Understanding the potential of taxi sharing: The case of Chengdu.

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network.

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.

Assessing landscape fragmentation in a desert-oasis region of Northwest China: patterns, driving forces, and policy implications for future land consolidation.

Landscape fragmentation is considered a serious threat to eco-environmental integrity and socioeconomic development. Although many studies have focused on landscape fragmentation resulting from agricultural production and urbanization, landscape fragmentation from the aspects of patterns, driving forces, and the policy perspective of ecosystems has rarely been investigated. Oases, as a unique landscape, face severe fragmentation in arid and semiarid regions. This study applied a combination of approaches, including remote sensing image interpretations, landscape fragmentation metrics, and community surveys, to analyze patterns and their driving forces, as well as the policy implications for future land consolidation, in the Hotan oasis of Northwest China from the space and time perspectives. Results show that the frequent occurrence of summer flood events changes the patch number, density, size, and splitting degree of oasis-desert ecotone vegetation. The socioeconomic factors including total population and irrigation area are more important driving forces on oasis landscape fragmentation, compared with natural factors such as temperature and precipitation. Rural expansion, road and canal system developments caused by population growth, and the rising number of households increase oasis landscape fragmentation. Rapid economic development, such as agricultural expansion and urbanization, has imposed the intensification of landscape fragmentation. Fragmentation reaches peak when agricultural development makes up 40-50% of study area. Rural residential reconstruction and farmland transfer policies facilitate the intensive utilization of land toward oasis fragmentation solutions, but many factors, such as landholders' household characteristics and living conditions, are partly responsible for the challenges in land consolidation. This study also demonstrates that intense human activities pose a great threat for land consolidation and sustainable development of oasis landscape.

Decoupling Effect of County Carbon Emissions and Economic Growth in China: Empirical Evidence from Jiangsu Province.

Under the pressure of low-carbon development at county level in China, this paper takes Jiangsu province as an example to analyze the relationship between economic growth and carbon emissions, aiming to provide a reference for the low-carbon development in Jiangsu and other regions in China. Based on the county-level panel data from 2000 to 2017, this paper uses the Tapio elasticity model and environmental Kuznets curve model, and focuses on the differences in regional economic development and the impacts of the 2008 global economic crisis. The results show that, in general, the decoupling effect of carbon emissions in Jiangsu counties has gradually increased during the study period. Since 2011, all counties achieved the speed decoupling, with more than half of them showing strong decoupling. The environmental Kuznets curves of carbon emissions in different income groups are established, and changed before and after the 2008 global economic crisis. In 2017, only 10 of the 53 counties were on the right side of the curve, realizing the quantity decoupling between the two. Therefore, to achieve a win-win situation between carbon emission reduction and economic growth, efforts should be made from the aspects of industrial structure and energy efficiency, and measures should be taken according to local conditions.

Does Environmental Regulation Promote Industrial Green Technology Progress? Empirical Evidence from China with a Heterogeneity Analysis.

The complex relationship between environmental regulation and green technology progress has always been a hot topic of research, especially in developing countries, where the impact of environmental regulation is important. Current research is mainly concerned with the impact of the single environmental regulation on technological progress and lacks study on the diversity of environmental regulations. The main purpose of this paper is to examine the heterogeneity of the effects of different types of environmental regulation on industrial green technology progress. As China's scale of economy and pollution emissions are both large, and the government has also made great efforts in environmental regulation, this paper takes China as the example for analyses. We first use the EBM-GML method to measure the industrial green technology progress of 30 provinces in China from 2000 to 2018, and then apply the panel econometric model and threshold model to empirically investigate the influence of 3 types of environmental regulation. The results show that, first, the impacts of environmental regulation on industrial green technology progress are significantly different; specifically, command-based regulation has no direct significant impact, and autonomous regulation has played a positive role, and market-based regulation's quadratic curve effect is significant, in which the cost-based and investment-based tool presents an inverted U-sharped and U-sharped, respectively. Second, there may be a weak alternative interaction among different types of environmental regulation. Third, a market-based regulatory tool has a threshold effect; with the upgrading of environmental regulation compliance, the effect of a cost-based tool is characterized by "promotion inhibition", and that of an investment-based tool is "inhibition promotion". Finally, the results of regional analysis are basically consistent with those of the national analysis. Based on the study, policy enlightenment is put forward to improve regional industrial green technology progress from the perspective of environmental regulation. This paper can provide a useful analytical framework for studying the relationship between environmental regulation and technological progress in a country, especially in developing countries.

Gender-specific and age-specific associations of the homoeostasis model assessment for IR (HOMA-IR) with albuminuria and renal function impairment: a retrospective cross-sectional study in Southeast China.

OBJECTIVES: The study aimed to investigate the association of insulin resistance (IR), which was estimated by the homoeostasis model assessment for IR (HOMA-IR), with albuminuria and renal function impairment in a general Chinese population. DESIGN: A retrospective cross-sectional study. SETTING AND PARTICIPANTS: A total of 13 742 adults (age: ≥18 years) who underwent a health check-up at a hospital in Southeast China during 2013-2014 were enrolled. 216 subjects were excluded due to lack of enough fasting time, be pregnant, have chronic diseases influencing metabolic functions or have glomerulonephritis, renal cancer, kidney transplant. Eventually, 7552 men and 5974 women were included for the present analysis. PRIMARY OUTCOME MEASURES: The association of HOMA-IR with albuminuria and renal function impairment were analysed. The HOMA-IR cut-off value for detecting albuminuria and renal function impairment were determined. RESULTS: An increase in the HOMA-IR quartile was significantly associated with the prevalence of albuminuria and renal function impairment in all men and women aged >45 years. The multivariable logistic regression analyses revealed a significant association of the HOMA-IR with albuminuria and renal function impairment in subjects aged >45 years of the fourth quartiles compared with those of the first quartile after adjusting for potential confounders (albuminuria: men OR, 2.39; 95% CI 1.51 to 3.79, p<0.001; women OR, 2.40; 95% CI 1.44 to 4.01; p=0.001; renal function impairment: men OR, 2.30; 95% CI 1.50 to 3.51; p<0.001; women OR, 2.20; 95% CI 1.35 to 3.58; p=0.002). The optimal cut-off value of HOMA-IR for detecting albuminuria and renal function impairment was 2.69 in men aged ≤45 years, 1.60 in men aged >45 years and 1.86 in women aged >45 years. CONCLUSIONS: Our study revealed that HOMA-IR was significantly associated with albuminuria and renal function impairment in individuals aged >45 years.

Optimal Threshold of Homeostasis Model Assessment of Insulin Resistance to Identify Metabolic Syndrome in a Chinese Population Aged 45 Years or Younger.

Background: Metabolic syndrome (MetS) is regarded as a major risk factor for diabetes mellitus and cardiovascular disease (CVD). The optimal threshold of the homeostasis model assessment of insulin resistance (HOMA-IR) has been established for predicting MetS in diverse populations and for different ages. This study assessed the serum HOMA-IR level in a healthy Chinese population aged ≤45 years to determine its relationship with metabolic abnormalities. Methods: Cross-sectional study data were collected from health checkup records of Chinese adults aged ≥18 years between 2013 and 2016 at Xiamen Chang Gung Hospital. Participants completed a standardized questionnaire, which was followed by a health examination and blood sample collection. Exclusion criteria were as follows: history of known CVDs; liver, kidney, or endocrine diseases or recent acute illness; hypertension; hyperlipidemia; and pregnancy or lactation. Results: The clinical and laboratory characteristics of 5954 men and 4185 women were analyzed. Significant differences were observed in all assessed variables (all P < 0.05). The optimal cutoff point of HOMA-IR for predicting MetS was 1.7 in men and 1.78 in women. Conclusions: We aimed to determine the optimal cutoff point of HOMA-IR for predicting MetS in a healthy Chinese population aged ≤45 years. The findings of this study would provide an evidence-based threshold for evaluating metabolic syndromes and further implementing primary prevention programs, such as lifestyle changes in the target population.

Research on the application of health management model based on the perspective of mobile health.

The aim of the present study was to explore the application and its effect of mobile medical treatment to chronic disease health management in physical examination population, and to provide references for comprehensive intervention and management of chronic diseases.From January to December 2016, 300 medical examiners in a general hospital health management center were randomly divided into health management group (155 cases) and control group (145 cases). The control group completed routine physical examination and health-risk assessment and provided corresponding reports, repeated annual physical examination and health-risks assessment. In addition to the routine physical examination and health-risk assessment, the health management group reminded the examiners to pay attention to their lifestyle and dietary habits by moving online and offline dynamic health interventions and provide targeted guidance for high-risk population such as diabetes, obesity, hypertension, etc. A review was made after 2 years. The clinical indexes and chronic disease behavior of patients before and after management were compared, and the effect was evaluated by statistical analysis.After management, all the clinical indexes were significantly improved, and the patients' dietary structure, bad living habits, psychologic state, and other chronic disease behaviors were obviously improved. The proportion of patients with high risk of hypertension, diabetes, and obesity in health management group was significantly lower than that before intervention and control group (P < .05).Using mobile network online, offline dynamic health intervention model can reduce the risk of common chronic diseases in health management objects, this health management model of chronic disease is worth popularizing.

[Particle Size Distribution and Human Health Risk Assessment of Heavy Metals in Atmospheric Particles from Beijing and Xinxiang During Summer].

Under a condition of good air quality (AQI:55-90, PM10:37-97 µg·m-3, PM2.5:17-76 µg·m-3), six groups of 54 samples were collected using an Andersen cascade impactor from both the indoor and outdoor stations in Beijing and Xinxiang from June to August in 2016. The samples were digested by microwave digestion, and nine heavy metal elements (Pb, Cr, Ni, Cu, Zn, As, Cd, Mn, and Co) in the atmospheric particles were determined with an inductively coupled plasma source mass spectrometer (ICP-MS). The results showed that the enrichment index (0-3) of most elements were low in both cities except for Cd[15.0 (Beijing) and 8.47 (Xinxiang)]. Cr, Co, Cu, and Mn in the atmospheric particles from Beijing park, Cd, Pb, and Mn in the atmospheric particles from the Beijing office, Cr, Co, Ni, and As in the atmospheric particles from Xinxiang park, and all nine heavy metal elements in the atmospheric particles from roads in both cities were found to be more concentrated in the coarse fractions; however, Pb, Zn, Cd, Ni, and As in the atmospheric particles from Beijing park, Co, Zn, Ni, Cr, As, and Cu in the atmospheric particles from the Beijing office, Pb, Zn, Cd, Cu, and Mn in the atmospheric particles from Xinxiang park, and all nine metal elements in the atmospheric particles from the Beijing office showed the opposite pattern. The result of a human health risk assessment indicated that the carcinogenic risk of the five carcinogenic elements were all less than 10-4, but a lower potential cancer risk would also occur under long term exposure. For the four non-carcinogenic elements (Pb, Zn, Mn, and Cu), the non-carcinogenic health risk values of Pb, Zn, Mn, and Cu in the atmospheric particulates in Beijing were all far less than 1, which means the corresponding non-carcinogenic risk was negligible; and, except for Mn, there was no obvious non-carcinogenic risk from Pb, Zn, and Cu in the atmospheric particles of Xinxiang.

Assessment of the key aroma compounds in rose-based products.

In this study, headspace solid phase microextraction-gas chromatography-mass spectrometry and GC-olfactometry were used to analyze the key aroma compounds in three types of rose-based products, including low-temperature extracts (LTEs), high-temperature extracts (HTEs), and rose drinks (RDs). In combination with the Guadagni theory, it was confirmed that the key aroma components of LTE were ß-phenyl ethyl alcohol, citronellol, geraniol, and eugenol. The main aroma compounds in HTE were ß-phenyl ethyl alcohol, citronellol, geraniol, eugenol, linalool, and rose oxide. The four key aroma compounds in RDs were ß-phenyl ethyl alcohol, eugenol, geraniol, and linalool.