From black to green: Quantifying the impact of economic growth, resource management, and green technologies on CO2 emissions

In an exploration of environmental concerns, this groundbreaking research delves into the relationship between GDP per capita, coal rents, forest rents, mineral rents, oil rents, natural gas rents, fossil fuels, renewables, environmental tax and environment-related technologies on CO2 emissions in 30 highly emitting countries from 1995 to 2021 using instrumental-variables regression Two-Stage least squares (IV-2SLS) regression and two-step system generalized method of moments (GMM) estimates. Our results indicate a significant positive relationship between economic growth and CO2 emissions across all quantiles, showcasing an EKC with diminishing marginal effects. Coal rents exhibit a statistically significant negative relationship with emissions, particularly in higher quantiles, and mineral rents show a negative association with CO2 emissions in lower and middle quantiles, reinforcing the idea of resource management in emissions reduction. Fossil fuels exert a considerable adverse impact on emissions, with a rising effect in progressive quantiles. Conversely, renewable energy significantly curtails CO2 emissions, with higher impacts in lower quantiles. Environmental tax also mitigates CO2 emissions. Environment-related technologies play a pivotal role in emission reduction, particularly in lower and middle quantiles, emphasizing the need for innovative solutions. These findings provide valuable insights for policymakers, highlighting the importance of tailoring interventions to different emission levels and leveraging diverse strategies for sustainable development.

Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models

Consistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR; (ii) energy transition curbs CO2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO2 emissions in industrial and power sectors; (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO2 emissions in all sectors except for transport across various quantiles as time passes; (iv) the results differ according to the aggregated and disaggregated levels; (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA.

Unleashing sustainability in uncertain times: Can we leverage economic complexity, uncertainty, and remittances to combat environmental degradation?

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO2) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation.

A factorial-analysis-based Bayesian neural network method for quantifying China's CO2 emissions under dual-carbon target

Energy-structure transformation and CO2-emission reduction are becoming particularly urgent for China and many other countries. Development of effective methods that are capable of quantifying and predicting CO2 emissions to achieve carbon neutrality is desired. This study advances a factorial-analysis-based Bayesian neural network (abbreviated as FABNN) method to reflect the complex relationship between inputs and outputs as well as reveal the individual and interactive effects of multiple factors affecting CO2 emissions. FABNN is then applied to analyzing CO2 emissions of China (abbreviated as CEC), where multiple factors involve in energy (e.g., the consumption of natural gas, CONG), economic (e.g., Gross domestic product, GDP) and social (e.g., the rate of urbanization, ROU) aspects are investigated and 512 scenarios are designed to achieve the national dual carbon targets (i.e., carbon peak before 2030 and carbon neutrality by 2060). Comparing to the conventional machine learning methods, FABNN performs better in calibration and validation results, indicating that FABNN is suitable for CEC simulation and prediction. Results disclose that the top three factors affecting CEC under the dual‑carbon target are GDP, CONG, and ROU; energy, economic and social contributions are 43.5 %, 34.6 % and 21.9 %, respectively. CEC reaches its carbon peak during 2027-2032 and achieve carbon neutrality during 2053-2057 under all scenarios. Under the optimal scenario (S195), the CO2-emission reduction potential is about 772.2 million tonnes and the consumptions of coal, petroleum and natural gas can be respectively reduced by 3.1 %, 9.9 % and 23.0 % compared to the worst scenario (S466). The results can provide solid support for national energy-structure transformation and CO2-emission reduction to achieve carbon-peak and carbon-neutrality targets.

Effects of polypropylene microplastics on carbon dioxide dynamics in intertidal mangrove sediments

Microplastics (MPs) in soil can influence CO2 dynamics by altering organic carbon (OC) and microbial composition. Nevertheless, the fluctuation of CO2 response attributed to MPs in mangrove sediments is unclear. This study explores the impact of micro-sized polypropylene (mPP) particles on the carbon dynamics of intertidal mangrove sediments. In the high-tide level sediment, after 28 days, the cumulative CO2 levels for varying mPP dosages were as follows: 496.86 ± 2.07, 430.38 ± 3.84 and 447.09 ± 1.72 mg kg-1 for 0.1%, 1% and 10% (w/w) mPP, respectively. The CO2 emissions were found to be increased with a 0.1% (w/w) mPP level and decreased with 1% and 10% (w/w) mPP at high-tide level sediment, suggesting a tide level-specific dose dependence of the CO2 emission pattern in mangrove sediments. Overall, results indicated that the presence of mPP in mangrove sediments would potentially affect intertidal total CO2 storage under given experimental conditions.

The climate impacts and potential benefits of services export growth in developing countries

Promoting the services trade is considered an effective means of revitalizing the economy at a marginal environmental cost in the post-pandemic era. However, the impact of services trade growth and how to promote services development remain to be addressed. This study investigates the performance of the services trade for both developed and developing countries as well as the impact of their services trade growth on the Paris Agreement climate target and the possible synergy for achieving the Sustainable Development Goals (SDGs). Moreover, policy recommendations are provided for developing countries to facilitate services trade growth. Input-output analysis, comparative advantage theory, and the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC) are used in this study. The results show that services trade accounted for 44.4 % of global trade-induced value added but only 14.7 % of CO2 emissions. Services trade growth would lead to 199.8 Mt and 311.2 Mt CO2 emissions under the ServGrow scenario and DoubDeve scenario, respectively, suggesting that vigorously promoting services exports growth of developing countries has limited carbon implications. Further simulation indicates that the global atmospheric temperature increase caused by services trade growth in both scenarios is within 0.05 °C. Notably, accelerating services exports growth in developing countries helps to mitigate the inequality between developed and developing countries. The findings of this study can inform policymakers regarding the formulation and implementation of policies for economic recovery, reducing inequality, addressing climate change, and contributing to the achievement of the SDGs.

Improved estimation of CO2 emissions from thermal power plants based on OCO-2 XCO2 retrieval using inline plume simulation

CO2 emissions from power plants are the dominant source of global CO2 emissions, thus in the context of global warming, accurate estimation of CO2 emissions from power plants is essential for the effective control of carbon emissions. Based on the XCO2 retrievals from the Orbiting Carbon Observatory 2 (OCO-2) and the Gaussian Plume Model (GPM), a series of studies have been carried out to estimate CO2 emission from power plants. However, the GPM is an ideal model, and there are a number of assumptions that need to be made when using this model, resulting in large uncertainties in the inverted emissions. Here, based on 6 cases of power plant plumes observed by the OCO-2 satellite over the Yangtze River Delta, China, we use an inline plume rise module coupled in the Community Multi-scale Air Quality model (CMAQ) to simulate the plumes and invert the emissions, and compare the simulated plumes and inverted emissions using the GPM model. We found that CO2 emissions can be significantly overestimated or underestimated based on the GPM simulations, and that the CMAQ inline plume simulation could significantly improve the estimates. However, the simulation bias in wind speed can significantly affect the inversion results. These results indicate that accurate meteorological field and plume simulations are critical for future inversion of point source emissions.

Downed woody debris carbon emissions in a European temperate virgin forest as driven by species, decay classes, diameter and microclimate

Downed woody debris (DWD) plays an important role as regulator of nutrient and carbon (C) cycling in forests, accounting for up to the 20 % of the total C stocks in primary forests. DWD persistence is highly influenced by microbial decomposition, which is determined by various environmental factors, including fluctuations in temperature and moisture, as well as in intrinsic DWD properties determined by species, diameter, or decay classes (DCs). The relative importance of these different drivers, as well as their interactions, remains largely unknown. Moreover, the importance of DWD for C cycling in virgin forests remains poorly understood, due to their scarcity and poor accessibility. To address this research gap, we conducted a study on DWD respiration (RDWD), in a temperate virgin forest dominated by European beech and silver fir. Our investigation analysed the correlation between RDWD of these two dominant tree species and the seasonal changes in climate (temperature and moisture), considering other intrinsic DWD traits such as DCs (1, 2 and 4) and diameters (1, 10 and 25 cm). As anticipated, RDWD (normalized per gram of dry DWD) increased with air temperature. Surprisingly, DWD diameter also had a strong positive correlation with RDWD. Nonetheless, the sensitivity to both variables and other intrinsic traits (DC and density) was greatly modulated by the species. On the contrary, water content, which exhibited a considerable spatial variation, had an overall negative effect on RDWD. Virgin forests are generally seen as ineffective C sinks due to their lack of net productivity and high respiration and nutrient turnover. However, the rates of RDWD in this virgin forest were significantly lower than those previously estimated for managed forests. This suggests that DWD in virgin forests may be buffering forest CO2 emissions to the atmosphere more than previously thought.

Clinical Medicine and Climate Change

The health care system contributes substantially to global greenhouse gas emissions, a driver of climate change. At the same time, climate change has caused disruptions in health care delivery. In this article, the authors describe both how the health care industry contributes to climate change and how climate change affects patient care. The authors also provide clinical recommendations for health care practitioners to counsel patients on health effects of climate change and underscore the need for developing the workforce needed to respond to unique health care delivery challenges resulting from climate-related factors.

Spatial distribution of degradation and deforestation of palm swamp peatlands and associated carbon emissions in the Peruvian Amazon

The vast peat deposits in the Peruvian Amazon are crucial to the global climate. Palm swamp, the most extensive regional peatland ecosystem faces different threats, including deforestation and degradation due to felling of the dominant palm Mauritia flexuosa for fruit harvesting. While these activities convert this natural C sink into a source, the distribution of degradation and deforestation in this ecosystem and related C emissions remain unstudied. We used remote sensing data from Landsat, ALOS-PALSAR, and NASA's GEDI spaceborne LiDAR-derived products to map palm swamp degradation and deforestation within a 28 Mha area of the lowland Peruvian Amazon in 1990-2007 and 2007-2018. We combined this information with a regional peat map, C stock density data and peat emission factors to determine (1) peatland C stocks of peat-forming ecosystems (palm swamp, herbaceous swamp, pole forest), and (2) areas of palm swamp peatland degradation and deforestation and associated C emissions. In the 6.9 ± 0.1 Mha of predicted peat-forming ecosystems within the larger 28 Mha study area, 73% overlaid peat (5.1 ± 0.9 Mha) and stored 3.88 ± 0.12 Pg C. Degradation and deforestation in palm swamp peatlands totaled 535,423 ± 8,419 ha over 1990-2018, with a pronounced dominance for degradation (85%). The degradation rate increased 15% from 15,400 ha y-1 (1990-2007) to 17,650 ha y-1 (2007-2018) and the deforestation rate more than doubled from 1,900 ha y-1 to 4,200 ha y-1. Over 1990-2018, emissions from degradation amounted to 26.3 ± 3.5 Tg C and emissions from deforestation were 12.9 ± 0.5 Tg C. The 2007-2018 emission rate from both biomass and peat loss of 1.9 Tg C yr-1 is four times the average biomass loss rate due to gross deforestation in 2010-2019 reported for the hydromorphic Peruvian Amazon. The magnitude of emissions calls for the country to account for deforestation and degradation of peatlands in national reporting.

The impact of economic development of primary and secondary industries on national CO2 emissions: The case of Russian regions

In today's world, where economic development and environmental sustainability are becoming increasingly important aspects of national strategy, attention to the impact of different economic sectors on climate change is becoming an integral part of scientific research. This article focuses on analyzing the impact of primary and secondary economic sectors development on carbon dioxide (CO2) emissions at the sub-national level in Russia from 2005 to 2019. The aim of the study is to provide an in-depth understanding of the relationships between the dynamics of these sectors and CO2 emission levels in different regions of the country. Weighted regression and panel data methods were applied to better identify the patterns of the impact. The results show that the size of population and electricity consumption have the highest impact on CO2 emissions. So that, the expansion of nuclear and gas generation capacity, as well as significant improvement of energy efficiency, are of crucial importance to reduce the emissions. Other sectors have a heterogeneous impact and requires more differential approaches, considering the specifics of regions. Taking into account the significant differences between the Russian constituent entities, this paper emphasizes the low informativeness of assessments at the national level and their inadequacy in terms of improving the efficiency of domestic management, including decarbonization policies.

Toward a low carbon path: Do E-commerce reduce CO2 emissions? Evidence from China

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality.

A review of low-carbon technologies and projects for the global cement industry

Carbon dioxide (CO2) emissions from the cement industry account for 26% of the total industrial emissions, and the need to develop low-carbon techniques within the cement industry is extremely urgent. Low-carbon projects and technologies for the cement industry in different regions and countries have been thoroughly reviewed in this manuscript, and the low-carbon development concept for each county has been analyzed. For developing countries such as China and India, energy saving and efficiency enhancement are currently the key points, while for developed countries and regions such as Europe, more efforts have been focused on carbon capture, utilization, and storage (CCUS). Global CCUS projects have been previously conducted, and the majority of CCUS projects are currently performed in Europe where major projects such as the CEMCAP, CLEANKER, and IEILAC projects represent the latest research progress in cement production technologies and low-carbon technologies for the global cement industry. The development of low-carbon cement technologies has changed from focusing on the end point to instead focusing on the source and process through the exploration of hydrogen and solar energies, and more disruptive and original technologies are expected to be developed, particularly in the cement industry in China.

Asymmetric trade barriers and CO2 emissions in carbon-intensive industry

Since large carbon emissions are transferred through international trade, it is vital to explore the role country-specific trade policy has on carbon-intensive industries. The present study contributes to a deeper understanding of the connection between trade and environment in the literature, especially the impacts of trade barriers on carbon emissions. This topic has received little attention despite the importance of trade barriers to climate change and carbon emissions. Thus, we investigate the asymmetric trade barriers in carbon-intensive industries across different countries and describe the facts and motivations of these trade barriers in carbon-intensive industries. We list some political and trade explanations for the existence of trade barriers and empirically test the impacts of interest groups on trade barriers by the IV-2SLS method. Further, we have observed that certain highly developed countries, including Belgium, Switzerland, and Japan, are providing a notable implicit subsidy valued at over 200 USD per ton for carbon-intensive imported products. Our work carries essential implications for understanding how the manipulation of trade barriers could cause impacts on the environment.

Coordinated effect of green expansion and carbon reduction: Evidence from sustainable development of resource-based cities in China

Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction.

Tidal effects on carbon dioxide emission dynamics in intertidal wetland sediments

Understanding the control mechanisms of carbon dioxide (CO2) emissions in intertidal wetland sediments is beneficial for the concern of global carbon biogeochemistry and climate change. Nevertheless, multiple controls on CO2 emissions from intertidal wetland sediments to the atmosphere still need to be clarified. This study investigated the effect of tidal action on CO2 emissions from salt marsh sediments covered by Spartina alterniflora in the Jiaozhou Bay wetland using the static chamber method combined with an infrared CO2 detector. The results showed that the CO2 emission fluxes from the sediment during ebb tides were higher than those during flood tides. The whole wetland sediment acted as a weak source of atmospheric CO2 (average flux: 24.44 ± 16.80 mg C m-2 h-1) compared to terrestrial soils and was affected by the cycle of seawater inundation and exposure. The tidal influence on vertical dissolved inorganic carbon (DIC) transport in the sediment was also quantitated using a two-end member mixing model. The surface sediment layer (5-15 cm) with maximum DIC concentration during ebb tides became the one with minimum DIC concentration during flood tides, indicating the DIC transport from the surface sediment to seawater. Furthermore, aerobic respiration by microorganisms was the primary process of CO2 production in the sediment according to 16 S rDNA sequencing analysis. This study revealed the strong impact of tidal action on CO2 emissions from the wetland sediment and provided insights into the source-sink pattern of CO2 and DIC at the land-ocean interface.

Mapping high-resolution energy consumption CO2 emissions in China by integrating nighttime lights and point source locations

High-resolution CO2 emission inventories are essential to accurately assess spatiotemporal patterns of carbon emissions, analyze factors affecting carbon emissions, and develop sound emission reduction policies. The top-down approach is often used to map CO2 emissions from energy consumption due to its simplicity. However, the spatial proxy variables commonly used in this method, such as nighttime light (NL), land use, and population, are difficult to reflect the spatial distribution of CO2 emissions from large point sources. Therefore, this study uses the active fire product provided by Visible Infrared Imaging Radiometer Suite (VIIRS) sensors on Suomi National Polar-Orbiting Partnership (Suomi-NPP) satellite to extract the location of industrial heat sources in China, and then develops an improved CO2 emission estimation model by integrating industrial heat sources, Global Energy Monitor (GEM) power plant location and nighttime lights. The model is used to map CO2 emissions from energy consumption at a resolution of 1 km*1 km from 2012 to 2019 in China. It is found that the overall accuracy of the model is greatly improved at the provincial level, the R2 value is >0.75, and RMSE is distributed in 40-110 Mt. At the grid level, the improved model allocates more carbon emissions to the grid where the point source is located, which makes the spatial distribution of CO2 emissions more reasonable.

How climate change may shift power demand in Japan: Insights from data-driven analysis

The impact of climate change on power demand in Japan and its related CO2 emissions is a matter of concern for the Japanese authorities and power companies as it may have consequences on the power grid, but is also of global importance as Japan is a significant contributor to global greenhouse gas emissions. In this study, we trained random forest models against daily power data in ten Japanese regions and for different types of power generation to project changes in future power production and its carbon intensity. We used climate variables, heat stress indices, and one variable for the level of human activities. We then used the models trained from the present-day period to estimate the future power demand, carbon intensity, and pertaining CO2 emissions over the period 2020-2100 under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP126, SSP370, and SSP585). The impact of climate change on CO2 emissions via power generation shows seasonal and regional disparities. In cold regions, a decrease in power demand during winter under future warming leads to an overall decrease in power demand over the year. In contrast, the decrease in winter power demand in hot regions can be overcompensated by an increase in summer power demand due to more frequent hot days, resulting in an overall annual increase. From our regional models, power demand is projected to increase the most in most Japanese regions in May, June, September, and October rather than in the middle of summer, as found in previous studies. This increase could result in regular power outages during those months as the power grid could become particularly tense. Overall, we observed that power demand in regions with extreme climates is more sensitive to global warming than in temperate regions. The impact of climate change on power demand induces a net annual decrease in CO2 emissions in all regions except for Okinawa, in which power demand strongly increases during the summer, resulting in a net annual increase in CO2 emissions. However, climate change's impact on carbon intensity may reverse the trend in some regions (Shikoku, Tohoku). Additionally, we assessed the relative impacts of socioeconomic factors such as population, GDP, and environmental policies on CO2 emissions. When combined with these factors, we found that the climate change effect is more important than when considered individually and significantly impacts total CO2 emissions under SSP585. The contrasting results observed in the warm and cold regions of Japan can offer valuable insight into the potential future variations in energy demand and resulting CO2 emissions on a global scale.

Effect of particle sizes of biochar on CO2 emissions in a poplar plantation of ancient Yellow River channel, China

Forest soil is a vital pool of organic carbon, which is sensitive to management. Biochar addition could change the CO2 emissions from soil, but its effects are still ambiguous. Moreover, the impacts of particle sizes of biochar on CO2 emissions are still unknown. In this study, a series of field experiments were conducted to investigate the effects of biochar addition on CO2 emissions in a poplar plantation (Populus nigra), China. Biochar with two application rates of (10 and 50 t/ha) and three particle sizes (3-1 mm, 1-0.1 mm, and <0.1 mm) was applied into the surface soil (0-10 cm), and the soil without biochar was set as control. The results showed that a high level of fine biochar addition (1-0.1 mm and <0.1 mm) had similar and positive effects on CO2 emissions by increasing the contents of soil ammonium, available phosphorus, easily oxidizable carbon, soil moisture, soil capillary pore, and the activity of β-glucosidase. However, biochar addition (1-0.1 mm and <0.1 mm) reduced the bioavailability of dissolved organic carbon (DOC), producing a negative relationship between DOC content and CO2 emissions. This investigation highlights the importance of biochar with different particle sizes in adjusting CO2 emissions from temperate soils.

The mediating effect of financial development on CO2 emissions: An empirical study based on provincial panel data in China

Global climate change has become the greatest threat to humanity, and China is developing policies among various industries to peak CO2 emissions as soon as possible and expects the reduction of CO2 emissions through financial development. Based on the panel data of 30 provinces in China from 2000 to 2017, this paper uses fixed effect model and mediating effect model to explore the mechanism and effective pathway of financial development on CO2 emissions per capita among different regions in China. Empirical results consistently indicate that financial development has the significantly positive effect on CO2 emissions per capita, but the impact is inverted U-shaped. It means that only when the financial development in China gradually increased to 4.21 can achieve the goal of reducing CO2 emissions per capita. These results provide new explanatory ideas for the inconsistent direction of the impact of financial development on carbon emissions in existing studies. Then, the technological innovation and industrial structure are intermediaries for financial development to reduce CO2 emissions per capita, while the economic scale is the opposite. And it illustrates not only theoretical but also empirical results on the mediating pathways of financial development driven CO2 emission reduction. Under the theory of "natural resource curse", in regions with high fossil energy dependence, the mediating effect of the economic scale is greater than that in regions with low fossil energy dependence. But the mediating effects of technological innovation and industrial structure from financial development on CO2 emissions per capita are all negative and more powerful than that in regions with low fossil energy dependence. This provides an important practical basis for the development of differentiated carbon reduction policies through finance in different fossil energy dependent regions.

Carbon mitigation and health effects of fleet electrification in China's Yangtze River Delta

Fleet electrification is one of the most promising strategies to mitigate carbon emissions and improve air quality. This study provides a comprehensive analysis of the currently unclear CO2 mitigation and human health benefits from electric vehicle (EV) adoption and energy decarbonization in the Yangtze River Delta (YRD) region by integrating fleet modeling, emission projection, air quality modeling and health risk assessment. Based on future socioeconomic trajectories, we project that the total vehicle stock in the YRD region will peak at 107-117 million around 2045-2050. The transition to EVs combined with largely renewable energy in the YRD region can potentially reduce CO2 emissions by 870 Tg in 2060 and brings along substantial health co-benefits with ∼360 avoided premature deaths per million from reduced PM2.5 and O3 concentrations. This study further explores the NO2-attributable burden from road transportation and reveals that fleet electrification could yield greater NO2-attributable health benefits than those from reduced PM2.5 and O3, especially in traffic-dense urban areas. Those findings indicate that China's near-term energy development plans (35% renewable energy) have created the conditions for large-scale EV adoption. Our results imply that the benefits of EVs exhibit substantial spatial heterogeneity, underscoring the importance of region-specific EV incentive policies, and hint that policymakers should prioritize densely populated megacities to maximize the potential for public health gains.

Impact of ecosystem metabolism on CO2 emissions: Insights from high-resolution time series of pH measured in situ

Lakes and reservoirs are important sources/sinks of atmospheric CO2. Primary production and respiration transforming inorganic to organic carbon and vice versa alter CO2 concentrations in the surface waters and thus affect CO2 emissions. Here we investigate the link between net-production (NEP) and CO2 concentrations and emissions at high temporal resolution over more than two months in a German pump storage reservoir. Continuous in-situ pH measurements in combination with few alkalinity measurements provided concentrations of CO2 and dissolved inorganic carbon (DIC) at high temporal resolution over more than 75 days. Time series of metabolic rates of carbon were determined with an open-water diel pH technique, which utilizes the diel changes in DIC obtained from the observed diel changes in pH and data on alkalinity. During the measuring period, average NEP was positive and CO2 concentrations were typically substantially under-saturated. On average, the reservoir acted as a sink for CO2, whereby CO2 uptake was 39% larger in the evening than in the morning. Only few consecutive days with negative NEP were sufficient to turn the reservoir temporally into a source of CO2. Therefore, the average CO2 uptake determined from continuous data can be 80% larger to 30% smaller than estimates of average uptake based on bi-weekly data. Daily mean NEP explained only 9% and 4% of the variance of daily mean DIC and CO2. Note that NEP is proportional to the time derivative of DIC and therefore not expected to correlate well with DIC in general. Because CO2 changes nonlinearly with DIC, NEP explains less variance of CO2 than of DIC. Numerical experiments confirmed the arguments above and revealed that at positive average NEP the total CO2 uptake over several weeks is not well predicted by average NEP but depends on the detailed temporal pattern of NEP. However, if average NEP is negative, average NEP may be a good predictor of total CO2 emissions. Similar conclusions apply for high and low alkalinity waters, but uptake rates and temporal variability of CO2 emissions are smaller in high than in low alkalinity waters. Assessment of the link between NEP and CO2 emissions requires differentiation between lakes with different alkalinity and, because of the non-linear relationship between NEP and CO2, strongly benefits from data with high temporal resolution especially during time-periods with positive net-production.

The impact of green technology innovation on carbon dioxide emissions: The role of local environmental regulations

Environmental pollution has become a global issue attracting ever-increasing attention. Green technology innovation (GTI) is considered an effective strategy in countering this problem and helping achieve sustainability goals. However, the market failure suggests that intervention from the government is necessary to promote the effectiveness of technological innovation and hence, its positive social impacts on emissions reduction. This study investigates how the environmental regulation (ER) influences the relationship between green innovation and CO₂ emissions reduction in China. Employing data from 30 provinces from the period 2003 to 2019, the Panel Fixed-effect model, the Spatial Durbin Model (SDM), the System Generalised Method of Moments (SYS-GMM) and the Difference-In-Difference (DID) models are applied to take issues relating to endogeneity and spatial impact into consideration. The results indicate that environmental regulations positively moderate the impact of green knowledge innovation (GKI) on CO₂ emissions reduction but have a much weaker moderation effect when green process innovation (GPI) is considered. Among different types of regulatory instruments, investment-based regulation (IER) is the most effective in promoting the relationship between green innovation and emissions reduction, followed by command-and-control-based regulation (CER). Expenditure-based regulation (EER) is less effective and can encourage short-termism and opportunistic behaviour among firms, who can accept the paying of fines as a cheaper cost over the short-term than investment in green innovation. Moreover, the spatial spillover effect of green technological innovation on carbon emissions in neighbouring regions is confirmed, in particular when IER and CER are implemented. Lastly, the heterogeneity issue is further examined by considering differences in the economic development and the industrial structure across different regions, and the conclusions reached remain robust. This study identifies that the market-based regulatory instrument, IER, works best in promoting green innovation and emissions reduction among Chinese firms. It also encourages GKI which may assist firms in achieving long-term sustained growth. The study recommends further development of the green finance system to maximise the positive impact of this policy instrument.

Warming influences CO2 emissions from China's coastal saltmarsh wetlands more than changes in precipitation

Coastal wetlands are an important carbon sink but are sensitive to climate changes. The response of CO₂ emissions to these changes differs under different hydroclimatic conditions. Here, this article used meta-analysis to synthesize data from Chinese coastal salt marshes, to analyze sensitivities for CO₂ emissions, and then to assess the relative contributions of air temperature (T_a) and precipitation (Pre). This article used the ratio between potential evaporation (E_p) and Pre to divide Chinese coastal saltmarshes into water- (E_p/Pre > 1) and energy-limited regions (E_p/Pre ≤ 1). Results show that emissions are more sensitive to both Pre and T_a in water-limited regions (E¯ = 0.60 eV, slope = 0.37) than in energy-limited regions (E¯ = 0.23 eV, slope = 0.04). Comparing the relative effects of changes in T_a (△CO₂ = 21.86 mg m^-2 h^-1) and Pre (△CO₂ = 7.19 mg m^-2 h^-1) on CO₂ emissions shows that warming contributes more to changes in CO₂ emissions. The response of emissions to changes in Pre is asymmetric and shows that warmer and drier may have antagonistic effects, while warmer and wetter may have synergistic effects. There was a 2.15 mg m^-2 h^-1 change in emissions in energy-limited regions when Pre increased by 139.69 mm, and a decrease of -0.15 mg m^-2 h^-1 in emissions when Pre decreased by 1.28 mm in water-limited regions. Climate change has the greatest impact on Phragmites australis in CO₂ emissions, especially under warmer and wetter conditions in energy-limited regions. This indicates that warming drives CO₂ emissions, while changes in Pre (resulting in wetter or dryer conditions) can mitigate or strengthen CO₂ emissions from coastal wetlands in China. This article offers a new perspective and suggests that differences in hydroclimatic conditions should be considered when discussing carbon emissions from coastal wetlands.

Revisiting the environmental Kuznetz curve and pollution haven hypothesis in N-11 economies: Fresh evidence from panel quantile regression

Human activities in recent decades have severely affected environmental quality, and CO₂ emissions have irreparable consequences on human health and the survival of the earth. Moreover, achieving sustainable development goals requires the expansion of environmental literature to accelerate the performing of critical actions. With this in mind, this study evaluates the impact of foreign direct investment, economic complexity, and the utilization of renewable energy on CO₂ emission in N-11 countries from 1995 to 2019 by Panel Quantile Regression. As a novelty, the interaction between economic complexity and foreign direct investment is considered to get a better comprehension. Given the results, Environmental Kuznetz Curve is validated in N-11 countries through economic complexity. Notably, the impact of economic complexity is more substantial and robust in the incipient stages of industrialization. Furthermore, foreign direct investment is a destructive factor for environmental quality, and Pollution Haven Hypothesis is not rejected. Interestingly, the interaction of economic complexity and foreign direct investment mitigates the trend of CO₂ emissions. Eventually, the utilization of renewable energy reduces CO₂ emissions. Thereby, applying more strict environmental regulations and standards, developing green energy infrastructure and technologies, improving institutional quality, and supporting knowledge-based and technology-intensive exports are the main policy recommendations of this study.

Presence of different microplastics promotes greenhouse gas emissions and alters the microbial community composition of farmland soil

Microplastics (MPs) are regarded as potential persistent organic pollutants owing to their small size and low degradability. However, the effect of MP pollution on greenhouse gas (GHG) emissions from farmland soil is yet unclear. Therefore, a series of microcosm experiments were set up using polyvinyl chloride (PVC), polypropylene (PP), polyethylene (PE), polystyrene (PS), and polyester (PET) at concentrations of 0.25 %, 2 %, and 7 % (w/w). Each treatment had three replicates. This experiment was carried out to verify the effect of MP pollution on greenhouse gas (GHG) emissions from farmland soil. The results showed that the addition of MPs significantly promoted the emissions of the three main GHGs, including nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄). Especially, PE may cause most GHG emissions which would contribute to climate warming when its pollution concentration increased. In addition, different doses and types of MPs could affect microbial community structure. These findings of this present study may provide a scientific and practical reference for the prevention and control of MPs pollution and risk assessment of global climate change caused by MPs.

Climate change mitigation role of renewable energy consumption: Does institutional quality matter in the case of reducing Africa's carbon dioxide emissions?

Renewable energy and institutions have emerged among other variables touted to address climate change problems. However, empirical results have been conflicting. With a relatively poorer state of institutional quality and a lower level of renewable energy development amidst rising carbon dioxide (CO₂) emissions in Africa, the study assesses: a) the direct effect of renewable energy and institutional quality on CO₂ emissions in Africa; and b) the moderation role of institutional quality on the effect of renewable energy on CO₂ emissions in Africa. The study relies on panel data covering 2002-2021 for 32 African countries. The Fully-Modified OLS regression method is employed to analyze the data based on the environmental Kuznets curve (EKC) hypothesis and Stochastic Impacts by Regression on Population, Affluence, & Technology (STIRPAT) model. The results show that urbanization and trade openness increase CO₂ emissions. Although income has a positive effect on carbon emissions, the square term has a negative confirming the EKC hypothesis. Renewable energy also reduces CO₂ emissions. Institutional quality variables of control of corruption, rule of law, regulatory quality, political stability and absence of violence, voice and accountability, government effectiveness and institutional index created from the above indicators reduce CO₂ emissions. In addition, except government effectiveness, the remaining indicators of institutional quality negatively moderate the effect of renewable energy on CO₂ emissions. The results among other things imply that intensifying the development and usage of renewable energy would help address the rising carbon dioxide emissions trend in Africa. Also, strengthening institutions promises to reduce CO₂ emissions.

CO2 emissions and global value chains indicators:new evidence for 1995-2018

Globalization and the configuration of production processes around Global Value Chains (GVCs) have become key factors for explaining the recent evolution of environmental and economic indicators. Indeed, previous research found evidence on the significant impact of GVCs indicators (participation and position) on CO₂ emissions. Additionally, results obtained in previous literature vary depending on the time period and geographical areas considered. In this context, the main aims of this paper are to analyze the role the GVCs in explaining the evolution of CO₂ emissions, and to identify possible structural breaks. This study uses the Multiregional Input-Output framework to calculate a position indicator and two different measures of participation in GVCs (interpreted either as trade openness or international competitiveness). The analysis useS Inter-Country Input-Output tables (ICIO) as main database, which includes 66 countries and 45 industries and covers the period 1995-2018. It is first concluded that upstream positions in GVCs are associated to lower global emissions. Additionally, the effect of participation depends on the measure used: trade openness is linked to lower emissions, while a higher competitiveness in international trade leads to higher emissions. Finally, two structural breaks are identified in 2002 and 2008, revealing that position is significant in the two first subperiods, while participation becomes significant from 2002 onwards. Thus, policies to mitigate CO₂ emissions might to be different before and after 2008: currently, reductions in emissions can be achieved by increasing value-added embodied in trade while decreasing the volume of transactions.

Heterotrophic aquatic metabolism and sustained carbon dioxide emissions in a mineral-soil wetland restored with treated effluent

Wetlands are economically valuable ecosystems, in part because they purify wastewater by retaining and processing nutrients, organic matter (OM), and other pollutants. While natural wetlands are highly productive and sequester large pools of carbon (C), it is unclear whether the C cycle of restored treatment wetlands is functionally consistent with natural systems. This knowledge gap limits our appreciation for the role that wetland restoration can play as a natural solution to climate change. Here, we quantified metabolic and C cycling patterns of a restored, multi-basin wetland (Frank Lake, Alberta, Canada) receiving municipal and beef processing plant effluents rich in nutrients and OM. We conducted metabolic measurements in all three basins using dissolved oxygen sensors deployed under ice and in open water. Extreme production and respiration indicated that effluent was largely mineralized and replaced with wetland OM in transit. The heterotrophic status of all basins aligned with a published mass budget demonstrating the aquatic habitat of the wetland was an OM sink under current drought conditions that lengthen effluent processing time. Floating chamber measurements in open water zones confirmed that the wetland was a source of CO₂ to the atmosphere. From input to outflow, sustained emissions led to declining pCO₂ and a decline in the ratio of dissolved inorganic to organic C. Over 30 years post-restoration, the open water habitats in Frank Lake remain heterotrophic and a net source of CO₂, suggesting that the trajectory of aquatic C cycling may be distinct from wetlands restored with non-effluent water sources.

Driving factors and emission reduction scenarios analysis of CO2 emissions in Guangdong-Hong Kong-Macao Greater Bay Area and surrounding cities based on LMDI and system dynamics

As one of the most open and economically dynamic regions in China, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is at the forefront of low-carbon development and has an exemplary and leading role for other regions. This study provides a research framework based on the Logarithmic Mean Divisia Index (LMDI) and system dynamics (SD) by first compiling an inventory of CO₂ emissions in the GBA and surrounding cities from 2000 to 2019 and then systematically and comprehensively analyzing the driving factors, future trends and policy implications of CO₂ emissions in the GBA and surrounding cities. The results show that (a) CO₂ emissions in the GBA and surrounding cities grew from 253.39 Mt in 2000 to 627.86 Mt in 2019, with an average annual growth rate of 4.89 %. The per capita CO₂ emissions showed a continuous decreasing trend, and the overall carbon intensity of each sector showed a decreasing trend. (b) GDP per capita growth has the greatest effect on CO₂ emissions, followed by the number of transport vehicles and population. The negative effects are energy intensity, average output of transportation vehicles, and residential energy intensity, with energy intensity being the most critical. (c) In the baseline scenario, regional CO₂ emissions in 2030 are 1.25 times higher than those in 2019 and continue to grow. (d) Technological innovation measures are the most effective among individual emission reduction policies, followed by optimization of industrial structure. Furthermore, energy structure adjustment, vehicle licensing restrictions, and residents' green living are less effective. (e) Under comprehensive emission reduction measures, the region can achieve carbon emissions peaking in 2026 and reduce the regional carbon intensity by 66.24 % in 2030 compared with 2005. This study provides effective data support for the GBA and surrounding cities to formulate low carbon policies, promote carbon emission reduction and achieve carbon emissions peaking early.

Emission growth and drivers in Mainland Southeast Asian countries

Mainland Southeast Asian (MSEA) countries (Cambodia, Laos, Thailand, Myanmar, and Vietnam) are likely to become one of the next hotspots for emission reduction, since CO₂ emissions in this area will have a two-thirds increase by 2040 due to rapid economy growth and associated energy consumption. As one of the most vulnerable areas to climate change, MSEA countries need to develop low-carbon roadmaps based on accurate emission data. This study provides emission inventories for MSEA countries for 2010-2019, based on the IPCC territorial emission accounting approach , including emissions from five types of fuels (i.e., coal, crude oil, oil products, natural gas, and biofuels & waste) used in 47 economic sectors. The results show that the emissions in MSEA countries are on the rise, with average annual growth rates ranging from 2.5% in Thailand to 19.3% in Laos. Biomass is one of the most important sources of carbon emissions, contributing between 11.8% and 76.7% of total carbon emissions, but its share has been declining in most countries, whereas the share of emissions from coal has risen sharply in Laos, Vietnam, and Cambodia. We further examine the drivers behind the changes in emissions using index decomposition analysis. Economic growth was the strongest driver of growth in emissions, while population growth has only had a small effect on emission growth. Energy intensity varies widely across nations, but only significantly reduced CO₂ emission growth in Thailand. The secondary sector considerable contributed to an increase in CO₂ emissions in Laos and Vietnam, while the tertiary sector only moderately contributed to emissions in Thailand. Our study provides a better understanding of the composition and underlying factors of emission growth in MSEA countries, this could shape their low-carbon development pathway. Our results could also inform other emerging economies, which may become emission hotspots in the next decades, to develop low-carbon roadmaps, thereby contributing to the achievement of global climate change targets.

Variability of fuel consumption and CO2 emissions of a gasoline passenger car under multiple in-laboratory and on-road testing conditions

An increasing divergence regarding fuel consumption (and/or CO₂ emissions) between real-world and type-approval values for light-duty gasoline vehicles (LDGVs) has posed severe challenges to mitigating greenhouse gases (GHGs) and achieving carbon emissions peak and neutrality. To address this divergence issue, laboratory test cycles with more real-featured and transient traffic patterns have been developed recently, for example, the China Light-duty Vehicle Test Cycle for Passenger cars (CLTC-P). We collected fuel consumption and CO₂ emissions data of a LDGV under various conditions based on laboratory chassis dynamometer and on-road tests. Laboratory results showed that both standard test cycles and setting methods of road load affected fuel consumption slightly, with variations of less than 4%. Compared to the type-approval value, laboratory and on-road fuel consumption of the tested LDGV over the CLTC-P increased by 9% and 34% under the reference condition (i.e., air conditioning off, automatic stop and start (STT) on and two passengers). On-road measurement results indicated that fuel consumption under the low-speed phase of the CLTC-P increased by 12% due to the STT off, although only a 4% increase on average over the entire cycle. More fuel consumption increases (52%) were attributed to air conditioning usage and full passenger capacity. Strong correlations (R² > 0.9) between relative fuel consumption and average speed were also identified. Under traffic congestion (average speed below 25 km/hr), fuel consumption was highly sensitive to changes in vehicle speed. Thus, we suggest that real-world driving conditions cannot be ignored when evaluating the fuel economy and GHGs reduction of LDGVs.

Endorsing sustainable development in BRICS: The role of technological innovation, renewable energy consumption, and natural resources in limiting carbon emission

This research aimed to examine the complex interaction between technological innovation, renewable energy consumption, natural resources, and carbon dioxide (CO₂) emissions of BRICS (i.e., Brazil, Russia, India, China, and South Africa) countries from 1990 to 2019, to accomplish the Paris Climate Conference (COP-21) objective of reducing CO₂ emissions to promote environmental sustainability. The long-run empirical estimations derived from the CS-ARDL technique, which considered other estimation issues like cross-sectional dependency and slope heterogeneity, indicated that technological innovation, renewable energy consumption, and natural resources increase environmental sustainability by limiting CO₂ emissions, in the short-run and long-run. The technological innovation-related activities have a CO₂ mitigating effect as shown by the negative coefficients which ranges between -0.05 and -0.14. This shows that they increase environmental sustainability and aid in achieving Sustainable Development Goals (SDGs) 13. Similarly, renewable energy and natural resources decrease CO₂ emissions as shown by the coefficient of renewable energy (-0.31 to -0.81) and natural resources (-0.01 to 0.95); thereby increasing ecological quality by limiting CO₂ emissions. Furthermore, the interaction of technological innovation with natural resource rent and renewable energy consumption also aids in mitigating CO₂ emissions and increases environmental health. Finally, panel causality analysis revealed a significant causality from all explanatory variables to CO₂ emissions. Based on the results, significant policy suggestions are provided, such as improving energy effectiveness, investing in energy technologies, and increasing renewable energy consumption to stimulate technological innovation to achieve the target of a net-zero‑carbon economy.

An aging giant at the center of global warming: Population dynamics and its effect on CO2 emissions in China

Revealing the complex correlation between population aging and CO₂, and projecting their future dynamics are fundamentally necessary to inform effective policies toward a low-carbon and sustainable development in China. Differing from the existing studies, this study highlighted a quantitative investigation on the impact of aging on CO₂ emissions across the different stages of regional development in China through a STIRPAT model based on balanced provincial panel data from 1995 to 2019, and projected the demographic change and CO₂ emissions till 2050 by employing cohort model and scenario analysis. It is found that CO₂ emissions in China has witnessed a significant growth during 1995-2019, and will exhibit an inverted U-shaped growth till 2050 with its peak appears between 2030 and 2040. Statistically, every 1% growth of aging population will cause a 0.62% increase in CO₂ emissions in China. However, a big regional difference was also detected as aging contributed to CO₂ reduction in the eastern region, but stimulated CO₂ emissions in the central and western regions. Policy implications for achieving a low-carbon and aging-oriented sustainable development may include the integration of aging into the decision-making in industrial structure upgrading and CO₂ emission reduction at both national and region levels, the promotion of further transition to low-carbon consumption and green products in the eastern region, and strengthening the deep fusion of aging-oriented industries with local resource and environmental endowment in the central and western regions such as the development of eco-agriculture and green pension industries.

Estimating the CO2 emissions of Chinese cities from 2011 to 2020 based on SPNN-GNNWR

Global warming is a serious threat to human survival and health. Facing increasing global warming, the issue of CO₂ emissions has attracted more attention. China is a major contributor of anthropogenic CO₂ emissions and so it is essential to accurately estimate China's CO₂ emissions and analyze their changing characteristics. This study recalculates CO₂ emissions from Chinese cities from 2011 to 2020 using the SPNN-GNNWR model and multiple factors to reduce the uncertainty in emission estimates. The SPNN-GNNWR model has excellent predictions (R²: 0.925, 10-fold CV R²: 0.822) when cross-validation is used. The results indicate that the total CO2 emissions in China calculated by the model are close to those accounted for by other authorities in the world, with the total CO₂ emissions increasing from 9.122 billion tonnes in 2011 to 9.912 billion tonnes in 2020. The city with the largest increase in CO₂ emissions is Tianjin, and the city with the largest decrease is Beijing. The study also reveals the regional differences in CO₂ emissions in Chinese mainland, including emissions, emission intensity and per capita emissions. Capturing and understanding the emissions and the related socioeconomic characteristics of different cities can help to develop effective emission mitigation strategies.

Optical and molecular indices of dissolved organic matter for estimating biodegradability and resulting carbon dioxide production in inland waters: A review

Biodegradable dissolved organic carbon (BDOC) constitutes the most labile fraction of dissolved organic matter (DOM), which also functions as a source of CO₂ emissions from inland waters. However, no systematic review is available on DOM indicators of BDOC and CO₂ production potential. Optical and molecular indices can be used to track small changes in DOM composition during biodegradation. In this review, we identified four different methods for measuring BDOC together with their strengths and limitations. In addition, we discuss the potential of using documented optical indices based on absorption and fluorescence spectroscopy and molecular indices based on Fourier transform ion cyclotron mass spectrometry as proxies for estimating BDOC and biodegradation-induced CO₂ production based on previously reported relationships in the literature. Many absorbance- and fluorescence-based indices showed inconsistent relationships with BDOC depending on watershed characteristics, hydrology, and anthropogenic impacts. Nevertheless, several indices, including specific UV absorbance at 254 nm (SUVA₂₅₄), humification index (HIX), and terrestrial humic-like fluorescent DOM (FDOM) components, tended to have negative relationships with BDOC in tropical and temperate watersheds under baseflow or drought periods. Protein-like FDOM exhibited the strongest correlation with BDOC in different systems, except during storms and flood events. Despite the limited number of studies, DOM molecular indices exhibited consistent relationships with BDOC, suggesting that the relative abundance of aliphatic formulas and the molecular lability index could act as reliable proxies. The DOM optical indices explain up to 96% and 78% variability in BDOC and CO₂, respectively; nonetheless, there were limited studies on molecular indices, which explain up to 74% variability in BDOC. Based on literature survey, we recommend several sensitive indices such as SUVA₂₅₄, HIX, and terrestrial humic- and protein-like FDOM, which could be useful indicators of BDOC and dissolved CO₂ in inland water. Future research should incorporate a wider range of geographic regions with various land use, hydrology, and anthropogenic disturbances to develop system- or condition-specific DOM optical or molecular proxies for better prediction of BDOC and CO₂ emissions.

Decomposing manufacturing CO2 emission changes: An improved production-theoretical decomposition analysis based on industrial linkage theory

Identifying key drivers of manufacturing CO₂ emissions is critical to carbon reduction practices. For manufacturing, CO₂ emissions are mainly determined by production capacity and production scale. However, traditional production-theoretical decomposition analysis (PDA) fails to consider production-scale-related drivers. To better support policy development and implementation, this paper improves PDA based on industrial linkage theory. The improved model can identify seven production-capacity-related drivers and five production-scale-related drivers, allowing a comprehensive understanding of CO₂ emission drivers. Then this model is implemented to investigate CO₂ emission changes in 18 manufacturing sectors in Hubei Province, China, from 2012 to 2017. Results show that manufacturing CO₂ reduction efforts in Hubei Province have yielded some achievements, with reduced potential energy intensity and improved CO₂ emission technical efficiency in most sectors. Changes in external market demand and final demand structure have contributed to CO₂ reduction in most sectors. Results also reveal some problems in manufacturing in Hubei Province, such as the inability to improve CO₂ emission technical efficiency and CO₂ emission technology strength, the slow improvement of energy utilization technical efficiency and energy utilization technology strength, and the reduction of value-added rate.

Spatiotemporal association of carbon dioxide emissions in China's urban agglomerations

The reduction of carbon dioxide (CO₂) emissions and sustainable development in low-carbon ways are of great significance to urban agglomerations. However, few studies are exploring the relationship between CO₂ emissions and socioeconomic development at city levels from the perspective of clusters of regions. Based on the open data of inventory for anthropogenic CO₂ emissions, nighttime light data, and population dataset as a proxy for the socioeconomic development levels of urban agglomerations, we used Mann-Kendall trend test, Tapio decoupling analysis, and spatial autocorrelation analysis to explore the spatiotemporal association of CO₂ emissions and the impact of socioeconomic development on emissions in the nineteen urban agglomerations in China. Findings showed that the growth of CO₂ emissions in China was primarily concentrated in urban agglomerations. The CO₂ emissions in eastern coastal and northern urban agglomerations were much higher than those in other areas, while the emissions in western urban agglomerations were the lowest. The periodic characteristics of CO₂ emissions were consistent with China's five-year development plan. Urban agglomerations in the early stage from 2000 to 2002 or with developed and stable industrial structures tended to achieve decoupling. High-high (HH) clusters of socioeconomic development with CO₂ emissions were mainly distributed in urban agglomerations of the Beijing-Tianjin-Hebei region (BTH), the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), Yangtze River Delta (YRD), Huhhot-Baotou-Ordos-Yulin (HBOY), Shandong Peninsula (SP), and Central Shanxi (CS). Most of the clusters except those in HBOY shrunk from 2000 to 2010 and remained relatively stable from 2010 to 2019. These urban agglomerations should promote synergistic emission reduction. High-low (HL) clusters mostly appeared in central cities with a high socioeconomic level and surrounding cities with low CO₂ emissions s, i.e., in urban agglomerations of Chengdu-Chongqing region (CC), the Beibu Gulf (BG), and Lanzhou-Xining (LX). These urban agglomerations with prominent polarization phenomena should adhere to regional overall coordination and thus minimize total regional costs of CO₂ emission reduction. The results could provide references for the synergistic reduction of CO₂ emissions and the coordinated development in urban agglomerations.

Using carbon dioxide-added microalgal-bacterial granular sludge for carbon-neutral municipal wastewater treatment under outdoor conditions: Performance, granule characteristics and environmental sustainability

Microalgal-bacterial granular sludge (MBGS) process has a gorgeous prospect for municipal wastewater treatment, but the research on the treatment of complex organic wastewater by MBGS process with CO₂ addition under outdoor conditions is not enough. Therefore, this paper evaluated the feasibility of CO₂-added MBGS process for complex organic wastewater disposal under natural day-night cycles. The results showed that the addition of CO₂ overall improved the removal efficiency of pollutants. Typically, the removal efficiency of total phosphorus increased averagely from 88.5 % to 95.0 % in 12-h day cycle and from 26.2 % to 45.3 % in 12-h night cycle. The addition of CO₂ increased the size of MBGS from 1.0 mm to 16.5 mm within 30 days due to extracellular polymeric substances secretion and the dominant filamentous microalgae on granules. The decrease of catalase activity and malondialdehyde content indicated that CO₂ reduced oxidative damage and maintained the normal growth of MBGS. Further estimates of the collected gas showed that CO₂-added MBGS process could reduce global CO₂ emissions by one hundred million tons per year. This study is expected to contribute to the goal of carbon neutrality in the area of wastewater treatment by MBGS process.

Using a combination of nighttime light and MODIS data to estimate spatiotemporal patterns of CO2 emissions at multiple scales

Accurate mapping spatiotemporal patterns of CO₂ emissions and understanding its driving factors are very important, it is useful for the scientific and rational formulation of carbon emission reduction policies. Nevertheless, due to data availability issues, most studies have been limited to the global and national scales, and the models used were relatively simple. In this paper, we used the 500 m Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS-DNB) data and the 250 m Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index (MODIS NDVI) and proposed an improved CO₂ emissions index (ICEI) to calculate CO₂ emissions. Compared with the total nighttime light (NTL), the average regression coefficient (R²) can be improve from 0.73 to 0.78. We also used the coefficient of variation, spatial autocorrelation, and geographically weighted regression models to analyze the temporal and spatial variation mode of CO₂ emissions, as well as the associated correlation and heterogeneity, at three different administrative unit scales during 2012-2019. Our experimental results demonstrate that: (1) the improved index (ICEI) is better than the traditional variable (NTL) in estimating CO₂ emissions; (2) the highest CO₂ emissions are primarily gathered in the developed coastal areas in eastern China; and (3) at the provincial level, the added value of the secondary industry is the most significant factor, whereas the added value of the tertiary industry is negatively correlated with CO₂ emissions.

The influence of urban form compactness on CO2 emissions and its threshold effect: Evidence from cities in China

Although compact urban form plays an important role in constraining emissions of carbon dioxide (CO₂), the boundary for the impact of compact urban form on these emissions has nevertheless received little attention. We consequently applied the entropy weight method and several key landscape metrics to a dataset from 295 cities in China to quantify urban form compactness (UFC) between 2000 and 2015. The STIRPAT model then was employed to estimate the impact of UFC on CO₂ emissions, and a panel threshold regression model was used to estimate threshold effects capable of limiting the impact of compact urban form on emissions. Although CO₂ emissions increased sharply over the 15-year study period, a significant negative relationship between UFC and CO₂ emissions was detected. Two thresholds of UFC were detected, and this allowed three categories to be differentiated: before the first threshold, between the two thresholds, and after the second threshold. These categories were respectively associated with no impact, strong impact, and weak impact of UFC on reduction of carbon emissions in the 295 cities. Carbon emissions reduction consequently becomes effective when the UFC exceeds the first threshold and effectiveness persists but at a reduced level when the UFC exceeds the second threshold. Further temporal analysis confirmed that an increasing number of mostly small- and medium-sized cities could constrain their future carbon emissions by adopting a compact urban form. Thus, government policies should emphasize UFC as a strategy to reduce CO₂ emissions. Moreover, by defining the range of compact urban form that has the greatest impact on CO₂ emissions, our study deepens the overall understanding of the influence of UFC on carbon emission reductions, so as to make contributions to the design of low-carbon cities.

Unveiling the spatial and sectoral characteristics of a high-resolution emission inventory of CO2 and air pollutants in China

Under the target of carbon neutrality as well as stringent air quality guideline, understanding the spatial characteristics of both greenhouse gases and air pollutants emissions, in particular of their mutual sources, is crucial for assessing the feasibility of achieving their concomitant emission control, which, nevertheless, remains to be unclear yet. To this end, we construct a high-resolution (10 km × 10 km) emission inventory including both CO₂ and air pollutants in China, which fosters us an opportunity to examine their spatial and sectoral characteristics. The primary sources for both CO₂ and air pollutant emissions are power and industry. Among different subsectors in industry, detailed information indicates cement, iron and steel are the major subsectors for both CO₂ and majority of air pollutants. Analysis of the high-resolution spatial distribution indicates that for CO₂, 5 % of the grids account for 90 % of the total CO₂ emissions, indicative of the existence of spatial heterogeneity. These grids are the major locations with air pollutant emissions as well, i.e., 73 % for SO₂ emissions, and more than 50 % for volatile organic compounds (VOCs), CO, NOx, PM₁₀ and PM_2.5, stressing the spatial consistency between greenhouse gases and air pollutant emissions. A large portion of emissions concentrate in a relatively small number of grids further implies the possibility to achieve the mutual control of both greenhouse gas emissions and air pollutant emissions, which is useful for future policy in particular of achieving the carbon neutrality and air quality improvement.

The spatial differences of the synergy between CO2 and air pollutant emissions in China's 296 cities

The emissions reduction of CO₂ and air pollutants are the main task in China. The two have the same roots and they interact with each other. However, CO₂ and air pollutants are quite different in space, so it is of great practical significance to explore the spatial differences of their synergy. As PM_2.5 and O₃ are more concerned at present, thus, this paper examined the decoupling of CO₂, PM_2.5 and O₃ from GDP in China's 296 cities using the latest available data from 2015 to 2016. And the spatial differences of synergy among CO₂, PM_2.5 and O₃ were quantitatively analyzed by using spatial autocorrelation analysis and geographically weighted regression model. The results showed that: (1) The cities achieving the three synergy emissions reduction were mainly in the southeast of China. (2) Only 26 cities had achieved the strong decoupling of CO₂, PM_2.5 and O₃ from GDP. (3) The synergy characteristics between CO₂ and PM_2.5, CO₂ and O₃ were different. This paper put forward the policies according to the conclusions.

Perennial alley cropping contributes to decrease soil CO2 and N2O emissions and increase soil carbon sequestration in a Mediterranean almond orchard

The implementation of alley cropping in orchards can be a sustainable strategy to increase farm productivity by crop diversification and contribute to climate change mitigation. In this research, we evaluated the short-term effect of alley cropping with reduced tillage on soil CO₂ and N₂O emissions and soil total organic carbon (TOC) in an almond orchard under Mediterranean rainfed conditions. We compared an almond monoculture with tillage in all plot surface (MC) with almond crop with reduced tillage and growth of Capparis spinosa (D1) and almond crop with reduced tillage and growth of Thymus hyemalis (D2). For two years, soil CO₂ and N₂O were measured, with soil sampling at the start and end of the experimental period. Results showed that CO₂ emission rates followed the soil temperature pattern, while N₂O emissions were not correlated with temperature nor moisture. Soil CO₂ emissions were significantly higher in MC (87 mg m^-2 h^-1), with no significant differences between D1 and D2 (69 mg m^-2 h^-1). Some peaks in CO₂ effluxes were observed after tillage operations during warm days. Soil N₂O emission rates were not significantly different among treatments. Cumulative CO₂ and CO₂ equivalent (CO₂e) emissions were significantly highest in MC. When CO₂e emissions were expressed on a crop production basis, D2 showed the significantly lowest values (5080 g kg^-1) compared to D1 (50,419 g kg^-1) and MC (87,836 g kg^-1), owing to the high thyme yield, additional to the almond yield. No production was obtained for C. spinosa, since at least two more years are required. TOC did not change with time in MC neither D1, but it significantly increased in D2 from 3.85 g kg^-1 in 2019 to 4.62 g kg^-1 in 2021. Thus, alley cropping can contribute to increase the agroecosystem productivity and reduce CO₂ emissions. However, it is necessary to grow evergreen alley crops such as thyme to obtain short-term increases in soil organic matter. Thus, to estimate increases in TOC with alley cropping, the plantation density and the period required by the crop to cover most of the surface are essential factors at planning the cropping strategy.

A green approach towards sorption of CO2 on waste derived biochar

Carbon capture technologies have advanced in recent years to meet the ever-increasing quest to minimize excessive anthropogenic CO₂ emissions. The most promising option for CO₂ control has been identified as carbon capture and storage. Among the numerous sorbents, char generated from biomass thermal conversion has shown to be an efficient CO₂ adsorbent. This study examines various characteristics that can be used to increase the yield of biochar suited for carbon sequestration. This review gives recent research progress in the area, stressing the variations and consequences of various preparation processes on textural features such as surface area, pore size and sorption performance with respect to CO₂'s sorption capacity. The adjoining gaps discovered in this field have also been highlighted herewith, which will serve as future work possibility. It aims to analyse and describe the possibilities and potential of employing pristine and modified biochar as a medium of CO₂ capture. It also examines the parameters that influence biochar's CO₂ adsorption ability and pertinent challenges regarding the production of biochar-based CO₂ sorbent materials.

Decomposition of residential electricity-related CO2 emissions in China, a spatial-temporal study

The COVID-19 pandemic brings a surge in household electricity consumption, thereby enabling extensive research interest on residential carbon emissions as one of the hot topics in carbon reduction. However, research on spatial-temporal driving forces for the increase of residential CO₂ emissions between regions still remains unknown in terms of emissions mitigation in post-pandemic era. Therefore, we studied the residential CO₂ emissions from the electricity consumption of China during the period 1997-2019. Afterward, the regional specified production emission factors, combining with electricity use pattern, living standard and household size, were modelled to reveal the spatial-temporal driving forces at national and provincial scales. We observed that the national residential electricity-related CO₂ increased from 1997 to 2013, before fluctuating to a peak in 2019. Guangdong, Shandong and Jiangsu, from East China were the top emitters with 27% of the national scale. The decomposition results showed that the income improvement was the primary driving force behind the emission increase in most provinces, while the household size and production emission effects were the main negative effects. For the spatial decomposition, differences in the total households between regions further widen the gaps of total emissions. At the provincial scale of temporal decomposition, eastern developed regions exhibited the most significant decrease in production emissions. In contrast, electricity intensity effect showed negative emission influences in the east and central regions, and positive in north-eastern and western China. The research identified the different incremental patterns of residential electricity-related CO₂ emissions in various Chinese provinces, thereby providing scientific ways to save energy and reduce emissions.

Interactive effects of microplastics, biochar, and earthworms on CO2 and N2O emissions and microbial functional genes in vegetable-growing soil

Soil carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions are two main greenhouse gases that play important roles in global warming. Studies have shown that microplastics, biochar, and earthworms can significantly affect soil greenhouse gas emissions. However, few studies have explored how their interactions affect soil CO₂ and N₂O emissions. A mesocosm experiment was conducted to investigate their interactive effects on soil greenhouse gases and soil microbial functional genes in vegetable-growing soil under different incubation times. Biochar alone or combined with microplastics significantly decreased soil CO₂ emissions but had no effect on soil N₂O emissions. Microplastics and biochar inhibited CO₂ emissions and promoted N₂O emissions in the soil with earthworms. The addition of microplastics, biochar, and earthworms had significant effects on soil chemical properties, including dissolved organic carbon, ammonia nitrogen, nitrate nitrogen, total nitrogen, and pH. Microplastics and earthworms selectively influenced microbial abundances and led to a fungi-prevalent soil microbial community, while biochar led to a bacteria-prevalent microbial community. The interactions of microplastics, biochar, and earthworms could alleviate the reduction of the bacteria-to-fungi ratio and the abundance of microbial functional genes caused by microplastics and earthworms alone. Microplastics significantly inhibited microorganisms as well as C and N cycling functional genes in earthworm guts, while biochar obviously stimulated them. The influence of the addition of exogenous material on soil greenhouse gas emissions, soil chemical properties, and functional microbes differed markedly with soil incubation time. Our results indicated that biochar is a promising amendment for soil with microplastics or earthworms to simultaneously mitigate CO₂ emissions and regulate soil microbial community composition and function. These findings contribute to a better understanding of the interaction effects of microplastics, biochar, and earthworms on soil carbon and nitrogen cycles, which could be used to help conduct sustainable environmental management of soil.

City-level emission peak and drivers in China

China is playing an increasing role in global climate change mitigation, and local authorities need more city-specific information on the emissions trends and patterns when designing low-carbon policies. This study provides the most comprehensive CO₂ emission inventories of 287 Chinese cities from 2001 to 2019. The emission inventories are compiled for 47 economic sectors and include energy-related emissions for 17 types of fossil fuels and process-related emissions from cement production. We further investigate the state of the emission peak in each city and reveal hidden driving forces. The results show that 38 cities have proactively peaked their emissions for at least five years and another 21 cities also have emission decline, but passively. The 38 proactively peaked cities achieved emission decline mainly by efficiency improvements and structural changes in energy use, while the 21 passively emission declined cities reduced emissions at the cost of economic recession or population loss. We propose that those passively emission declined cities need to face up to the reasons that caused the emission to decline, and fully exploit the opportunities provided by industrial innovation and green investment brought by low-carbon targets to achieve economic recovery and carbon mitigation goals. Proactively peaked cities need to seek strategies to maintain the downward trend in emissions and avoid an emission rebound and thus provide successful models for cities with still growing emissions to achieve an emission peak.

Transition to renewable energy and environmental technologies: The role of economic policy uncertainty in top five polluted economies

The United Nations' "Sustainable Development Goals" (SDGs) express attention to climate action. Even though a considerable number of papers have targeted this issue, the literature on the top five, "China, India, Japan, Russia, and the United States" economies is uncommon. Therefore, this paper is targeted to examine the influence of renewable energy (RE), environmental technologies (ETs), and economic policy uncertainty (EPU) on carbon emissions. By using the most recent data available from 1992 to 2020, results are estimated with robust econometric techniques, i. e. "cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and augmented mean group (AMG)". Findings reflect the harmful role of EPU. However, RE and ETs have a supportive role in the transition towards a sustainable environment. The findings are also strong in terms of policy implications for the top five polluters.

Assessment of hydrogen production from municipal solid wastes as competitive route to produce low-carbon H2

An economic and CO₂ emission impact assessment of the production of H₂ from municipal solid waste in the two configurations of retrofitting an existing waste to energy plant with an electrolysis unit (WtE + El) and of hydrogen production via waste gasification (WtH₂) is made with respect to reference cases of H₂ production by steam reforming of methane (SMR) or of water electrolysis (El). The results are analyzed with reference to two scenarios depending on whether the fate of waste disposal emissions for SMR and El is accounted. The costs of H₂ production as a function of waste gate fee and CO₂ taxation as well as the CO₂ emissions for both scenarios and the four cases of H₂ production analyzed are reported. The results show that produce H₂ from a WtE plant hybridized with an electrolyzer could be economic only when the plant is free from depreciation costs and no CO₂ taxation exists. Conversely, WtH₂ solution results preferable when CO₂ taxation will be applied to the non-biogenic fraction of waste. Conditions when WtH₂ may results competitive to SMR are defined, in terms of both cost of production and CO₂ emissions. With respect to El case, WtH₂ results more competitive under the assumption made in terms of combined costs and CO₂ emissions.