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This study focuses on the efficient removal of Ni(II) from spent lithium-ion batteries (LIBs) to support environmental conservation and sustainable resource management. A composite material, known as molecular sieve (MS)-based metal-organic framework (MOF) composites (MMCs), consisting of a synthesized MS matrix with integrated MOFs, was developed for the adsorption of Ni(II). The structural and performance characteristics of the MMCs were evaluated using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and N2 adsorption-desorption isotherms (BET). Batch adsorption experiments were conducted to assess the Ni(II) adsorption performance of the MMCs. The results revealed that, under conditions of pH 8 and a temperature of 298 K, the MMCs achieved near-equilibrium Ni(II) adsorption within 6 h, with a maximum theoretical adsorption capacity of 204.1 mg/g. Further analysis of the adsorption data confirmed that the adsorption process followed a pseudo-second-order kinetic model and Langmuir isotherm model, indicating a spontaneous, endothermic chemical adsorption mechanism. Importantly, the MMCs exhibited superior Ni(II) adsorption compared to the MS. This study provides valuable insights into the effective recovery and recycling of Ni(II) from spent LIBs, emphasizing its significance for environmental sustainability and resource circularity.
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Central Plains urban agglomeration (CPUA) had developed rapidly, but its air pollution was also serious. Despite advances in study on China's PM2.5 emissions from coal consumption (CC), the differentiation characteristics and the affecting variables of PM2.5 in CPUA required further investigation. This paper computed the PM2.5 emissions of each city from 2000 to 2020 using CC data from CPUA, evaluated its spatio-temporal fluctuation characteristics using the spatial autocorrelation and analyzed its influencing factors by combining various indicators through the spatial Durbin model (SDM). The results verified that: (1) There was a trend of rapid increase of PM2.5 emissions from CC; (2) The Moran's I of the PM2.5 emissions from CC showed a significant agglomeration effect; (3) PM2.5 emissions from CC had a strong spillover effect. The recommendations were in this following: (1) The urban pollution regulation and the pace of industrial green transformation should be Strengthened; (2) Close linkages between cities should be established and attention should be paid to pollution management; (3) The spillover of PM2.5 emissions from CC should be lessened and development of environmental governance technology should be enhanced.
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China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006-2014 and 2015-2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed.
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Carbono , Desarrollo Sostenible , China , HumanosRESUMEN
Carbon emission reduction is an environmental and development issue that needs to consider various factors, such as the economy and people's livelihood. Supporting the achievement of emission reduction targets has become an important planning goal for provincial governments; however, there are differences in provincial industrial structure and economic development, which cannot be ignored in goal setting. This study measures the equity degrees of carbon emissions based on economic output by using provincial panel data from 2000 to 2019 and evaluates the spatial distribution characteristics of the carbon emission inequity index (CII). Then, analysis of the influencing factors to CII is employed by spatial econometric methods. Furthermore, multi-index panel data factor analysis and cluster analysis are used to divide regions. The empirical results show that nearly half of the provinces have the problem of carbon emissions inequity with significant spatial correlation. For local development, economic growth and population expansion will significantly improve the equity degrees of carbon emissions. In contrast, the growth of urbanization level, the percentage of secondary industry, and increased energy intensity will significantly improve the equity degrees of carbon emissions in neighboring regions. Policymakers should consider the factors influencing CII and formulate emission reduction plans according to regional characteristics.
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Carbono , Industrias , Humanos , Carbono/análisis , Desarrollo Económico , China , Urbanización , Dióxido de Carbono/análisisRESUMEN
China put forward that it would strive to achieve the carbon peaking in 2030 and carbon neutrality goals in 2060, which needed realizing the synergistic effect of pollution reduction and CO2 reduction. CO2 and PM2.5 from coal consumption were "homogenous and synchronous" and they had significant synergistic effect. The synergistic reduction of PM2.5 from coal consumption could have impacts on public health. The Logarithmic Mean Divisia Index (LMDI) was adopted to decompose the PM2.5 from coal consumption in China from 2012 to 2017 based on data availability and quantified the synergy. PM2.5 emissions from coal consumption were forecasted in 2030, 2035, 2050 and 2060, and its health effects of PM2.5 were estimated. The main conclusions were: (1) the synergy of CO2 and PM2.5 was the largest contribution factor of PM2.5 from coal consumption. (2) PM2.5 from coal consumption in 2060 would achieve the WHO air quality guidelines. (3) The most health effects economic loss from PM2.5 generated by coal consumption in China was in 2014. The health effects economic loss would have been decreased to negative by 2050. We should reinforce the synergistic effect of CO2 and PM2.5, improve energy efficiency and optimize energy structure to achieve PM2.5 pollution control and reduce health effects economic loss.
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Contaminantes Atmosféricos , Contaminación del Aire , Carbón Mineral , Dióxido de Carbono/análisis , Contaminación del Aire/prevención & control , Contaminación del Aire/análisis , China , Carbono , Material Particulado/análisis , Contaminantes Atmosféricos/análisisRESUMEN
Objective: To examine the prevalence of suicide-related behaviors among junior middle school students, and to explore the mediating role of depression in the relationship between suicide-related behaviors and family function. Methods: A total of 2572 junior middle school students from three middle schools in Chengdu were interviewed face-to-face by using suicide-related items from Youth Risk Behavior Surveillance System (YRBSS), Chinese Family Assessment Instrument (C-FAI), and Center for Epidemiologic Studies Depression Scale for Children (CES-DC). The mediating role of depression was analyzed with structural equation model. Results: The prevalence of suicide-related behaviors was 26.01% among the respondents. The prevalence of suicide ideation, suicide plan and suicide attempt were 24.38%, 13.49% and 10.77%, respectively. Depression played a partial mediating role in how family function impacted on suicide-related behaviors, presenting a direct effect value of 0.170 (95% CI: 0.117-0.218, P<0.001) and an indirect effect value of 0.205 (95% CI: 0.176-0.234, P<0.001), with the mediating effect accounting for 54.67% of the total effect. Conclusion: Poor family function may increase the risk of suicide-related behaviors, and this effect is produced mostly through the impact on children's mental health. Improving family function will not only improve children's psychological status, but also reduce suicide-related behaviors.
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Depresión , Asunción de Riesgos , Adolescente , Niño , Depresión/epidemiología , Humanos , Prevalencia , Factores de Riesgo , Instituciones Académicas , Estudiantes/psicologíaRESUMEN
Due to the fast growth of China's economy, urban atmospheric pollution has become a serious problem affecting the public's physical and mental health. The '2 + 26' cities, as the Jing-Jin-Ji atmospheric pollution transmission channel, has attracted widespread concern. There were several previous studies on the economic loss of public health caused by PM2.5 pollution in '2 + 26' cities. To assess the economic loss caused by PM2.5 on human health in '2 + 26' cities, this paper used the exposure-response model, the health effect loss model and willingness to pay method to obtain the economic loss from PM2.5 pollution with the latest available data in 2020. It was concluded that, in 2020, the economic loss of '2 + 26' cities from PM2.5 was spatially distributed low in the east and high in the west. In addition, it was larger in the southern and northern part, which was smaller in the middle of the region. Based on the conclusions, policy recommendations were put forward.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Ciudades , Monitoreo del Ambiente , Humanos , Material Particulado/análisis , Salud PúblicaRESUMEN
To better track the source of goods and maintain the quality of goods, the present work uses blockchain technology to establish a system for trusted traceability queries and information management. Primarily, the analysis is made on the shortcomings of the traceability system in the field of agricultural products at the present stage; the study is conducted on the application of the traceability system to blockchain technology, and a new model of agricultural product traceability system is established based on the blockchain technology. Then, a study is carried out on the task scheduling problem of resource clusters in cloud computing resource management. The present work expands the task model and uses the deep Q network algorithm in deep reinforcement learning to solve various optimization objectives preset in the task scheduling problem. Next, a resource management algorithm based on a deep Q network is proposed. Finally, the performance of the algorithm is analyzed from the aspects of parameters, structure, and task load. Experiments show that the algorithm is better than Shortest Job First (SJF), Tetris ∗ , Packer, and other classic task scheduling algorithms in different optimization objectives. In the traceability system test, the traceability accuracy is 99% for the constructed system in the first group of samples. In the second group, the traceability accuracy reaches 98% for the constructed system. In general, the traceability accuracy of the system proposed here is above 98% in 8 groups of experimental samples, and the traceability accuracy is close for each experimental group. The resource management approach of the traceability system constructed here provides some ideas for the application of reinforcement learning technology in the construction of traceability systems.
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Cadena de Bloques , Algoritmos , Nube Computacional , TecnologíaRESUMEN
Objective: To analyze the supply and demand adaptation of nursery care services for children under 3 in Sichuan Province and to provide strategic suggestions for optimizing nursery care services in Sichuan Province. Methods: Data on the supply and demand of nursery school services in all 21 cities (prefectures) of Sichuan Province were collected with questionnaires for nursery care institutions and family needs questionnaires. Applying the theory of supply and demand adaptability, we analyzed the adaptability of nursery care services in Sichuan Province in four dimensions, including relevance, adaptability, accessibility and quality. Results: A total of 6883 valid institutional questionnaires and 41081 valid family questionnaires were collected. The analysis of the adaptability of supply and demand showed that there was insufficient adaptability in all four dimensions of relevance, adaptability, accessibility, and quality of nursery care services for children under 3 in Sichuan Province, which was characterized by the coexistence of insufficient supply and underutilization of services, the mismatch between the structure of services provided and the needs of families with children under 3, low economic accessibility for the general population, and low quality of services. Conclusion: There is insufficient adaptability in the supply and demand of nursery care services for children under 3 in Sichuan Province. Demand-oriented supply-side reforms should be implemented to promote the construction of a system of government-subsidized affordable nursery care services, reinforced support for the care of infants and toddlers for families, standardized management of infant and toddler care institutions, and the implementation of various supportive policies so as to comprehensively meet the diversified needs of infant and toddler care and promote their healthy growth.
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Guarderías Infantiles , Casas Cuna , Preescolar , China , Femenino , Humanos , Lactante , MasculinoRESUMEN
The emissions reduction of CO2 and air pollutants are the main task in China. The two have the same roots and they interact with each other. However, CO2 and air pollutants are quite different in space, so it is of great practical significance to explore the spatial differences of their synergy. As PM2.5 and O3 are more concerned at present, thus, this paper examined the decoupling of CO2, PM2.5 and O3 from GDP in China's 296 cities using the latest available data from 2015 to 2016. And the spatial differences of synergy among CO2, PM2.5 and O3 were quantitatively analyzed by using spatial autocorrelation analysis and geographically weighted regression model. The results showed that: (1) The cities achieving the three synergy emissions reduction were mainly in the southeast of China. (2) Only 26 cities had achieved the strong decoupling of CO2, PM2.5 and O3 from GDP. (3) The synergy characteristics between CO2 and PM2.5, CO2 and O3 were different. This paper put forward the policies according to the conclusions.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Dióxido de Carbono/análisis , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisisRESUMEN
After years of governance, China's PM2.5 pollution has improved significantly, but some problems remain. PM2.5 is the carrier of many heavy metals, and it has a stronger capacity to carry heavy metals, causing more significant harm to public health. At present, most of the studies on PM2.5-bound heavy metals in China are based on individual cities, and there are few studies from China's provincial capital cities. Given the above reasons, this paper described the pollution characteristics of PM2.5-bound heavy metal (Hg, Pb, Cd, As, Cr(VI), Ni) in 29 provincial capital cities in China (except Hohhot and Lhasa). Furthermore, the human health risk assessment recommended by US EPA was used to evaluate the carcinogenic and non-carcinogenic risks of the male adults, the female adults, and the children. The results indicated that (1) the children were facing a higher risk value of PM2.5-bound heavy metals than the adults; (2) Cr, As, and Pb were the top three elements that contributed to the average non-carcinogenic risk, while Cr(VI), As, and Cd were the three elements with the highest carcinogenic risk; and (3) the concentrations of PM2.5-bound heavy metals in the provincial capital cities of northern China were worse than those in the South. In response to the above conclusions, this paper put forward: (1) the government should strengthen the management of metallurgical industry and coal-burning industrial enterprises; (2) establish a real-time monitoring system for toxic and harmful heavy metal pollutants carried in the atmosphere as soon as possible; (3) concern on the regional synergies to form pollution control metropolitan areas.
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Contaminantes Ambientales , Mercurio , Metales Pesados , Adulto , Cadmio , Carcinógenos/análisis , Niño , China , Cromo , Ciudades , Carbón Mineral , Monitoreo del Ambiente/métodos , Femenino , Humanos , Plomo , Masculino , Metales Pesados/análisis , Material Particulado/análisis , Medición de RiesgoRESUMEN
INTRODUCTION: It is not clear whether there are differences in the risk factors for nonsuicidal self-injury (NSSI) between children and early adolescents. Clarifying this question is crucial for identifying actionable prevention strategies for NSSI in these two age groups. METHOD: The study, comprising 8611 children and early adolescents (4409 (51.2%) children, 4202 (48.8%) early adolescents), was based on the baseline data of the Chengdu Positive Child Development (CPCD) in China. NSSI behaviours, emotional and behavioural problems and family environment were assessed and obtained via self-reports and parent reports. RESULTS: Overall, 2520 (29.26%) participants reported having ever engaged in NSSI. There was a higher lifetime NSSI rate in males than in females during childhood, contrasting with higher NSSI rates in females than in males during early adolescence. Furthermore, NSSI shared similar risk factors, including major family conflict and poor relationships with caregivers, in both age groups. Specifically, in children, the risk of NSSI increased along with thought and attention problems (OR, 95% CI: 1.194, 1.106-1.288 and 1.114, 1.028-1.207, respectively), whereas in early adolescents, it increased with anxiety and depressive problems (OR, 95% CI: 1.259, 1.116-1.422). CONCLUSIONS: The findings suggested the need for difference in preventive strategies for NSSI in the two age groups. It may be more efficacious to screen for NSSI in children with thought and attention problems and in early adolescents with anxiety and depressive problems.
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Trastornos Mentales , Problema de Conducta , Conducta Autodestructiva , Adolescente , Niño , Femenino , Humanos , Masculino , Psicopatología , Factores de Riesgo , Conducta Autodestructiva/diagnóstico , Conducta Autodestructiva/epidemiología , Conducta Autodestructiva/prevención & controlRESUMEN
The increasing uncertainty related to disaster risk under climate change brings about new challenges for sustainable urban management. The emergence of the urban resilience concept can improve the ability and extent to which cities can absorb and resolve risks, providing insight into the sustainable development of cities and regions. Yet, to date, the impact of climate change on regional urban resilience is not well understood. This paper measures the changes in urban resilience of the Beijing-Tianjin-Hebei (BTH) region from 1998 to 2019, and then explores the contribution of climate influencing factors such as temperature, precipitation and wind speed to urban resilience using econometric models. Results demonstrate the following: (1) Urban resilience shows a large spatial heterogeneity in the BTH region. Overall, Beijing and Tianjin have better and more stable resilience than Hebei Province. (2) Regarding the static impact of climate change on urban resilience, a 1 unit increase in Ln temperature and Ln precipitation will respectively increase Ln resilience by 1.01 units and 0.54 units, indicating that it has a significant positive impact on urban resilience. Each 1 unit increase in Ln wind speed will decrease resilience by 1.65 units, representing a significant negative effect. (3) Regarding the dynamic impact of climate change on urban resilience, a positive 1 unit impact of climatic factors indicates that an increase in temperature will first increase and then decrease urban resilience, and an increase in precipitation and wind speed will initially support improvement in urban resilience. Based on these findings, this article offers policy recommendations to improve urban resilience.
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Contaminación del Aire , Cambio Climático , Contaminación del Aire/análisis , Beijing , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisis , VientoAsunto(s)
Desarrollo Infantil , Niño , China/epidemiología , Estudios de Cohortes , Humanos , Encuestas y CuestionariosRESUMEN
Depression is one of the most prevalent psychiatric disorders and the leading cause of disability among adolescents, with sleep duration as its vital influential factor. Adolescents might be mentally sensitive to the stress caused by the COVID-19 pandemic. Yet, the alteration of adolescents' sleep duration, depression, and their associations within the context of the COVID-19 pandemic have not been well documented. We conducted a longitudinal study, recruiting 2496 adolescents from 3 junior high schools to examine the alteration of their sleep duration and depressive symptoms before and during the pandemic, and to explore their potential association(s). Data were collected before (December 2019) and during the pandemic (July 2020). Paired samples t-test revealed a significant decrease in sleep duration and a significant increase in depressive symptoms during the COVID-19 pandemic. Higher grades, COVID-19 infection history, higher CES-DC score, and the COVID-19 pandemic itself might contribute to decreased sleep duration, while longer exercise duration during the pandemic might be a protective factor. According to the cross-lagged analysis, the existence of depressive symptoms before the pandemic was significantly associated with a shorter sleep duration during the pandemic (ß = -0.106, p < 0.001). Previously shortened sleep duration was significantly associated with a greater likelihood of depressive symptoms during the pandemic (ß = -0.082, p < 0.001). Our findings revealed that the COVID-19 pandemic has a negative influence on adolescents' mental health and sleep. Mental preparedness should be highlighted to mitigate the psychosocial influences of any possible public emergencies in the future. Sleep duration represents a viable home-based intervention for depressive symptoms.
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COVID-19 , Trastornos Mentales , Adolescente , China/epidemiología , Estudios Transversales , Depresión/epidemiología , Humanos , Estudios Longitudinales , Pandemias , SARS-CoV-2 , SueñoRESUMEN
To address the CO2 emissions issue, China promised to increase its nationally determined contributions, trying to reach a CO2 emissions peak by 2030. For optimizing emission reduction policies, it is important to clarify the CO2 linkage structure and transfer characteristics. Previous research mainly focused on the calculation and comparison of CO2 linkage at the national level or the regional level and lacked inter-provincial sector-sector transfer analysis. This study uses hypothetical extraction method (HEM) to calculate the inter-provincial sectoral linkages of embodied CO2 in 2012 and 2015, providing a new perspective for sectoral CO2 linkage studies in China. We use net transfer to reveal the impact of provincial trade on the embodied CO2 emissions, and identify key CO2 emitter sectors. Combined with complex networks, we describe the clustering feature visualized and identify the transfer media sectors. The results are as follows: (1) the key sectors with large linkage are mainly the heavy industries located in North China. The electricity industry has the largest net CO2 outflow as the energy supplier, whereas the construction industry has the largest net inflow as the driving sector. (2) The CO2 transfer networks present closely connected and spatial clustering features, reflecting the embodied CO2 linkage between geographically adjacent sectors closer. (3) The important media sectors are mostly located in northwest China with small industrial scale and linkage degrees, such as the transport equipment industry in Shanxi. Emission reduction policies should be overall planned and tailored to local conditions. Consequently, possible policy implications of the results are discussed, which could provide additional insights for CO2 mitigation.
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ABSTRACT: Chronic obstructive pulmonary disease (COPD) is the fourth and third leading cause of death worldwide and in China, respectively. Sedentary behavior has been shown to increase the risk of respiratory disease, such as asthma. However, the relationship between sedentary behavior and COPD is unclear. This study aimed to investigate the association between sedentary behavior and COPD.Data was extracted from the 2018 a large-scale cross-sectional study of Chronic Disease and Lifestyle Population Survey in Sichuan Province of China, in which sedentary behavior and chronic diseases were self-reported according to medical records. The association between sedentary behavior on risk of COPD was estimated using multivariable regression model in non-matching cohorts and generalized propensity score-weighted (GPSW)cohorts, respectively, controlling for potential confounders.Individuals who remained sedentary for more than 7âhours per day were more likely to have COPD than the control group (<3âhours) both in conventional multivariate logistic regression analysis (ORâ=â2.020, 95%CI: 1.575-2.585, Pâ<â.001) and GPSW analysis (ORâ=â2.381, 95%CI: 1.778-3.188, Pâ<â.001). After GPSW and the sensitivity analysis using refined smoking variable further found a dose-effect between sedentary behavior and COPD, with 1.242 (95%CI: 1.006-1.532, Pâ<â.05) times risk of COPD in those sedentary behavior of more than 5âhours per day (GPSW) and 1.377 (95%CI: 1.092-1.736, Pâ<â.05) times risk in those sedentary behavior above 5âhours per day (sensitivity analysis), comparing with the control group.Sedentary behavior is independently associated with increased risk of COPD, adjusting for other confounders. The findings of this study have important implications for future research and public health guidance. Reducing sedentary time may have a significant role in COPD prevention.
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Enfermedad Pulmonar Obstructiva Crónica/epidemiología , Conducta Sedentaria , Adolescente , Adulto , Anciano , China/epidemiología , Factores de Confusión Epidemiológicos , Estudios Transversales , Femenino , Encuestas Epidemiológicas/estadística & datos numéricos , Humanos , Masculino , Persona de Mediana Edad , Puntaje de Propensión , Enfermedad Pulmonar Obstructiva Crónica/fisiopatología , Estudios Retrospectivos , Medición de Riesgo/estadística & datos numéricos , Factores de Riesgo , Adulto JovenRESUMEN
Carbon dioxide (CO2) emissions are currently a hot topic of global concern. It is of great significance for reducing CO2 emissions to fully understand the transfer pattern of CO2 emissions among industries and the key factors affecting CO2 emissions. This paper uses the structural path analysis model to explore deeply the main paths of inter-industry transfer of CO2 emissions in China from 2002 to 2017 and applies the structural path decomposition model to analyze the main factors affecting CO2 emissions in specific paths from the perspectives of CO2 emission intensity, intermediate product input structure, final demand structure, per capita final demand, and population size. The results show that: (1) China's CO2 emissions increased from 3500.41 million tons (Mt) in 2002 to 9475.66Mt in 2017, with an average annual growth rate of 6.86%. The growth rate of China's CO2 emissions slowed down after 2012. (2) Non-metallic mineral industry\electricity industry\metal products industryâ(intermediate sector)âinvestment demand and electricity industryâ(intermediate sector)âconsumption demand are two types of key paths that affect China's CO2 emissions, and these paths remain basically unchanged during the study period. (3) The CO2 emission intensity effect is the main factor in restraining the growth of emissions, and the per capita final demand effect and intermediate product structure effect are the main promoting factors. The effect of driving factors on different industrial paths is different, and the offsetting effect of the driving factor in different paths may lead to the insignificant effect of this factor in the overall decomposition. To effectively reduce CO2 emissions, China should focus on specific industrial paths and implement upstream and downstream comprehensive governance to achieve a low-carbon industrial chain throughout the whole process.
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At present, the concentration of PM2.5 in the Fenwei Plain has become the second highest in China, ranking second to the Beijing-Tianjin-Hebei region. At the same time, China began to monitor and control the PM2.5 concentration in the Fenwei Plain, but the data indicated that the concentration of PM2.5 in the Fenwei Plain rose instead of falling. PM2.5 concentrations in 6 cities from the Fenwei Plain ranked highest among the 20 cities in 2018 in China, and PM2.5 pollution can cause some health economic loss. Based on this background, the exposure-response model is used to estimate the impact of PM2.5 pollution on the health economic loss in the Fenwei Plain, and PM2.5 concentration in 2020, 2025, and 2030 is also predicted based on the setting of three scenarios: baseline scenario, emission reduction scenario, and enhanced emission reduction scenario. Then, according to the estimated results, the paper provides suggestions for reducing public health loss in the Fenwei Plain in the future.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Beijing , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisis , Salud PúblicaRESUMEN
In China, cities are the basic units for implementing CO2 abatement policies. However, few studies have comprehensively explored the spatial characteristics of CO2 emissions (CEs) and their influencing factors at the city level from different perspectives. After collecting spatial data from 280 Chinese prefecture-level cities for 2005, 2012, and 2015, this work firstly uncovered the overall and local spatial characteristics of CEs by adopting spatial autocorrelation analysis. Then, five influencing factors, including the total resident population (POP), per capita GDP (PCGDP), energy intensity (EI), the proportion of secondary industry (SI), and climate factor-heating degree days (HDD), were examined using global and local regression models. The analyses revealed that (1) CEs presented spatial agglomeration features from global and local perspectives, indicating spatial association between neighboring cities; and (2) POP, PCGDP, EI, and HDD had statistically significant spatial correlations with CEs, and their effect sizes were as follows: PCGDP > POP > EI > HDD. More importantly, the impacts of these influencing factors on CEs varied across cities, exhibiting obvious spatial heterogeneity. According to these findings, local governments should strengthen coordination and cooperation with their surrounding cities to promote regional synergistic action on emission reduction. In addition, policymakers should also design differentiated abatement policies based on regional characteristics and differences instead of applying similar policies to all cities.