set-based model for predicting soil greenhouse gases response to biochar

基于粗糙集模型的生物炭对土壤温室气体响应预测

Abstract China is one of the largest contributors to global greenhouse gas (GHG) emissions, and the livestock sector is a major source of non-CO 2 GHG emissions. Mitigation of GHG emissions from the livestock sector is beneficial to the sustainable development of the livestock sector in China. This study investigated the provincial level of GHG emissions from the livestock sector between 2000 and 2020 in China, to determine the driving factors affecting the provincial-level GHG emissions from the livestock sector, based on the logarithmic mean Divisia index (LMDI) model, which took into account of technological progress, livestock structure, economic factor, and agricultural population. Moreover, a gray model GM (1, 1) was used to predict livestock GHG emissions in each province until 2030 in China. The results showed that the GHG of Chinese livestock sector was decreased from 195.1 million tons (MT) CO 2 e in 2000 to 157.2 MT CO 2 e in 2020. Henan, Shandong, and Hebei provinces were the main contributors to the reduction in Chinese livestock GHG emissions, with their livestock GHG emissions reduced by 60.1%, 53.5% and 45.5%, respectively, in 2020 as compared to 2000. The reduction in GHG emissions from the Chinese livestock sector can be attributed to two main factors: technological progress and the shrinking of the agricultural laborers. In contrast, the agricultural economic development model with high input and high emissions showed a negative impact on GHG emission reduction in China’s livestock sector. Furthermore, the different livestock structure in each province led to different GHG reduction effects on the livestock sector. Under the gray model GM (1,1), the GHG emissions of the livestock sector will be reduced by 33.7% in 2030 as compared with 2020 in China, and the efficiency factor will account for 76.6% of the positive effect of GHG reduction in 2030. The eastern coastal region will be the main contributor to the reduction of GHG emissions from the Chinese livestock sector in 2030. Moreover, recommendations (such as upgrading livestock management methods and promoting carbon emission mitigation industries) should be proposed for the environmentally sustainable development of the livestock sector in the future.

Yulong Chen

Le Qi

Hafiz Athar Hussain

Greenhouse gas emissions from Chinese livestock sector can be decreased by one third in 2030 by the improvement in management

中国畜牧业温室气体排放量可通过管理改善在2030年减少三分之一

Abstract The components and sources of dissolved organic matter (DOM) in urban water bodies are extremely complicated due to multiple environmental and anthropogenic factors. The comprehensive analysis of the DOM molecular composition is crucial for deep understanding their reactivities, environmental behaviors, and fates in aquatic ecosystems, thereby improving our ability to monitor and protect aquatic systems. In this study, ultraviolet–visible spectroscopy (UV–Vis) and excitation-emission matrix fluorescence spectroscopy (EEM) were combined with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to investigate the optical and molecular characteristics of DOM in the Yongding River (YDH) and Beiyun River (BYH), two typical urban rivers with distinct landscapes and anthropogenic influences in Beijing, China. Results showed that DOM in BYH was mainly composed of proteins from microbial and sewage sources with low aromaticity, molecular weight, and abundant saturated labile compounds, along with a significant presence of anthropogenic surfactants. Whereas the YDH was primarily composed of humic substances from plant- and soil-derived terrestrials, with higher aromaticity humification, unsaturation and refractory compounds. In addition, due to the accumulation of refractory compounds, the concentration of DOC and the degree of organic pollution increased from upstream to downstream of the rivers, manifested as an increase in humification and molecular weight at the molecular level. Our results confirmed that landscape urbanization broadly modified the structure of DOM to be more aliphatic and saturated. The findings of this study will provide important insights into the chemdiverse molecular composition of DOM undergoing different influences from human activities and provide significant guidance for water quality management in urban river ecosystems. Graphical Abstract

Yi Ren

Shasha Liu

Leizhen Liu

Chengyu Suo

Rui Fu

Yuxin Zhang

Yue Qiu

Fengchang Wu

Deciphering the molecular composition and sources of dissolved organic matter in urban rivers based on optical spectroscopy and FT-ICR-MS analyses

基于光学光谱和FT-ICR-MS分析解析城市河流中溶解有机质的分子组成和来源

Abstract Monoculture cultivation patterns in agro-ecosystems only provide less varied soil organic matter (SOM) molecules of plant origin. Whether and how the natural fallow stage between cultivation seasons facilitates the restoration of SOM molecular diversity and mitigates the adverse impacts of constant cropping pattern is elusive. Here, we utilized FT-ICR-MS, UHPLC-MS/MS, and high-throughput sequencing to investigate the biological change processes in SOM molecular composition under cultivation and fallow status in a long-farmed paddy field. Our study showed that SOM molecular diversity increased by 45.70%–85.36% in fallow stage compared to rice cultivation season. SOM molecular diversity was positively correlated with bacterial diversity and root exudate molecular diversity, and negatively correlated with fungal diversity. Notably, root exudate molecular diversity accounted for 48.48% of the variation in SOM molecular diversity. The increased SOM molecular diversity in fallow stage was attributed more to the diverse plant-produced molecules than the microbe-consumed molecules. Plant species turnover resulted in the conversion of root exudate components to Organoheterocyclic compounds and Organic acids/derivatives from rice planting stage to fallow stage. Recruited microbes were dominated by Basidiomycita , Ascomycot a, Acidobacteria , Chloroflexi and Proteobacteria , resulting in the transformation from carbohydrates, lipid-like SOM molecules to lipid-like and lignin-like SOM molecules. Both field and microcosm experiments confirmed that root exudates are the main source of SOM molecules, and are influenced by the soil microbial community. This study provides solid evidence that fallow status in agro-ecosystems provides explosion of biodiversity and counteracts the negative effects of long-term monoculture cultivation on SOM diversity. Graphical Abstract

Guozhen Gao

Pengfa Li

Ming Liu

Jian Cui

Meng Wu

Zhongpei Li

Diverse biological communities promote SOM molecular diversity and compositional transformations during natural fallow stage in paddy fields

多样化的生物群落促进水稻田自然休闲期土壤有机质分子多样性和组成转化

Abstract Forest soils store substantial amounts of carbon in various soil organic matter (SOM) components due to high plant litter inputs and active microbial turnover. However, the variations in plant- and microbial-derived SOM components in surface and subsurface forest soils across a wide geographic scale remain poorly understood. This study investigated the SOM components from aboveground and belowground plant inputs and fungal and bacterial necromass in surface (soil 0–5 cm ) and subsurface (soil 5–10 cm ) soils across 32 forest sites in China and analyzed their relationships with climate and edaphic factors. Compared to soil 0–5 cm , soil 5–10 cm exhibited lower soil organic carbon content and cutin biomarker concentration but higher concentrations of fungal necromass carbon and lignin phenols. Higher mean annual precipitation led to higher concentrations of cutin and suberin biomarkers in soil 0–5 cm and soil 5–10 cm , respectively. Higher soil organic carbon content was associated with lower plant-derived lignin biomarkers, higher lignin oxidation degrees, and increased microbial necromass-derived amino sugars across sites, highlighting the pivotal role of microbial necromass in SOM stabilization. Additionally, both fungal and bacterial necromass decreased with increasing mineral weathering across sites. These insights improve the understanding of environmental drivers of source-specific carbon storage in forest soils. Graphical Abstract

Guodong Sun

Mengke Wang

Qiang Zhang

Yinghui Wang

Yuanxi Yang

Shan Xu

Junjian Wang

Variations in source-specific soil organic matter components across 32 forest sites in China

中国32个森林站点土壤有机质组分来源的变异

Abstract Oxytetracycline (OTC) and ciprofloxacin (CIP) contamination have caused serious risks to human health, and modified biochar is considered as a potential adsorbent for their removal. The typical agricultural waste of cotton husk was used as the feedstock, then was combined with γ-Fe 2 O 3 and ball milling to innovatively synthesize nano zero-valent iron (nZVI) supporting magnetic cotton hush-derived biochar (Fe 2 O 3 @BMBC) by reductive calcination. Fe 2 O 3 @BMBC performed excellent adsorption performance with a maximum adsorption capacity for OTC (266.7 mg · g −1 ) and CIP (83.36 mg · g −1 ), and its adsorption capacity was 1.6 and 2.3 times that of cotton husk biochar (BC). Characterization analysis showed that Fe 2 O 3 @BMBC contained abundant oxygenated functional groups (e.g., -OH, C = O and Fe–O) and its surface was covered by diverse iron oxides. The high magnetization sensitivity of Fe 2 O 3 @BMBC guaranteed that it was easily to be separated by a magnet. Oxygenated functional groups (e.g., -OH, C = O and Fe–O) participated in the adsorption process, and solution pH significantly affected the adsorption behaviour, and pseudo-second-order model and Freundlich model better fitting the kinetics and isotherms data. These results confirmed that π-π conjugation, H-bonding, Fe–O complexation and electrostatic interactions contributed to the greater adsorption capacity of Fe 2 O 3 @BMBC. Ethanol + ultrasound could efficiently regenerate the used Fe 2 O 3 @BMBC and maintain its sustainable adsorption performance for OTC and CIP. Additionally, Fe 2 O 3 @BMBC performed a good environmental security in a wide pH range (from 3 to 11) in view of the low leaching risk of Fe. Graphical Abstract

Chen Chen

Fengxia Yang

Yongfei Ma

Lihong Dai

Zulin Zhang

Haixin Guo

Yongzhen Ding

Ball milling boosted magnetic cotton husk-derived biochar adsorptive removal of oxytetracycline and ciprofloxacin from water

球磨增强磁性棉秆生物炭对水中土霉素和环丙沙星的吸附去除

Emerging energy storage devices are vital approaches towards peak carbon dioxide emissions. Zinc-ion energy storage devices (ZESDs), including zinc ion capacitors and zinc ion batteries, are being intensely pursued due to their abundant resources, economic effectiveness, high safety, and environmental friendliness. Carbon materials play their important role in the development of ZESDs, from cathode, electrolyte, to metallic Zn anode. Though thrilling development has been achieved in ZESDs, they still face the challenges of unsatisfactory capacity and kinetics for cathode, and irreversibility and low utilization rate of Zn anode. Hence, the roles of carbon materials in ZESDs are systematically discussed, starting with investigating carbons with different dimensions as cathodes and the corresponding strategies to improve their performance. Also, carbons as coatings or skeletons for other types of cathode materials are introduced. Besides, the functions of carbons in electrolyte development are explored. Further, the influence of carbon materials on Zn anode is elucidated with the corresponding operational mechanisms. Finally, an outlook for carbon materials in ZESDs is provided. We envision the presented minireview can pay way on exploring novel carbon research towards next-generation energy storage technologies.

Yujiao Yang

Yiyang Xiao

Xiaoxin Nie

Meng Yao

Hanfeng Liang

Du Yuan

Carbon Res.

Carbon materials in current zinc ion energy storage devices towards sustainability

碳材料在当前锌离子储能装置中向可持续发展的应用

期刊	Carbon Research
ISSN	2731-6696
h-index	17