Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (887)

Search Parameters:
Keywords = CO2 emission trends

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
27 pages, 3470 KiB  
Article
Spatiotemporal Evolution and Influencing Factors of Carbon Emission Efficiency of Apple Production in China from 2003 to 2022
by Dejun Tan, Juanjuan Cheng, Jin Yu, Qian Wang and Xiaonan Chen
Agriculture 2025, 15(15), 1680; https://doi.org/10.3390/agriculture15151680 - 2 Aug 2025
Viewed by 261
Abstract
Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, [...] Read more.
Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO2e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO2e/ha) and 2014 (6.52 × 107 t CO2e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
Show Figures

Figure 1

15 pages, 1806 KiB  
Article
Drought and Shrub Encroachment Accelerate Peatland Carbon Loss Under Climate Warming
by Fan Lu, Boli Yi, Jun-Xiao Ma, Si-Nan Wang, Yu-Jie Feng, Kai Qin, Qiansi Tu and Zhao-Jun Bu
Plants 2025, 14(15), 2387; https://doi.org/10.3390/plants14152387 - 2 Aug 2025
Viewed by 156
Abstract
Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q10) vary with depth and plant litter input [...] Read more.
Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q10) vary with depth and plant litter input under these stressors remains poorly understood. We incubated peat from two depths with different degrees of decomposition, either alone or incubated with Sphagnum divinum shoots or Betula ovalifolia leaves, under five temperature levels and two moisture conditions in growth chambers. We found that drought and Betula addition increased CO2 emissions in both peat layers, while Sphagnum affected only shallow peat. Deep peat alone or with Betula exhibited higher Q10 than pure shallow peat. Drought increased the Q10 of both depths’ peat, but this effect disappeared with fresh litter addition. The CO2 production rate showed a positive but marginal correlation with microbial biomass carbon, and it displayed a rather similar responsive trend to warming as the microbial metabolism quotient. These results indicate that both deep and dry peat are more sensitive to warming, highlighting the importance of keeping deep peat buried and waterlogged to conserve existing carbon storage. Additionally, they further emphasize the necessity of Sphagnum moss recovery following vascular plant encroachment in restoring carbon sink function in peatlands. Full article
(This article belongs to the Section Plant–Soil Interactions)
Show Figures

Figure 1

19 pages, 2528 KiB  
Systematic Review
The Nexus Between Green Finance and Artificial Intelligence: A Systemic Bibliometric Analysis Based on Web of Science Database
by Katerina Fotova Čiković, Violeta Cvetkoska and Dinko Primorac
J. Risk Financial Manag. 2025, 18(8), 420; https://doi.org/10.3390/jrfm18080420 - 1 Aug 2025
Viewed by 274
Abstract
The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, [...] Read more.
The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article
(This article belongs to the Special Issue Commercial Banking and FinTech in Emerging Economies)
Show Figures

Figure 1

19 pages, 2530 KiB  
Article
Soil Microbiome Drives Depth-Specific Priming Effects in Picea schrenkiana Forests Following Labile Carbon Input
by Kejie Yin, Lu Gong, Xinyu Ma, Xiaochen Li and Xiaonan Sun
Microorganisms 2025, 13(8), 1729; https://doi.org/10.3390/microorganisms13081729 - 24 Jul 2025
Viewed by 311
Abstract
The priming effect (PE), a microbially mediated process, critically regulates the balance between carbon sequestration and mineralization. This study used soils from different soil depths (0–20 cm, 20–40 cm, and 40–60 cm) under Picea schrenkiana forest in the Tianshan Mountains as the research [...] Read more.
The priming effect (PE), a microbially mediated process, critically regulates the balance between carbon sequestration and mineralization. This study used soils from different soil depths (0–20 cm, 20–40 cm, and 40–60 cm) under Picea schrenkiana forest in the Tianshan Mountains as the research object. An indoor incubation experiment was conducted by adding three concentrations (1% SOC, 2% SOC, and 3% SOC) of 13C-labelled glucose. We applied 13C isotope probe-phospholipid fatty acid (PLFA-SIP) technology to investigate the influence of readily labile organic carbon inputs on soil priming effect (PE), microbial community shifts at various depths, and the mechanisms underlying soil PE. The results indicated that the addition of 13C-labeled glucose accelerated the mineralization of soil organic carbon (SOC); CO2 emissions were highest in the 0–20 cm soil layer and decreased trend with increasing soil depth, with significant differences observed across different soil layers (p < 0.05). Soil depth had a positive direct effect on the cumulative priming effect (CPE); however, it showed negative indirect effects through physico-chemical properties and microbial biomass. The CPE of the 0–20 cm soil layer was significantly positively correlated with 13C-Gram-positive bacteria, 13C-Gram-negative bacteria, and 13C-actinomycetes. The CPE of the 20–40 cm and 40–60 cm soil layers exhibited a significant positive correlation with cumulative mineralization (CM) and microbial biomass carbon (MBC). Glucose addition had the largest and most significant positive effect on the CPE. Glucose addition positively affected PLFAs and particularly microbial biomass. This study provides valuable insights into the dynamics of soil carbon pools at varying depths following glucose application, advancing the understanding of forest soil carbon sequestration. Full article
(This article belongs to the Section Environmental Microbiology)
Show Figures

Figure 1

16 pages, 2199 KiB  
Article
Carbon Footprint and Energy Balance Analysis of Rice-Wheat Rotation System in East China
by Dingqian Wu, Yezi Shen, Yuxuan Zhang, Tianci Zhang and Li Zhang
Agronomy 2025, 15(8), 1778; https://doi.org/10.3390/agronomy15081778 - 24 Jul 2025
Viewed by 271
Abstract
The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies [...] Read more.
The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies addressing carbon footprint (CF) and energy balance (EB) at the regional scale and long time series. Therefore, we analyzed the evolution patterns of the CF and EB of the rice-wheat system in Jiangsu Province from 1980 to 2022, as well as their influencing factors. The results showed that the sown area and total yield of rice and wheat exhibited an increasing–decreasing–increasing trend during 1980–2022, while the yield per unit area increased continuously. The CF of rice and wheat increased by 4172.27 kg CO2 eq ha−1 and 2729.18 kg CO2 eq ha−1, respectively, with the greenhouse gas emissions intensity (GHGI) showing a fluctuating upward trend. Furthermore, CH4 emission, nitrogen (N) fertilizer, and irrigation were the main factors affecting the CF of rice, with proportions of 36%, 20.26%, and 17.34%, respectively. For wheat, N fertilizer, agricultural diesel, compound fertilizer, and total N2O emission were the primary contributors, accounting for 42.39%, 22.54%, 13.65%, and 13.14%, respectively. Among energy balances, the net energy (NE) of rice exhibited an increasing and then fluctuating trend, while that of wheat remained relatively stable. The energy utilization efficiency (EUE), energy productivity (EPD), and energy profitability (EPF) of rice showed an increasing and then decreasing trend, while wheat decreased by 46.31%, 46.31%, and 60.62% during 43 years, respectively. Additionally, N fertilizer, agricultural diesel, and compound fertilizer accounted for 43.91–45.37%, 21.63–25.81%, and 12.46–20.37% of energy input for rice and wheat, respectively. Moreover, emission factors and energy coefficients may vary over time, which is an important consideration in the analysis of long-term time series. This study analyzes the ecological and environmental effects of the rice-wheat system in Jiangsu Province, which helps to promote the development of agriculture in a green, low-carbon, and high-efficiency direction. It also offers a theoretical basis for constructing a low-carbon sustainable agricultural production system. Full article
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
Show Figures

Figure 1

30 pages, 9606 KiB  
Article
A Visualized Analysis of Research Hotspots and Trends on the Ecological Impact of Volatile Organic Compounds
by Xuxu Guo, Qiurong Lei, Xingzhou Li, Jing Chen and Chuanjian Yi
Atmosphere 2025, 16(8), 900; https://doi.org/10.3390/atmos16080900 - 24 Jul 2025
Viewed by 383
Abstract
With the ongoing advancement of industrialization and rapid urbanization, the emission of volatile organic compounds (VOCs) has increased significantly. As key precursors of PM2.5 and ozone formation, VOCs pose a growing threat to the health of ecosystems. Due to their complex and [...] Read more.
With the ongoing advancement of industrialization and rapid urbanization, the emission of volatile organic compounds (VOCs) has increased significantly. As key precursors of PM2.5 and ozone formation, VOCs pose a growing threat to the health of ecosystems. Due to their complex and dynamic transformation processes across air, water, and soil media, the ecological risks associated with VOCs have attracted increasing attention from both the scientific community and policy-makers. This study systematically reviews the core literature on the ecological impacts of VOCs published between 2005 and 2024, based on data from the Web of Science and Google Scholar databases. Utilizing three bibliometric tools (CiteSpace, VOSviewer, and Bibliometrix), we conducted a comprehensive visual analysis, constructing knowledge maps from multiple perspectives, including research trends, international collaboration, keyword evolution, and author–institution co-occurrence networks. The results reveal a rapid growth in the ecological impact of VOCs (EIVOCs), with an average annual increase exceeding 11% since 2013. Key research themes include source apportionment of air pollutants, ecotoxicological effects, biological response mechanisms, and health risk assessment. China, the United States, and Germany have emerged as leading contributors in this field, with China showing a remarkable surge in research activity in recent years. Keyword co-occurrence and burst analyses highlight “air pollution”, “exposure”, “health”, and “source apportionment” as major research hotspots. However, challenges remain in areas such as ecosystem functional responses, the integration of multimedia pollution pathways, and interdisciplinary coordination mechanisms. There is an urgent need to enhance monitoring technology integration, develop robust ecological risk assessment frameworks, and improve predictive modeling capabilities under climate change scenarios. This study provides scientific insights and theoretical support for the development of future environmental protection policies and comprehensive VOCs management strategies. Full article
Show Figures

Figure 1

21 pages, 1934 KiB  
Article
Energy Conservation and Carbon Emission Reduction Potentials of Major Household Appliances in China Leveraging the LEAP Model
by Runhao Guo, Aijun Xu and Heng Li
Buildings 2025, 15(15), 2615; https://doi.org/10.3390/buildings15152615 - 23 Jul 2025
Viewed by 285
Abstract
Household appliances constitute the second largest source of residential energy consumption in China, accounting for over 20% of the total and exhibiting a steady growth trend. Despite their substantial impact on energy demand and carbon emissions, a comprehensive analysis of the current status [...] Read more.
Household appliances constitute the second largest source of residential energy consumption in China, accounting for over 20% of the total and exhibiting a steady growth trend. Despite their substantial impact on energy demand and carbon emissions, a comprehensive analysis of the current status and future trends of household appliances in China is still lacking. This study employs the Long-Range Energy Alternatives Planning (LEAP) system to model energy consumption and carbon emissions for five major household appliances (air conditioners, refrigerators, washing machines, TVs, and water heaters) from 2022 to 2052. Three scenarios were analyzed: a Reference (REF) scenario (current trends), an Existing Policy Option (EPO) scenario (current energy-saving measures), and a Further Strengthening (FUR) scenario (enhanced efficiency measures). Key results show that by 2052, the EPO scenario achieves cumulative savings of 1074.8 billion kWh and reduces emissions by 580.7 million metric tons of CO2 equivalent compared to REF. The FUR scenario yields substantially greater benefits, demonstrating the significant potential of strengthened policies. This analysis underscores the critical role of improving appliance energy efficiency and provides vital insights for policymakers and stakeholders aiming to reduce residential sector emissions. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
Show Figures

Figure 1

41 pages, 16361 KiB  
Review
Progress on Sustainable Cryogenic Machining of Hard-to-Cut Material and Greener Processing Techniques: A Combined Machinability and Sustainability Perspective
by Shafahat Ali, Said Abdallah, Salman Pervaiz and Ibrahim Deiab
Lubricants 2025, 13(8), 322; https://doi.org/10.3390/lubricants13080322 - 23 Jul 2025
Viewed by 318
Abstract
The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to [...] Read more.
The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to maintain strength at high operating temperatures. Due to these characteristics, such materials are employed in applications such as aerospace, marine, energy generation, and structural. The purpose of this article is to investigate the machinability of these alloys under various cutting conditions. The purpose of this article is to compare cryogenic cooling and cryogenic processing from the perspective of machinability and sustainability in the manufacturing process. Compared to conventional machining, hybrid techniques, which mix cryogenic and minimal quantity lubricant, led to significantly reduced cutting forces of 40–50%, cutting temperatures and surface finishes by approximately 20–30% and more than 40%, respectively. A carbon footprint is determined by several factors including power consumption, energy requirements, and carbon dioxide emissions. As a result of the cryogenic technology, the energy consumption, power consumption, and CO2 emissions were reduced by 40%, 28%, and 35%. Full article
Show Figures

Figure 1

26 pages, 1579 KiB  
Article
Forecasting Infrastructure Needs, Environmental Impacts, and Dynamic Pricing for Electric Vehicle Charging
by Osama Jabr, Ferheen Ayaz, Maziar Nekovee and Nagham Saeed
World Electr. Veh. J. 2025, 16(8), 410; https://doi.org/10.3390/wevj16080410 - 22 Jul 2025
Viewed by 279
Abstract
In recent years, carbon dioxide (CO2) emissions have increased at the fastest rates ever recorded. This is a trend that contradicts global efforts to stabilise greenhouse gas (GHG) concentrations and prevent long-term climate change. Over 90% of global transport relies on [...] Read more.
In recent years, carbon dioxide (CO2) emissions have increased at the fastest rates ever recorded. This is a trend that contradicts global efforts to stabilise greenhouse gas (GHG) concentrations and prevent long-term climate change. Over 90% of global transport relies on oil-based fuels. The continued use of diesel and petrol raises concerns related to oil costs, supply security, GHG emissions, and the release of air pollutants and volatile organic compounds. This study explored electric vehicle (EV) charging networks by assessing environmental impacts through GHG and petroleum savings, developing dynamic pricing strategies, and forecasting infrastructure needs. A substantial dataset of over 259,000 EV charging records from Palo Alto, California, was statistically analysed. Machine learning models were applied to generate insights that support sustainable and economically viable electric transport planning for policymakers, urban planners, and other stakeholders. Findings indicate that GHG and gasoline savings are directly proportional to energy consumed, with conversion rates of 0.42 kg CO2 and 0.125 gallons per kilowatt-hour (kWh), respectively. Additionally, dynamic pricing strategies such as a 20% discount on underutilised days and a 15% surcharge during peak hours are proposed to optimise charging behaviour and improve station efficiency. Full article
Show Figures

Figure 1

16 pages, 2720 KiB  
Communication
Wildland and Forest Fire Emissions on Federally Managed Land in the United States, 2001–2021
by Coeli M. Hoover and James E. Smith
Forests 2025, 16(8), 1205; https://doi.org/10.3390/f16081205 - 22 Jul 2025
Viewed by 269
Abstract
In the United States, ecosystems regularly experience wildfires and as fire seasons lengthen, fires are becoming a more important disturbance. While all types of disturbance have impacts on the carbon cycle, fires result in immediate emissions into the atmosphere. To assist managers in [...] Read more.
In the United States, ecosystems regularly experience wildfires and as fire seasons lengthen, fires are becoming a more important disturbance. While all types of disturbance have impacts on the carbon cycle, fires result in immediate emissions into the atmosphere. To assist managers in assessing wildland fire impacts, particularly on federally managed land, we developed estimates of area burned and related emissions for a 21-year period. These estimates are based on wildland fires defined by the interagency Monitoring Trends in Burn Severity database; emissions are simulated through the Wildland Fire Emissions Inventory System; and the classification of public land is performed according to the US Geological Survey’s Protected Areas Database of the United States. Wildland fires on federal land contributed 62 percent of all annual CO2 emissions from wildfires in the United States between 2001 and 2021. During this period, emissions from the forest fire subset of wildland fires ranged from 328 Tg CO2 in 2004 to 37 Tg CO2 in 2001. While forest fires averaged 38 percent of burned area, they represent the majority—59 to 89 percent of annual emissions—relative to fires in all ecosystems, including non-forest. Wildland fire emissions on land belonging to the federal government accounted for 44 to 77 percent of total annual fire emissions for the entire United States. Land managed by three federal agencies—the Forest Service, the Bureau of Land Management, and the Fish and Wildlife Service—accounted for 93 percent of fire emissions from federal land over the course of the study period, but year-to-year contributions varied. Full article
(This article belongs to the Section Natural Hazards and Risk Management)
Show Figures

Figure 1

25 pages, 5001 KiB  
Article
Impact of Regional Characteristics on Energy Consumption and Decarbonization in Residential and Transportation Sectors in Japan’s Hilly and Mountainous Areas
by Xiyue Hao and Daisuke Narumi
Sustainability 2025, 17(14), 6606; https://doi.org/10.3390/su17146606 - 19 Jul 2025
Viewed by 410
Abstract
In Japan’s hilly and mountainous areas, which cover over 60% of the national land area, issues such as population outflow, aging, and regional decline are intensifying. This study explored sustainable decarbonization pathways by examining two representative regions (Maniwa City and Hidakagawa Town), while [...] Read more.
In Japan’s hilly and mountainous areas, which cover over 60% of the national land area, issues such as population outflow, aging, and regional decline are intensifying. This study explored sustainable decarbonization pathways by examining two representative regions (Maniwa City and Hidakagawa Town), while accounting for diverse regional characteristics. A bottom-up approach was adopted to calculate energy consumption and CO2 emissions within residential and transportation sectors. Six future scenarios were developed to evaluate emission trends and countermeasure effectiveness in different regions. The key findings are as follows: (1) in the study areas, complex regional issues have resulted in relatively high current levels of CO2 emissions in these sectors, and conditions may worsen without intervention; (2) if the current trends continue, per-capita CO2 emissions in both regions are projected to decrease by only around 40% by 2050 compared to 2020 levels; (3) under enhanced countermeasure scenarios, CO2 emissions could be reduced by >99%, indicating that regional decarbonization is achievable. This study provides reliable information for designing localized sustainability strategies in small-scale, under-researched areas, while highlighting the need for region-specific countermeasures. Furthermore, the findings contribute to the realization of multiple Sustainable Development Goals (SDGs), particularly goals 7, 11, and 13. Full article
(This article belongs to the Section Development Goals towards Sustainability)
Show Figures

Figure 1

22 pages, 1534 KiB  
Article
Predictability of Air Pollutants Based on Detrended Fluctuation Analysis: Ekibastuz Сoal-Mining Center in Northeastern Kazakhstan
by Oleksandr Kuchanskyi, Andrii Biloshchytskyi, Yurii Andrashko, Alexandr Neftissov, Svitlana Biloshchytska and Sergiy Bronin
Urban Sci. 2025, 9(7), 273; https://doi.org/10.3390/urbansci9070273 - 16 Jul 2025
Viewed by 600
Abstract
Environmental comfort and air pollution are among the most important indicators for assessing the population’s quality of life in urban agglomerations. This study aims to explore long-term memory in air pollution time series by analyzing the dynamics of the Hurst exponent and evaluating [...] Read more.
Environmental comfort and air pollution are among the most important indicators for assessing the population’s quality of life in urban agglomerations. This study aims to explore long-term memory in air pollution time series by analyzing the dynamics of the Hurst exponent and evaluating the predictability index. This type of statistical pre-forecast analysis is essential for developing accurate forecasting models for such time series. The effectiveness of air quality monitoring systems largely depends on the precision of these forecasts. The Ekibastuz coal-mining center, which houses one of the largest coal-fired power stations in Kazakhstan and the world, with a capacity of about 4000 MW, was chosen as an example for the study. Data for the period from 1 March 2023 to 31 December 2024 were collected and analyzed at the Ekibastuz coal-fired power station. During the specified period, 14 indicators (67,527 observations) were collected at 10 min intervals, including mass concentrations of CO, NO, NO2, SO2, PM2.5, and PM10, as well as current mass consumption of CO, NO, NO2, SO2, dust, and NOx. The detrended fluctuation analysis of a time series of air pollution indicators was used to calculate the Hurst exponent and identify long-term memory. Changes in the Hurst exponent in regards to dynamics were also investigated, and a predictability index was calculated to monitor emissions of pollutants in the air. Long-term memory is recorded in the structure of all the time series of air pollution indicators. Dynamic analysis of the Hurst exponent confirmed persistent time series characteristics, with an average Hurst exponent of about 0.7. Identifying the time series plots for which the Hurst exponent is falling (analysis of the indicator of dynamics), along with the predictability index, is a sign of an increase in the influence of random factors on the time series. This is a sign of changes in the dynamics of the pollutant release concentrations and may indicate possible excess emissions that need to be controlled. Calculating the dynamic changes in the Hurst exponent for the emission time series made it possible to identify two distinct clusters corresponding to periods of persistence and randomness in the operation of the coal-fired power station. The study shows that evaluating the predictability index helps fine-tune the parameters of time series forecasting models, which is crucial for developing reliable air pollution monitoring systems. The results obtained in this study allow us to conclude that the method of trended fluctuation analysis can be the basis for creating an indicator of the level of air pollution, which allows us to quickly respond to possible deviations from the established standards. Environmental services can use the results to build reliable monitoring systems for air pollution from coal combustion emissions, especially near populated areas. Full article
Show Figures

Figure 1

18 pages, 1414 KiB  
Article
Field Validation of the DNDC-Rice Model for Crop Yield, Nitrous Oxide Emissions and Carbon Sequestration in a Soybean System with Rye Cover Crop Management
by Qiliang Huang, Nobuko Katayanagi, Masakazu Komatsuzaki and Tamon Fumoto
Agriculture 2025, 15(14), 1525; https://doi.org/10.3390/agriculture15141525 - 15 Jul 2025
Viewed by 394
Abstract
The DNDC-Rice model effectively simulates yield and greenhouse gas emissions within a paddy system, while its performance under upland conditions remains unclear. Using data from a long-term cover crop experiment (fallow [FA] vs. rye [RY]) in a soybean field, this study validated the [...] Read more.
The DNDC-Rice model effectively simulates yield and greenhouse gas emissions within a paddy system, while its performance under upland conditions remains unclear. Using data from a long-term cover crop experiment (fallow [FA] vs. rye [RY]) in a soybean field, this study validated the DNDC-Rice model’s performance in simulating soil dynamics, crop growth, and C-N cycling processes in upland systems through various indicators, including soil temperature, water-filled pore space (WFPS), soybean biomass and yield, CO2 and N2O fluxes, and soil organic carbon (SOC). Based on simulated results, the underestimation of cumulative N2O flux (25.6% in FA and 5.1% in RY) was attributed to both underestimated WFPS and the algorithm’s limitations in simulating N2O emission pulses. Overestimated soybean growth increased respiration, leading to the overestimation of CO2 flux. Although the model captured trends in SOC stock, the simulated annual values differed from observations (−9.9% to +10.1%), potentially due to sampling errors. These findings indicate that the DNDC-Rice model requires improvements in its N cycling algorithm and crop growth sub-models to improve predictions for upland systems. This study provides validation evidence for applying DNDC-Rice to upland systems and offers direction for improving model simulation in paddy-upland rotation systems, thereby enhancing its applicability in such contexts. Full article
(This article belongs to the Special Issue Detection and Management of Agricultural Non-Point Source Pollution)
Show Figures

Figure 1

22 pages, 2150 KiB  
Article
Resource Utilization Enhancement and Life Cycle Assessment of Mangosteen Peel Powder Production
by Alisa Soontornwat, Zenisha Shrestha, Thunyanat Hutangkoon, Jarotwan Koiwanit, Samak Rakmae and Pimpen Pornchaloempong
Sustainability 2025, 17(14), 6423; https://doi.org/10.3390/su17146423 - 14 Jul 2025
Viewed by 506
Abstract
In alignment with the United Nations’ Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production) and 13 (Climate Action), this research explores the sustainable valorization of mangosteen peels into mangosteen peel powder (MPP), a value-added product with pharmaceutical properties. Mangosteen peels are an [...] Read more.
In alignment with the United Nations’ Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production) and 13 (Climate Action), this research explores the sustainable valorization of mangosteen peels into mangosteen peel powder (MPP), a value-added product with pharmaceutical properties. Mangosteen peels are an abundant agricultural waste in Thailand. This study evaluates six MPP production schemes, each employing different drying methods. Life Cycle Assessment (LCA) is utilized to assess the global warming potential (GWP) of these schemes, and the quality of the MPP produced is also compared. The results show that a combination of frozen storage and freeze-drying (scheme 4) has the highest GWP (1091.897 kgCO2eq) due to substantial electricity usage, whereas a combination of frozen storage and sun-drying (scheme 5) has the lowest GWP (0.031 kgCO2eq) but is prone to microbial contamination. Frozen storage without coarse grinding, combined with hot-air drying (scheme 6), is identified as the optimal scheme in terms of GWP (11.236 kgCO2eq) and product quality. Due to the lack of an onsite hot-air-drying facility, two transportation strategies are integrated into scheme 6 for scenarios A and B. These transportation strategies include transporting mangosteen peels from orchards to a facility in another province or transporting a mobile hot-air-drying unit to the orchards. The analysis indicates that scenario B is more favorable both operationally and environmentally, due to its lower emissions. This research is the first to comparatively assess the GWP of different MPP production schemes using LCA. Furthermore, it aligns with the growing trend in international trade which places greater emphasis on environmentally friendly production processes. Full article
Show Figures

Figure 1

22 pages, 2101 KiB  
Article
Forecast of CO2 and Pollutant Emission Reductions from Electric Vehicles in Beijing–Tianjin–Hebei
by Li Li, Honglin Liu and Bingchun Liu
Sustainability 2025, 17(14), 6386; https://doi.org/10.3390/su17146386 - 11 Jul 2025
Viewed by 293
Abstract
The promotion of new energy vehicles (NEVs) represents a critical strategy for mitigating carbon emissions and air pollution. To evaluate the CO2 and air pollutant reduction potential of NEVs in the Beijing–Tianjin–Hebei region, this study developed an integrated framework combining gray correlation [...] Read more.
The promotion of new energy vehicles (NEVs) represents a critical strategy for mitigating carbon emissions and air pollution. To evaluate the CO2 and air pollutant reduction potential of NEVs in the Beijing–Tianjin–Hebei region, this study developed an integrated framework combining gray correlation analysis (GRA) and bidirectional long short-term memory (BiLSTM), referred to as the GRA-BiLSTM model, to forecast the adoption trend of NEVs and calculate the CO2 and air pollutant emission reduction. The GRA-BiLSTM model developed in this study shows optimal predictive performance. The results indicate that new energy vehicles (NEVs) have great potential for environmental collaborative emission reduction in the transportation sector: it is predicted that by 2035, the total number of NEVs will be nearly 11.88 million, with a cumulative reduction of 2.76 billion tons of carbon emissions and significant reductions in various key air pollutants. This study provides an important quantitative basis for formulating pollution reduction and carbon reduction policies in the transportation sector. Full article
Show Figures

Figure 1

Back to TopTop