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The chemical oxygen demand (COD) in the Seto Inland Sea, Japan has increased in the recent decades due to the increase of bottom dissolved oxygen (DO) concentration which stimulated several autotrophic microorganisms, specially sulfur oxidizing bacteria (SOB). This increased SOB activity due to the oxygenation of the bottom sediment synthesized new organic matter (OM) which contributed dissolved organic carbon to the overlying seawater. This phenomenon further led to hypoxia in some subareas in the Seto Inland Sea. Higher pH or alkaline environment has been found to be an unfavorable condition for SOB. In this research, we used decarburization slag to elevate the pH of sediment to control the SOB activity and consequently reduce OM production in the sediment. Ignition loss of the surface sediment increased from 5.14% 6.38% after 21 days of incubation with aeration; whereas the sediment showed the less ignition loss of 5.71% after 21 days when the slag was incubated in the same experimental setup. Microbial community analysis showed less SOB activity in the slag added aerated sediment which accounts for the controlled increase of OM in the sediment. An additional experiment was conducted with magnesium oxide to confirm whether elevated pH can control the OM increase in sediment due to rising DO. All these results showed that decarburization slag can elevate the pH of the sediment to a certain level which can control the SOB activity followed by controlled increase of OM in the sediment. The findings may be beneficial to control accumulation of sedimentary OM which can act as a source of organic carbon in the overlying seawater., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Japan is progressing towards its circular economy (CE) goals as many of its cities have adopted circular city (CC) policies and programs, although further progress is constrained as a result of the lack of a common framework. A novel framework was proposed with the "European circular cities declaration" (ECCD) (2020), consisting of a list of 10 principles committing to integrate circularity into the city's design, development, and management. As a foremost finding, and building on the authors' previous studies of Japan's CE and CC, this work shaped a circular cities declaration (CCD) for Japan following a triple-axis methodology; It (1) evaluates the ECCD as a baseline, (2) adapts it to Japan's unique socio-economic landscape, and (3) considers the three pillars of sustainable development, offering practical guidance for governments facing similar challenges. This environmental management tool goes beyond the EU one providing a model of hybrid governance and monitoring and evaluation mechanism. The resulting declaration is intended for the government to facilitate a transition from insulated CE policies to holistic CC ones, but also for businesses, academia, and communities; Thus, it may aid in endorsing a cities' common framework and shared vision to harness the potential of CC to address environmental issues, foster innovation and collaboration toward a resilient future in Japan., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

A deep learning architecture, denoted as CNNsLSTM, is proposed for hourly rainfall-runoff modeling in this study. The architecture involves a serial coupling of the one-dimensional convolutional neural network (1D-CNN) and the long short-term memory (LSTM) network. In the proposed framework, multiple layers of the CNN component process long-term hourly meteorological time series data, while the LSTM component handles short-term meteorological time series data and utilizes the extracted features from the 1D-CNN. In order to demonstrate the effectiveness of the proposed approach, it was implemented for hourly rainfall-runoff modeling in the Ishikari River watershed, Japan. A meteorological dataset, including precipitation, air temperature, evapotranspiration, longwave radiation, and shortwave radiation, was utilized as input. The results of the proposed approach (CNNsLSTM) were compared with those of previously proposed deep learning approaches used in hydrologic modeling, such as 1D-CNN, LSTM with only hourly inputs (LSTMwHour), a parallel architecture of 1D-CNN and LSTM (CNNpLSTM), and the LSTM architecture, which uses both daily and hourly input data (LSTMwDpH). Meteorological and runoff datasets were separated into training, validation, and test periods to train the deep learning model without overfitting, and evaluate the model with an independent dataset. The proposed approach clearly improved estimation accuracy compared to previously utilized deep learning approaches in rainfall = runoff modeling. In comparison with the observed flows, the median values of the Nash-Sutcliffe efficiency for the test period were 0.455-0.469 for 1D-CNN, 0.639-0.656 for CNNpLSTM, 0.745 for LSTMwHour, 0.831 for LSTMwDpH, and 0.865-0.873 for the proposed CNNsLSTM. Furthermore, the proposed CNNsLSTM reduced the median root mean square error (RMSE) of 1D-CNN by 50.2%-51.4%, CNNpLSTM by 37.4%-40.8%, LSTMwHour by 27.3%-29.5%, and LSTMwDpH by 10.6%-13.4%. Particularly, the proposed CNNsLSTM improved the estimations for high flows (≧75th percentile) and peak flows (≧95th percentile). The computational speed of LSTMwDpH is the fastest among the five architectures. Although the computation speed of CNNsLSTM is slower than LSTMwDpH's, it is still 6.9-7.9 times faster than that of LSTMwHour. Therefore, the proposed CNNsLSTM would be an effective approach for flood management and hydraulic structure design, mainly under climate change conditions that require estimating hourly river flows using meteorological datasets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Land-use change worldwide has been driven by anthropogenic activities, which profoundly regulates terrestrial C and N cycles. However, it remains unclear how the dynamics and decomposition of soil organic C (SOC) and N respond to long-term conversion of rice paddy to wetland. Here, soil samples from five soil depths (0-25 cm, 5 cm/depth) were collected from a continuous rice paddy and an adjacent wetland (a rice paddy abandoned for 12 years) on Shonai Plain in northeastern Japan. A four-week anaerobic incubation experiment was conducted to investigate soil C decomposition and N mineralization. Our results showed that SOC in the wetland and rice paddy decreased with soil depth, from 31.02 to 19.66 g kg -1 and from 30.26 to 18.86 g kg -1 , respectively. There was no significant difference in SOC content between wetland and rice paddy at any depth. Soil total nitrogen (TN) content in the wetland (2.61-1.49 g kg -1 ) and rice paddy (2.91-1.78 g kg -1 ) showed decreasing trend with depth; TN was significantly greater in the rice paddy than in the wetland at all depths except 20-25 cm. Paddy soil had significantly lower C/N ratios but significantly larger decomposed C (Dec-C, CO 2 and CH 4 production) and mineralized N (Min-N, net NH 4 + -N production) than wetland soil across all depths. Moreover, the Dec-C/Min-N ratio was significantly larger in wetland than in rice paddy across all depths. Rice paddy had higher exponential correlation between Dec-C and SOC, Min-N and TN than wetland. Although SOC did not change, TN decreased by 14.1% after the land-use conversion. The Dec-C and Min-N were decreased by 32.7% and 42.2%, respectively, after the12-year abandonment of rice paddy. Conclusively, long-term conversion of rice paddy to wetland did not distinctly alter SOC content but increased C/N ratio, and decreased C decomposition and N mineralization in 0-25 cm soil depth., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Ninety-four percent of CO 2 emissions induced by final demand in the global construction sector stem from the supply chain. Therefore, it is necessary to identify the CO 2 emission hotspots within the supply chain and implement targeted reduction measures. This study proposed a supply chain clustering approach considering the functional unit of houses and identified CO 2 emission hotspots within the supply chain structure of wooden houses, which accounted for approximately 90% of the total housing stock in Japan. We founded that the top ten CO 2 emission clusters (i.e., emission hotspots) account for approximately 40% of the carbon footprint (38 t-CO 2 ) of a wooden house. Specifically, the iron and steel cluster, which includes the pig iron and crude steel sectors, and the cement cluster, comprising the cement and ready-mixed concrete sectors, collectively contribute to approximately 75% of the CO 2 emissions within the top 10 clusters. Therefore, the reduction of CO 2 emissions from these clusters is of paramount importance. Decision-makers should promote renovation and remodeling policies for vacant houses and prioritize the reuse of foundations, predominantly constructed using steel and cement products, to reduce the supply-chain emissions from wooden houses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In the face of climate-related challenges in agriculture, Japan's 'Direct Payment for Environmentally Friendly Farming' policy stands as a proactive effort to incentivize sustainable practices among smallholder farmers. This study evaluates the policy's impact on smallholder farmers' net farm income within the Tohoku Region, employing a propensity score matching (PSM) methodology to analyze survey data encompassing household-specific attributes and engagement with the policy. Our results indicate that participation in the direct payment scheme enhances farmer income, averting an estimated reduction of 125 thousand JPY per annum. While direct payments demonstrated a positive effect on smallholder income, our findings surprisingly revealed that skill training, a key non-financial support, had a negligible impact on household earnings. The findings highlight the policy's efficacy in promoting practices that decrease reliance on chemical inputs and increase organic farming, thereby contributing to carbon emissions mitigation. Notably, our analysis suggests that subsidies directed towards integrating renewable energy on farms may have a less immediate financial impact compared to other forms of support. This research underscores the complex interplay between agricultural subsidies, environmental sustainability, and farmer income, revealing that direct financial incentives are pivotal in fostering climate-conscious agricultural practices among smallholders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This research presents an in-depth investigation into the dynamic correlation between geopolitical conflicts and carbon markets utilizing the Time-Varying Parameter Vector Autoregression (TVP-VAR) technique. The analysis focuses on the interconnectedness between the Geopolitical Risk Index Daily (GPRD) and vital carbon pricing instruments, specifically the Intercontinental Exchange Endex European Union Allowance (ECEFDC), KraneShares California Carbon Allowance Strat ETF (KCCAK), Shanghai Environment and Energy Exchange China Emission Allowances Online Transactions (SAXCEA), and S&P Global Ex-Japan LargeMidCap Carbon Efficient Index (SPGJ). The daily fluctuations were traced from May 2021 to July 2023. The analysis is divided into short- and long-term connectedness, with particular emphasis on the impact of the Russia-Ukraine conflict on the GPRD's spillover on carbon markets. The short-term connectedness (1-5 days) between GPRD and ECEFDC shows variability, fluctuating between 10% and 40%. Conversely, long-term connectedness exhibited a significant increase during the conflict, peaking at approximately 34% by mid-2022. The analysis of the Total Dynamic Connectedness (TCI) between the GPRD and the KCCAK indicates comparable magnitudes, although with minor initial discrepancies. The short-term connectedness of GPRD and KCCAK decreases from its peak of approximately 10% to approximately 1%. Conversely, long-term connectedness varies between approximately 32% and 2% from May 2022 onwards. The long-term connectedness between GPRD and SAXCEA revealed variable patterns, peaking at around 18% at the beginning of the sample period and rapidly reducing to around 1% within two months. The analysis of the connectedness between GPRD and the SPG) identifies intense fluctuations in both TCI and long-term connectedness. After an initial increase and decrease, these patterns rebound and experience another increase. This research provides significant insights into the complex dynamics of geopolitical conflicts and carbon markets, particularly the impact of the Russia-Ukraine conflict on carbon market behavior., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Japan is a leading country in establishing an efficient waste management system. However, the recycling rate of plastic waste remains low, as different types of plastic are separated into different categories based on local policies in different municipalities. In April 2022, Japan introduced the new Plastic Resource Circulation Act, which requires all plastic waste to be separated and collected in a new category as recyclable resource. Thus, the waste separation criteria received major revision, providing a good opportunity to observe citizens' behavior change. This study aims to investigate the factors that influence citizens' waste separation behavior with the introduction of a new plastic waste category in Japan. A questionnaire survey was conducted among 1676 Kansai citizens, extending the theory of planned behavior by including personal norms, plastic sorting knowledge and government policy. The sample population was divided into two groups based on whether the respondent's municipality implements mandatory plastic container and packaging waste separation policies and governance. The results show that people living in municipalities with mandatory separation policies were more likely to participate in plastic waste separation and showed greater consistency between their intentions and actual behavior compared to those living in areas without such policies. Moreover, the influence of knowledge and personal norms on the intention was more significant in the mandatory separation policy group. In both groups, there was a positive relationship between knowledge, personal norms, and people's intention. The findings provide insights for promoting plastic waste separation, recycling, and reducing plastic pollution by improving plastic circulation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)