Electrochemical oxidation of organic pollutants and simultaneous capture of generated carbon dioxide in wastewater treatment.

Solar energy is emerging as beneficial renewable energy sources and it is considered as the best choice to be implemented to realize net zero carbon emission target. Compare with other renewable energy systems, solar energy system is more proven technology which marking a pivotal shift in global power production technologies. Indonesia received average solar irradiation about 4.8 kW/m2/day. This huge solar energy potential has to be optimized in order to fulfill energy demand. In the present work, an effect of water cooling on performance of 300 watt peaks solar panel is investigated at different solar irradiation. The performance of the panel evaluated in terms of output current, output voltage, output power, and conversion efficiency. It can be concluded that PV panel cooling gives negative impact on performance of PV panel. The highest output power and conversion efficiency were found at the highest solar irradiation when the panel operated without cooling. The values of maximum power and maximum conversion efficiency are 254.96 W and 84.99%, accordingly.

ABSTRACT The determination of the urban form–carbon relationships has traditionally relied on survey-based estimates, limiting analytical precision. We investigated regional heterogeneity in carbon emissions by linking urban form, socioeconomic factors, and spatial carbon footprint data. This study leveraged South Korea's newly developed Carbon Spatial Map, containing actual energy consumption data from 7.27 million buildings and comprehensive forest carbon absorption measurements, to examine the indirect pathways through which the urban form influences net carbon emissions across 227 municipalities. Using structural equation modelling, we assessed three urban-form variables: residential land share, urban population density, and residential population density. None of them directly affected net per-capita carbon emissions, but all exerted significant indirect effects through transportation, building energy, and carbon absorption pathways. Residential density emerged as the most influential factor, primarily decreasing transportation emissions and seasonal building energy consumption. Green spaces increased carbon absorption but created trade-offs by increasing transport emissions when spatially segregated. Seasonal analysis revealed consistent indirect patterns, with differential effects between summer cooling and winter heating demands. These findings fundamentally shift the focus of urban carbon management from direct impacts to strategic pathway interventions. For evidence-based planning, policies should integrate compact development with efficient transportation, high-performance buildings, and strategically distributed green infrastructure to optimize benefits while managing inherent trade-offs.

The Malaysian government has committed unequivocally to achieve zero net carbon emissions by 2050. Construction sector consequently faces challenges in embracing sustainable development with ESG disclosure becomes critical to investors and other stakeholders in making investment decisions to prevent imminent risk. This study analyses the ESG disclosures of 52 construction firms listed on Bursa Malaysia from year 2020 to 2022 by employing a content analysis approach. Utilising a binary scoring system, the analysis assesses the firms' adherence to the three pillars of ESG. The findings reveal a strong emphasis on the social pillar, with health and safety receiving significant weight. Environmental concerns, particularly pollution and resource disclosure are the highest due to strict regulatory oversight. Meanwhile, the governance pillar, anti-corruption emerged as a primary focus reflecting a commitment to maintaining business integrity. These findings assist regulators, investors, and stakeholders in fostering sustainable business practices within Malaysian construction sector.

Exploring the spatio-temporal pattern， dynamic evolution， and carbon compensation zoning of the county land use carbon budget has great practical significance for territorial spatial pattern optimization and building a fair and effective regional carbon compensation mechanism in the Beijing-Tianjin-Hebei Region. Based on land use cover， nighttime light， and energy consumption data， a land use carbon budget estimation model was constructed in the Beijing-Tianjin-Hebei Region area. Based on the exploratory spatial data analysis method and kernel density estimation， the spatio-temporal pattern and dynamic evolution trend of carbon emissions were analyzed. The economic value of carbon offsetting was calculated based on the carbon offsetting value model. Finally， carbon compensation zoning was carried out based on K-means clustering combined with ecological function zoning. The results indicated that： ① The fitting R2 of the indirect carbon emission estimation model for construction land was 0.776 8， with good simulation accuracy and the estimation effect meeting the expected standards. ② The carbon sink in the Beijing-Tianjin-Hebei Region showed a continuous growth trend； the carbon source showed a decreasing trend after peaking； and the overall increase in net carbon emissions was consistent with the carbon source and exhibited significant positive spatial correlation， with four types of aggregation patterns. ③ The absolute difference in net carbon emissions between districts and counties in the Beijing-Tianjin-Hebei Region as a whole， Tianjin， and Hebei Province showed a trend of expansion， while the absolute difference in net carbon emissions between districts in Beijing shifted from expansion to a trend of narrowing. The tailing effect in the Beijing-Tianjin-Hebei region as a whole and the three provinces was quite significant. ④ In 2022， Xicheng and Dongcheng districts in Beijing and Heping district in Tianjin were key areas for payment. Chongli district in Zhangjiakou， Daxing district in Beijing， and Fengning Manchu Autonomous County in Chengde were key areas for compensation. The compensation areas-restricted development zones included 76 districts and counties， which was the type with the highest proportion， mainly concentrated in most districts and counties of the Yanshan-Taihang Mountain ecological conservation area and the Bashang Plateau ecological protection area in Hebei Province.

As an important ecological civilization pilot zone and free trade port in China， Hainan Province undertakes the important task of coordinated development of carbon reduction and economic development under the background of the implementation of the strategy of "carbon peak and carbon neutrality." Based on the calculation of carbon source， carbon sink， and net carbon emissions in Hainan Province from 2004 to 2023， the LMDI model and Lasso analysis were used to decompose and screen the influencing factors of carbon emissions in Hainan Province， and four Lasso-Transformer neural network models were included to predict carbon emissions in Hainan Province from 2024 to 2030. The results showed that： ① The trend of total carbon sink in Hainan Province from 2004 to 2023 was relatively stable， and the change trend of net carbon emission was basically consistent with the total carbon source. ② The main influencing factors of carbon emissions in Hainan Province were energy intensity， land carbon emission intensity， economic efficiency， land use structure， population size， and land use efficiency. ③ Through model optimization， the Lasso-PatchTST model was used to predict the carbon emission of Hainan Province from 2024 to 2030 and its influencing factors， and the carbon emission in 2030 was predicted to be 43，455，300 tons. The growth rate of land use efficiency factor was the fastest， and the growth rate of population size was the slowest. By optimizing industrial structure， improving resource utilization efficiency and strengthening ecosystem protection， it can promote the coordinated development of carbon reduction and economy in Hainan Province. The results of this study can provide a reference for decision-making of low-carbon economic development in Hainan Province.

Marine fisheries play a dual role in global warming as both a “carbon source” and “carbon sink.” This study analyzed carbon emissions from marine fisheries in Shandong Province from 2010 to 2022 by integrating carbon accounting, extended Kaya-LMDI decomposition, and System Dynamics (SD) modeling. The results reveal a distinct temporal trend characterized by an initial increase followed by a gradual decline in net carbon emissions, while marine carbon sinks increased steadily over the study period. Marine capture fisheries consistently remained the dominant source of total carbon emissions. Decomposition analysis reveals that economic scale and population were the primary drivers of carbon emission growth, while carbon intensity exerted a smaller but positive effect, whereas improvements in energy intensity and industrial structure contribute to emission reduction, highlighting the importance of energy efficiency improvement and industrial structural adjustment. Using a validated SD model to project trends from 2023 to 2035, we simulated three scenarios: Baseline (BS), High-Growth (HG), and Low-Carbon Development (LD) scenarios. The results show that the low-carbon development scenario achieves the most pronounced reduction in net carbon emissions, driven by simultaneous declines in capture emissions and a strong enhancement of carbon sink capacity from shellfish and algae aquaculture. In contrast, the baseline and high-growth scenarios exhibit relatively weaker mitigation effects. Overall, this study provides quantitative evidence and a strategic roadmap for advancing the green, sustainable transition of marine fisheries in Shandong Province, China.

Future climate change poses unprecedented challenges to agricultural production worldwide. Therefore, designing region-specific rotation patterns is crucial for achieving synergies among multiple objectives, including agricultural productivity and ecological conservation. Based on a long-term field experiment in the Northern Agro-pastoral Ecotone of China, we calibrated and validated the Agricultural Production Systems Simulator (APSIM) and simulated rotation patterns involving four representative crops under eight climate scenarios, including warming, extreme precipitation, and combined temperature–precipitation changes. Analysis combined with carbon footprint assessment was employed to quantitatively evaluate the productivity, ecological benefits, and economic returns of different rotation patterns. The results showed that warming generally reduced crop productivity and economic returns, weakened soil carbon sequestration, and increased net carbon emissions across rotation patterns. Increasing intensity of extreme precipitation further constrained the capacity of rotation patterns to enhance yields, improve incomes, and reduce carbon emissions. Under scenarios of warming and extreme precipitation, the faba bean–oat rotation pattern was found to be the most effective for increasing crop yields, while the faba bean–potato rotation is beneficial for enhancing the incomes from local agriculture. The potato–faba bean rotation pattern was most effective for environmental sustainability due to low net carbon emissions. The findings provide a scientific basis for developing diversified planting strategies with synergistic multi-objectives in the Northern Agro-pastoral Ecotone of China, contributing to food security and sustainable agricultural development under a changing climate focused on changes in temperature and precipitation. Nevertheless, the potential effects of rising atmospheric CO2 concentrations may be incorporated in future studies.

The Qinling Mountains contain the largest forest ecosystem in central China. Examining the spatiotemporal variations of urban carbon lock-in and the pathways for unlocking it on the northern and southern piedmont of the Qinling hinterland is of great significance for achieving carbon balance in central and western China. Based on panel data from seven cities on the northern and southern piedmont of the Qinling Mountains from 2008 to 2022, we mea-sured regional carbon lock-in levels and carbon budgets from a land-use perspective, and investigated the spatio-temporal trends. We applied fuzzy-set qualitative comparative analysis to identify the high-carbon and low-carbon configuration effects of regional carbon lock-in at both macro and micro levels. The results showed that the degree of carbon lock-in in cities on the northern and southern piedmont of the Qinling Mountains increased from 1.79 to 5.61 and exhibited a certain degree of spatial clustering between 2008 and 2022. Net carbon emissions ranged from 31.22 Mt to 113.14 Mt, while carbon sinks remained in the range of 18 Mt to 21 Mt. The ratio of total carbon emission from construction land to that from cropland was 2.96:1. At the macro scale, regional carbon lock-in could be attributed to three configuration types: weak carbon sink function, gap in regulatory function, and misaligned industrial structure. At the micro scale, we identified nine high-carbon and ten low-carbon configurations. The main drivers of carbon emissions from natural ecosystem, construction land, and cropland were environmental regulation, industrial structure, and cropping structure, respectively. The degree of carbon lock-in in cities on the northern and southern piedmont of the Qinling Mountains followed a "slow-fast-slow" growth pattern. Spatially, it was characterized by lower in the south and higher in the north, with clustering that diffused from core cities to surrounding areas. On the basis of implementing overarching environmental policies, each region should select appropriate enhancement pathways in line with resource endowments and carbon lock-in drivers, so as to achieve the goal of carbon unlocking.

An LCA-BIM-GIS integrated model for net carbon emission quantification of buildings

The UK NHS is committed to reaching net zero carbon emissions by 2040. Volatile anaesthetic agents are potent greenhouse gases and alternative intravenous methods exist. We aimed to predict the cost-effectiveness of a transition from volatile anaesthesia to total intravenous anaesthesia to reduce carbon emissions. A general anaesthetic for a 40-year-old, 78-kg patient was modelled. Two volatile anaesthetic agents (desflurane and sevoflurane) were compared with propofol-remifentanil total intravenous anaesthesia. Total intravenous anaesthesia with and without processed electroencephalography was modelled. Cost-effectiveness was calculated as the cost per kg carbon dioxide equivalent saved by transition to total intravenous anaesthesia, benchmarked against the UK emission trading scheme carbon permit price of £41.84 (US$54.90, €47.28) per tonne carbon dioxide equivalent. Total intravenous anaesthesia was less carbon intensive than sevoflurane and desflurane (2.0 vs. 9.8 kg and 209.2 kg carbon dioxide equivalent, respectively). Total intravenous anaesthesia was more expensive than sevoflurane when processed electroencephalography was used (£13.03 (US$17.08, €14.72) vs. £9.76 (US$12.79, €11.03)) but cheaper when it was not (£5.31 (US$6.95, €6.00) vs. £9.76 (US$12.79, €11.03)). When processed electroencephalography was used, the incremental cost-effectiveness ratio of transitioning from sevoflurane to total intravenous anaesthesia was £416 (US$544, €470) per tonne carbon dioxide equivalent. Total intravenous anaesthesia (with and without processed electroencephalography) was cheaper than desflurane (£18.94 (US$24.77, €21.41)). Using our model parameters and the different carbon dioxide emissions and similar cost, transitioning from desflurane anaesthesia to total intravenous anaesthesia is cost-effective. Transitioning from sevoflurane anaesthesia to total intravenous anaesthesia without processed electroencephalography is likely to be cost-effective but is not recommended due to the increased risk of awareness. Transitioning from sevoflurane anaesthesia to total intravenous anaesthesia with processed electroencephalography is unlikely to be cost-effective.

The article is devoted to the analysis of the role of the International Civil Aviation Organization in solving the problem of global warming, one of the main causes of which is considered to be the increase in greenhouse gas emissions into the atmosphere, highlights directions for achieving the goal of decarbonization of civil aviation by 2050. An analysis of aviation experts' proposals for reducing CO₂ emissions through AI was conducted, which can help reduce the environmental impact of aviation, improve aircraft and engine technologies, use sustainable aviation fuel (SAF), implement economic measures, and improve air traffic management and aircraft operations. Harnessing the power of AI to develop more efficient aircraft and engines will help bring zero-emission aircraft to market by 2035. An important area of carbon reduction is the ability of airports to provide clean airspace. Airports Council International has set high standards for reducing absolute carbon emissions. ACI and its member airports have already committed globally to achieving net zero carbon emissions by 2050, with the support of governments. Ukraine has undertaken international legal obligations to implement a program to reduce greenhouse gas emissions into the atmosphere, which are mandatory for implementation after the restoration of airport infrastructure destroyed as a result of the Russian invasion, in particular, obtaining Airport Carbon Accreditation. It is argued that research into AI capabilities, technological advancements, infrastructure development and operational improvements, and collaboration between governments and industry stakeholders are crucial to creating the necessary foundation to achieve decarbonization goals.

Under the background of “dual carbon”, Taking the Inner Mongolia Autonomous Region as the research area, based on land use data and local economic data, were used to measure the land use change and carbon emission of the research area from 2000 to 2024, The carbon balance of various cities in Inner Mongolia is zoned and to provide a basis and support for the optimization of territorial space. [Result](1) During the period, the land use dynamics of forest land, construction land and wetland increased, while the changes in the areas of farmland, grassland, water area and unused land decreased. (2) The total carbon emissions of construction land and cultivated land in Inner Mongolia showed an upward trend. The total amount of carbon absorption rose slightly. (3) The total net carbon emissions in 2024 increase by approximately 133% compared to 2000. In terms of carbon budget balance, Hulunbuir City was in a state of carbon balance from 2000 to 2015, but after 2015, all prefecture-level cities have been in an unbalanced state where carbon emissions exceed carbon absorption. (4) The economic contribution rate of carbon emissions in various cities of Inner Mongolia shows significant differences. The cities with an ecological carrying coefficient greater than 1 are Alxa League and Hulun Buir City. (5) Based on the carbon balance analysis, Inner Mongolia are divided into low-carbon development zones, low-carbon economic zones, low-carbon maintenance zones, economic development zones, carbon intensity control zones, and high-carbon optimization zones. The value of this research demonstrates that arid and semi-arid regions can achieve the synergy of ecological protection, economic development, and carbon reduction through land-use optimization. It provides a scientific approach for similar regions to resolve the conflict between development and emission reduction, and it is of great significance for the implementation of the national “dual-carbon” strategy, the construction of ecological security barriers in northern China, and the study of carbon cycles in global arid areas.

Resource-based cities generally have large carbon-emission, and their carbon balance status is receiving more attention. Land use is a key factor in regulating regional carbon balance. To explore the relationship between land use patterns and carbon balance in resource-based cities, we selected nine cities in Anhui, a major energy province, as the research object. Based on the land use data (2000–2020) and the carbon emission coefficient method, we calculated the carbon emissions, carbon sequestration, and net carbon emissions to show their spatiotemporal evolution. The Logarithmic Mean Divisia Index (LMDI) method was employed to explore the driving factors of carbon emissions. The results indicated the following: (1) Net carbon emissions increased by 149.60%, and the growth rate had slowed down since 2015. Forestland constituted the primary carbon sink, whereas cropland was the dominant carbon source. The spatial distribution of carbon emissions and carbon sequestration was uneven. (2) The economic development level and energy consumption density were the principal factors of emission increases. Conversely, carbon emission intensity and land use economic efficiency served as the key mitigating factors.

Carbon emissions from land use have become one of the hotspots in global climate change research, and their impact is second only to carbon emissions from fossil energy combustion. Taking 325 county units in the middle reaches of the Yangtze River economic zone as the research object, the change rules and spatial characteristics of land use carbon emissions from 2000 to 2022 were explored. On this basis, coordinated zoning was carried out, and targeted strategies were proposed. The results showed that： ① From 2000 to 2022, the net carbon emissions in the study area showed a fluctuating and rising trend. From 2000 to 2010, the average annual growth rate was approximately 1 322.47×104 t； from 2010 to 2015, the growth rate slowed down； and the net carbon emissions in 2020 were reduced by 414.54×104 t compared with those in 2015. It was expected to gradually recover from 2020 to 2022. ② The spatial pattern of land use carbon emissions showed significant regional differences, with Wuhan, Changsha, and Nanchang County as the high-value core. The spatial distribution pattern of net carbon emissions increased significantly in most districts and counties from 2000 to 2022, but the Le'an, Yihuang, Hefeng, Suining, Yuanling, and Shennongjia forest areas maintained very low carbon emissions for many years. ③ The economic contribution coefficient of carbon emissions was higher in the west and south and lower in the east and north, and the coefficient interval showed a significant growth trend. The number of county units with less high values but a coefficient less than 1 increased from 149 in 2000 to 231 in 2022, and the regional gap of economic efficiency of carbon emissions increased. ④ The carbon ecological carrying coefficient distribution was concave in space, showing lower carbon ecological carrying coefficients in the northern districts and counties with Wuhan metropolitan area as the core than those in the southern, eastern, and western regions. During the study period, the maximum carbon ecological carrying coefficient first increased and then decreased, reaching a peak of 28.11 in 2015. ⑤ According to the carbon emission economic contribution coefficient, carbon ecological carrying coefficient, and net carbon emission in the study area over the years, the 325 county units were divided into carbon sink functional zones （11）, low-carbon economic zones （8）, low-carbon maintenance zones （57）, economic development zones （126）, carbon intensity control zones （44）, and high-carbon optimization zones （79）, and differentiated low-carbon development strategies were proposed. District-based regulation is conducive to promoting coordinated emission reduction among counties in the middle reaches of the Yangtze River economic zone, promoting regional low-carbon economic development, and creating a model for regional linkage carbon emission reduction.

Regional carbon emissions are closely related to land use composition and its pattern. Optimizing the spatial distribution of land use is pivotal for reducing carbon emissions and enhancing carbon sequestration, thereby contributing to the achievement of the "carbon neutrality" goal in 2060. This study established a future land use simulation （FLUS） model of Guangzhou based on the land use change in 2015-2020 and optimally allocated the land uses in Guangzhou using the carbon emission coefficient method and the linear programming model, which was triggered by the goal of carbon neutrality. The integrated valuation of ecosystem services and trade-offs （InVEST） model was employed to assess the carbon emission and carbon storage of land uses in 2015-2020 and the optimized land use pattern for 2060 in Guangzhou. Adaptive strategies and suggestions were proposed to achieve carbon neutrality in Guangzhou. The findings are as follows： ① During the period of 2015-2020, land use changes in Guangzhou were characterized by the outward and infill expansion of urban land, occupying the surrounding farmland and ecological land. This resulted in a reduction of 2.4×106 t carbon emissions and 1.26×105 t carbon stock, with 89.02% of the land achieving carbon balance. ② Land use optimization under the 2060 carbon neutrality goal could greatly restrict land use conversion. The built-up land could increase by 17 038 hm2, predominantly through extension, while ecological land would increase by 6 521.68 hm2, mainly through the integration of small patches. Farmland would decrease by 23 446 hm2. ③ With the carbon neutrality target, the 2060 land use could reduce net carbon emission, accounting for 5.5% of that in 2015, and bolster carbon stock by an additional 1.12×105 t. The spatial effects of carbon emissions could be weakened, and 96.89% of the land would achieve carbon balance. This study contributes a robust scientific foundation, using Guangzhou as a reference towards a low-carbon urbanization, thereby promoting the attainment of carbon neutrality.

The Yangtze River Delta urban agglomeration is one of the most economically developed regions in China and a hotspot for carbon emissions. Analyzing the spatiotemporal changes in carbon emissions and the changes in carbon compensation zoning in the Yangtze River Delta urban agglomeration is of great significance to achieving the regional "dual carbon" goals. The land use carbon balance method was used in this study to calculate the land use carbon emissions and absorption of 26 cities in the Yangtze River Delta urban agglomeration from 2000 to 2021. The carbon compensation value of each city was calculated and zoned using the revised carbon compensation value calculation method, and its spatial evolution was analyzed through compensation priority. Finally, corresponding policy recommendations were given. The results showed that： ① From 2000 to 2021, the total net carbon emissions from land use in the Yangtze River Delta urban agglomeration increased by 274.88%, from -120.008 1 million tons to 209.875 million tons, with an average increase of 68.72% every five years. ② The key areas of carbon emissions were consistently in the northeastern cities of the Yangtze River Delta, and the key areas of carbon absorption were in the southwestern cities. ③ From 2000 to 2021, the carbon compensation rate of most cities in Zhejiang Province and Anhui Province was greater than 1, requiring that they obtain carbon compensation funds. Shanghai and some cities in Jiangsu Province also need to pay carbon compensation funds. The compensation areas were concentrated in the central part of the Yangtze River Delta, and the compensated areas were mainly distributed on both sides of the compensation areas. ④ From 2000 to 2021, the priority of the compensation area showed a trend of moving from central to the southeast, and the priority of the compensated area showed a trend of moving from the south to the northwest.

The trajectory of India’s energy system is a combination of technology and policy mix which extends to reliable, affordable and attainable energy sources. More than 60 % of electrical power is generated by coal in India as well as globally. The major air pollution take place due to the thermal power plants and the country needs to deploy carbon capture, utilization, and storage (CCUS) technology in thermal power plants that can help to decarbonize the economy. In present era, the CCUS is a cutting-edge technology for the power plants and Industries. The paper is validating the use of CCUS technology as a better option for India in the present scenario. The Fuzzy Analytical Hierarchy Process (FAHP) multi-criteria method is used to compare the potential of CCUS and renewable energy. The value of CCUS is evaluated by 0.981 and the value of Renewables (REW) is 0.609 in India. Presently the study suggests that CCUS has an advantage over (Renewables) REW in comparison to time taken for CO 2 reduction and present energy mix is in favorable for CCUS whereas REW has a cost advantage over CCUS. The Business As Usual (BAU) estimation is also forecasted the future energy demand and CO 2 reduction till 2050.

Achieving a carbon-negative region through carbon sinks and reduction initiatives: A case study of a coastal bay.

Electrochemical CO2 reduction to single-carbon products is central to sustainable fuels and chemicals, but under industrially relevant conditions elevated temperature fundamentally alters reaction behavior and the mechanistic basis for steering hydrogenation of carbon-based intermediates toward selective C1 formation remains elusive. By integrating artificial intelligence-guided literature mining with theoretical modeling, single-atom alloy catalysts combining thermodynamic advantage with temperature-dependent dynamic surface stability were identified. We report that the coverage and lifetime of surface-active hydrogen (*H) serve as intrinsic, temperature-dependent descriptors for catalyst design, enabling tunable C1 activity and selectivity under thermally enhanced electrocatalysis. Au1Cu single-atom alloys are shown to direct CO2 to either CO or CH4 via thermally stabilized hydrogenation dynamics; in situ surface-interrogation scanning electrochemical microscopy quantitatively resolves *H coverage and lifetime and links their balance to suppression of hydrogen evolution and promotion of deep hydrogenation to methane. Selectivity was modulated by Au content, delivering about 60% faradaic efficiency for CH4 at 353 K, whereas higher loadings favored approximately 85-90% CO. Under device-relevant operation and high renewable electricity share, net carbon emissions were reduced relative to conventional electrocatalysis. These findings highlight a quantitative, temperature-explicit mechanistic framework based on *H coverage and lifetime, providing general principles for C1-selective CO2 electroreduction and guiding catalyst design beyond room-temperature conditions.