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All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently. [ABSTRACT FROM AUTHOR]

Theoretical studies on evolutionary algorithms have developed vigorously in recent years. Many such algorithms have theoretical guarantees in both running time and approximation ratio. Some approximation mechanism seems to be inherently embedded in many evolutionary algorithms. In this paper, we identify such a relation by proposing a unified analysis framework for a global simple multiobjective evolutionary algorithm (GSEMO) and apply it on a minimum weight general cover problem, which is general enough to subsume many important problems including the minimum submodular cover problem in which the submodular function is real-valued, and the minimum connected dominating set problem for which the potential function is nonsubmodular. We show that GSEMO yields theoretically guaranteed approximation ratios matching those achievable by a greedy algorithm in expected polynomial time when the potential function g is polynomial in the input size and the minimum gap between different g-values is a constant. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Funding: This work was supported by National Natural Science Foundation of China [11771013, U20A2068]; Zhejiang Provincial Natural Science Foundation of China [LD19A010001]. [ABSTRACT FROM AUTHOR]

It is normally difficult to identify the ground deformation of potential landslides in highly vegetation-covered areas in terms of field investigation or remote sensing interpretation. In order to explore a methodology to effectively identify potential landslides in highly vegetation-covered areas, this paper established an integrated identification method, including sliding prone area identification based on regional geological environment analysis, target area identification of potential landslides in terms of comprehensive remote sensing methods, and landslide recognition through engineering geological survey. The Miaoyuan catchment in Quzhou City, Zhejiang Province, southeastern China, was taken as an example to validate the identification methods. Particularly, the Shangfang landslide was successfully studied in terms of comprehensive methods, such as geophysical survey, drilling, mineral and chemical composition analysis, and microstructure scanning of the sliding zone. In order to assess the landslide risk, the potential runout of the Shangfang landslide was evaluated in a quantitative simulation. This paper suggests a methodology to identify potential landslides from a large area to a specific slope covered by dense vegetation. [ABSTRACT FROM AUTHOR]

As more attention is given to green and sustainable industries, an analysis of the industrial impacts on all aspects of life, including inclusive affluence, is gradually developing. Idle rural residential land is a valuable resource and an important factor in promoting sustainable development. Balanced urban and rural development contributes to inclusive prosperity, so understanding the relationship between industry and the balanced development of urban and rural can significantly impact social development. In China, achieving the balanced development requires narrowing the urban-rural income gap. This paper analyzed the impact of reallocating idle rural residential land on promoting the balanced development. The study found that industry development has a positive impact on the balanced development, with a regression coefficient of 1.478. Regions with higher industry indices in counties had better outcomes regarding the balanced development. When the development of rural industry derived from idle residential land was in good condition, the effect increased by 3.326 percentage. The results showed heterogeneity, with the regression coefficient of industry development on the balanced development in county-level cities being 0.498 larger than in urban areas. In summary, the reallocation of idle residential land can promote sustainable development, increase residents' income, and improve overall regional economic development. The results are applicable to the comprehensive reallocation of rural land resources. [ABSTRACT FROM AUTHOR]

Both long‐term but small number of national stations and short‐term but large number of regional stations have been frequently used to study the extreme hourly precipitation (EXHP) in China. However, few studies focus on the differences of the two for revealing the features of EXHP. In this study, the characteristics of EXHP in Zhejiang Province are investigated using three rainfall data sets at three threshold criteria. The comparison between different data sets shows that increasing the station density can better reflect the climatic spatial distribution of EXHP thresholds if long‐term data is absent. The majority of EXHP can be classified into four weather types: the southwesterly wind type (30.7%–48.5%), the trough type (12.2%–23.6%), the tropical cyclone (TC) type (11.4%–17.5%) and the easterly wind type (4.9%–17.9%). The selection of stations is more sensitive to the proportions of the four weather types than the statistical years and threshold criteria. The monthly and diurnal variations of EXHP, as well as their differences revealed by the three data sets, are varied by weather type. Only using national stations cannot distinguish the spatial differences between the TC type and the easterly wind type, and there is an underestimation for southwesterly wind type and trough type in the mountainous area of southwest Zhejiang. The statistical year and station height are the main reasons for the differences in the duration of EXHP events calculated by different data sets, with the TC type having the largest effect and the southwesterly wind type the smallest. Plain Language Summary: Station data is the most common and reliable data for studying the characteristics of precipitation in China. There are two sources of station data available, that is, national station data with long time series but sparse and regional stations with short time series but numerous. However, few studies have compared the differences between these two sources of data for revealing the characteristics of extreme hourly precipitation (EXHP). In this study, the possible impact of different data sets for revealing the characteristics of EXHP under four weather types are investigated in Zhejiang Province. Zhejiang is located on the southeast coast of China with a long coastline and many mountains. Results suggest that increasing the station density can better reflect the spatial distribution of the EXHP thresholds if long‐term data is absent. EXHP events with strong synoptic‐scale forcing are more sensitive to the results obtained by different data sets. As the national stations are mostly located in the plains, the high frequency centers of EXHP are biased in each weather type if only using national stations, especially in southwest Zhejiang and near the coast. In summary, this paper provides additional perspectives for understanding the characteristics of regional EXHP by using the most common observations. Key Points: The selection of stations is sensitive to the proportions of the four main weather types in Zhejiang where extreme hourly rainfall occursExtreme hourly precipitation events with strong synoptic‐scale forcing are more sensitive to results obtained using different data setsThe sparse national stations located on the plains could hardly reflect the spatial distribution of extreme rainfall in mountainous Zhejiang [ABSTRACT FROM AUTHOR]

Global warming, white pollution, ecological degradation and other environmental and resource issues have become the focus of attention in all areas of society today, and sustainable development is no longer a slogan. Design practitioners are committed to developing new visions and approaches. The application of materials is an important part of realising a circular economy. Sugar cane is the world's number one sugar crop and the second largest bioenergy crop, while bagasse is one of the most produced agricultural wastes in the world. This study is located in the hometown of brown sugar in China - Yiwu City, Zhejiang Province. The research objective is to develop the design and application of bagasse fibre composites in the brown sugar industry of Yiwu using waste bagasse materials as a starting point. The aim is to use design to drive the circular flow of waste resources, extend the economic chain of the brown sugar industry, and help build a local ecological civilisation and sustainable economic development. The researcher used theoretical framework, qualitative research and data analysis as research methods. In this study, the theoretical framework of sustainable development of the brown sugar industry in Yiwu is proposed, and the circular path diagram of the brown sugar industry ecological park. With theory guiding practice, and successfully developed bagasse paper material and bagasse bioplastic material and applied them in the field of lamps and brown sugar product packaging. [ABSTRACT FROM AUTHOR]

Social and organizational innovations are one of the most effective ways to gain social collaboration for effective, rapid, and coordinated interventions. An analysis of the relationship among organizational performance (OP), social innovations (SI) and organizational innovation (OI) in social organizations (SOs) is little discussed in the literature and much less with main component analysis. This paper is an effort to provide some empirical evidences about social and organizational innovations that social organizations in China have implemented to address the social issues of the society. A survey of Chinese SO's is conducted during beginning two months of 2022 in provinces of Jiangsu, Guangdong and Zhejiang to attain the statistics and assessing the insights of the executives of the SOs participating in this study with respect to organizational performance, social and organizational innovations. The technique used to select the sample is a non-probabilistic sampling and multiple linear regression model is applied to determine the partial impact of organizational innovations and social innovations on the organizational performance. The grouping of the variables is carried out through main components analysis. The empirical findings of the study highlight that Chinese SOs are innovative because they adopt management strategies to address the social issues associated with their institutional mission. There are four groups of derived components from organizational and social innovations based on the empirical evidence: SO's innovative activities to modify the environment; inside innovative measures to enhance SO's performance; innovative activities of SO's to enhance their relationships with outside actors; innovative measures to improve the management of SOs related to their mission and institutional projects. The findings of this study offer an efficient solution to government and policy makers for involving SOs in terms of planning of social development in China. The social and organizational innovations are very necessary to overcome the social issues so government should encourage the establishment and sustainability of social organizations. [ABSTRACT FROM AUTHOR]

In China, rapid urbanization and the decline of the canal's shipping function have directly led to the decline of the space and style of ancient towns with canals. The ancient town of Xixing, known to be the first canal town, is located west of the Zhedong canal section of the Grand Canal. It used to be the most active transportation hub and trade transit point in the east Zhejiang Province. However, the canal is now facing problems in protection and renewal, which require urgent attention. For example, the streets of the ancient town are separated from the water system space, the self-organizing and development ability of the ancient town has weakened, and the spatial vitality is scarce. Firstly, by comparing and analyzing whether the canal is used as a road network under two different spatial scales, the area with the highest degree of spatial integration is obtained before judging whether the canal has an important influence and control on the street spaces of the ancient town. Secondly, as the canal is no longer used as a transportation network nowadays, the internal spatial structure characteristics of streets and alleys are analyzed. Finally, the topological structure analysis is carried out in the 3 km area from the border of the planning control area, and the integrated development of the ancient town space and urban transportation network is then discussed. Further, the vitality renewal strategies of the ancient town under different spatial scales are put forward to provide the empirical basis and decision-making reference for the better sustainable development of ancient towns with canals. According to research, once the ancient town is considered on a larger urban scale, the areas with the best integration and accessibility, like the water-adjoined spaces change to intersection spaces and urban road network areas. Consequently, in order to realize the sustainable development of Xixing ancient town, the city system must overcome its shortfalls in operation. The methods and conclusions in the paper can effectively contribute to the development of the ancient town. The research significantly helps to improve the average land sharing, commercial distribution, and public facilities layout in the practice of protection and development in ancient towns and provides an empirical basis and decision-making references for relevant management departments. [ABSTRACT FROM AUTHOR]

• The "linkage" role of micro-kinetic parameters between road characteristics and accidents was discovered. • The longitudinal kinetic characteristics of tires can reflect the risk of rear-end accidents. • Demonstrates changes in vehicle operating on high-risk segments through micro-kinetic parameters. • Proposed a relatively novel modeling method. • Reveals the reliability of micro-kinetic parameters in the field of accident analysis. Freeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the "link role" of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident. Method: A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established. Results: The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions. [ABSTRACT FROM AUTHOR]

This paper provides a critique of the "specialty towns" program, a key constituent of China's current new-style urbanization campaign. It problematizes the contradictory accounts of the program, namely, emphasizing "place-based" strengths while simultaneously standardizing forms, functions, and goals with a strong "place-neutral" approach. We argue that three key building blocks are critical for understanding specialty towns: place dependence, embeddedness, and locational advantage. Through multiple-case studies in Zhejiang, evidence has shown that there is a mismatch between national policies and local practices in specialty town development. The latter has its own place-specific logic of development shaped by history, geography, institutions, and agency. In particular, existing small-scale growth settings (e.g., industrial parks, specialized markets) and characteristics of local agency are the main factors affecting local practices. This paper argues that without considering the specificities of places in a broader socioeconomic context, the program may fail to work as effectively as expected in its local implementation. [ABSTRACT FROM AUTHOR]

Second emission trading market is not active in China so far, and the reason mainly lies in that enterprises do not have strong initiative for transaction. Thus it's meaningful to study related guiding mechanisms from the perspective of enterprises behavior. In this paper, an evolutionary game model and a small-world network model considering stock heterogeneity are constructed based on four given guiding mechanisms, and a simulation study is conducted through China Zhejiang emission trading market. The result shows that: (1) the optimal guiding mechanism is dynamic and changes from reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock to reward-punishment for enterprises with insufficient stock when trading preferential profit coefficient increases to 1. (2) when penalty coefficient changes, the optimal guiding mechanism is the reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock and keeps unchanged. (3) the enterprises with insufficient stock are more sensitive to penalty coefficient and trading preferential profit coefficient, especially to the latter, so it's better to stimulate the emission rights purchasing side and formulate positive reinforcement methods. The study of this paper can provide decision-making suggestions for Chinese government to stimulate the activity of second emission trading market. [Display omitted] • Four guiding mechanisms are given based on implementation objects. • An evolutionary game model is constructed. • A complex network model is constructed considering stock heterogeneity. • The optimal guiding mechanism is simulated and dynamically analyzed. • The policy recommendations are highlighted. [ABSTRACT FROM AUTHOR]

This paper aims to reveal the relationship between intellectual property protection (IPP) and industrial transformation and upgrading (T&U) in southeastern China's Zhejiang Province. Taking five representative industries as objects, the shift-share analysis was adopted to measure the T&U level of each industry, with the total output in 2004–2019 as the basis. The results show that wholesale and retail, lodging and catering, finance, and real estate are the four advantageous industries. Further, the authors calculated Pearson's correlation coefficients between IPP intensity and the T&U levels of the four industries. By the coefficients, the four industries can be ranked in descending order as lodging and catering (0.8743), real estate (0.6908), wholesale and retail (0.5891), and finance (0.5468). In addition, the IPP was found to be positively correlated with total manufacturing output (0.8027). Hence, the IPP can significantly promote the development of these five industries. [ABSTRACT FROM AUTHOR]

Background: Extensive parasitic diseases epidemiology in Zhejiang province has not been carried out since the second national survey in 2004. Therefore, dynamics in prevalence and infection pattern of the major intestinal parasites should be explored.Methods: The distribution of three parasites including soil-transmitted helminths (STH), intestinal protozoa and C. sinensis in Zhejiang from 2014 to 2015 were explored. Kato-Katz technique was used for STH and C. sinensis detection, whereas transparent adhesive paper anal swab was used for pinworm detection, and iodine smear was used for protozoa detection. A questionnaire survey on alimentary habits and sanitary behaviors was conducted in half of the studied counties.Results: This study recruited 23,552 participants: 19,935 from rural and 3617 from urban area. Overall prevalence of intestinal helminth infections was 1.80%. In this study, seven helminth species were identified including A. duodenale, N. americanus, Trichuris trichiura, Ascaris lumbricoides, C. sinensis, Fasciolopsis buski and pinworm. The average prevalence of STH infection was 1.71%: 1.94% in rural and 0.44% in urban area. Hookworm was the most prevalent infection at 1.58%: 1.79% in rural and 0.44% in urban area. Prevalence varied considerably in the studied counties. Prevalence was highest in Yongkang county at 10.25%. Only 2.79% of children from rural area were infected with pinworm. A proportion of 0.40% of rural participants were infected with protozoa, whereas Endolimax nana was the most prevalent at 0.23%. C. sinensis showed infection only in one man. Awareness on C. sinensis was 24.47% in rural and 45.96% in urban area, respectively.Conclusions: Prevalence of STH and protozoa infections declined considerably whereas C. sinensis infections remained few in Zhejiang province compared with the prevalence reported in previous large scale surveys (19.56% for national STH infection in 2004, 18.66% and 4.57% for provincial STH and protozoa infection, respectively in 1999). The findings of this study showed that hookworm, mainly N. americanus remained a parasitic threat to population health, mainly in the central and western Zhejiang. Therefore, more health education regarding fertilization and farming habits is necessary in rural areas. The awareness concerning hookworm infection should be reinforced. [ABSTRACT FROM AUTHOR]

Background: One of the most noticeable integrated care-related policies in China is the growth and proliferation of County-level Integrated Health Organizations (CIHOs), which take over a set of primary healthcare institutions to form an integrated delivery network in order to achieve an ordered hierarchical delivery system by strengthening primary care. Objectives: This paper presents emerging findings from an ongoing evaluation of the early impacts of the demonstrator site, Deqing CIHO, in Zhejiang Province, in order to examine the extent to which the implementation has achieved its core objectives: (1) establishing the hierarchical referral system, (2) capacity building of primary healthcare providers, and (3) reducing the costs. Design: This case study was conducted to determine institutional and managerial processes. Settings: Data were collected and analyzed at the CIHO and county level. A structured questionnaire was used for data collection. Primary and secondary outcome measures: Indicators were selected from the existing database of the county health system and arranged into three segments to assess (1) service utilization among each level of care; (2) capacity-building progress for primary care centers, (3) cost-related indicators for both levels of care. Results: Service utilization data show that one year after CIHO implementation, the proportion of patients who chose to get inpatient care outside of the county decreased from 27.3% to 24.5%. Hospital admissions were retrieved from outside the county, while service volume slightly shifted from hospitals to primary care sites. Capacitybuilding indicators for township health centers show that 6 out of 12 items showed better performance compared to the national average growth rate, and a moderated growth rate appeared in terms of per capita cost. Conclusion: Progress evaluation results from Deqing CIHO indicated some positive effects on three main outcomes, which reveal the potential of CIHOs in not only strengthening primary care but also controlling cost as a result of early implementation. Further emphases of evaluation are required to determine the impacts on the quality and experience of care that are estimated using claim-based data at the individual level. [ABSTRACT FROM AUTHOR]

The volatility and uncertainty of wind energy has brought great challenges to its accommodation in electric power systems. To determine a wind power trading strategy in the real-time power market, the accurate assessment of wind energy accommodation capability (WAC) is of great significance. However, most current studies investigate the wind energy accommodation potential from the perspective of dispatch, but rarely provide quantitative assessment results. Additionally, the non-anticipativity of decisions has not been considered in the assessment yet. This paper proposes a novel quantitative assessment method for WAC based on the multi-stage robust optimization (RO), which addresses the anticipativity issues in the traditional two-stage method while maintaining the decision-making process' robustness. In the assessment method, the operational risk is integrated via a tractable scheme to obtain dynamic admissible WAC boundaries. To obtain the optimal solution of the proposed multi-stage RO problem, a fast robust dual dynamic programming (FRDDP) algorithm is employed, where the adaptive techniques are developed to accelerate the computation. Numerical studies on the modified IEEE 14-Bus system and a real-world system in Zhejiang Province of China validate the effectiveness of the proposed assessment model and adaptive acceleration techniques. The simulation results demonstrate the presented method brings a 18.87% reduction in operational cost, and reduces 29.34% curtailment of wind energy. Compared with the original FRDDP, the adaptive technique significantly reduces the computational consumption by 73.34% on the real-world test system. • A novel assessment method for WAC is proposed based on the multi-stage robust optimization. • Tractable risk evaluation method is integrated in the multi-stage framework. • Adaptive techniques are designed for FRDDP method to accelerate the optimal solution. • The proposed method achieves both non-anticipative and robust assessment decisions. [ABSTRACT FROM AUTHOR]

Accurate and timely carbon emission accounting (CEA) is vital to industrial corporations, especially those who participate in the carbon market. With the rapid development of artificial intelligence and power systems, the power data-based method provides a new way for real-time CEA. However, the extensive installation of distributed photovoltaics (PV) significantly increases the accounting difficulty of corporate carbon emissions. This paper proposes a non-intrusive method of real-time CEA for industrial corporations from the perspective of modern power systems. First, a device operation state (DOS) estimation model based on a modified Informer algorithm is proposed to calculate corporate direct carbon emissions. Wherein, an equivalent distributed PV output estimation model is used to decrease the impact of invisible PVs on direct emission accounting. Second, an improved carbon emission flow model is proposed to calculate corporate indirect carbon emissions, which considers "prosumers" arising from the installation of distributed PVs. Finally, the total corporate carbon emissions, including direct and indirect parts, are obtained by using the CEA model. Case studies based on four typical high‑carbon-emission factories in Zhejiang province, China demonstrate that the proposed method can make accurate CEA for industrial corporations by effectively lessening the impact of distributed PVs. • A non-intrusive carbon emission accounting method for industrial corporations. • A novel perspective of modern power systems for carbon emission accounting. • Calculating carbon emissions considering distributed photovoltaics' impacts. • The method becomes superior as the photovoltaic output proportion increases. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has impacted electricity consumption patterns and such an impact cannot be analyzed by simple data analytics. In China, specifically, city lock-down policies lasted for only a few weeks and the spread of COVID-19 was quickly under control. This has made it challenging to analyze the hidden impact of COVID-19 on electricity consumption. This paper targets the electricity consumption of a group of regions in China and proposes a new clustering-based method to quantitatively investigate the impact of COVID-19 on the industrial-driven electricity consumption pattern. This method performs K-means clustering on time-series electricity consumption data of multiple regions and uses quantitative metrics, including clustering evaluation metrics and dynamic time warping, to quantify the impact and pattern changes. The proposed method is applied to the two-year daily electricity consumption data of 87 regions of Zhejiang province, China, and quantitively confirms COVID-19 has changed the electricity consumption pattern of Zhejiang in both the short-term and long-term. The time evolution of the pattern change is also revealed by the method, so the impact start and end time can be inferred. Results also show the short-term impact of COVID-19 is similar across different regions, while the long-term impact is not. In some regions, the pandemic only caused a time-shift in electricity consumption; but in others, the electricity consumption pattern has been permanently changed. The data-driven analysis of this paper can be the first step to fully interpret the COVID-19 impact by considering economic and social parameters in future studies. [ABSTRACT FROM AUTHOR]

Regional energy development and approaches are significant for China's overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy's scale is the most crucial factor affecting Zhejiang's energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal. [ABSTRACT FROM AUTHOR]

With the rapid development of the tourism industry, various travel websites are emerging. The tourism question answering system explores a large amount of information from these travel websites to answer tourism questions, which is critical for providing a competitive travel experience. In this paper, we propose a framework that automatically constructs a tourism knowledge graph from a series of travel websites with regard to tourist attractions in Zhejiang province, China. Backed by this domain-specific knowledge base, we developed a tourism question answering system that also incorporates the underlying knowledge from a large-scale language model such as BERT. Experiments on real-world datasets demonstrate that the proposed method outperforms the baseline on various metrics. We also show the effectiveness of each of the question answering components in detail, including the query intent recognition and the answer generation. [ABSTRACT FROM AUTHOR]

Zhejiang province in China experienced an extreme climate phenomenon in August 2014 with temperature rises, sunshine duration decreases, and precipitation increases, particularly, the successive heavy rainfall events occurring from 16 to 20 August 2014 that contributed to this climate anomaly. This study investigates the spatial-temporal variation characteristics of precipitable water vapor (PWV) and the normalized difference vegetation index (NDVI) associated with this phenomenon. Multiple sources of PWV values derived from the Global Positioning System (GPS), Radiosonde (RS) and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data are used with different spatiotemporal resolutions. The monthly averaged PWV in August 2014 exceeded the 95% percentiles of climatological value (53 mm) while the monthly averaged temperature was less than the 5% percentiles of climatological value (26.6 °C). Before the extreme precipitation, the PWV increased from the yearly averaged value of about 35 mm to more than 60 mm and gradually returned to the August climatological average of 50 mm after the precipitation ended. A large-scale atmospheric water vapor was partially conveyed by the warm wet air current of anticyclones which originated over the South China Sea (25° N, 130° E) and the Western Pacific Ocean. The monthly NDVI variation over the past 34 years (1982–2015) was investigated in this paper and the significant impact of extreme climate on vegetation growth in August 2014 was found. The extreme negative temperature anomaly and positive PWV anomaly are the major climate-driven factors affecting vegetation growth in the north and south of Zhejiang province with correlation coefficients of 0.83 and 0.72, respectively, while the extreme precipitation does not show any apparent impact on NDVI. [ABSTRACT FROM AUTHOR]

As the world's largest inland shipping channel, the Yangtze River Economic Belt (YREB) is strategic to China's sustainable development where policymakers are increasingly emphasizing not only this region's economic development but also its CO 2 emission reduction targets. To achieve emission targets in the YREB region, it is essential to identify the driving forces of its CO 2 emissions. However, existing studies are not very refined and only examine the overall effects of drivers on CO 2 emission changes, while neglecting the sub-regional and sectoral level effects across China. More refined research, therefore, will provide better-targeted policies for emission reduction relevant to regional levels such as the YREB region. Towards this end, this paper integrates the methods of structural decomposition analysis and attribution analysis to demonstrate the driving forces, at both sub-regional and sectoral levels, for YREB's emission changes from 2002 to 2012. Our results reveal the following: (1) Jiangsu Province has always been the main regional source of increasing CO 2 emissions in the YREB, accounting for more than 20% of total CO 2 emission growth. (2) The Electricity and Heat Production and Supply sector is responsible for most of the increases in CO 2 emissions, both in 2002–2007 (609.8 Mt, 54.8%) and 2007–2012 (287.6 Mt, 34%). (3) During the period of 2007–2012, changes in per capita final demand were the primary driving force for the increases in CO 2 emissions, while changes in CO 2 emission intensity were the largest driving force for decreasing CO 2 emissions, respectively accounting for 179.9% and −119.4% of total emission changes in the YREB region. (4) Moreover, the effect of emission intensity mainly exists in the Electricity and Heat Production and Supply sector in the Jiangsu and Zhejiang provinces, accounting for respectively, 10% and 10.4% of the total effects across all economic sectors. Considering the diverse impacts of driving forces in different sub-regions and economic sectors, policymakers should apply more refined measures to utilize varying driving forces in different sub-regions and economic sectors towards sustainable development. • We analyze drivers of CO 2 emissions in the Yangtze River Economic Belt (YREB). • Drivers of CO 2 emissions are decomposed into both sub-regions and sectors. • Jiangsu province and three main sectors dominated CO 2 emissions in the YREB. • Intensity changes in Jiangsu's three sectors largely reduced YREB's emissions. [ABSTRACT FROM AUTHOR]