Real-road NOx and CO2 emissions of city and highway China-6 heavy-duty diesel vehicles.

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.

Growth, Morphology and Respiratory Cost Responses to Salinity in the Mangrove Plant Rhizophora Stylosa Depend on Growth Temperature.

Mangrove plants, which have evolved to inhabit tidal flats, may adjust their physiological and morphological traits to optimize their growth in saline habitats. Furthermore, the confined distribution of mangroves within warm regions suggests that warm temperature is advantageous to their growth in saline environments. We analyzed growth, morphology and respiratory responses to moderate salinity and temperature in a mangrove species, Rhizophora stylosa. The growth of R. stylosa was accelerated in moderate salinity compared with its growth in fresh water. Under warm conditions, the increased growth is accompanied by increased specific leaf area (SLA) and specific root length. Low temperature resulted in a low relative growth rate due to a low leaf area ratio and small SLA, regardless of salinity. Salinity lowered the ratio of the amounts of alternative oxidase to cytochrome c oxidase in the mitochondrial respiratory chain in leaves. Salinity enhanced the leaf respiration rate for maintenance, but under warm conditions this enhancement was compensated by a low leaf respiration rate for growth. In contrast, salinity enhanced overall leaf respiration rates at low temperature. Our results indicate that under moderate saline conditions R. stylosa leaves require warm temperatures to grow with a high rate of resource acquisition without enhancing respiratory cost.

Evaluating and optimizing environmental tax, carbon trading scheme and renewable portfolio standard in China: An E-DSGE model.

In the pursuit of multifaceted objectives encompassing energy, environment, and climate considerations, a prevalent phenomenon across various nations is the simultaneous implementation of diverse policies. These policies may exhibit synergies that mutually reinforce each other, while also entailing the risk of policy failure. This study constructs an environmental dynamic stochastic general equilibrium (E-DSGE) model to evaluate and optimize the policy mix in China, incorporating the environmental tax (APT), carbon emission trading scheme (CET), and renewable portfolio standard (RPS). Regarding policy evaluation, we observe that (1) the effective range of both CET and RPS decreases with the increasing intensity of other policies; for instance, with RPS at 18% and APT at 3 CNY/kg, the CO2 emission cap must be below 93.56%; (2) all three policies exhibit automatic stabilizer functions, and policy failure weakens their stabilizing effects, resulting in a reduction in welfare. Concerning policy optimization, we observe that (1) from a static perspective, the optimal tax rate is 32.68 CNY/kg, the optimal CO2 emission cap is 66.62%, and the optimal renewable energy proportion is 62.4%; (2) from a dynamic perspective, the optimal tax rate, quantity of CO2 quota (or CO2 emission cap), and renewable energy proportion all exhibits pro-cyclical patterns.

Towards sustainable development: Examining renewable energy consumption in E-7 countries.

In the contemporary landscape, sustainable development became major challenge for the economy which is tackled if environmental issues are resolved. In this regard, this study investigate renewable energy, institutional quality, foreign direct investment (FDI), economic growth on environmental pollution in E-7 countries (Brazil, Russia, China, Indonesia, India, Mexico, and Turkey). Utilizing annual data from 2002 to 2023, selected the panel Nonlinear Autoregressive Distributed Lag (NARDL) after applying stationary process. The results depict that there is short and long run relationship among the selected variables, CO2 emissions exhibit an asymmetrical response to positive and negative shocks in exogenous variables. A one-percent change in FDI, GDP, IQ and EC reduce the carbon emission. Our research concludes with policy recommendation that prioritize priorities economic growth and environmental sustainability. To achieve a healthy environment and sustainable growth in the E7 countries, it is essential to strengthen institutional frameworks, encourage green investments, and foster technical innovation.

Efficient arsenic removal from water using iron-impregnated low-temperature biochar derived from henequen fibers: performance, mechanism, and LCA analysis.

The present study aims to investigate the low-energy consumption and high-efficiency removal of arsenic from aqueous solutions. The designed adsorbent Fe/TBC was synthesized by impregnating iron on torrefaction henequen fibers. Isothermal adsorption experiments indicated maximum adsorption capacities of 7.30 mg/g and 8.98 mg/g for arsenic(V) at 25.0 °C and 40.0 °C, respectively. The interference testing showed that elevated levels of pH, HCO3- concentration, and humic acid content in the solution could inhibit the adsorption of arsenic by Fe/TBC. Characterization of the adsorbent before and after adsorption using FTIR and SEM-EDS techniques confirmed arsenic adsorption mechanisms, including pore filling, electrostatic interaction, surface complexation, and H-bond adhesion. Column experiments were conducted to treat arsenic-spiked water and natural groundwater, with effective treatment volumes of 550 mL and 8792 mL, respectively. Lastly, the life cycle assessment (LCA) using OpenLCA 2.0.3 software was performed to treat 1 m3 of natural groundwater as the functional unit. The results indicated relatively significant environmental impacts during the Fe/TBC synthesis stage. The global warming potential resulting from the entire life cycle process was determined to be 0.8 kg CO2-eq. The results from batch and column experiments, regeneration studies, and LCA analysis indicate that Fe/TBC could be a promising adsorbent for arsenic(V).

Assessment of thermal power plant CO2 emissions quantification performance and uncertainty of measurements by ground-based remote sensing.

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.

PBAT biodegradable microplastics enhanced organic matter decomposition capacity and CO2 emission in soils with and without straw residue.

Recent studies show that biodegradable microplastics (BMPs) could increase soil CO2 emission, but whether altered carbon emission results from modified soil organic matter (SOM) decomposition remains underexplored. In this study, the effect and mechanisms of BMPs on CO2 emission from soil were investigated, using poly(butylene adipate-co-terephthalate) (PBAT, the main component of agricultural film) as an example. Considering that straw returning is a common agronomic measure which may interact with microplastics through affecting microbial activity, both soils with and without wheat straw were included. After 120 d, 1 % (w/w) PBAT BMPs ificantly increased cumulative CO2 emission by 1605.6 and 1827.7 mg C kg-1 in soils without and with straw, respectively. Cracks occurred on the surface of microplastics, indicating that CO2 was partly originated from plastic degradation. Soil dissolved organic matter (DOM) content, carbon degradation gene abundance (such as abfA, xylA and manB for hemicellulose, mnp, glx and lig for lignin, and chiA for chitin) and enzyme activities increased, which significantly positively correlated with CO2 emission rate (p < 0.05), suggesting that PBAT enhanced carbon emission by stimulating the decomposition of SOM (and possibly the newly added straw) via co-metabolism and nitrogen mining. This is supported by DOM molecular composition analysis which also demonstrated stimulated turnover of carbohydrates, amino sugars and lignin following PBAT addition. The findings highlight the potential of BMPs to affect SOM stability and carbon emission.

Assessing the carbon footprint of soybean transportation in Brazil: a network equilibrium model approach.

Brazil has historically invested few resources in its transport infrastructure, leaving gaps and reducing its efficiency. The country presents a high dependence on road transport, which results in increased operational costs and higher greenhouse gas (GHG) emissions. Consequently, the performance of cargo transportation in Brazil has been deteriorating, accompanied by a rise in the consumption of fossil fuels and noteworthy levels of GHG emissions. This article assesses the carbon intensity of soybean transport operations within Brazil. Utilizing a network equilibrium model, this study estimated the soybean transportation flows that minimize the total cost of transporting this product across the origins and destinations within the grain handling system. The modeling also calculated the GHG emissions in transportation. The results show that the transportation of soybeans produced 2.74 million tonnes of CO2 equivalent annually, with road transport accounting for 81.7% of these emissions. The state of Mato Grosso, responsible for 44.08 kg CO2 equivalent per tonne of soybeans transported, contributed almost 49% of the total emissions due to the extensive distances involved. In contrast, states like Paraná and Rio Grande do Sul, located closer to southern ports, exhibited the lowest emissions, with rates of 11.55 kg CO2 eq/t and 12.52 kg CO2 eq/t, respectively. The analysis highlights the significant potential for reducing GHG emissions by increasing the use of rail and barge transport, particularly in high-emission regions such as Mato Grosso.

Modified biochar affects CO2 and N2O emissions from coastal saline soil by altering soil pH and elemental stoichiometry.

The application of biochar in degraded farmland improves soil productivity while achieving the recycling of agricultural waste. The collapse of the physical structure of coastal saline soils will greatly reduce the carbon sequestration potential of biochar. Phosphorus- and magnesium-modified biochar greatly improve the stability of biochar, which endows them with the potential to greatly improve the organic carbon pool of coastal saline soil. However, changes in the properties of modified biochar increase the uncertainty of microbial driven CO2 and N2O release by affecting soil chemistry properties. In this study, through laboratory soil microcosmic experiment, we investigated the effects of magnesium-modified biochar (BCMg) and phosphorus-modified biochar (BCP) on CO2 and N2O releases from coastal saline soils, and further uncovered their potential mechanisms. Compared with unapplied biochar (CK) and unmodified biochar (BC) treatment, BCMg reduced both the releases of CO2 and N2O, and BCP decreased N2O release but enhanced CO2 release. pH is the medium through which BCMg affects the release of CO2 and N2O. Specifically, BCMg increased soil pH above 8.5, which reduced the metabolic activity of the microbial community, and the abundance of bacteria directly or indirectly involved in N2O production, thereby decreasing the releases of CO2 and N2O. The amendment of BCP changed soil elemental stoichiometry causing microbial N-limitation. Increasing CO2 release and decreasing N2O release were strategies for microorganisms to cope with N-limitation. These findings suggested that BCMg is superior to BCP in mitigating greenhouse gas emissions, providing a basis for the application of modified biochar to improve the carbon pool and reduce greenhouse gas emissions of coastal saline soil.

Harnessing the power of AI and IoT for real-time CO2 emission monitoring.

Global CO2 emissions have been an essential topic of the environmental discussion. Still, empirical data is needed to support arguments that high-quality government actions could reduce these emissions. By analyzing data from 137 nations from 2000 to 2020, we offer strong evidence that state policies focused on promoting healthy ecosystems, sustainable economic growth, and transcendent legislative changes are capable of decreasing CO2 emissions. Based on our findings, there are essentially three critical institutional factors that need to be improved for environmental policies to be efficient: the concept of law, which protects citizens' intellectual property rights; citizens' speech, which allows them to participate in elections and represent themselves freely, and the management of corruption. Policies aimed at promoting economic growth, lowering oil and gas use, enhancing the usage of green energy by the public and private sectors, and enhancing such institutional factors are all necessary components of a climate-friendly financial strategy.

Potential of CO2 sequestration by olivine addition in offshore waters: A ship-based deck incubation experiment.

Ocean alkalinity enhancement is considered as an effective atmospheric CO2 removal approach, but currently, little is known about the carbon sequestration potential of implementing olivine addition in offshore waters. We investigated the effect of olivine addition on the seawater carbonate system by carrying out a deck incubation experiment in the Northern Yellow Sea; the dissolution rate of olivine was calculated based on the increase in seawater alkalinity (TA), and the CO2 sequestration potential was evaluated. The results showed that the dissolution of olivine increased seawater TA and decreased partial pressure of CO2, resulting in oceanic CO2 uptake from the atmosphere through sea-air exchange; it also increased seawater pH and mitigated ocean acidification to a certain extent. The addition of 1 ‰ olivine had a more significant effect on the seawater carbonate system than 0.5 ‰ olivine addition. The average dissolution rate constant of olivine was 1.44 ± 0.15 µmol m-2 d-1. Assuming that olivine settles completely on the seabed due to gravity, the theoretically maximum amount of CO2 removed by applying 1 tonne of olivine per square meter area in the Northern Yellow Sea is only 2.0 × 10-4 t/m2. Therefore, when olivine addition is implemented in the offshore waters, it is necessary to consider reducing the olivine size, prolonging the settling time of olivine in the water column; and spreading olivine in well-mixed waters to prolong the residence time through repeated resuspension, thus increasing its potential in carbon sequestration.

Recent CO2 emission and projections in Chinese provinces: New drivers and ensemble forecasting.

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.

Thermal and structural changes of a starch flexible film and cellulosic semi-rigid tray during the biodegradation process under controlled composting conditions.

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 ±â€¯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 %.

Fertilizer use and agricultural practices in the paradox of maize crop production and environmental sustainability.

The enduring existence of pollution presents a substantial danger to human health, natural systems, and social welfare. Human activities mostly generate greenhouse gas emissions, namely carbon dioxide, which negatively impacts the environment. This study used annual datasets to examine the association between maize crop production, maize yield, fertilizer consumption, agricultural land use, and environmental quality in China. In order to identify the positive and negative shocks with the assessment of short- and long-run dynamics, the study used an asymmetric Nonlinear Autoregressive Distributed Lag (NARDL) approach. A Robust Least Squares method was also used to locate the parameters nexus in order to assess the series' robustness. Results from the long-run interaction indicate that the maize crop production and agricultural land use has a positive impact on CO2 emissions with probability values of (0.000), (0.000), and (0.001), (0.780), respectively, via both positive and negative interruptions. Additionally, maize yield exposed a detrimental effect on environmental quality. Results of the robust least squares analysis showed that maize crop production, fertilizer consumption, and agricultural land use had a positive influence on environmental quality, with probability values of (0.000), (0.004), and (0.949), respectively. However, there is an unfavourable relationship between variable maize yields and CO2 emissions. China should play a significant role in seeking to reduce carbon dioxide emissions and adopt the beneficial policies necessary to ensure the environment's long-term sustainability, since these emissions are now a rising issue around the world.

Health-Oriented Emission Control Strategy of Energy Utilization and Its Co-CO2 Benefits: A Case Study of the Yangtze River Delta, China.

Reducing air pollutants and CO2 emissions from energy utilization is crucial for achieving the dual objectives of clean air and carbon neutrality in China. Thus, an optimized health-oriented strategy is urgently needed. Herein, by coupling a CO2 and air pollutants emission inventory with response surface models for PM2.5-associated mortality, we shed light on the effectiveness of protecting human health and co-CO2 benefit from reducing fuel-related emissions and generate a health-oriented strategy for the Yangtze River Delta (YRD). Results reveal that oil consumption is the primary contributor to fuel-related PM2.5 pollution and premature deaths in the YRD. Significantly, curtailing fuel consumption in transportation is the most effective measure to alleviate the fuel-related PM2.5 health impact, which also has the greatest cobenefits for CO2 emission reduction on a regional scale. Reducing fuel consumption will achieve substantial health improvements especially in eastern YRD, with nonroad vehicle emission reductions being particularly impactful for health protection, while on-road vehicles present the greatest potential for CO2 reductions. Scenario analysis confirms the importance of mitigating oil consumption in the transportation sector in addressing PM2.5 pollution and climate change.

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.

Spatiotemporal dynamics and influencing factors of CO2 emissions under regional collaboration: Evidence from the Beijing-Tianjin-Hebei region in China.

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.

A hybrid method of system dynamics and design of experiments for investigating the economic and environmental indicators of electricity industry.

Electricity plays a pivotal role in the socio-economic development of nations. However, heavy reliance on fossil fuels for electricity generation, as observed in Iran, poses significant environmental challenges. This study proposes a novel hybrid methodology that combines system dynamics modeling and Design of Experiments (DOE) to examine economic and environmental indicators within Iran's electricity sector. The system dynamics model delineates four key subsystems: consumption, production, CO2 emissions, and power trade. By integrating DOE into this framework, various economic and environmental metrics are assessed for the year 2040. Through a comprehensive analysis of variable impacts on these indicators, optimal levels are identified to achieve favorable outcomes. Notably, variables such as the allocation coefficient of export income to capacity development and electricity export price emerge as critical determinants. Due to economic, environmental, and economic-environmental indicators, the most appropriate level of allocation of export income towards capacity development is estimated at 30, 10, and 20 percent, respectively. The study recommends allocating 80 % of the capacity development budget to renewable energy sources and 20 % to thermal power plants to optimize future conditions. In business as usual, the Export CO2 emission damage to export income index will be 0.19. In implementing the proposed scenario, according to the economic-environmental index, this value will decrease and reach 1.73E-06, which indicates the improvement of electricity export from the economic-environmental dimension. This research underscores the importance of balancing economic prosperity with environmental sustainability in electricity industry planning and policy formulation.

Evolution and driving factors of inequality in CO2 emissions from agricultural energy consumption in China.

The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China's agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya-Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China's agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

Undervalued dry riverbeds: A key factor in equating intermittent river CO2 emissions to perennial rivers.

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.