Development of family resource indicators for people with schizophrenic disorder in community by modified Delphi method in Beijing, China.

INTRODUCTION: Most people with schizophrenia in China are supported by their family members in community. The patient's family is confronted with severe care burden and pressure, which directly affects the caregiver's own health and social life, and indirectly affects the patient's rehabilitation. Adequate family resources can reduce the burden and pressure on families. But there is an absence of systematic family resource indicators for people with schizophrenic disorder in China. OBJECTIVES: This study aimed to develop a set of family resource indicators for people with schizophrenic disorder in China. DESIGN: Preliminary family resource indicators were generated and refined by literature review and an expert consultation meeting. Two rounds of email-based Delphi survey were carried out to identify family resource indicators. SETTING: Two rounds of email-based Delphi survey were performed from July to September 2021 in Beijing, China. PARTICIPANTS: There were 15 mental health doctors from community health service centres and four psychiatrists from tertiary hospitals, and two primary care researchers from universities in the first and second rounds Delphi survey. RESULTS: All the 21 experts participated in both rounds of Delphi survey. A total of 46 indicators achieved consensus for inclusion in the final set of indicators after two rounds of Delphi survey. The final set of indicators was grouped into 10 domains: financial support (three indicators), psychological and spiritual support (eight indicators), medical treatment (three indicators), information and education (three indicators), structural support (two indicators), external family resources included social resources (five indicators), cultural resources (two indicators), economic resources (seven indicators), environmental resources (four indicators) and medical resources (nine indicators). CONCLUSIONS: A set of 46 family resource indicators for people with schizophrenic disorder in community was identified by an iterative Delphi process in Beijing, China. However, the indicators still need to be validated by testing in further studies.

[Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020].

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Quality adjustment and analysis of human resource prices in China: Based on a hedonic price model.

The competition in the world has shifted from natural resources and capital resources to human resources. The human resources have become the real power source of the economic growth. Firstly, the price of human resources in China is calculated. Secondly, in order to measure the human resources quality adjustment index, the indicators system is constructed. Third, the Hedonic method is used to calculate the human resources "pure price" of 31 provinces (autonomous regions and municipalities directly under the Central Government) in China. The "pure price" has no the factor of human resources quality. Lastly, comparing the price of human resources before and after quality adjustment. The results show that: first, the number of human resources in China increased continuously during 1995-2015 and decreased during 2016-2020. Second, the price of nominal human resources in China keeps rising. In 2020, the nominal price is 39,087 yuan per person which is 15.44 times as many as in 1995. Thirdly, after the quality adjustment, the price of human resources has decreased significantly. The multiple between the actual and nominal price of human resources is between 1.75 and 2.12. Fourthly, the province with high human resource quality adjustment index generally have high quality human resource level or quantity. Fifth, the top five provinces of actual human resource prices are Shanghai, Beijing, Guangdong, Tianjin, Zhejiang, the bottom five provinces are Guizhou, Yunnan, Henan, Xizang, Gansu. Finally, the paper puts forward some policy recommendations: Improving the data collection mechanism of human resources accounting to provide a basic guarantee for the accurate accounting of human resources. Improving the price of human resources in the central and western regions to attract the talents to transfer to the central and western regions. Enhancing the skills training of human resources to improve the quality of human resources in the western region.

[Efficiency Characteristics and Evolution Patterns of Urban Carbon Metabolism of Production-Living-Ecological Space in Beijing-Tianjin-Hebei Region].

This study explored the carbon metabolism efficiency of a production-living-ecological space system, which is of great significance for regional factor integration and spatial optimization. In this study, the material flow analysis method was introduced to establish a framework for evaluating the carbon metabolism efficiency of the production-living-ecological space system, and the super-efficiency DEA model and Malmquist index were used to empirically analyze the spatio-temporal distribution, dynamic change, and evolution patterns of the carbon metabolism efficiency of production-living-ecological space in the Beijing-Tianjin-Hebei Region, China, from 2000 to 2020 on the basis of the urban metabolic perspective. The results showed that:① the carbon metabolism efficiency of the production-living-ecological space showed a fluctuating growth trend, indicating the significant spatial differentiation of carbon metabolism efficiency in each city. There was a low overall carbon metabolism efficiency level, with a distribution pattern of being high in the middle and low in the north and south. ② The Malmquist index showed that the Total Factor Productivity (TFP) of carbon metabolism efficiency was greater than 1, and both the Technical Change (TC) and Pure Efficiency Change (PEC) were less than 1, in which the TFP showed an increasing trend, whereas there was no significant contribution of technological progress or pure technical efficiency to carbon metabolism efficiency. The total factor productivity of more than 50% of the cities showed an improving trend, only 38.46% of which made technological progress in improving carbon metabolism efficiency, and more than half of the urban pure technical efficiency showed a decreasing trend, in which the technical efficiency change and scale efficiency change were greater than 1 in most cities. ③ There were different types of carbon efficiency characteristics in each city, and according to the movement rules of the corresponding points in the quartile map, the evolution patterns of tourism industry efficiency were classified into stable, reciprocating, progressive, and abrupt. Therefore, local governments should adopt differentiated strategies to reasonably allocate spatial resources of production-living-ecological space and improve the technical level and scale efficiency, so as to improve the efficiency of urban carbon metabolism.

Preliminary study on the enhanced bioremediation of PAH-contaminated soil in Beijing and assessment of remediation effects based on toxicity tests.

In this study, we focused on soil contaminated by polycyclic aromatic hydrocarbons (PAHs) at typical coking-polluted sites in Beijing, conducted research on enhanced PAH bioremediation and methods to evaluate remediation effects based on toxicity testing, and examined changes in pollutant concentrations during ozone preoxidation coupled with biodegradation in test soil samples. The toxicity of mixed PAHs in soil was directly evaluated using the Ames test, and the correlation between mixed PAH mutagenicity and benzo(a)pyrene (BaP) toxicity was investigated in an effort to establish a carcinogenic risk assessment model based on biological toxicity tests to evaluate remediation effects on PAH-contaminated soil. This study provides a theoretical and methodological foundation for evaluating the effect of bioremediation on PAH-contaminated soil at industrially contaminated sites. The results revealed that the removal rate of PAHs after 5 min of O3 preoxidation and 4 weeks of soil reaction with saponin surfactants and medium was 83.22%. The soil PAH extract obtained after remediation had a positive effect on the TA98 strain at a dose of 2000 µg·dish-1, and the carcinogenic risk based on the Ames toxicity test was 8.98 times greater than that calculated by conventional carcinogenic PAH toxicity parameters. The total carcinogenic risk of the remediated soil samples was approximately one order of magnitude less than that of the original soil samples.

Digital inclusive finance, industrial structure, and economic growth: An empirical analysis of Beijing-Tianjin-Hebei region in China.

As a product of combining digital technology and traditional finance, digital inclusive finance plays a vital role in economic growth. This paper deeply analyzes the impact of digital inclusive finance on economic growth and the specific transmission path. This research selects the municipal panel data of Beijing-Tianjin-Hebei from 2011 to 2020 and empirically studies the impact of digital inclusive finance on economic growth. From the perspectives of industrial structure transformation speed, industrial structure upgrading, and industrial structure rationalization, this study analyzes the role of industrial structure in the impact of digital inclusive finance on economic growth and tests the heterogeneity of the impact of digital inclusive finance on economic growth. The results show that digital inclusive finance has a significant role in promoting economic growth. The depth of use of digital inclusive finance has the most significant impact, followed by the breadth of coverage, and the degree of digitization is the smallest. The industrial structure transformation speed and the industrial structure rationalization play a significant intermediary role in the economic growth effect of digital inclusive finance, and the industrial structure upgrading has no significant impact on the economic growth effect of digital inclusive finance; the promotion effect of digital inclusive finance on economic growth is bigger in the economically developed group, the higher digital inclusive finance group and the technologically developed group, and the promotion effect is smaller in the economically underdeveloped group, the lower digital inclusive finance group and the technologically underdeveloped group. The results provide a strong reference for policy formulation to promote the development of digital inclusive finance and economic growth.

Spatial accessibility and equity of residential care facilities in Beijing from 2010 to 2020.

In recent years, the aging population in Beijing has rapidly increased and the demand for residential care facilities (RCFs) has also risen. As RCFs have quickly developed, the question of whether residential care resources dynamically match the changes in the demand of the elderly population is an urgent issue that must be addressed. This study analyzes the spatiotemporal variation in the supply and demand of RCFs, applies a Gaussian two-step floating catchment area method with a multi-level search radius to measure the spatial accessibility of RCFs in Beijing in 2010 and 2020, and evaluates the equity of spatial accessibility. The results show that the elderly population was decentralized from the central urban area to New Urban Development Area. However, the distribution of RCF beds shows further agglomeration towards the central urban area. The accessibility of residential care resources in the central urban area and New Urban Development Area has increased, while accessibility in Ecological Protection Area has decreased. The spatial disparities in accessibility have been reduced and the spatial equity in accessibility has been improved over the past decade. The findings provide policy recommendations for the future allocation of RCFs by considering the spatiotemporal changes in the distribution of the supply and demand of residential care resources.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Spatial disparities and internal subsystems'coupling coordination analysis of green development in Chinese animal husbandry.

This study establishes an indicator system encompassing economic, social, and environmental dimensions to assess the level of green development in animal husbandry from 2010 to 2020. It further examines the coupling coordination degree within each dimension. The Dagum Gini coefficient is employed to scrutinize the regional disparities in coupling coordination degree of the economic benefit, social benefit, and environmental benefit of the green development in Chinese animal husbandry. Additionally, Moran's I is utilized to identify the degree of spatial autocorrelation and aggregation types. The results demonstrate the following: (1) From 2010 to 2020, the level of green development in the animal husbandry in China has steadily improved. Among the three dimensions, economic benefits exhibit the highest performance, followed by environmental benefits and social benefits. There are obvious regional disparities in the green development of animal husbandry, which are "strong in north and weak in south" and "strong in west and weak in east." The Gini coefficient for green development in the animal husbandry in China experienced a fluctuating upward trend. (2) From 2010 to 2020, the overall coupling coordination degree of the economic benefit, social benefit, and environmental benefit of green development in the animal husbandry in China remains at a rudimentary level and demonstrates a steady upward trend. Spatially, it manifests an agglomeration pattern primarily centered around Beijing, with the northeastern region being the main focus. (3) The Gini coefficient for the coupling coordination degree experienced a slight fluctuating upward trend. In terms of inter-regional disparities, significant differences are observed between the northeastern region and the central region, as well as between the northeastern region and the eastern region. In terms of contribution to disparities, inter-regional contributions were the most substantial, followed by super-variable density, with intra-regional contributions being the smallest. (4) The coupling coordination degree displayed spatial autocorrelation, with "high-high" aggregation areas predominantly concentrated in the northeastern region.

Carbon emissions in China's urban agglomerations: spatio-temporal patterns, regional inequalities, and driving forces.

Urban agglomerations are the centers of carbon emissions. However, research on sector-specific carbon emissions in different urban agglomerations is still limited. Drawing on the data of China's six urban agglomerations in 2005, 2010, and 2015, this study investigates the spatio-temporal patterns, regional inequalities, and driving forces of total, industrial, transportation, and residential carbon emissions. The study found that Beijing-Tianjin-Hebei was the total and sectoral emission center among the studied urban agglomerations. Additionally, regional carbon inequalities gradually decreased, implying a growing regional synergistic carbon pattern. The driving forces of carbon emissions, including population, GDP, energy intensity, secondary industry, tertiary industry, foreign investment, urbanization, and green coverage, varied across sectors and regions. Notably, foreign investment could lead to lower carbon emissions in less developed agglomerations like Beijing-Tianjin-Hebei, the Central Plains, and the middle reaches of the Yangtze River, whereas more developed agglomerations like the Yangtze River Delta and the Pearl River Delta benefited less from foreign investment. Besides, ChengYu has good ecological conditions and sustainable development modes, which linked urbanization and green space to reduced carbon emissions in the industrial sector. The findings can help formulate differentiated carbon policy and support sustainable development.

Medical expenses of patients with severe mental disorders in Beijing, China.

OBJECTIVES: Mental health has become a significant public health problem that impacts both economic and social development, with severe mental disorders (SMDs) being the top priority. Over recent years, Beijing, China, has introduced several policies to reduce the economic burden on patients with mental health disorders. The aim of this study was to investigate the current status and composition of patients' medical expenses following the introduction of multiple medical policies, explore the factors that may impact the utilisation of medical services and provide a reference and basis for subsequent policy improvements. STUDY DESIGN: Multistage sampling was used to select a representative study population. A retrospective survey was used to collect patient information and data on medical expenses in 2019. METHODS: Descriptive statistics were applied to analyse the current status of patients' medical expenses, and a two-part model was used to examine the factors influencing healthcare utilisation and to model predicted expenses. RESULTS: Among 4940 participants, the average outpatient expenses of patients with SMD who incurred medical expenses were 8373.61 Yuan, and the average hospitalisation expenses were 81,594.05 Yuan. The out-of-pocket expenses were 29.22% of outpatient expenses and 8.13% of inpatient expenses. Factors such as age, household status, economic status, marital status, participation in the Community Free-Medication Service (CFMS) and the type of disease diagnosed influenced the differences in medical expenses and utilisation of services. CONCLUSIONS: The medical expenses of patients with SMD in Beijing are high, but a number of introduced policies have effectively reduced these costs for patients. Future studies should focus on the impact of factors such as age, economic status, participation in the CFMS and the type of disease diagnosed on medical expenses.

Spatial pattern of China's rural digital economy based on subjective-Objective evaluation: Evidence from 2085 counties.

The rural digital economy plays an essential role in China's industrial upgrading, transformation, and urban-rural integration. To determine the state of China's rural digital economy, we constructed a county-level evaluation system using the subjective-objective evaluation method and calculated the digital economic levels of 2085 counties. Then, we analyzed the spatial distribution characteristics, spatial autocorrelation pattern, spatial disequilibrium degree, and spatial driving force of the rural digital economy at the county level using spatial analysis technology and a self-organizing feature mapping model. The results are as follows: 1) Compared with the real economy, the agglomeration effect of the digital economy was more obvious, and the economic gradient was more significant. Specifically, the dense high-value regions formed a continuous belt on the eastern coast from the Beijing-Tianjin area to the Pearl River Delta, opposite the dense low-value regions in the west. 2) There were significant differences in the rural digital economy within cities or provinces. Intraregional differences were not necessarily linked to the overall digital economy level because central and northeastern China presented a more balanced rural digital economy. 3) Digital network performance, e-commerce level, and economic vitality were identified as the core factors influencing the rural digital economy.

A novel integrated Urban flood risk assessment approach coupling GeoDetector-Dematel and clustering method.

Urban flood risk assessment plays a crucial role in disaster prevention and mitigation. A scientifically accurate assessment and risk stratification method are of paramount importance for effective flood risk management. This study aims to propose a comprehensive urban flood risk assessment approach by coupling GeoDetector-Dematel and Clustering Method to enhance the accuracy of urban flood risk evaluation. Based on simulation results from hydraulic models and existing literature, the research established a set of urban flood risk assessment indicators comprising 10 metrics across two dimensions: hazard factors and vulnerability factors, among which vulnerability factors include exposure factors, sensitivity factors, and adaptability factors. Subsequently, the research introduced the GeoDetector-Dematel method to determine indicator weights, significantly enhancing the scientific rigor and precision of weight calculation. Finally, the research employed the K-means clustering method to risk zonation, providing a more scientifically rational depiction of the spatial distribution of urban flood risks. This novel comprehensive urban flood risk assessment method was applied in the Fangzhuang area of Beijing. The results demonstrated that this integrated approach effectively enhances the accuracy of urban flood risk assessment. In conclusion, this research offers a new methodology for urban flood risk assessment and contributes to decision-making in disaster prevention and control measures.

Polychlorinated naphthalenes in freshwater fish from Beijing markets: Species-specific differences, effects of cooking, and health risk assessment.

Fish are an important source of human dietary exposure to polychlorinated naphthalenes (PCNs). The occurrence and sources of PCNs in different species of freshwater fish are unknown, and few studies have assessed human exposure risks to PCNs through freshwater fish. In this study, 140 freshwater fish samples from 10 species were collected from Beijing markets, China. The Σ75CNs concentration range in the fish was 20.7-1310 pg/g wet weight (ww). The highest median Σ75PCNs concentration (80.4 pg/g ww) was found in mandarin fish (Siniperca chuatsi), and the lowest (29.6 pg/g ww) in snakehead (Channa argus). Di- and tri-CNs were the dominant PCN homologues with contributions of 35.3 % and 30.8 %, respectively. Unintentionally produced PCNs from metal smelting might be the source of PCN contamination in freshwater fish. The cooking temperature and time did not significantly affect the PCN concentrations in fish or the PCN homologue profiles. The highest toxic equivalent (TEQ) value was observed in sturgeon (Acipenser sinensis), followed by mandarin fish. Hexa-CNs were the most abundant homologue for the PCN TEQs. A risk assessment indicated that the dietary exposure risks for local residents to PCNs through freshwater fish were low. However, the relatively high concentrations of PCNs in the samples deserve attention to avoid PCNs exposure risks for groups with high fish consumption rates. Furthermore, freshwater fish likely contain a mixture of contaminants including dioxin and furans which also display a similar mode of toxicity as the PCNs and could enhance the risk to fish consumers.

The spatial and temporal situation of China's digital technology innovation and its influencing factors.

Digital technology innovation is the core driving force for the high-quality development of the digital economy, and in-depth exploration of the regional distribution pattern and formation mechanism of digital technology innovation in China is conducive to the rational layout and coordinated development of the inter-provincial digital economy. Based on the Reference Relationship Table of the Classification of Core Industries of Digital Economy and the International Patent Classification (2023), the patent authorization data of digital technology from 2012 to 2022 were obtained, and the spatiotemporal situation of China's digital technology innovation was analyzed by using ArcGIS software, Dagum's Gini coefficient, and Moran's I index, and the spatial Dubin panel model was used to explore the influencing factors of digital technology innovation. It is found that: (1) the scale and vitality of China's digital technology innovation have increased significantly, and there are obvious spatial differentiation characteristics, and the innovation level of "eastern coastal-central and western interior" is decreasing, forming a cluster distribution pattern in the Yangtze River Delta region, Beijing, Guangdong, and other places, and the degree of agglomeration is decreasing. (2) The overall regional differences in China's digital technology innovation are large, the differences between the East and the West dominate the interregional differences, and the net differences between regions are the main factors leading to regional differences. (3) There is a significant positive spatial correlation between the scale and vitality of digital technology innovation, which has a significant spatial spillover effect. (4) The results confirm that the level of economic development, digital access, financial scientific and technological support, technology market development level, and R&D intensity have a significant positive impact on the scale and vitality of digital technology innovation; The investment in scientific and technological talents has a significant positive impact on the scale of digital technology innovation, but has no significant impact on the vitality of digital technology innovation.

Evaluation on evolution of spatial relationship between carbon emissions and economic growth in Beijing-Tianjin-Hebei region.

The Beijing-Tianjin-Hebei region is not only an important economic center in China, but also one of the major regions contributing to China's carbon emissions. Revealing the spatial distribution between carbon emissions and economic growth is essential for the formulation of low-carbon development policies. Following the principle from macro to micro, this paper investigates the spatial evolution trend and distribution characteristics between carbon emissions and economic growth in the Beijing-Tianjin-Hebei region from 2005 to 2020 by applying imbalance index model, the rank-scale rule, and decoupling index model. The results show that the imbalance index of carbon emissions decreased between 0.0601 and 0.0533 in a fluctuating way, indicating that the imbalance of spatial distribution of carbon emissions decreases. The imbalance index of economic growth increased between 0.0738 and 0.0851, indicating that economic growth has become more disequilibrated, and the spatial evolution of carbon emissions is not coordinated with economic growth. The Zipf dimension of carbon emissions declined from 1.1806 in 2005 to 0.9594 in 2020, and carbon emissions declined in big cities and increased in cities of the middle order. The Zipf dimension of economic growth increased from 1.1384 in 2005 to 1.2388 in 2020, and the economic growth monopoly in big cities increased. The decoupling coefficient of carbon emissions to economic growth declined, and the driving effect of economic growth on carbon emissions diminished. It is recommended that the Beijing-Tianjin-Hebei region should coordinate the allocation of factors and coordinate industrial adjustment. Hebei should accelerate industrial upgrading and establish a diversified industrial system.

Responsibility-sharing and compensation scheme of transboundary water pollution embodied in China's inter-provincial trade: a perspective from economic value capturing.

Transboundary water pollution induced by inter-regional trade is a complex and challenging issue due to the multiple jurisdictions involved. This study combined water pollution discharge inventory, multi-regional input-output analysis, discharge responsibility-sharing, and ecological compensation model to advance the collaborative control of water pollution embodied in China's inter-provincial trade. Over a fifth of China's water pollution discharges in 2017, equivalent to 1376 Kt, were a result of inter-provincial trade, which primarily flowed from wealthier coastal provinces to less developed ones. Moreover, the analysis demonstrates a mismatch between economic gains and environmental costs. In particular, Jiangxi and Guangxi bear the greatest environmental impact (64 and 58 Kt, respectively) while only receiving meager economic returns (131 and 80 billion Yuan). The economic benefit shared responsibility results for the great majority of provinces fell between production- and consumption-based discharges, and this compromise-based allocation of responsibility is more likely to gain acceptance across various regions. Provinces such as Shanghai, Jiangsu, and Beijing necessitate the highest compensation volumes to others, with 31 Kt, 25 Kt, and 20 Kt, respectively, while provinces including Guangxi, Jiangxi, and Ningxia require the largest inflows of compensation, totaling 26 Kt, 23 Kt, and 18 Kt, respectively. The compensation outcomes ensure that less developed regions, bearing a greater pollution burden, receive compensation from more developed regions with lower pollution burdens. The compensation values aligned with compensation volumes, with a few exceptions driven by variations in shadow prices of water pollution. Our study sheds light on the inter-provincial water pollution burdens and benefits and provides a quantitative basis for optimizing the responsibility-sharing and compensation strategies in China, thereby promoting regional cooperation on water pollution control.

An analysis and prediction of carbon emissions in the sphere of consumer lifestyles in Beijing.

In alignment with China's "dual carbon" goals and its quest to build an ecological civilization, this study scrutinizes the carbon emissions derived from consumer lifestyles, with a particular focus on Beijing, a high-consumption urban metropolis. Utilizing the expanded STIRPAT model and ridge regression, factors such as permanent population, per capita consumption expenditure, energy intensity, energy structure, and consumption structure are examined to evaluate their impact on lifestyle-associated carbon emissions. A scenario analysis is also conducted to project future carbon emissions in Beijing. From 2010 to 2020, there was an overall upward trend in lifestyle-associated carbon emissions, up to a maximum of 87.8260 million tons. Indirect consumption-related carbon emissions, particularly those associated with residential and transportation-related consumption, constituted the primary sources. The most influential factors on carbon emissions were found to be the consumption structure. Notably, adopting a low-carbon consumption mindset and an optimized consumption structure could foster significant carbon reduction. Projections suggest that by 2035, carbon emissions due to residents' consumption could decline by 39.72% under a low-carbon consumption scenario and by 48.74% under a coordinated development scenario. Future efforts should prioritize promoting green, low-carbon living, refining consumption structure and practices, curbing excessive housing consumption, improving energy structure, and raising technological and energy efficiency standards.

[Cardiovascular diseases burden attributed to low physical activity in China, 1990-2019].

Objective: To analyze the burden of cardiovascular disease (CVD) attributed to low physical activity (LPA) and its changing trends in China from 1990 to 2019. Methods: On the basis of the province results of the Study of Global Burden of Disease 2019 in China, we described the distribution of CVD death and disability-adjusted life year (DALY) attributed to LPA by sex, age and province. Joinpoint 4.9.1.0 was used to calculate the average annual percentage change. Results: In 2019, the number of CVD deaths and DALY attributed to LPA in people aged ≥25 years were 0.127 million and 1.863 million person-years in China, respectively, The age-standardized mortality rate (ASMR) and standardized DALY rate of CVD attributed to LPA were slightly higher in men than in women, and much higher in ischemic heart disease patients than in ischemic stroke patients. The ASMR (8.85/100 000) and the standardized DALY rate (112.34/100 000) of CVD attributed to LPA in China in 2019 showed no obvious change compared with 1990, while decreased in the last decade. The largest increases in the mortality rate and DALY rate were observed in people aged ≥75 years from 1990 to 2019 (26.89%, 15.61%), but the mortality rate and DALY rate in people aged 60-74 years showed a decreasing trend. The mortality rate and DALY rate in men aged 25- 44 years showed the largest increases (37.50%, 35.49%), while women aged ≥75 years had the largest increases (31.00%, 18.02%). In 2019, the highest ASMR and standardized DALY rate of CVD attributed to LPA were found in Jilin, Inner Mongolia and Hebei. The largest increases were found in Qinghai (182.41%, 154.70%), Gansu (181.29%, 152.77%), and Chongqing (132.01%, 102.79%) and the largest decreases were found in Beijing (59.11%, 62.09%), Macau (41.89%, 39.37%) and Guangdong (36.93%, 40.72%) from 1990 to 2019. Conclusion: The disease burden of CVD attributed to LPA in China was quite high and showed gender, age and area specific differences.

Quantifying the direct and indirect impacts of urban waterlogging using input‒output analysis.

Increasingly frequent urban waterlogging disasters are having profound social and economic consequences. An appropriate and integrated evaluation of the total economic impacts of such disasters is crucial for achieving effective urban disaster risk management and sustainable development. However, existing metrics are inadequate for measuring the economic impacts of rainfall events of different intensities and their ripple effects across regions. Moreover, their ecological impacts have received insufficient attention. To address these gaps, we developed an integrated assessment framework for analyzing urban waterlogging losses and evaluating their various impacts. Taking Beijing as a case study, we used the InfoWorks ICM model to simulate urban waterlogging disaster risks, quantified direct economic losses, and assessed their environmental impacts. Additionally, we estimated indirect economic losses using input-output analysis and explored spillover effects. The results revealed increasing trends of direct economic losses and environmental losses corresponding to a longer return period. We observed synergies between these losses and their spatial heterogeneity. However, indirect impacts far outweighed direct impacts, with the former being 2.43 times larger than the latter. The cascading effect resulting from damage to infrastructure was also particularly pronounced. The industrial and spatial heterogeneity of interregional impacts was striking, with eastern provinces evidencing the most significant effects. By mapping the transmission paths of disaster losses along industrial chains and across regions, this study provides inputs that could assist policymakers in developing more effective measures for preventing and mitigating urban waterlogging disasters.