Responses of greenhouse gas fluxes to experimental warming in wheat season under conventional tillage and no-tillage fields

Bayesian model of tilling wheat confronting climatic and sustainability challenges

Conventional farming poses threats to sustainable agriculture in growing food demands and increasing flooding risks. This research introduces a Bayesian Belief Network (BBN) to address these concerns. The model explores tillage adaptation for flood management in soils with varying organic carbon (OC) contents for winter wheat production. Three real soils, emphasizing texture and soil water properties, were sourced from the NETMAP soilscape of the Pang catchment area in Berkshire, United Kingdom. Modified with OC content at four levels (1, 3, 5, 7%), they were modeled alongside relevant variables in a BBN. The Decision Support System for Agrotechnology Transfer (DSSAT) simulated datasets across 48 cropping seasons to parameterize the BBN. The study compared tillage effects on wheat yield, surface runoff, and GHG-CO2 emissions, categorizing model parameters (from lower to higher bands) based on statistical data distribution. Results revealed that NT outperformed CT in the highest parametric category, comparing probabilistic estimates with reduced GHG-CO2 emissions from "7.34 to 7.31%" and cumulative runoff from "8.52 to 8.50%," while yield increased from "7.46 to 7.56%." Conversely, CT exhibited increased emissions from "7.34 to 7.36%" and cumulative runoff from "8.52 to 8.55%," along with reduced yield from "7.46 to 7.35%." The BBN model effectively captured uncertainties, offering posterior probability distributions reflecting conditional relationships across variables and offered decision choice for NT favoring soil carbon stocks in winter wheat (highest among soils "NT.OC-7%PDPG8," e.g., 286,634 kg/ha) over CT (lowest in "CT.OC-3.9%PDPG8," e.g., 5,894 kg/ha). On average, NT released minimum GHG- CO2 emissions to "3,985 kgCO2eqv/ha," while CT emitted "7,415 kgCO2eqv/ha." Conversely, NT emitted "8,747 kgCO2eqv/ha" for maximum emissions, while CT emitted "15,356 kgCO2eqv/ha." NT resulted in lower surface runoff against CT in all soils and limits runoff generations naturally for flood alleviation with the potential for customized improvement. The study recommends the model for extensive assessments of various spatiotemporal conditions. The research findings align with sustainable development goals, e.g., SDG12 and SDG13 for responsible production and climate actions, respectively, as defined by the Agriculture and Food Organization of the United Nations.

Decomposition analysis of electricity generation on carbon dioxide emissions in Ghana

This study analyses the factors driving CO2 emissions from electricity generation in Ghana from 1990 to 2020. Employing Logarithmic Mean Divisia Index (LMDI) and Autoregressive Distributed Lag (ARDL) techniques, the research decomposes electricity generation into different factors and assesses their impact on CO2 emissions, considering both short and long-run effects. The LMDI analysis reveals that the total CO2 emissions from electricity generation amount to 3.33%, with all factors contributing positively in each subperiod. Notably, fossil fuel intensity, production, and transformation factors exhibit substantial contributions of about 1.16%, 0.49%, and 0.48%, respectively. Contrastingly, the ARDL results highlight that only electricity intensity and production factors significantly increase CO2 emissions by about 0.20% and 0.09% (0.38% and 0.10%) in the short-run (long-run), while other factors contribute to a reduction in electricity generation emissions. Overall, we conclude that electricity intensity and production factors are the primary drivers of CO2 emissions from electricity generation in Ghana. Nevertheless, effective measures to address all decomposition factors is crucial for effective mitigation of electricity generation CO2 emissions.

Effects of whole-soil warming on CH4 and N2 O fluxes in an alpine grassland

Global climate warming could affect the methane (CH4 ) and nitrous oxide (N2 O) fluxes between soils and the atmosphere, but how CH4 and N2 O fluxes respond to whole-soil warming is unclear. Here, we for the first time investigated the effects of whole-soil warming on CH4 and N2 O fluxes in an alpine grassland ecosystem on the Tibetan Plateau, and also studied the effects of experimental warming on CH4 and N2 O fluxes across terrestrial ecosystems through a global-scale meta-analysis. The whole-soil warming (0-100 cm, +4°C) significantly elevated soil N2 O emission by 101%, but had a minor effect on soil CH4 uptake. However, the meta-analysis revealed that experimental warming did not significantly alter CH4 and N2 O fluxes, and it may be that most field warming experiments could only heat the surface soils. Moreover, the warming-induced higher plant litter and available N in soils may be the main reason for the higher N2 O emission under whole-soil warming in the alpine grassland. We need to pay more attention to the long-term response of greenhouse gases (including CH4 and N2 O fluxes) from different soil depths to whole-soil warming over year-round, which could help us more accurately assess and predict the ecosystem-climate feedback under realistic warming scenarios in the future.

Nitrogen availability mediates soil carbon cycling response to climate warming: A meta-analysis

Global climate warming may induce a positive feedback through increasing soil carbon (C) release to the atmosphere. Although warming can affect both C input to and output from soil, direct and convincing evidence illustrating that warming induces a net change in soil C is still lacking. We synthesized the results from field warming experiments at 165 sites across the globe and found that climate warming had no significant effect on soil C stock. On average, warming significantly increased root biomass and soil respiration, but warming effects on root biomass and soil respiration strongly depended on soil nitrogen (N) availability. Under high N availability (soil C:N ratio < 15), warming had no significant effect on root biomass, but promoted the coupling between effect sizes of root biomass and soil C stock. Under relative N limitation (soil C:N ratio > 15), warming significantly enhanced root biomass. However, the enhancement of root biomass did not induce a corresponding C accumulation in soil, possibly because warming promoted microbial CO₂ release that offset the increased root C input. Also, reactive N input alleviated warming-induced C loss from soil, but elevated atmospheric CO₂ or precipitation increase/reduction did not. Together, our findings indicate that the relative availability of soil C to N (i.e., soil C:N ratio) critically mediates warming effects on soil C dynamics, suggesting that its incorporation into C-climate models may improve the prediction of soil C cycling under future global warming scenarios.

Ignoring the Effects of Photovoltaic Array Deployment on Greenhouse Gas Emissions May Lead to Overestimation of the Contribution of Photovoltaic Power Generation to Greenhouse Gas Reduction

Photovoltaic (PV) power generation is one of the world's most promising options for carbon emission reduction. However, whether the operation period of solar parks can increase greenhouse gas (GHG) emissions in hosting natural ecosystems has not been fully considered. Here, we conducted a field experiment to compensate for the lack of evaluation of the effects of PV array deployment on GHG emissions. Our results show that the PV arrays caused significant differences in air microclimate, soil properties, and vegetation characteristics. Simultaneously, PV arrays had more significant effects on CO₂ and N₂O emissions but a minor impact on CH₄ uptake in the growing season. Of all the environmental variables included, soil temperature and moisture were the main drivers of GHG flux variation. The sustained flux global warming potential from the PV arrays significantly increased by 8.14% compared to the ambient grassland. Our evaluation models identified that the GHG footprint of PV arrays during the operation period on grasslands was 20.62 g CO₂-eq kW h^-1. Compared with our model estimates, GHG footprint estimates reported in previous studies were generally less by 25.46-50.76%. The contribution of PV power generation to GHG reduction may be overestimated without considering the impact of PV arrays on hosting ecosystems.

Effects of no-tillage on greenhouse gas emissions in maize fields in a semi-humid temperate climate region

Agricultural tillage practices have a significant impact on the generation and consumption of greenhouse gases (GHGs), the primary causes of global warming. Two tillage systems, conventional tillage (CT) and no-tillage (NT), were compared to evaluate their effects on GHG emissions in this study. Averaged from 2018 to 2020, significant decreases of CO₂ and N₂O emissions by 7.4% and 51.1% were observed in NT as compared to those of CT. NT was also found to inhibit the soil CH₄ uptake. In this study, soil was a source of CO₂ and N₂O but a sink for CH₄. The effect of soil temperature on the fluxes of CO₂ was more pronounced than that of soil moisture. However, soil temperature and soil moisture had a weak correlation with CH₄ and N₂O flux variations. As compared to CT, NT did not affect maize yields but significantly reduced global warming potential (GWP) by 8.07%. For yield-scaled GWP, no significant difference was observed in NT (9.63) and CT (10.71). Taken together, NT was an environment-friendly tillage practice to mitigate GHG emissions in the soil under the tested conditions.

Long term impact of residue management on soil organic carbon stocks and nitrous oxide emissions from European croplands

Application of crop residues to agricultural fields is a significant source of the greenhouse gas nitrous oxide (N₂O) and an essential factor affecting the soil organic carbon (SOC) balance. Here we present a biogeochemical modelling study assessing the impact of crop residue management on soil C stocks and N₂O fluxes for EU-27 using available information on soils, management and climate and by testing various scenarios of residue management. Three biogeochemical models, i.e. CERES-EGC, LandscapeDNDC and LandscapeDNDC-MeTrx, were used in an ensemble approach on a grid of 0.25° × 0.25° spatial resolution for calculating EU-27 wide inventories of changes in SOC stocks and N₂O emissions due to residue management for the years 2000-2100 using different climate change projections (RCP4.5 and RCP8.5). Our results show, that climate change poses a threat to cropping systems in Europe, resulting in potential yield declines, increased N₂O emissions and loss of SOC. This highlights the need for adapting crop management to mitigate climate change impacts, e.g. by improved residue management. For a scenario with 100% residues retention and reduced tillage we calculated that in average SOC stocks may increase over 50-100 years by 19-23% under RCP8.5 and RCP4.5. However, complete retention of crop residues also resulted in an increase of soil N₂O emissions by 17-30%, so that climate benefits due to increases in SOC stocks were eventually compensated by increased N₂O emissions. The long-term EF_N2O for residue N incorporation was 1.18% and, thus slightly higher as the 1% value used by IPCC. We conclude that residue management can be an important strategy for mitigating climate change impacts on SOC stocks, though it requires as well improvements in N management for N₂O mitigation.

Mitigated Greenhouse Gas Emissions in Cropping Systems by Organic Fertilizer and Tillage Management

Cultivating ecological benefits in agricultural systems through greenhouse gas emission reduction will offer extra economic benefits for farmers. The reported studies confirmed that organic fertilizer application could promote soil carbon sequestration and mitigate greenhouse gas emissions under suitable tillage practices in a short period of time. Here, a field experiment was conducted using a two-factor randomized block design (organic fertilizers and tillage practices) with five treatments. The results showed that the application of microbial fertilizers conserved soil heat and moisture, thereby significantly reducing CO2 emissions (6.9–18.9%) and those of N2O and CH4 fluxes during corn seasons, compared with chemical fertilizer application. Although deep tillage increased total CO2 emissions by 4.9–37.7%, it had no significant effect on N2O and CH4 emissions. Application of microbial organic fertilizer increased corn yield by 21.5%, but it had little effect on the yield of wheat. Overall, application of microbial fertilizers significantly reduced soil GHG emission and concurrently increased yield under various tillage practices in a short space of time. With this, it was critical that microbial fertilizer be carefully studied for application in wheat–corn cropping systems.

Effects of warming and precipitation changes on soil GHG fluxes: A meta-analysis

Increased atmospheric greenhouse gas (GHG) concentrations resulting from human activities lead to climate change, including global warming and changes of precipitation patterns worldwide, which in turn would have profound effects on soil GHG emissions. Nonetheless, the impact of the combination of warming and precipitation changes on all three major biogenic GHGs (CO₂, CH₄ and N₂O) has not been synthesized, to build a global synthesis. In this study, we conducted a global meta-analysis concerning the effects of warming and precipitation changes and their interactions on soil GHG fluxes and explored the potential factors by synthesizing 39 published studies worldwide. Across all studies, combination of warming and increased precipitation showed more significant effect on CO₂ emissions (24.0%) than the individual effect of warming (8.6%) and increased precipitation (20.8%). Additionally, warming increased N₂O emissions (28.3%), and decreased precipitation reduced CO₂ (-8.5%) and N₂O (-7.1%) emissions, while the combination of warming and decreased precipitation also showed negative effects on CO₂ (-7.6%) and N₂O (-14.6%) emissions. The interactive effects of warming and precipitation changes on CO₂ emissions were usually additive, whereas CO₂ and N₂O emissions were dominated by synergistic effects under warming and decreased precipitation. Moreover, climate, biome, duration, and season of manipulations also affected soil GHG fluxes as well. Furthermore, we also found the threshold effects of changes in soil temperature and moisture on CO₂ and N₂O emissions under warming and precipitation changes. The findings indicate that both warming and precipitation changes substantially affect GHG emissions and highlight the urgent need to study the effect of the combination of warming and precipitation changes on C and N cycling under ongoing climate change.

Evaluation of no-tillage impacts on soil respiration by 13C-isotopic signature in North China Plain

It is a challenge to characterize soil respiration of crop residue return systems in the North China Plain (NCP) under no-tillage (NT) and conventional tillage (CT) practices. In this study, we addressed the "hot spot" research challenge of impacts of tillage practices on soil carbon storage and soil CO₂ emissions in the NCP by ¹³C-isotopic signature. A short-term (2018-2020) field experiment was conducted with two tillage practices: NT and CT. The results showed that in the tested area, NT had advantages of lower CO₂ emissions compared to CT with average reduced CO₂ emissions by 10.82%-19.14%. The results of this study suggested that the NT facilitated enhanced soil carbon storage by 2.80%, which was evidenced by the δ¹³C data. Based on the path analysis model, the main line of soil respiration reduced by NT was attributed to the increased of soil microbial carbon and nitrogen as well as soil moisture in NT, which further increased δ¹³C and eventually inhibited soil respiration. Overall, adopting NT in NCP is an effective means to improve soil carbon pool and decrease soil CO₂ emissions in agriculture practices.

Greenhouse gas emissions from the wheat-maize cropping system under different tillage and crop residue management practices in the North China Plain

With increasing attention being placed on mitigating global warming and achieving agricultural sustainable intensification, conservation agriculture practices have gradually been implemented in the North China Plain (NCP). However, there are still knowledge gaps on the effects of conservation practices on greenhouse gas (GHG) emissions in this area. In this study, a four-year field experiment was conducted from 2014 to 2018 to assess the effects of tillage and crop residue management practices on the emissions of nitrous oxide (N₂O) and methane (CH₄). Subsequently, crop yields, area-scaled and yield-scaled total non-carbon dioxide (CO₂) GHG emissions were assessed. Our research found that no-till (NT) decreased N₂O emissions by 22.6% compared with conventional tillage (CT) in winter wheat (Triticum aestivum L.) seasons, but there was no difference between tillage practices in summer maize (Zea mays L.) seasons. Crop residue retention practice (+R) increased N₂O emissions by 28.1% and 26.7% compared with residue removal practice (-R) in winter wheat and summer maize seasons, respectively. The NT soils took up more CH₄ compared with the CT soils in summer maize seasons. Area-scaled total non-CO₂ GHG emissions showed trends similar to those of N₂O emission. Since crop residue retention improved the maize yield compared with the residue removal treatments, yield-scaled total non-CO₂ GHGs emission did not differ between residue management practices in summer maize seasons. Our four-year field measurements indicated that no-till practice could be more useful as an option to mitigate non-CO₂ GHG emissions in the wheat - maize cropping system.

The club convergence of green productivity across African countries

This study investigates economic convergence and sustainable development in Africa. By introducing an aggregate production technology and directional distance function, it examines the productivity growth of 28 African economies from 1990 to 2019. The proposed approach considers all decision-making units (countries) as a whole, and the productivity gains are then estimated under a nonparametric framework. In the empirical analysis, the carbon emissions are included in the Luenberger productivity measurement, called green productivity. The results show that the annual average growth rate of green productivity is 1.51% in African, and different types of club convergence for green productivity indicator and its decomposition are observed during the sample period. The decomposition of the Luenberger indicator shows that green African growth is mainly driven by technological progress, not efficiency change. Furthermore, the overall inefficiency is decomposed into technical and structural effects. The latter measure the potential improvement in terms of resource reallocation. Structural inefficiency is larger than technical inefficiency, suggesting that African countries could improve their economic and environmental performances by optimizing input/output mixes.

Influence of no-tillage and precipitation pulse on continuous soil respiration of summer maize affected by soil water in the North China Plain

Soil respiration (R_S) from cropland in response to tillage practices contribute to global climate change. We quantified the effect of no-tillage (NT) and conventional tillage (CT) on R_S and precipitation in the North China Plain (NCP). An in-situ automatic sampling and measurement method was applied during the maize (Zea mays L.) growth stages in 2018 and 2019. The continuous daily R_S, soil water content and temperature were monitored during all the maize growth stages, whereas maize grain yield, aboveground biomass, and soil microbial biomass were measured after harvest. The mean R_S across tillage practices on bright days was higher in 2018 (16.69 g CO₂ m^-2 d^-1) than that in 2019 (12.99 g CO₂ m^-2 d^-1). Compared with CT, NT increased R_S on bright days by 31.44% in 2018 and 15.60% in 2019. However, mean R_S on rain-affected days across tillage practices was lower in 2018 than that in 2019. NT increased mean R_S after precipitation in 2018 (p < 0.05). The contribution of R_S after precipitation to cumulative R_S (across tillage practices) was higher in 2019 (51.90%) than that in 2018 (41.18%). Mean soil water content and temperature were higher in 2018 than that in 2019 (p < 0.05). NT increased soil water content on bright days in 2019. Furthermore, soil water content was more important in regulating R_S in 2018, while soil temperature was more critical after precipitation in 2019. Crop productivity was lower in 2019 than in 2018 (p < 0.05). However, neither crop productivity nor soil microbial biomass varied with tillage practices (p > 0.05). Overall, influence of tillage practices and precipitation on R_S were different according to soil water content. Therefore, it is necessary to decrease excessive irrigation to reduce R_S in dry years and to conduct continuous observations on R_S after precipitation in the NCP.

Decomposition and decoupling analysis of carbon dioxide emissions in African countries during 1984‒2014

The potential for mitigating climate change is growing worldwide, with an increasing emphasis on reducing CO₂ emissions and minimising the impact on the environment. African continent is faced with the unique challenge of climate change whilst coping with extreme poverty, explosive population growth and economic difficulties. CO₂ emission patterns in Africa are analysed in this study to understand primary CO₂ sources and underlying driving forces further. Data are examined using gravity model, logarithmic mean divisia index and Tapio's decoupling indicator of CO₂ emissions from economic development in 20 selected African countries during 1984-2014. Results reveal that CO₂ emissions increased by 2.11% (453.73 million ton) over the research period. Gravity centre for African CO₂ emissions had shifted towards the northeast direction. Population and economic growth were primary driving forces of CO₂ emissions. Industrial structure and emission efficiency effects partially offset the growth of CO₂ emissions. The economic growth effect was an offset factor in central African countries and Zimbabwe due to political instability and economic mismanagement. Industrial structure and emission efficiency were insufficient to decouple economic development from CO₂ emissions and relieve the pressure of population explosion on CO₂ emissions in Africa. Thus, future efforts in reducing CO₂ emissions should focus on scale-up energy-efficient technologies, renewable energy update, emission pricing and long-term green development towards sustainable development goals by 2030.

Comparison of Soil Greenhouse Gas Fluxes during the Spring Freeze–Thaw Period and the Growing Season in a Temperate Broadleaved Korean Pine Forest, Changbai Mountains, China

Soils in mid-high latitudes are under the great impact of freeze–thaw cycling. However, insufficient research on soil CO2, CH4, and N2O fluxes during the spring freeze–thaw (SFT) period has led to great uncertainties in estimating soil greenhouse gas (GHG) fluxes. The present study was conducted in a temperate broad-leaved Korean pine mixed forest in Northeastern China, where soils experience an apparent freeze–thaw effect in spring. The temporal variations and impact factors of soil GHG fluxes were measured during the SFT period and growing season (GS) using the static-chamber method. The results show that the soil acted as a source of atmospheric CO2 and N2O and a sink of atmospheric CH4 during the whole observation period. Soil CO2 emission and CH4 uptake were lower during the SFT period than those during the GS, whereas N2O emissions were more than six times higher during the SFT period than that during the GS. The responses of soil GHG fluxes to soil temperature (Ts) and soil moisture during the SFT and GS periods differed. During the SFT period, soil CO2 and CH4 fluxes were mainly affected by the volumetric water content (VWC) and Ts, respectively, whereas soil N2O flux was influenced jointly by Ts and VWC. The dominant controlling factor for CO2 was Ts during the GS, whereas CH4 and N2O were mainly regulated by VWC. Soil CO2 and N2O fluxes accounted for 97.3% and 3.1% of the total 100-year global warming potential (GWP100) respectively, with CH4 flux offsetting 0.4% of the total GWP100. The results highlight the importance of environmental variations to soil N2O pulse during the SFT period and the difference of soil GHG fluxes between the SFT and GS periods, which contribute to predicting the forest soil GHG fluxes and their global warming potential under global climate change.

Effects of soil warming and increased precipitation on greenhouse gas fluxes in spring maize seasons in the North China Plain

Climatic changes, such as global warming and altered precipitation are of major environmental concern. Given that ecosystem processes are strongly regulated by temperature and water content, climate changes are expected to affect the carbon (C) and nitrogen (N) cycles, especially in agricultural systems. However, the interactive effects of soil warming and increased precipitation on greenhouse gas emissions are poorly understood, particularly in the North China Plain (NCP). Therefore, a field experiment was conducted over two spring maize seasons (May-Sept.) in 2018 and 2019. Two levels of temperature (T0: ambient temperature; T1: increase on average of 4.0 °C) combined with two levels of precipitation (W0: no artificial precipitation; W1: +30% above ambient precipitation) were carried out in the NCP. Our results showed that soil warming significantly promoted cumulative N₂O and CO₂ emissions by 49% and 39%, respectively. Additionally, increased precipitation further enhanced the N₂O and CO₂ emissions by 54% and 14%, respectively. This suggests that high soil temperature and water content have the capacity to stimulate microbial activities, and thus accelerate the soil C and N cycles. Soil warming increased CH₄ uptake by 293%, but increased precipitation had no effect on CH₄ fluxes. Overall, soil warming and increased precipitation significantly enhanced the GHG budget by 39% and 16%, respectively. This study suggests that climate warming will lead to enhanced GHG emissions in the spring maize season in the NCP, while increased precipitation in the future may further stimulate GHG emissions in a warming world.

Terrestrial N2 O emissions and related functional genes under climate change: A global meta-analysis

Nitrous oxide (N₂ O) emissions from soil contribute to global warming and are in turn substantially affected by climate change. However, climate change impacts on N₂ O production across terrestrial ecosystems remain poorly understood. Here, we synthesized 46 published studies of N₂ O fluxes and relevant soil functional genes (SFGs, that is, archaeal amoA, bacterial amoA, nosZ, narG, nirK and nirS) to assess their responses to increased temperature, increased or decreased precipitation amounts, and prolonged drought (no change in total precipitation but increase in precipitation intervals) in terrestrial ecosystem (i.e. grasslands, forests, shrublands, tundra and croplands). Across the data set, temperature increased N₂ O emissions by 33%. However, the effects were highly variable across biomes, with strongest temperature responses in shrublands, variable responses in forests and negative responses in tundra. The warming methods employed also influenced the effects of temperature on N₂ O emissions (most effectively induced by open-top chambers). Whole-day or whole-year warming treatment significantly enhanced N₂ O emissions, but daytime, nighttime or short-season warming did not have significant effects. Regardless of biome, treatment method and season, increased precipitation promoted N₂ O emission by an average of 55%, while decreased precipitation suppressed N₂ O emission by 31%, predominantly driven by changes in soil moisture. The effect size of precipitation changes on nirS and nosZ showed a U-shape relationship with soil moisture; further insight into biotic mechanisms underlying N₂ O emission response to climate change remain limited by data availability, underlying a need for studies that report SFG. Our findings indicate that climate change substantially affects N₂ O emission and highlights the urgent need to incorporate this strong feedback into most climate models for convincing projection of future climate change.

Variations in Greenhouse Gas Fluxes in Response to Short-Term Changes in Weather Variables at Three Elevation Ranges, Wakiso District, Uganda

Weather conditions are among the major factors leading to the increasing greenhouse gas (GHG) fluxes from the agricultural soils. In this study, variations in the soil GHG fluxes with precipitation and soil temperatures at different elevation ranges in banana–coffee farms, in the Wakiso District, Uganda, were evaluated. The soil GHG fluxes were collected weekly, using the chamber method, and analyzed by using gas chromatography. Parallel soil temperature samples were collected by using a REOTEMP soil thermometer. Daily precipitation was measured with an automated weather station instrument installed on-site. The results showed that CO2, N2O, and CH4 fluxes were significantly different between the sites at different elevation ranges. Daily precipitation and soil temperatures significantly (p < 0.05) affected the soil GHG fluxes. Along an elevation gradient, daily precipitation and soil temperatures positively associated with the soil GHG fluxes. The combined factors of daily precipitation and soil temperatures also influence the soil GHG fluxes, but their effect was less than that of the single effects. Overall, daily precipitation and soil temperatures are key weather factors driving the soil GHG fluxes in time and space. This particular study suggests that agriculture at lower elevation levels would help reduce the magnitudes of the soil GHG fluxes. However, this study did not measure the soil GHG fluxes from the non-cultivated ecosystems. Therefore, future studies should focus on assessing the variations in the soil GHG fluxes from non-cultivated ecosystems relative to agriculture systems, at varying elevation ranges.

Factor decomposition of carbon emissions in Chinese megacities

In this article, per capita urban carbon emissions were decomposed into manufacturing, transportation, and construction sectors using logarithmic mean Divisia index (LMDI) method. This new decomposition method can provide information about specific drivers of carbon emissions, including urban growth and resident living standards, rather than general demographic and economic factors identified by traditional methods. Using four Chinese megacities (Beijing, Tianjin, Shanghai, and Chongqing) as case studies, we analyzed the factors that influenced per capita carbon emissions from 2010 to 2015. The results showed that per capita carbon emissions increased in Tianjin and Chongqing whereas decreased in Beijing and Shanghai, and that manufacturing was a key driving force. In these four megacities, energy conservation strategies were successfully implemented despite poor energy structure optimization during 2010-2015. Development of manufacturing and improvement of resident living standards in the cities led to an increase in carbon emissions. The unique dual-core urban form of Tianjin might mitigate the increased carbon emissions caused by the transportation sector. Reductions in carbon emissions could be achieved by further optimizing energy structures, limiting the number of private cars, and controlling per capita construction.

Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen

The construction of a reasonable evaluation index system for low-carbon cities is an important part of China’s green development strategy in urban areas. In this study, based on the theoretical framework for the concept of low-carbon cities, the perspectives from three index systems—that is, the Drivers, Pressures, State, Impact, Response model of intervention (DPSIR), a complex ecosystem, and a carbon source/sink process—were integrated to extract common indicators from existing evaluation index systems for low-carbon cities. Subsequently, a standardized evaluation index system for low-carbon cities that contained five indicators—carbon emission, low carbon production, low carbon consumption, low-carbon policy, and social economic development—was established. Thereafter, Xiamen was selected for an empirical analysis by determining the indicator weight with an entropy weight method and by carrying out a comprehensive evaluation using a linear summation model. The results showed that the weights of the five selected primary indicators for the evaluation of low-carbon cities were: low-carbon production > low-carbon consumption > social economic development > carbon emission > low-carbon policy. Among the secondary indicators, the average entropy weight of “pollution emission” was the highest at 0.1591, while the average entropy weight of “urbanization rate” was the lowest at 0.0360. Furthermore, the comprehensive index of low-carbon development in 2015 was higher than that in 2010, while the rate of economic growth was greater than the growth rate of carbon emission, which indicated that the relative decoupling of economic growth from carbon emission was basically achieved.

Effects of turbulence on carbon emission in shallow lakes

Turbulent mixing is enhanced in shallow lakes. As a result, exchanges across the air-water and sediment-water interfaces are increased, causing these systems to be large sources of greenhouse gases. This study investigated the effects of turbulence on carbon dioxide (CO₂) and methane (CH₄) emissions in shallow lakes using simulated mesocosm experiments. Results demonstrated that turbulence increased CO₂ emissions, while simultaneously decreasing CH₄ emissions by altering microbial processes. Under turbulent conditions, a greater fraction of organic carbon was recycled as CO₂ instead of CH₄, potentially reducing the net global warming effect because of the lower global warming potential of CO₂ relative to CH₄. The CH₄/CO₂ flux ratio was approximately 0.006 under turbulent conditions, but reached 0.078 in the control. The real-time quantitative PCR analysis indicated that methanogen abundance decreased and methanotroph abundance increased under turbulent conditions, inhibiting CH₄ production and favoring the oxidation of CH₄ to CO₂. These findings suggest that turbulence may play an important role in the global carbon cycle by limiting CH₄ emissions, thereby reducing the net global warming effect of shallow lakes.