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Considering the current global goal of carbon neutrality, the relationship between cultivated land intensive use (CLIU) and carbon emission efficiency (CEE) should be explored to address the global climate crisis and move toward a low-carbon future. However, previous work in this has been conducted at provincial/regional scales and few have identified the spatial correlation between CLIU and CEE at the scale of large river basins. Therefore, this study explored the spatiotemporal characteristics of CLIU, cultivated land carbon emissions (CLCE), and CEE, as well as the spatial correlation between CLIU and CEE in the Yellow River Basin (YRB), China. A comprehensive evaluation model, the Intergovernmental Panel on Climate Change (IPCC) coefficient methodology, existing data envelopment analysis model, and bivariate spatial autocorrelation models were used to analyze statistical data from 2005 to 2017. We found that the overall CLIU and CLCE values in the YRB exhibited a continuous increase; the average carbon emission total efficiency and carbon emission scale efficiency first decreased and then increased, and the average carbon emission pure technical efficiency gradually decreased. Areas of high CLCE were concentrated in eastern areas of the YRB, whereas those of high CLIU, carbon emission total efficiency, carbon emission scale efficiency, and carbon emission pure technical efficiency predominantly appeared in the eastern areas, followed by central and western areas of the YRB. Spatial analysis revealed a significant spatial dependence of CLIU on CEE. From a global perspective, the spatial correlations between CLIU and CEE changed from positive to negative with time. Moreover, the aggregation degree between CLIU and CEE gradually decreases with time, while the dispersion degree increases with time, and the spatial correlation gradually weakens. The local spatial autocorrelation further demonstrates that the number of high–low and low–high clusters between CLIU and CEE gradually increases over time, while the number of high–high and low–low clusters gradually decreased over time. Collectively, these findings can help policymakers formulate feasible low-carbon and efficient CLIU policies to promote win–win cooperation among regions. [ABSTRACT FROM AUTHOR]

• Average daytime SUHII showed higher seasonal fluctuations than nighttime. • RF model explained 68% of day/night SUHII SAV on average. • We highlighted the multi-factor driven of day/night SUHII SAV. • Climatic zones showed significant impact on variations, trends, and drivers of UHI. Urban heat island (UHI) adversely impacts the human-earth system. However, the impact of climatic zones on UHI remains unclear. This study, therefore, aimed at investigating how climatic zones affect spatiotemporal variations, trends and potential drivers of surface UHI intensity (SUHII) based upon 253 Chinese cities in five climatic zones: middle temperate zone (MTZ), south temperate zone (STZ), north subtropical zone (NSZ), middle subtropical zone (MSZ), and south subtropical zone (SSZ) during 2001–2020. The results showed that the SUHII ranged from -2.59 to 6.20 °C, average daytime SUHII showed higher seasonal fluctuations and larger variation than nighttime and summer daytime had the highest seasonal and annual SUHII variation (SUHII SAV). Cities in NSZ, MSZ, and SSZ had high average daytime SUHII SAV and a large proportion had significant increasing trends (Trend SI) (P <0.05) from 2001–2020, while the nighttime showed opposite rule in general. Random forest (RF) model explained 68% of day/night SUHII SAV on average. Except for city area, which greatly impacted day/night SUHII SAV in all periods and climatic zones, other drivers more significantly influenced SUHII in certain periods and climatic zones, e.g. aerosol optical depth (AOD) in winter nighttime in MTZ and STZ. Compared with single or serval drivers' determination of UHI effect, we highlighted the multi-factor driven of day/night SUHII SAV. Specific suggestions, e.g. controlling haze pollution can bring co-benefits on urban air quality and UHI mitigation were proposed. These findings could help to provide valuable reference for future climatic adaptive strategy. [ABSTRACT FROM AUTHOR]

This study represents an initial attempt to examine environmental justice on inequalities in access to ecological attractions that provide top cultural ecosystem services at a national scale. With big data from social media, billions of anonymized samples were analysed via an experimental procedure to capture the behavioral characteristics of visitors who accessed China's Five-A ecological attractions. The results indicate that (1) social equity can be achieved in the context of ecosystem services in China, especially at the individual level; and (2) although China's vulnerable groups do not appear to have been treated unfairly, market mechanisms may exacerbate the inequitable development of ecosystem services among different regions. To address the problem of inequality and uneven development on ecosystem services that may result from the capital, the government should take measures to reduce the accessibility threshold and consider providing appropriate green infrastructure for different social groups apart from Five-A ecological attractions. Image 1 • A big data method to re-visit access of top ecological spaces at a national scale. • Vulnerable groups were not unequally treated on environment recreation in China. • The equality of accessibility frequency appears much greater than distance. • People-based measures of accessibility are more reliable than place-based measures. • Age, income, and hukou rate were unrelated to accessibility at a national scale. [ABSTRACT FROM AUTHOR]

• The spatial flow was included in assessing the sub-basin importance for water supply. • The beneficial population was based on the direction and path of spatial flow. • The importance index was proposed to explore the contribution of sub-basins. • Considering the service delivery, the upstream sub-basin maybe not most important. • The importance ranking provided information for ecological compensation. Water provision service is crucial for human society to survive and develop. It is essential to evaluate the importance of sub-watersheds, based on their different capacities to provide water resources to manage an entire watershed. Previous studies have assessed the importance of the sub-watershed by analyzing its supply and/or demand of water provision service. However, few studies have considered the influence of the spatial flow. In this study, we proposed an assessment framework that combined supply, demand, and spatial flow of water provision service. The Qiantang River Basin in China was selected as our study area. The importance of the sub-watershed was evaluated using the importance index, which was calculated using the spatial flow and the accumulative beneficial population of the water provision service. The spatial flow was simulated using a simplified water flow model, and the accumulative beneficial population was based on the direction and path of water provision service spatial flow. The results indicated that 60% of sub-watersheds with "very high" importance were located in the middle and lower reaches of Xin'an River and Lan River. Due to the internal consumption and sink of the water provision service, the upstream area may provide less spatial flow and may have a lower level of importance. When limited by the direction and scope of water provision service delivery, some sub-watersheds with high surpluses and without external beneficiaries were of low importance. Our study emphasizes the quantity and routing of water provision service delivery and enhances the understanding of the capacity of the sub-watershed for providing water provision service. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cultivated land use efficiency (CLUE) was assessed based on carbon emissions. • The overall CLUE values in the YRB increased and subsequently decreased with time. • Per capita grain possession was main driver of CLUE in most areas. • Road network density was the key driver of CLUE in the QTP. • Results will assist China for food security and cultivated land use carbon emission reduction. China is accelerating green and low-carbon transformations of cultivated land to achieve a carbon peak by 2030 and to actively respond to global climate change. Evaluating the cultivated land use efficiency (CLUE) and determining its driving factors help reduce cultivated land-use carbon emissions and promote green and low-carbon transformations of cultivated land. However, previous carbon emission-based studies of CLUE and its driving factors have been insufficient. Therefore, in this study, we explored the spatiotemporal characteristics and driving factors of CLUE in the Yellow River Basin (YRB), China, based on carbon emissions. A slacks-based model with undesirable (bad) outputs, spatial autocorrelation models, and geographic detector models was used for the analysis, with statistical data from 2005 to 2017 as inputs. The overall CLUE values in the YRB increased and subsequently decreased with time. The Huang-Huai-Hai Plain (HHHP) consistently had the highest values, followed by the northern arid and semi-arid regions (NASR), the Loess Plateau (LP), and the Qinghai-Tibet Plateau (QTP). According to the global spatial autocorrelation, the CLUE had a positive association with themselves. The major cluster types moved from high–high and low–low to high–high cluster types in eastern Henan and southern Shanxi provinces, according to local spatial autocorrelation. Per capita grain possession was the main driver of CLUE in the YRB, HHHP, LP, and NASR, and road network density was the key driver of CLUE in the QTP, according to Geodetector analysis. Furthermore, non-linear enhancement dominates the driving factors of CLUE in the YRB, with non-linear enhancement dominating the HHHP, LP, and NASR, and bi-factor enhancement dominating the QTP. The findings of this study can be used to assist policymakers in formulating feasible, green, and efficient cultivated land-use policies. [ABSTRACT FROM AUTHOR]

Climate change pressure and biodiversity degradation in coastal regions have caused an increase in urban vulnerability. Current coastal vulnerability studies fail to consider the interactions among the perturbations. Increases in such interactions contribute to the indeterminate changes in the ecosystem productivity and impact on human well-being. Therefore, by integrating water, heat, and vegetation biodiversity (WHB) indicators using catastrophe theory in the study, the interaction among subsystems was explored to expound on the multi-effect of the urban. The results showed that (1) the overall vulnerability of China's coastal cities has increased, and high-value areas were mainly distributed in the three southern provinces; (2) the spatial-temporal pattern of vulnerability was highly heterogeneous. As low-low clusters, Shanghai and its surrounding cities exhibited spatial aggregation characteristics; (3) social, physical and financial capitals were the first three main adaptive capacity factors. The distance-based linear model (DistLM) evidenced that per capita GDP, and road density explained about 30 % and 10 % of the difference in vulnerability variation. The proposed framework could help decision-makers detect how vulnerable coastal areas exposed to WHB impacts are, with crucial implications for future sustainable management., Competing Interests: Declaration of competing interest The authors declaim that there is no conflict of interest., (Copyright © 2022. Published by Elsevier B.V.)

Background: First-line nursing staff are responsible for protecting residents, the most vulnerable population, from COVID-19 infections. They are at a high risk of being infected with COVID-19 and experience high levels of psychological distress., Aims: To explore the challenges and coping strategies perceived by nursing staff during the COVID-19 pandemic in China., Methods: In April,2020, we conducted a qualitative study using in-depth semi-structured interviews with nursing staff. Participants were selected from seven nursing homes in three cities in Hunan Province, China., Results: A total of 21 nursing staff participated in the study, including seven nurse managers, seven registered nurses and seven nursing assistants. Three main themes were identified. Different groups encountered different sources of stress and adopted various coping strategies to fulfil their responsibilities., Conclusions: Nursing home staff were underprepared for dealing with COVID-19-related challenges. Educational programs to improve the ability to deal with COVID-19 prevention and control are needed., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest, (Copyright © 2021 Elsevier Inc. All rights reserved.)

With annual Glycyrrhiza uralensis seedlings as experimental material, using "3414" optimal regression design and applied fertilizer, through the sampling of G. uralensis at harvest, root fresh weight and content of active components were measured in Lanzhou, Bayan Nur city, Chifeng, Jiuquan. Combined with NPK content in soil, potted experiments were used to study the effects of different nitrogen and phosphorus ratios on the dry matter accumulation and accumulation of active components of G. uralensis. The results reported as follows: the optimum fertilizer treatment in Lanzhou, Bayan Nur city, Chifeng, Jiuquan was N₁P₂K₁,N₂P₂K₁,N₁P₁K₂ and N₂P₁K₂, respectively. The efforts of single fertilizer on the fresh root weight acted as parabolic type.There was no significant effect of fertilizer treatment on the accumulation of active components of G. uralensis. Furthermore, in terms of nitrogen and phosphorus, the type of fertilizers that restricted the growth of the region was the type of elements with lower content in the soil. The optimal fertilizer usage was in inverse proportion to content of elements in soil. When the content of phosphorus in soil was low, nitrogen fertilizer and potash fertilizer showed positive interaction with phosphorus fertilizer, whereas, they showed negative interaction., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Chinese Pharmaceutical Association.)

A novel strain, Pusillimonas sp. T2, which is capable of degrading nicotine, was isolated and identified. This strain could completely degrade 500 mg/L nicotine within 8 h at 30 °C, pH 7.0. Six intermediates were detected and identified as 6-hydroxy-nicotine, 6-hydroxy-N-methylmyosmine, 6-hydroxypseudooxynicotine, 2,6-dihydroxypyridine, 6-hydroxy-3-succinoyl-pyridine and 2,5-dihydroxypyridine. Activities of 6-hydroxy-3-succinoyl-pyridine hydroxylase and 2,6-dihydroxypyridine hydroxylase were demonstrated in the cell extracts of strain T2, indicating that this strain may employ a novel variant of the pyridine and pyrrolidine pathways that is different from those of other species. This study provides the first evidence that Pusillimonas bacteria participate in nicotine degradation., (Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.)