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Mobility-as-a-Service (MaaS) system becomes a significant part of urban transportation network system based on the information and communication technologies, but rarely received attention in tourism transport. This paper explored the impact of travel mode preferences on habitual choice behavior for MaaS in tourism, and an online survey and stated preference experiments were designed and carried out. Respondents were divided into three categories including strictly preference (SP) group, weak preference (WP) group, and no preference (NP) group, accounting for 25.09%, 72.24%, and 2.67% respectively. Estimation results of the mode choice random parameter logit (RPL) models indicate that explanatory variables of the alternatives (e.g., the total travel time, in-vehicle cost, and walking distance) only affect the travel mode choices for WP group, which are insensitive to the SP group and NP group. Marginal effect analysis shows that mode choice preferences for MaaS are influenced as tour experience and daily travel habits change. [ABSTRACT FROM AUTHOR]

Amidst urbanization and industrialization in China, abandoned farmland plays a crucial role in safeguarding plant diversity within agricultural landscapes. This study aimed to examine the patterns of seasonal variation in plant diversity within abandoned farmland habitats in the Huang–Huai Plain region. Nonparametric tests were employed to analyze plant species diversity and phylogenetic diversity across seasons. Redundancy analysis and linear regression were conducted to examine the associations between plant species composition, species diversity, phylogenetic diversity, and soil environmental factors. Our results showed that plant species diversity, richness, and phylogenetic diversity were highest in spring, followed by summer, and lowest in autumn. The phylogenetic structure of plant communities demonstrated a tendency to diverge in spring, become random in summer, and cluster in autumn. Soil available potassium and soil organic matter emerged as important factors influencing plant species composition. The content of soil organic matter and ammonium nitrogen level exhibited a significantly positive correlation with the species diversity and phylogenetic diversity of plants. This study underscores the significance of considering seasonal and temporal scales when investigating plant diversity and provides a theoretical basis for biodiversity conservation in agricultural landscapes. [ABSTRACT FROM AUTHOR]

This study focuses on the significance of improving the land degradation of Mu Us Sandy Land to increase cultivated land area and promote ecological green development. The research objects were four kinds of mixed soils, and rhizosphere soils were collected during the crop harvesting period. The volume ratio of soft rock to sand was 0:1 (control check, CK), 1:5 (composite soil one, PS1), 1:2 (composite soil two, PS2), and 1:1 (composite soil three, PS3). The results showed that the large aggregates were primarily mechanically stable aggregates, while the small aggregates were mainly water-stable aggregates. The soft rock promoted the increase of clay and silt content in sandy soil, and the soil texture changed from sand to loam. The contents of organic matter, available phosphorus, and available potassium increased significantly under PS2 and PS3 treatments, but there was no significant difference between them. Total nitrogen had no significant difference among treatments. Actinobaciota, Proteobateria, and Chloroflexi were the dominant bacteria in rhizosphere soil, accounting for about 75% of all microorganisms. At the Genus level, the soft rock contributes to richer species composition. The diversity index, evenness index, and richness index was higher in PS1, and the available phosphorus and available potassium content promoted the increase of diversity. Therefore, when the proportion of soft rock and sand compound soil is between 1: 5 and 1: 2, it can be used as an important basis and technical parameter for Mu Us Sandy Land improvement. [ABSTRACT FROM AUTHOR]

Facing the problem of energy shortage and the responsibility of carbon reduction, to achieve sustainable regional economic development, renewable energy must be vigorously developed. Technology can not only boost the development of renewable energy but be a new driving force for the economy. However, the development of the economy, technology, and renewable energy are interrelated, and the coupling and coordination among them lack sufficient evaluation and analysis. Therefore, an evaluation index system is constructed for the economy–technology–renewable energy ternary group. The evaluation model is applied to measure the coupling coordination degree, and a geographically weighted regression model is used to analyze the influence of key factors and their spatial differences. 30 provinces in China are used as examples for the study, and the results show that the coupling coordination degree is low in most regions, except for Guangdong, which has been maintained at an extremely coordinated level, and most provinces are in a fluctuating upward trend during the decade. Additionally, the results of the geographically weighted regression report that the influence of factors has spatial heterogeneity. The study provides a basis for relevant policy formulation in China, and the evaluation and analysis ideas can provide a reference for other countries or regions. [ABSTRACT FROM AUTHOR]

In order to achieve sustainable development goals, China has further increased its goal of reducing carbon intensity and has made digitalization an important support for sustainable development. However, the impact of digitalization on carbon intensity reduction is still unclear. In this context, this paper first evaluates the digitalization level of 30 provincial regions in China and then constructs a spatial Durbin model for two stages, 2012–2015 and 2016–2019, so as to explore the spatial spillover effects of carbon intensity in different stages and the important roles of digital infrastructure and digital inputs in carbon intensity reduction. The main findings are as follows: (1) the current digitization level of each province in China is widely disparate, with the region showing a high level in the east and a low level in the west; (2) carbon intensity reduction has a significant spatial spillover effect, as shown by a 1% reduction in local carbon intensity and a 0.21% reduction in neighboring regions; and (3) digitalization has a more significant positive impact on the reduction in carbon intensity in stage 2. The research results are strong demonstration that digitalization drives sustainable development. [ABSTRACT FROM AUTHOR]

In 2019, China proposed the weight of consumption responsibility (WCR) policy for renewable energy. This study first analyzes the interaction between the electricity market and the green certificate market and establishes a two-market equilibrium model with multiple subjects. Secondly, a system dynamics model of the development decision of the new energy manufacturers (NEMs) under the interaction of the two markets is established. Finally, taking Henan province as an example, the development trend of NEMs is simulated, and sensitivity analysis is conducted to explore the key influencing factors for the development of NEMs. The results show that the electricity market and the green certificate market interact with each other mainly through the price of electricity and the price of green certificates, thus evolving the trading behavior of trading subjects. By 2035, for every 0.25% increase in non-hydropower WCR in Henan province, the annual added new energy installation will be around 1200 MW. In the current scenario, the policy of certificate multiplier will be detrimental to the overall development of NEMs, and a conservative investment strategy and accelerated technology improvements are more beneficial to NEMs. Carbon emission peaking and carbon neutrality policies can also accelerate the growth of new energy installations. [ABSTRACT FROM AUTHOR]

China is an ancient civilization. History has left us with a rich cultural heritage, of which ancient cultural sites account for a large proportion. As far as the current scientific research and technology are concerned, due to the particularity and complexity of the humid environment, the protection of ancient cultural sites in the humid environment is still an important topic before us. The research topic involved in this article is about the application of composite nano-calcium-based materials for the reinforcement and protection of soil sites in humid environments. Combined with the development of the research content of this article, the research thinking of the thesis is also adjusted accordingly, making the analysis and solution of the problem clearer. The first is a conceptual study, expounding the relevant concepts in this article. The main purpose is to sort out and study the reinforcement and protection measures and methods of relevant sites and ancient cultural sites, as well as the classification, characteristics, and protection value of ancient cultural sites. Through the analysis and research of these aspects, the composite nano-calcium bases for ancient cultural sites in the subsequent humid environment is proposed based on material basic information. The second is a descriptive research, qualitative and quantitative analysis of humid environment. On the basis of summarizing previous researches, this paper mainly conducts qualitative and quantitative analysis on the judgment of humid environment, the influence mechanism on ancient cultural sites, and the main diseases. Then, it is analytical research, studying the main diseases and causes of the underground palace site in the engineering case, and it is concluded that it is mainly affected by the combined effect of the characteristics of the site's soil and the environment. Through the collection of data from the site survey, field test, and indoor experiment of the underground palace site, the preservation status of the site is collected, and the disease problems faced by the site were analyzed, making it more difficult to protect. The main problem facing the protection of soil relics in humid environment, that is, the research focus, is the research on the development and applicability of reinforcement protection materials. This article attempts to explore the protective effect of composite nano-calcium-based materials on wet sites. Practical research was conducted to verify the feasibility of composite nano-calcium-based materials in practice through indoor site soil simulation. After the completion of a series of experiments, the applicability and compatibility of the composite nano-calcium-based material to strengthen the wet site soil was verified through data analysis, data collection, and mechanism discussion. The experimental results show that the sample with a solid content of 0.4% composite nano-calcium matrix has better salt and alkali resistance. Moreover, the unconfined compressive strength growth rate of 0.4% of the samples has a qualitative improvement over other solid content samples. [ABSTRACT FROM AUTHOR]

The structure of renewable energy (RE) development varies substantially across China's provinces, and the spatio-temporal pattern evolution is too pronounced to allow direct comparisons. Therefore, a reasonable method for RE efficiency estimation is important. Markov and spatial Markov chains can be used to analyze the evolution of the temporal and spatial patterns of provincial RE. Simultaneously, data envelopment analysis game cross-efficiency evaluation can quantify the RE generation efficiency of each province from the perspective of competition. Nine factors were selected to identify the key influencing factors the RE generation efficiency. From the perspective of spatio-temporal heterogeneity, a geographically and temporally weighted regression model was combined for spatial modeling. Results show a significant change in the categories of wind and solar power installations, a medium change in biomass installations, and a small change in hydropower installations. Two-thirds of the provincial RE generation efficiency increased from 2015 to 2020. There is spatio-temporal heterogeneity regarding the impact of various factors on the RE generation efficiency: The impact of technology market transactions exhibits the greatest inter-provincial variation and the impact of electricity industry investment exhibits the smallest inter-provincial variation. [ABSTRACT FROM AUTHOR]

• Establishing HWPS investment limitation and suitability assessment indicator systems. • Determination of expert weights using dynamic social networks. • TIFN was used to quantify the qualitative indicators. • Combining BWM and CRITIC combination weighting and TODIM to rank the alternatives. • Investment suitability assessment of 62 completed hydropower plants in China. The hydropower-wind-photovoltaic-storage (HWPS) complementary system is one of the essential ways for China to build a new type of power system and to realize the dual-carbon goal. However, China's HWPS complementary system is still in the exploratory stage, and it is important to propose a rational multi-attribute decision-making (MADM) framework for investment suitability assessment based on completed hydropower plants. Therefore, this study first established a limitation indicator system for preliminary screening hydropower plants and an HWPS investment suitability assessment indicator system containing six dimensions: nature, market, infrastructure, land, society, and environment. Second, the weights among experts were determined based on the dynamic social network, and a mechanism for updating expert weights was proposed. Again, triangular intuitionistic fuzzy number (TIFN) was used to quantify the qualitative indicators and combined the weights according to the best-worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) methods. Finally, the TODIM (an acronym in Portuguese for interactive and MADM) method was used for scheme suitability assessment with sensitivity analysis and method comparison. The results show that 62 eligible hydropower plants were preliminarily screened out of 647 completed medium- and large-scale hydropower plants in China by combining GIS technology. Natural factors are the most important of the six dimensions, followed by social factors. According to the suitability assessment results of TODIM, #23 hydropower station has the highest suitability for HWPSCS investment, which provides a reference for the layout of China's HWPS complementary system. With different decision makers' risk preferences and different MADM methods, #23 hydropower plant is still the best investment option, which proves the effectiveness of the MADM framework proposed in this study. [ABSTRACT FROM AUTHOR]

Plant growth environment plays an important role in shaping soil microbial communities. To understand the response of soil rhizosphere microbial communities in Oplopanax elatus Nakai plant to a changed growth conditions from natural habitation to cultivation after transplant. Here, a comparative study of soil chemical properties and microbial community using high-throughput sequencing was conducted under cultivated conditions (CT) and natural conditions (WT), in Changbai Mountain, Northeast of China. The results showed that rhizosphere soil in CT had higher pH and lower content of soil organic matter (SOM) and available nitrogen compared to WT. These changes influenced rhizosphere soil microbial communities, resulting in higher soil bacterial and fungi richness and diversity in CT soil, and increased the relative abundance of bacterial phyla Acidobacteria, Chloroflexi, Gemmatimonadetes, Firmicutes and Patescibacteria, and the fungi phyla Mortierellomycota and Zoopagomycota, while decreased bacterial phyla Actinobacteria, WPS-2, Gemmatimonadetes, and Verrucomicrobia, and the fungi phyla Ascomycota, and Basidiomycota. Redundancy analysis analysis indicated soil pH and SOM were the primarily environmental drivers in shaping the rhizosphere soil microbial community in O. elatus under varied growth conditions. Therefore, more attention on soil nutrition management especially organic fertilizer inputs should be paid in O. elatus cultivation. [ABSTRACT FROM AUTHOR]

Background: Regional lymph node metastasis is a contributor for poor prognosis in osteosarcoma. However, studies on risk factors for predicting regional lymph node metastasis in osteosarcoma are scarce. This study aimed to develop and validate a model based on machine learning (ML) algorithms. Methods: A total of 1201 patients, with 1094 cases from the surveillance epidemiology and end results (SEER) (the training set) and 107 cases (the external validation set) admitted from four medical centers in China, was included in this study. Independent risk factors for the risk of lymph node metastasis were screened by the multifactorial logistic regression models. Six ML algorithms, including the logistic regression (LR), the gradient boosting machine (GBM), the extreme gradient boosting (XGBoost), the random forest (RF), the decision tree (DT), and the multilayer perceptron (MLP), were used to evaluate the risk of lymph node metastasis. The prediction model was developed based on the bestpredictive performance of ML algorithm and the performance of the model was evaluatedby the area under curve (AUC), prediction accuracy, sensitivity and specificity. A homemade online calculator was capable of estimating the probability of lymph node metastasis in individuals. Results: Of all included patients, 9.41% (113/1201) patients developed regional lymph node metastasis. ML prediction models were developed based on nine variables: age, tumor (T) stage, metastasis (M) stage, laterality, surgery, radiation, chemotherapy, bone metastases, and lung metastases. In multivariate logistic regression analysis, T and M stage, surgery, and chemotherapy were significantly associated with lymph node metastasis. In the six ML algorithms, XGB had the highest AUC (0.882) and was utilized to develop as prediction model. A homemade online calculator was capable of estimating the probability of CLNM in individuals. Conclusions: T and M stage, surgery and Chemotherapy are independent risk factors for predicting lymph node metastasis among osteosarcoma patients. XGB algorithm has the best predictive performance, and the online risk calculator can help clinicians to identify the risk probability of lymph node metastasis among osteosarcoma patients. [ABSTRACT FROM AUTHOR]

Increasing carbon emissions efficiency (CEE) is essential for Chinese cities to achieve their dual carbon goals. For cities with higher CEE, it is crucial to comprehensively evaluate their carbon emissions reduction potential (CERP) and develop targeted carbon reduction paths. This study first determined the input, expected output, and non-expected output indicators and used the super-efficiency Slack Based Measure model to calculate the CEE of 336 cities. Secondly, we evaluated the urban development level, structural optimization space, and natural resource endowment using the BWM-CRITIC-TOPSIS method and combined them with CEE to evaluate the CERP. Finally, we used K-means clustering to group cities according to the carbon emissions level and CERP and proposed targeted emission reduction recommendations. The results showed that cities in the northern part of China had lower CEE, while the coastal areas had higher CEE. In the primary indicators of CERP, structural optimization space was the most important, followed by efficiency improvement space. The eastern region has a greater potential for carbon reduction, with an average score of 63.71 points (out of 100 evaluation points) for the 336 cities. The cities could be classified into nine types, with the ninth category being the key focus cities for achieving the 2030 carbon peak goal with high carbon emissions and CERP. [ABSTRACT FROM AUTHOR]

Firstly, on the basis of literature research, sort out and summarize the critical coupling relationship among the upstream, middle, and downstream enterprises in the wind power industry chain. Secondly, the evaluation index system of coupling coordination degree of China's wind power industry chain was established. Based on entropy weight method and subsystem efficiency function, the capacity coupling (CC) coefficient model of wind power industry chain subsystem was established. The coupling coordination degree between the upstream subsystem and the midstream subsystem of the wind power industry chain, and between the midstream subsystem and the downstream subsystem is dynamically evaluated, and the coupling coordination degree evaluation model of the wind power industry chain in China is proposed. Thirdly, according to the relevant statistical data of China from 2010 to 2017, this paper conducts an empirical study on the coupling of the upstream, middle and downstream subsystems of the wind power industry chain. Finally, based on the collaborative coupling study of China's wind power industry chain, this paper analyzes the key factors influencing the collaborative development of wind power industry chain, and puts forward Suggestions on the optimization of the collaborative development of China's wind power industry chain. [ABSTRACT FROM AUTHOR]

To promote renewable energy consumption and achieve China's low-carbon energy transition, in 2019, China proposed the weight of consumption responsibility (WCR) for renewable energy in each province. This study aims to explore the micro-market behavior of new energy manufacturers in the context of WCR policy. A two-market bidding model for new energy manufacturers is first proposed, and a two-stage compound differential evolutionary game algorithm is proposed for solving the multi-party game problem. By selecting typical electricity demand scenarios, the evolution of new energy manufacturers' strategies in the electricity market and green certificate market as well as under different WCR and different thermal power unit parameters are analyzed. The research results show that when the non-hydropower WCR is relatively low, new energy manufacturers tend to adopt a low-price strategy for generation quotation and a low volume high price strategy for green certificate sales. Other conditions being unchanged, with the increase in non-hydropower WCR, all new energy manufacturers will still adopt a low-price strategy in the electricity market. New energy manufacturers with high installed capacity will increase progressively their certificate quotation. The higher output lower limit for thermal units is not conducive to electricity market bidding by new energy manufacturers. • A two-market bidding model for new energy manufacturers is established. • A two-stage compound differential evolutionary game algorithm for new energy manufacturers is proposed. • The optimal strategy of two-market bidding for new energy manufacturers is empirically analyzed. • The bidding strategies under different consumption responsibility weights are discussed. [ABSTRACT FROM AUTHOR]

Research on container port development is of great theoretical and practical significance because of the port's crucial role in the local economic system and regional transportation system. Understanding the development dynamics of container ports is important when formulating related operational and management strategies in the future. Hence, this article investigates the club convergence of 25 coastal ports in mainland China spanning from 2006 to 2020 in terms of container throughput, which signals the development of a port to some extent. The study finds three clubs in China's coastal container port system, with various transitional behaviors indicating that the whole system has shown a tendency toward a slight centralization since 2013 and that small and medium-sized ports are regressing. On this basis, analysis on the container port system is conducted by employing an allometric model. The result shows that allometric relations indeed exist not only among three factors linked with port development, namely, port container throughput, port city's import-export volume, and port maritime connectivity, but also among the three port clubs. Moreover, the allometric relations slightly differ and vary over time for the three port clubs, thus implying that large ports may have different growth mechanisms from small and medium-sized ports. Based on the findings mentioned above, several general policy implications are proposed, which may impact port production, construction, and operations management in mainland China. • Combined club convergence and the allometric model to analyze the development dynamics of coastal container ports of different scales. • The allometric relations between port container throughput, port city's import-export volume, and port liner shipping connectivity are analyzed. • The container port system in mainland China shows a trend of concentration, with the development momentum of small and medium-sized ports being insufficient. • Useful managerial and operational insights for the development of port with different scales are given. [ABSTRACT FROM AUTHOR]

• There was a significant positive spatial correlation between provincial CO 2 emissions in China. • Spatio-temporal heterogeneity analysis of driving factors of CO 2 emissions was carried out using GTWR model. • Inter-provincial differences in the impact of industrial structure on CO 2 emissions were minimal. • Energy intensity is a key factor in achieving dual reduction in provincial CO 2 emissions, followed by trade openness. To achieve the 2060 carbon neutrality target, each province in China needs to ensure rapid reduction in carbon dioxide (CO 2) emission according to its own developmental characteristics. Meanwhile, to achieve sustainable emission reduction, it is important to explore the development path of dual reduction of total CO 2 emissions and CO 2 emission intensity in each province. Based on the data of 30 provinces in China for the period 2005–2019, in this study, we analyzed the spatial and temporal evolution trends of CO 2 emissions in each province and determined the spatial autocorrelation of provincial CO 2 emissions. We used the geographically and temporally weighted regression (GTWR) model to analyze the spatio-temporal evolution of the driving factors of provincial CO 2 emissions. The results showed that CO 2 emission intensity of each province gradually decreased, and the CO 2 emissions between provinces were spatially autocorrelated. Energy intensity had the highest influence on total CO 2 emissions, and the influence of trade openness on CO 2 emission intensity had the largest inter-provincial differences. At present, reducing energy intensity and the proportion of secondary industries, improving trade openness, and using electricity alternatives are the key for some provinces to achieve dual reduction of total CO 2 emissions and CO 2 emission intensity. [ABSTRACT FROM AUTHOR]

The Baishaziling greisen-type tin deposit is located in the Dayishan ore field, Nanling Range, Southern China. In this study, for the first time, we present both zircon and cassiterite U Pb dating, whole-rock elements, zircon Lu Hf and apatite Nd isotopic compositions to better constrain the petrogenesis of granite and its genetic link with Sn mineralization. Zircon U Pb ages of fine-grained granite and coarse-grained granite are 154 ± 1.8 Ma and 153 ± 2.1 Ma, respectively, which are consistent with the cassiterite U Pb dating of 154 ± 5.4 Ma, implying genetic relationship between the Baishaziling granite and tin metallogenesis. The Baishaziling granites exhibit high SiO 2 , K 2 O + Na 2 O, Zr + Nb + Ce + Y contents, low P 2 O 5 and Sr contents, and high ratios of Ga/Al, TFeO/(TFeO + MgO), implying A-type granite affinity with characteristics of high-K calc-alkaline and weakly peraluminous. The zircon ε Hf (t) values and apatite ε Nd (t) values of the granite vary from −4.46 to −1.81 and −8.37 to −7.10, with two-stage Hf and Nd model ages of 1.40 to 1.50 Ga and 1.52 to 1.64 Ga, indicating that they were generated by the partial melt of the Proterozoic basement with the involvement of mantle magma. In addition, formation of Dayishan granite was likely associated with an intraplate extensional setting caused by the subduction of the Palaeo-Pacific plate. The Baishaziling reduced granites have high stannum and boron contents, which are in favor of the tin mineralization. • Zircon and cassiterite U–Pb dating confirm a Yanshanian granitic magmatism and associated Sn mineralization event. • The Baishaziling granites are A-type granite and were likely originated from the mixing of crust-mantle components. • Reduced granites are in favor of Sn mineralization. [ABSTRACT FROM AUTHOR]

• There is spatial autocorrelation of CO 2 emissions in China's 336 cities. • Quantitative analysis of the coordination level between CO 2 emissions level and urban development. • The carbon emissions in China's cities are reclassified into six categories using cluster analysis. • The influencing factors of CO 2 emissions have spatial heterogeneity. Cities play a critical role in achieving China's carbon emissions peak and carbon neutrality goals, but the policies of cities should be tailored to their developmental levels and local conditions. This study first analyzed the spatial autocorrelation of CO 2 emissions in 336 cities in 2019. The coupling degree and coupling coordination degree were used to measure the coordination level between the CO 2 emissions level and urban development by contemplating the urban development indicators. Depending on the coordination level and historical CO 2 emissions of the city, the urban regions were reclassified with the density peak (DP) clustering algorithm. Finally, a multiscale geographically weighted regression (MGWR) model was used to explore the spatial heterogeneity of the influencing factors of the total CO 2 emissions. The results showed that the coordination level of CO 2 emissions in Shenzhen, Chengdu, and Guangzhou is relatively high; China's urban carbon emissions can be divided into six categories; and the impact on GDP per capita, population, and the proportion of secondary industries on CO 2 emissions is spatially heterogeneous. In conclusion, this study divides China's cities and analyzes the key influencing factors of CO 2 emissions into different categories, providing a reference for cities to achieve CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

The coordinated development of upstream, midstream, and downstream of wind power industry chain is the key to solve the problem of wind power consumption. Therefore, this paper firstly constructs the performance evaluation index system of the upstream, midstream, and downstream of the wind power industry chain, and evaluates the performance of the upstream, midstream, and downstream of the wind power industry based on entropy weight-TOPSIS. Secondly, the coupling coordination degree (CCD) model between subsystems of wind power industry chain is established to dynamically evaluate the CCD between upstream and midstream, midstream and downstream, and among three subsystems of wind power industry chain. Finally, taking the development data of China's wind power industry from 2010 to 2019 as an example, the coupling coordination degree between subsystems is empirically studied. The results show that: the overall performance of wind power industry chain has a tortuous upward trend; the coupling degree (CD) of each subsystem is better than that of 2011 and 2012; The CCD of upstream and midstream of wind power industry chain fluctuates more than that of midstream and downstream and that of three subsystems. • The performance evaluation index of the upstream, midstream and downstream of the wind power industry chain is established. • Entropy weight-TOPSIS method is used to evaluate the performance of wind power industry chain. • The coupling coordination degree model between subsystems of wind power industry chain is established. • The coupling coordination degrees between subsystems of wind power industry chain are dynamically evaluated. [ABSTRACT FROM AUTHOR]

Same as other bay areas, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is also suffering atmospheric composite pollution. Even a series of atmospheric environment management policies have been conducted to win the "blue sky defense battle", the atmospheric secondary pollutants (e.g., O 3 ) originated from oxygenated volatile organic compounds (OVOCs) still threaten the air quality in GBA. However, there lacks a systematic summary on the emission, formation, pollution and environmental effects of OVOCs in this region for further air quality management. This review focused on the researches related to OVOCs in GBA, including their pollution characteristics, detection methods, source distributions, secondary formations, and impacts on the atmosphere. Pollution profile of OVOCs in GBA revealed that the concentration percentage among total VOCs from Guangzhou and Dongguan cities exceeded 50 %, while methanol, formaldehyde, acetone, and acetaldehyde were the top four highest concentrated OVOCs. The detection technique on regional atmospheric OVOCs (e.g., oxygenated organic molecules (OOMs)) underwent an evolution of off-line derivatization method, on-line spectroscopic method and on-line mass spectrometry method. The OVOCs in GBA were mainly from primary emissions (up to 80 %), including vehicle emissions and biomass combustion. The anthropogenic alkenes and aromatics in urban area, and natural isoprene in rural area also made a significant contribution to the secondary emission (e.g., photochemical formation) of OVOCs. About 20 % in average of ROx radicals was produced from photolysis of formaldehyde in comparison with O 3 , nitrous acid and rest OVOCs, while the reaction between OVOCs and free radical accelerated the NOx-O 3 cycle, contributing to 15 %-60 % cumulative formation of O 3 in GBA. Besides, the heterogeneous reactions of dicarbonyls generated 21 %-53 % of SOA. This review also provided suggestions for future research on OVOCs in terms of regional observation, analytical method and mechanistic study to support the development of a control and management strategy on OVOCs in GBA and China., 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 B.V. All rights reserved.)

Carbon emission reduction is an essential means to achieve the "double carbon goal," and the scientific and reasonable allocation of carbon emission quotas (CEQ) is the basis for promoting carbon emission reduction. In this study, the first level was based on the entropy TOPSIS scores of provinces under the principles of fairness, efficiency, sustainability, and feasibility and used the K-mean clustering method to cluster the 30 provinces and allocate the CEQ to each zone group; the second level consolidated the impacts of the four principles and the marginal abatement costs of CO 2 to allocate CEQ to the provinces within the zone group. Finally, each province's initial spatial balance of CEQ (ISBQ) is classified and evaluated. The study shows that the most quotas are for Guangdong, Zhejiang, and Inner Mongolia, and the least for Ningxia, Shanxi, and Guizhou. This study compares the results of CEQ allocation with the current carbon emission scale and finds that 11 provinces, such as Shandong and Hebei, show a deficit in future carbon emission space, and 19 provinces, such as Hainan and Beijing, show a surplus in carbon emission space. Given each province's different emission reduction tasks and pressures, differentiated emission control policies are the key to achieving China's "2030 target"., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Whether different serum HBV RNA detection assays can consistently predict treatment outcomes in patients with chronic hepatitis B remains controversial., Methods: We enrolled 188 patients who had stopped nucleos(t)ide analogues (NAs) (STOP cohort-1, -2) and 78 receiving entecavir (ETV) therapy (ETV cohort) and used double-target (targeting both 5' and 3' ends of the HBV pregenome RNA [DT-RNA]) and three single-target (targeting the S-region [S-RNA], X-region [X-RNA], and poly-A tail of HBV RNA [PolyA-RNA]) assays to predict treatment outcomes., Results: In STOP cohorts, DT-RNA, S-RNA and X-RNA at NAs cessation showed higher predictive powers for clinical relapse (time-dependent areas under the curve [AUCs] for years 1, 2, 3, and 4 ranged between 0.724 and 0.772 in cohort-1, and between 0.741 and 0.824 in cohort-2) than the PolyA-RNA (AUCs between 0.604 and 0.611 in cohort-1; and between 0.530 and 0.584 in cohort-2). The predictive power for 2-year HBeAg loss of the four targeted RNAs in the ETV cohort at 6 months were similar (AUCs, 0.848, 0.838, 0.825, and 0.801), and superior to that of the HBV DNA level at 6 months (AUC, 0.721)., Conclusion: The outcome prediction performance of serum HBV RNAs is methodology-dependent. PolyA-RNA detection was not recommended to predict off-treatment relapses., (Copyright © 2021 Elsevier B.V. All rights reserved.)