Changes in productivity partitioning induced by precipitation extremes increase inaccuracy of grassland carbon estimation.

The fraction of net primary productivity (NPP) allocated to belowground organs (fBNPP) in grasslands is a critical parameter in global carbon cycle models; moreover, understanding the effect of precipitation changes on this parameter is vital to accurately estimating carbon sequestration in grassland ecosystems. However, how fBNPP responds to temporal precipitation changes along a gradient from extreme drought to extreme wetness, remains unclear, mainly due to the lack of long-term data of belowground net primary productivity (BNPP) and the fact that most precipitation experiments did not have a gradient from extreme drought to extreme wetness. Here, by conducting both a precipitation gradient experiment (100-500 mm) and a long-term observational study (34 years) in the Inner Mongolia grassland, we showed that fBNPP decreased linearly along the precipitation gradient from extreme drought to extreme wetness due to stronger responses in aboveground NPP to drought and wet conditions than those of BNPP. Our further meta-analysis in grasslands worldwide also indicated that fBNPP increased when precipitation decreased, and the vice versa. Such a consistent pattern of fBNPP response suggests that plants increase the belowground allocation with decreasing precipitation, while increase the aboveground allocation with increasing precipitation. Thus, the linearly decreasing response pattern in fBNPP should be incorporated into models that forecast carbon sequestration in grassland ecosystems; failure to do so will lead to underestimation of the carbon stock in drought years and overestimation of the carbon stock in wet years in grasslands.

Inhibition of microbially mediated total organic carbon decomposition in different types of cadmium contaminated soils with wheat straw addition.

Wheat straw returning is a common agronomic measure in the farmland. Understanding organic carbon transformation is of great significance for carbon budget under the premise of widespread distribution of cadmium (Cd) contaminated soils. An incubation experiment was conducted to assess the influence of Cd contamination on the decomposition and accumulation of total organic carbon (TOC) as well as the composition and abundance of bacterial communities in eight soil types with wheat straw addition. The results showed that inhibition of Cd contamination on microbially mediated organic carbon decomposition was affected by soil types. The lower cumulative C mineralization and higher TOC content could be observed in the acidic soils relative to that in the alkaline soils. The content of Cd in soil exhibits different effects on the inhibition in decomposition of TOC. The high dosage level of Cd had stronger inhibitory impact due to its high toxicity. The decomposition of TOC was restricted by a reduction in soil bacterial abundance and weakening of bacterial activities. Redundancy analysis (RDA) indicated that Proteobacteria and Gemmatimonadetes were abundant in alkaline Cd-contaminated soils with wheat straw addition, while Bacteroidetes dominated cumulative C mineralization in acidic Cd-contamination soils. Moreover, the abundance of predicted functional bacteria indicated that high-dose Cd-contamination and acid environment all inhibited the decomposition of TOC. The present study suggested that pH played an important role on carbon dynamics in the Cd-contaminated soils with wheat straw addition.

Impact of wildfire on soil characteristics and arbuscular mycorrhizal fungi.

This study explored whether wildfire alters the soil properties and arbuscular mycorrhizal fungi (AMF) community composition when compared with burnt rangeland, non-burnt rangeland and adjacent tilled in mesothermal ecosystems. The study was carried out in August 2020, 1 year later after wildfire. The results of this study showed that the wildfire played a key role in altering soil characteristics and AMF community composition in Bartin Province located in the Western Black Sea Region. Soil samples were made according to standard methods. AMF spores were isolated according to the wet sieving method, and the spores of AMF were identified according to their morphological characteristics. Analysis of variance was performed to determine the differences between the parameters, and correlation analysis was performed to determine the relationships between the parameters. The highest values of soil organic carbon (2.20%), total nitrogen (0.18%), K2O (74.68 kg/da), root colonization (87.5%) and the frequency of occurrence of Funneliformis geosporum (20%), Claroideoglomus claroideum (16%) and Claroideoglomus etunicatum (11%) were found in burnt rangeland. Sporulation of Acaulospora dilatata, Acaulospora morrowiae, Acaulospora tuberculata, Scutellospora castanea, Scutellospora coralloidea, Scutellospora scutata, Glomus coremioides and Glomus multicaule was either decreased or completely inhibited in the burnt rangeland. While species diversity of AMF (12) decreased, the number of AMF spores (325.6 (number/50 gr soil)) increased in burnt areas. In conclusion, the number of spores and root colonization of AMF increased but species diversity of AMF reduced after the wildfire. In ecosystems with high fire risk where AMF transfer is planned, it is suggested that it would be more appropriate to select species with an increase in spore number after fire.

Simulating adaptive grazing management on soil organic carbon in the Southeast U.S.A. using MEMS 2.

Grazing lands play a significant role in global carbon (C) dynamics, holding substantial soil organic carbon (SOC) stocks. However, historical mismanagement (e.g., overgrazing and land-use change) has led to substantial SOC losses. Regenerative practices, such as adaptive multi-paddock (AMP) grazing, offer a promising avenue to improve soil health and help combat climate change by increasing SOC accrual, both in its particulate (POC) and mineral-associated (MAOC) organic C components. Because adaptive grazing patterns emerge from the combination of different levers such as frequency, intensity, and timing of grazing, studying AMP grazing management in experimental trials and representing it in models remains challenging. Existing ecosystem models lack the capacity to predict how different adaptive grazing levers affect SOC storage and its distribution between POC and MAOC and along the soil profile accurately. Therefore, they cannot adequately assist decision-makers in effectively optimizing adaptive practices based on SOC outcomes. Here, we address this critical gap by developing version 2.34 of the MEMS 2 model. This version advances the previous by incorporating perennial grass growth and grazing submodules to simulate grass green-up and dormancy, reserve organ dynamics, the influence of standing dead plant mass on new plant growth, grass and supplemental feed consumption by animals, and their feces and urine input to soil. Using data from grazing experiments in the southeastern United States and experimental SOC data from two conventional and three AMP grazing sites in Mississippi, we tested the capacity of MEMS 2.34 to simulate grass forage production, total SOC, POC, and MAOC dynamics to 1-m depth. Further, we manipulated grazing management levers, i.e., timing, intensity, and frequency, to do a sensitivity analysis of their effects on SOC dynamics in the long term. Our findings indicate that the model can represent bahiagrass forage production (BIAS = 9.51 g C m-2, RRMSE = 0.27, RMSE = 65.57 g C m-2, R2 = 0.72) and accurately captured the dynamics of SOC fractions across sites and depths (0-15 cm: RRMSE = 0.05; 15-100 cm: RRMSE = 1.08-2.07), aligning with patterns observed in the measured data. The model best captured SOC and MAOC stocks across AMP sites in the 0-15 cm layer, while POC was best predicted at-depth. Otherwise, the model tended to overestimate SOC and MAOC below 15 cm, and POC in the topsoil. Our simulations indicate that grazing frequency and intensity were key levers for enhancing SOC stocks compared to the current management baseline, with decreasing grazing intensity yielding the highest SOC after 50 years (63.7-65.9 Mg C ha-1). By enhancing our understanding of the effects of adaptive grazing management on SOC pools in the southeastern U.S., MEMS 2.34 offers a valuable tool for researchers, producers, and policymakers to make AMP grazing management decisions based on potential SOC outcomes.

Empirical analysis of trade costs and their impact on carbon emissions in RCEP countries.

Global economic integration and environmental issues have attracted widespread attention in recent years. As one of the world's most significant free trade agreements, the Regional Comprehensive Economic Partnership (RCEP) significantly impacts trade and the environment. However, research on the relationship between trade costs and carbon emissions still needs to be completed. This study explores the relationship between trade costs and carbon emissions within the framework of the Trade Benefit Theory, which posits that trade liberalization and openness generate economic benefits through increased efficiency, technological advancement, and economic growth. This study analyzes panel data from 12 RCEP countries from 2001 to 2014, employing static and dynamic panel models to examine the relationship between trade costs and carbon emissions. The analysis utilizes mixed regression, fixed (random) effects models, and the systematic GMM method. The results indicate that decreases in trade costs are associated with reduced environmental pollution, aligning with the Environmental Kuznets Curve (EKC) hypothesis, which posits an N-shaped relationship between trade costs and carbon emissions. Implementing RCEP facilitates a decrease in trade-related pollution, suggesting that reducing trade costs can help mitigate environmental pollution. Furthermore, the observed N-shaped EKC for trade costs and carbon emissions highlights the potential of RCEP to reduce the impact of trade-related pollution.

Evaluation of effects of heat released from SOC decomposition on soil carbon stock and temperature.

Heat released from soil organic carbon (SOC) decomposition (referred to as microbial heat hereafter) could alter the soil's thermal and hydrological conditions, subsequently modulate SOC decomposition and its feedback with climate. While understanding this feedback is crucial for shaping policy to achieve specific climate goal, it has not been comprehensively assessed. This study employs the ORCHIDEE-MICT model to investigate the effects of microbial heat, referred to as heating effect, focusing on their impacts on SOC accumulation, soil temperature and net primary productivity (NPP), as well as implication on land-climate feedback under two CO2 emissions scenarios (RCP2.6 and RCP8.5). The findings reveal that the microbial heat decreases soil carbon stock, predominantly in upper layers, and elevates soil temperatures, especially in deeper layers. This results in a marginal reduction in global SOC stocks due to accelerated SOC decomposition. Altered seasonal cycles of SOC decomposition and soil temperature are simulated, with the most significant temperature increase per unit of microbial heat (0.31 K J-1) occurring at around 273.15 K (median value of all grid cells where air temperature is around 273.15 K). The heating effect leads to the earlier loss of permafrost area under RCP8.5 and hinders its restoration under RCP2.6 after peak warming. Although elevated soil temperature under climate warming aligns with expectation, the anticipated accelerated SOC decomposition and large amplifying feedback on climate warming were not observed, mainly because of reduced modeled initial SOC stock and limited NPP with heating effect. These underscores the multifaceted impacts of microbial heat. Comprehensive understanding of these effects would be vital for devising effective climate change mitigation strategies in a warming world.

Towards a low-carbon and beautiful world: assessing the impact of digital technology on the common benefits of pollution reduction and carbon reduction.

When ecology thrives, civilization thrives, and when ecology declines, civilization declines. Based on panel data from 30 provinces in China from 2000 to 2021, this study used marginal abatement costs to estimate the co-benefits of pollution reduction and carbon reduction. Two-way fixed effect and two-stage intermediary effect models were used to evaluate the impact of digital technology on co-benefits and its indirect channels. The results indicated that China's total carbon emissions maintained a steady growth trend, while air pollution showed a fluctuating declining trend. Reaching peak carbon neutrality calls for more innovative solutions. Under joint emission reduction efforts, the study revealed marginal abatement cost savings of 535.8 million yuan/million tons and 6216.5 million yuan/µg/m3 for carbon reduction and pollution reduction, respectively. Most importantly, the study confirmed that joint emission reduction programs can reduce environmental governance costs more than individual emission reductions can, and the co-benefits increased from 37.983 to 44.757. The co-benefits generally showed a trend of fluctuation and increases and had the characteristics of phased transformation. Intragroup differences and cross-overlapping between regions made regional differences in co-benefits obvious. The subversive, permeable, and integrated features of digital technology have resulted in the all-around transformation of the economy and society, and the new technology-economy paradigm has significantly improved co-benefits. The conclusion remains valid after robustness testing and controlling for endogeneity problems. The results of the mechanism analysis suggest that digital technology can indirectly improve synergies through the intermediary channels of fostering green technology innovation, reducing energy consumption intensity and improving the energy structure.

Not all soil carbon is created equal: Labile and stable pools under nitrogen input.

Anthropogenic activities have raised nitrogen (N) input worldwide with profound implications for soil carbon (C) cycling in ecosystems. The specific impacts of N input on soil organic matter (SOM) pools differing in microbial availability remain debatable. For the first time, we used a much-improved approach by effectively combining the 13C natural abundance in SOM with 21 years of C3-C4 vegetation conversion and long-term incubation. This allows to distinguish the impact of N input on SOM pools with various turnover times. We found that N input reduced the mineralization of all SOM pools, with labile pools having greater sensitivity to N than stable ones. The suppression in SOM mineralization was notably higher in the very labile pool (18%-52%) than the labile and stable (11%-47%) and the very stable pool (3%-21%) compared to that in the unfertilized control soil. The very labile C pool made a strong contribution (up to 60%) to total CO2 release and also contributed to 74%-96% of suppressed CO2 with N input. This suppression of SOM mineralization by N was initially attributed to the decreased microbial biomass and soil functions. Over the long-term, the shift in bacterial community toward Proteobacteria and reduction in functional genes for labile C degradation were the primary drivers. In conclusion, the higher the availability of the SOM pools, the stronger the suppression of their mineralization by N input. Labile SOM pools are highly sensitive to N availability and may hold a greater potential for C sequestration under N input at global scale.

Plant diversity decreases greenhouse gas emissions by increasing soil and plant carbon storage in terrestrial ecosystems.

The decline in global plant diversity has raised concerns about its implications for carbon fixation and global greenhouse gas emissions (GGE), including carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). Therefore, we conducted a comprehensive meta-analysis of 2103 paired observations, examining GGE, soil organic carbon (SOC) and plant carbon in plant mixtures and monocultures. Our findings indicate that plant mixtures decrease soil N2O emissions by 21.4% compared to monocultures. No significant differences occurred between mixtures and monocultures for soil CO2 emissions, CH4 emissions or CH4 uptake. Plant mixtures exhibit higher SOC and plant carbon storage than monocultures. After 10 years of vegetation development, a 40% reduction in species richness decreases SOC content and plant carbon storage by 12.3% and 58.7% respectively. These findings offer insights into the intricate connections between plant diversity, soil and plant carbon storage and GGE-a critical but previously unexamined aspect of biodiversity-ecosystem functioning.

Dominant role of the non-forest woody vegetation in the post 2015/16 El Niño tropical carbon recovery.

The extreme dry and hot 2015/16 El Niño episode caused large losses in tropical live aboveground carbon (AGC) stocks. Followed by climatic conditions conducive to high vegetation productivity since 2016, tropical AGC are expected to recover from large losses during the El Niño episode; however, the recovery rate and its spatial distribution remain unknown. Here, we used low-frequency microwave satellite data to track AGC changes, and showed that tropical AGC stocks returned to pre-El Niño levels by the end of 2020, resulting in an AGC sink of 0.18 0.14 0.26 $$ {0.18}_{0.14}^{0.26} $$ Pg C year-1 during 2014-2020. This sink was dominated by strong AGC increases ( 0.61 0.49 0.84 $$ {0.61}_{0.49}^{0.84} $$ Pg C year-1) in non-forest woody vegetation during 2016-2020, compensating the forest AGC losses attributed to the El Niño event, forest loss, and degradation. Our findings highlight that non-forest woody vegetation is an increasingly important contributor to interannual to decadal variability in the global carbon cycle.

Investigating the effect of dynamic traffic distribution on network-wide traffic emissions: An empirical study in Ningbo, China.

Urban road traffic is one of the primary sources of carbon emissions. Previous studies have demonstrated the close relationship between traffic flow characteristics and carbon emissions (CO2). However, the impact of dynamic traffic distribution on carbon emissions is rarely empirically studied on the network level. To fill this gap, this study proposes a dynamic network carbon emissions estimation method. The network-level traffic emissions are estimated by combining macroscopic emission models and recent advances in dynamic network traffic flow modeling, namely, Macroscopic Fundamental Diagram. The impact of traffic distribution and the penetration of battery electric vehicles on total network emissions are further investigated using the Monte Carlo method. The results indicate the substantial effect of network traffic distribution on carbon emissions. Using the urban expressway network in Ningbo as an example, in the scenario of 100% internal combustion engine vehicles, increasing the standard deviation of link-level traffic density from 0 to 15 veh/km-ln can result in an 8.9% network capacity drop and a 15.5% reduction in network carbon emissions. This effect can be moderated as the penetration rate of battery electric vehicles increases. Based on the empirical and simulating evidence, different expressway pollution management strategies can be implemented, such as petrol vehicle restrictions, ramp metering, congestion pricing, and perimeter control strategies.

Study on carbon emission driving factors and carbon peak forecasting in power sector of Shanxi province.

The realisation of the low-carbon transition of the energy system in resource-intensive regions, as embodied by Shanxi Province, depends on a thorough understanding of the factors impacting the power sector's carbon emissions and an accurate prediction of the peak trend. Because of this, the power industry's carbon emissions in Shanxi province are measured in this article from 1995 to 2020 using data from the Intergovernmental Panel on Climate Change (IPCC). To obtain a deeper understanding of the factors impacting carbon emissions in the power sector, factor decomposition is performed using the Logarithmic Mean Divisia Index (LMDI). Second, in order to precisely mine the relationship between variables and carbon emissions, the Sparrow Search Algorithm (SSA) aids in the optimisation of the Long Short-Term Memory (LSTM). In order to implement SSA-LSTM-based carbon peak prediction in the power industry, four development scenarios are finally built up. The findings indicate that: (1) There has been a fluctuating upward trend in Shanxi Province's total carbon emissions from the power industry between 1995 and 2020, with a cumulative growth of 372.10 percent. (2) The intensity of power consumption is the main factor restricting the rise of carbon emissions, contributing -65.19%, while the per capita secondary industry contribution factor, contributing 158.79%, is the main driver of the growth in emissions. (3) While the baseline scenario and the rapid development scenario fail to peak by 2030, the low carbon scenario and the green development scenario peak at 243,991,100 tonnes and 258,828,800 tonnes, respectively, in 2025 and 2028. (4) Based on the peak performance and the decomposition results, resource-intensive cities like Shanxi's power industry should concentrate on upgrading and strengthening the industrial structure, getting rid of obsolete production capacity, and encouraging the faster development of each factor in order to help the power sector reach peak carbon performance.

Low-Cost Hourly Ambient Black Carbon Measurements at Multiple Cities in Africa.

There is a notable lack of continuous monitoring of air pollutants in the Global South, especially for measuring chemical composition, due to the high cost of regulatory monitors. Using our previously developed low-cost method to quantify black carbon (BC) in fine particulate matter (PM2.5) by analyzing reflected red light from ambient particle deposits on glass fiber filters, we estimated hourly ambient BC concentrations with filter tapes from beta attenuation monitors (BAMs). BC measurements obtained through this method were validated against a reference aethalometer between August 2 and 23, 2023 in Addis Ababa, Ethiopia, demonstrating a very strong agreement (R2 = 0.95 and slope = 0.97). We present hourly BC for three cities in sub-Saharan Africa (SSA) and one in North America: Abidjan (Côte d'Ivoire), Accra (Ghana), Addis Ababa (Ethiopia), and Pittsburgh (USA). The average BC concentrations for the measurement period at the Abidjan, Accra, Addis Ababa Central summer, Addis Ababa Central winter, Addis Ababa Jacros winter, and Pittsburgh sites were 3.85 µg/m3, 5.33 µg/m3, 5.63 µg/m3, 3.89 µg/m3, 9.14 µg/m3, and 0.52 µg/m3, respectively. BC made up 14-20% of PM2.5 mass in the SSA cities compared to only 5.6% in Pittsburgh. The hourly BC data at all sites (SSA and North America) show a pronounced diurnal pattern with prominent peaks during the morning and evening rush hours on workdays. A comparison between our measurements and the Goddard Earth Observing System Composition Forecast (GEOS-CF) estimates shows that the model performs well in predicting PM2.5 for most sites but struggles to predict BC at an hourly resolution. Adding more ground measurements could help evaluate and improve the performance of chemical transport models. Our method can potentially use existing BAM networks, such as BAMs at U.S. Embassies around the globe, to measure hourly BC concentrations. The PM2.5 composition data, thus acquired, can be crucial in identifying emission sources and help in effective policymaking in SSA.

Do Tasmanian devil declines impact ecosystem function?

Tasmanian eucalypt forests are among the most carbon-dense in the world, but projected climate change could destabilize this critical carbon sink. While the impact of abiotic factors on forest ecosystem carbon dynamics have received considerable attention, biotic factors such as the input of animal scat are less understood. Tasmanian devils (Sarcophilus harrisii)-an osteophageous scavenger that can ingest and solubilize nutrients locked in bone material-may subsidize plant and microbial productivity by concentrating bioavailable nutrients (e.g., nitrogen and phosphorus) in scat latrines. However, dramatic declines in devil population densities, driven by the spread of a transmissible cancer, may have underappreciated consequences for soil organic carbon (SOC) storage and forest productivity by altering nutrient cycling. Here, we fuse experimental data and modeling to quantify and predict future changes to forest productivity and SOC under various climate and scat-quality futures. We find that devil scat significantly increases concentrations of nitrogen, ammonium, phosphorus, and phosphate in the soil and shifts soil microbial communities toward those dominated by r-selected (e.g., fast-growing) phyla. Further, under expected increases in temperature and changes in precipitation, devil scat inputs are projected to increase above- and below-ground net primary productivity and microbial biomass carbon through 2100. In contrast, when devil scat is replaced by lower-quality scat (e.g., from non-osteophageous scavengers and herbivores), forest carbon pools are likely to increase more slowly, or in some cases, decline. Together, our results suggest often overlooked biotic factors will interact with climate change to drive current and future carbon pool dynamics in Tasmanian forests.

Aquatic processing enhances the loss of aged carbon from drained and burned peatlands.

Water-logged peatlands store tremendous amounts of soil carbon (C) globally, accumulating C over millennia. As peatlands become disturbed by human activity, these long-term C stores are getting destabilized and ultimately released as greenhouse gases that may exacerbate climate change. Oxidation of the dissolved organic carbon (DOC) mobilized from disturbed soils to streams and canals may be one avenue for the transfer of previously stored, millennia-aged C to the atmosphere. However, it remains unknown whether aged peat-derived DOC undergoes oxidation to carbon dioxide (CO2) following disturbance. Here, we use a new approach to measure the radiocarbon content of CO2 produced from the oxidation of DOC in canals overlying peatland soils that have undergone widespread disturbance in Indonesia. This work shows for the first time that aged DOC mobilized from drained and burned peatland soils is susceptible to oxidation by both microbial respiration and photomineralization over aquatic travel times for DOC. The bulk radiocarbon age of CO2 produced during canal oxidation ranged from modern to ~1300 years before present. These ages for CO2 were most strongly influenced by canal water depth, which was proportional to the water table level where DOC is mobilized from disturbed soils to canals. Canal microbes preferentially respired older or younger organic C pools to CO2, and this may have been facilitated by the use of a small particulate organic C pool over the dissolved pool. Given that high densities of canals are generally associated with lower water tables and higher fire risk, our findings suggest that peatland areas with high canal density may be a hotspot for the loss of aged C on the landscape. Taken together, the results of this study show how and why aquatic processing of organic C on the landscape can enhance the transfer of long-term peat C stores to the atmosphere following disturbance.

Soil carbon storage under different types of arid land use in Algeria.

This study aims to assess the amount of organic carbon stored in soils, as it is an intention of knowing the sustainable soil management, by using two common methods for determining soil organic matter (SOM), namely oxidation with acidified wet dichromate (Walkley-Black method-WB) and loss on ignition (LOI). The study was carried with soil samples collected from a depth of 0 to 30 cm in the Saharan arid region of Ghardaïa (Algeria), with different land uses: agricultural, forest and pastoral. The results obtained from the LOI and WB methods were subjected to statistical analysis, and the relations between both methods were tested to investigate their relationship. The mean percentage of SOM values were 1.86, 2.42, 1.54 by using LOI, but, lower values of 0.34, 0.33, 0.36 were determined by using WB method, for agricultural, forest and pastoral soils respectively. A weak linear relationship between the two analytical procedures was obtained (R2 of 0.19 and 0.13 for agricultural and forest soils), while a medium relationship (R2 = 0.65) was found for pastoral soils when using linear adjustment. However, the opposite behaviour was found when we use the logarithmic adjustment. The study outcomes indicated discrepancies in the measurements of SOM values between the two methods, been higher those estimated with LOI. Finally, in order to identify the best methodology to measure soil organic matter in arid soils, more research is required in these extreme arid regions as they are a gap in world soil organic matter maps.

Can digital financial inclusion converge the regional agricultural carbon emissions intensity gap?

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods.

Microplastic pollution promotes soil respiration: A global-scale meta-analysis.

Microplastic (MP) pollution likely affects global soil carbon (C) dynamics, yet it remains uncertain how and to what extent MP influences soil respiration. Here, we report on a global meta-analysis to determine the effects of MP pollution on the soil microbiome and CO2 emission. We found that MP pollution significantly increased the contents of soil organic C (SOC) (21%) and dissolved organic C (DOC) (12%), the activity of fluorescein diacetate hydrolase (FDAse) (10%), and microbial biomass (17%), but led to a decrease in microbial diversity (3%). In particular, increases in soil C components and microbial biomass further promote CO2 emission (25%) from soil, but with a much higher effect of MPs on these emissions than on soil C components and microbial biomass. The effect could be attributed to the opposite effects of MPs on microbial biomass vs. diversity, as soil MP accumulation recruited some functionally important bacteria and provided additional C substrates for specific heterotrophic microorganisms, while inhibiting the growth of autotrophic taxa (e.g., Chloroflexi, Cyanobacteria). This study reveals that MP pollution can increase soil CO2 emission by causing shifts in the soil microbiome. These results underscore the potential importance of plastic pollution for terrestrial C fluxes, and thus climate feedbacks.

How does urbanization impact China's carbon emissions: A regional heterogeneity perspective.

In the context of China's green development and "dual carbon" goal, urbanization, as a way to achieve Chinese modernization, has a particularly important effect on green and low-carbon economic development. Firstly, this paper empirically analyzed the influence of urbanization on per capita carbon emissions using Chinese city data and a panel fixed-effects model. Then, the impact mechanisms of urbanization on carbon emissions were examined from both the demand and supply sides. Finally, we analyzed the differences in the transmission mechanisms of urbanization affecting carbon emissions in the eastern, central, and western regions. The results show that (1) urbanization increases per capita carbon emissions. However, this effect shows inter-regional differences, with more significant promotion effects in the eastern and central regions; (2) on the demand side, the residents' consumption intensity can drive carbon emissions, while the rise of human capital agglomeration suppresses carbon emissions; on the supply side, industrial structure can drive carbon emissions, while the increase of green technological innovation suppresses carbon emissions; (3) the consumption effect and the industry effect play a major role in the eastern and central regions, while the intermediary effect is not obvious in the western region. This study can provide important insights for synergizing urbanization and achieving carbon reduction commitments.

Into the unknown: The role of post-fire soil erosion in the carbon cycle.

Wildfires directly emit 2.1 Pg carbon (C) to the atmosphere annually. The net effect of wildfires on the C cycle, however, involves many interacting source and sink processes beyond these emissions from combustion. Among those, the role of post-fire enhanced soil organic carbon (SOC) erosion as a C sink mechanism remains essentially unquantified. Wildfires can greatly enhance soil erosion due to the loss of protective vegetation cover and changes to soil structure and wettability. Post-fire SOC erosion acts as a C sink when off-site burial and stabilization of C eroded after a fire, together with the on-site recovery of SOC content, exceed the C losses during its post-fire transport. Here we synthesize published data on post-fire SOC erosion and evaluate its overall potential to act as longer-term C sink. To explore its quantitative importance, we also model its magnitude at continental scale using the 2017 wildfire season in Europe. Our estimations show that the C sink ability of SOC water erosion during the first post-fire year could account for around 13% of the C emissions produced by wildland fires. This indicates that post-fire SOC erosion is a quantitatively important process in the overall C balance of fires and highlights the need for more field data to further validate this initial assessment.