Thermal power plants serve as significant CO2 sources, and accurate monitoring of their emissions is crucial for improving the precision of global carbon emission estimates. In this study, a measurement method based on measuring point source plumes was employed in ground-based remote sensing experiments at the thermal power plant. By simulating CO2 plumes, we analyzed the impact of surrounding urban structures, the geometric relationship between measurement points and plumes, and the influence on measurement points selection. We also assessed the capability and uncertainties in quantifying CO2 emissions. For the Hefei power plant, CO2 emission estimates were on average 7.98 ± 10.01 kg/s higher with surface buildings compared to scenarios without buildings (approximately 4.09% error). By selectively filtering discrete data, the emission estimation errors were significantly reduced by 7.31 ± 7.13 kg/s compared to pre-filtered data. Regarding the relationship between observation paths and plume geometry, simulation studies indicated that the ability to estimate CO2 emissions varied for near and middle segment observations. The lowest emission rate error was found in the mid-segment near 1.5-2.0 km, reaching 7.13 ± 5.39 kg/s. CO2 distribution at the mid-segment position becomes more uniform relative to the near segment, making it more suitable for meeting emission estimation requirements. Optimizing measurement schemes by considering environmental factors and precisely selecting measurement points significantly enhances emission estimation accuracy, providing crucial technical support for top-down estimates of anthropogenic CO2 emissions.

The emission of heavy-duty vehicles has raised great concerns worldwide. The complex working and loading conditions, which may differ a lot from PEMS tests, raised new challenges to the supervision and control of emissions, especially during real-world applications. On-board diagnostics (OBD) technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles. This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals. Real-world NOx and CO2 emissions of China-6 heavy-duty vehicles have been examined. The results showed that city heavy-duty vehicles had higher NOx emission levels, which was mostly due to longer time of low SCR temperatures below 180°C. The application of novel methods based on 3B-MAW also found that heavy-duty diesel vehicles tended to have high NOx emissions at idle. Also, little difference had been found in work-based CO2 emissions, and this may be due to no major difference were found in occupancies of hot running.

Although extensive studies focused on the driver of changing CO2 emission, the roles of labor and capital were largely ignored in shaping spatiotemporal change in CO2 emission and forecasting differences on CO2 emission was few considered, hindering relevant policymaking towards sustainable development in both climate change mitigation and economic growth for developing countries in particular. To fill the gap above, the study explored the roles of capital and labor in contributing to recent CO2 emission in a case of China over 2010-2019 and projecting provincial CO2 emissions to 2030, by proposing two new spatiotemporal logarithmic mean Divisia index models with Cobb-Douglas production function and developing an ensemble forecasting model including machine learning. We found, first, the effects of capital and labor inputs and carbon factor were the positive drivers affecting aggregate CO2 emissions, while the effects of the total-factor productivity and energy intensity were negative drivers. Second, the effects of capital and labor inputs were the negative drivers for narrowing the emission gap. Third, the ensemble forecasting model can improve the generalization ability of CO2 emission predictions. Therefore, we recommend that policymakers focus on optimizing the carbon reduction effects of capital and labor inputs while promoting the development of a circular economy to achieve sustainable economic growth.

Biopolymers used to mitigate the environmental impact needed establish biodegradation percentage. The thermal and structural changes of two plastic materials, a flexible film based on cassava starch - Poly(lactic acid) (PLA) and a semi-rigid cassava flour-stay cellulose fique fiber, were evaluated biodegradation under ISO 4855-1 standard. The tests were carried out for four weeks at constant temperature and flow of 58 °C ± 2 °C and 250 mL/h, using a mature compost as inoculum. The percentages of CO2, thermal, morphological, and structural changes, variation of degradation temperatures, glass transition temperatures (Tg), Melting temperatures (Tm) and enthalpies of fusion (Hm), were properly evaluated as indicators of the materials biodegradation of two materials. Scanning electron microscopy (SEM), showed the microorganisms colonization on the materials surface, evidencing the appearance of cracks and microbial population. The flexible film showed a biodegradation percentage of 98.24 %, the semi-rigid tray 89.06 %, and the microcrystalline cellulose, 81.37 %.

Against the backdrop of global climate change and the \"dual carbon\" target, cities have a significant responsibility to achieve carbon reduction targets. As a crucial urban agglomeration in northern China, effectively balancing economic growth with CO2 emission reduction to achieve high-quality economic development remains a significant challenge that the Beijing-Tianjin-Hebei region should address both presently and in the future. The objective of this study is to utilize nighttime lighting data and energy consumption information to quantify the CO2 emissions of diverse cities within the Beijing-Tianjin-Hebei region spanning from 2006 to 2020. The research aims to analyze the spatial progression patterns of CO2 emissions across these urban centers, identify key determinants and their interrelations, and delve into the underlying mechanisms pivotal for advancing carbon mitigation strategies within urban agglomerations. The results indicate that: with an exception in Beijing where CO2 emissions slightly decreased compared to 2006, CO2 emissions increased across cities in the Beijing-Tianjin-Hebei region by 2020. High-value CO2 emission areas are primarily concentrated in central of the study area, exhibiting negative spatial correlation characteristics. Based on its urban development positioning, it is imperative for the Beijing-Tianjin-Hebei urban agglomeration to formulate and implement carbon reduction strategies on innovative development, industrial upgrading, and ecological protection among other aspects towards coordinated low-carbon development.

This study investigated the impact of climate change, grazing, manure application, and liming on soil organic carbon (SOC) stock and cumulative carbon dioxide (CO2) emissions in forest soils across different altitudes. Despite similar soil texture, acidity, and salinity across elevations, SOC stock significantly increased with altitude due to cooler temperatures and higher precipitation. The highest SOC stock (97.46 t ha-1) was observed at 2000-2500 m, compared to the lowest (44.23 t ha-1) at 500-1000 m. The Century C Model accurately predicted SOC stock, with correlation and determination coefficients exceeding 0.98. A climate change scenario projecting decreased precipitation (2.15 mm per decade) and increased temperature (0.4 °C) revealed potential SOC stock losses ranging from 28.36 to 36.35 %, particularly at higher altitudes. Grazing further decreased SOC stock, with a more pronounced effect at higher elevations. However, manure application (40 t ha-1 every four years) and liming (7-10 t ha-1 every three years) had positive effects on SOC stock, again amplified at higher altitudes and with an increase in lime application rate. In scenarios combining climate change with manure application and climate change with liming, manure application and liming mitigated some negative impacts of climate change, but could not fully offset them, resulting in 1.49-5.42 % and 0.39-4.07 % decreases respectively. Simulations of cumulative CO2 emissions mirrored the distribution of SOC stock, with higher emissions observed at higher altitudes and with management practices that increased SOC stock. This study emphasizes the critical role of conserving high-altitude forest soils and implementing optimal forest management strategies to combat climate change by minimizing SOC losses.

Intermittent rivers in semiarid and arid regions, constituting over half of the world\'s rivers, alternate the carbon cycle interactions among the biosphere, hydrosphere, and atmosphere. Inadequate quantification of flow duration and river water surface area, along with overlooked CO2 emissions from dry riverbeds, result in notable inaccuracies in global carbon cycle assessments. High-resolution remote sensing images combined with intensive field measurements and hydrological modelling were used to estimate and extract the flow duration, river water surface area and dry riverbed area of Huangfuchuan, an intermittent river watershed that acts as a major tributary of the Yellow River in semiarid Northwest China. CO2 emission rates and partial pressures in water and air across the watershed were in-situ measured. In 2018, the flow duration of Huangfuchuan increased from less than 5 days in the first-order tributary to 150 days in the sixth-order mainstream. River water surface area estimated by remote sensing extraction plus the hydrodynamic model simulation varied from 3.9 to 88.6 km2 under 5 %-95 % discharge frequencies. CO2 emissions from the water-air interface and dry riverbed in 2018 were estimated at 582.3 × 103 and 355.2 × 103 ton, respectively. The estimated total annual emission (937.5 × 103 ton) aligns closely with the range of emissions (67.3 × 103-1377.2 × 103 ton) calculated for the water-air interface alone, derived using DEM river length and hydraulic geometry method. This similarity can be attributed to the overestimation of flow duration and flow velocity, as well as the over- or under-estimation of river water surface area and slope. The new method proposed in this study has large potential to be applied in estimating CO2 emissions from data-scarce intermittent rivers located in mountainous regions and provides a standardized solution in the estimation of CO2 emission. Results of this research reveal the spatiotemporal distribution of CO2 emissions along an intermittent river system and highlight the substantial role of dry riverbed in carbon cycle.

Drained peatlands in temperate climates are under threat from climate change and human activities. The resulting decomposition of organic matter plays a major role in regulating the associated land subsidence rates, yet the determinants of aerobic and anaerobic peat decomposition rates are not fully understood. In this study, we sought to gain insight into the drivers of decomposition rates in botanically diverse peatlands (sedge, reed, wood, and moss dominant) under oxic and anoxic conditions. Peat samples were collected from the anoxic zone and incubated for 24 h (short) and 15 weeks (long) under either oxic or anoxic conditions. CO2 emissions, hydrolytic and oxidative exoenzyme potential activities, phenolic compound concentrations, and several edaphic factors were measured at the end of each incubation period. We found that 15 weeks of oxygen exposure of anoxic peat samples accelerated the average CO2 emissions by 3.9-fold. Reed and sedge peat respired more than wood and moss peat under anoxic conditions. Interestingly, CO2 emissions from anoxic peat layers under permanently anoxic conditions were substantial and given the thickness of peat deposits in the field, such activities may play an important role in long-term land subsidence rates and total CO2 emissions from drained peatlands. The results from the long-term incubations showed that decomposition rates appear to be also controlled by factors other than oxygen intrusion such as substrate availability. In summary, the botanical composition of the peat matrix, incubation conditions and time of incubation are all important factors that need to be considered when predicting peat decomposition and subsequent land subsidence rates.

Profound worldwide fleet electrification is thought to be the primary route for achieving the target of carbon neutrality. However, when and how electrification can help mitigate environmental impacts and carbon emissions in the transport sector remains unclear. Herein, the overall life-cycle environmental impacts and carbon saving range of two typical A-class vehicles in China, including electric vehicle (EV) and internal combustion engine vehicle (ICEV), were quantified by the life cycle assessment model for endpoint damage with localization parameters. The results showed that the EV outperformed the ICEV for the total environment impact after a travel distance of 39,153 km and for carbon emissions after 32,292 km. The ICEV was more carbon-friendly only when the driving distance was less than 3229 km/a. Considering a full lifespan travel distance of 150,000 km, the whole life-cycle average environmental impacts of EV and ICEV were calculated as 8.6 and 17.5 mPt/km, respectively, but the EV had 2.3 times higher impacts than the ICEV in the production phase. In addition, the EV unit carbon emission was 140 g/km, 46.8% lower than that of the ICEV. Finally, three potential reduction scenarios were considered: cleaner power mix, energy efficiency improvement and composite scenario. These scenarios contributed 19.1%, 13.0% and 32.1% reductions, respectively. However, achieving carbon peak and neutrality goals in China remains a great challenge unless fossil fuels are replaced by renewable energy. The research can provide scientific reference for the method and practice of emission reduction link identification, eco-driving choice and emission reduction path formulation.

Microplastics (MPs) accumulation in terrestrial ecosystems can affect greenhouse gases (GHGs) production by altering microbial and soil structure. Presently, research on the MPs effect on plants is not consistent, and underlying molecular mechanisms associated with GHGs are yet unknown. For the first time, we conducted a microcosm study to explore the impact of MPs addition (Raw vs. aged) and Trichoderma longibrachiatum and Bacillus subtilis inoculation (Sole vs. combination) on GHGs emission, soil community structure, physiochemical properties, and enzyme activities. Our results indicated that the addition of aged MPs considerably enhanced the GHGs emissions (N2O (+16%) and CO2 (+21%), respectively), C and N cycling gene expression, microbial biomass carbon, and soil physiochemical properties than raw MPs. However, the soil microbial community structure and enzyme activities were enhanced in raw MPs added treatments, irrespective of the MPs type added to soil. However, microbial inoculation significantly reduced GHGs emission by altering the expression of C and N cycling genes in both types of MPs added treatments. The soil microbial community structure, enzymes activities, physiochemical properties and microbial biomass carbon were enhanced in the presence of microbial inoculation in both type of MPs. Among sole and combined inoculation of Trichoderma and Bacillus subtilis, the co-applied Trichoderma and Bacillus subtilis considerably reduced the GHGs emission (N2O (-64%) and CO2 (-61%), respectively) by altering the expression of C and N cycling genes regardless of MPs type used. The combined inoculation also enhanced soil enzyme activities, microbial community structure, physiochemical properties and microbial biomass carbon in both types of MPs treatment. Our findings provide evidence that polyethylene MPs likely pose a high risk of GHGs emission while combined application of Trichoderma and Bacillus subtilis significantly reduced GHGs emission by altering C and N cycling gene expression, soil microbial community structure, and enzyme activities under MPs pollution in a terrestrial ecosystem.