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Rapid urban growth has become a global phenomenon. As these city populations expand, urban governance is even more of a daunting challenge in many countries. China is not an exception. It is at once a transitional state still undergoing urbanization and economic development; it is also currently experiencing a slowing economy. China's cities must simultaneously continue to improve the quality of urban life while maintaining social stability. Using the city of Guangzhou as an example of China's mega‐cities, this study explores the financing strategies used by Chinese cities to manage urban growth. While economic growth has always been the main priority, Guangzhou's strategy has not followed China's traditional approach of growth for growth's sake; instead, it is relying on investment in innovation and transportation to promote the local economy. Education is also being stressed as a means of fostering human resources. However, undisciplined infrastructure financing and ineffective intergovernmental fiscal relations are jeopardizing the city's fiscal sustainability. To correct this will require further reforms of China's fiscal system and a careful sequencing of reforms to maintain a sustainable growth in the urban area. [ABSTRACT FROM AUTHOR]

[Display omitted] • Associations between PFAS mixtures and APOB, GGT, TBIL, and DBIL were found in both the WQS and BKMR analyses. • Metabolic mechanism and markers involved in the associations between PFAS and liver function indices were identified. • The mechanisms linking PFAS to APOB and GGT largely involve amino acid and glycerophospholipid metabolism. Per- and polyfluoroalkyl substances (PFAS) can disrupt liver homeostasis. Studies have shown that a single exposure to PFAS may provoke abnormal liver function; however, few studies have investigated the overall effect of PFAS mixtures. We aimed to investigate associations between exposure to PFAS mixtures and liver function indices and explore the relevant mechanisms. This study included 278 adult males from Guangzhou, China. Serum metabolite profiles were analyzed using untargeted metabolomics. We applied weighted quantile sum (WQS) regression as well as Bayesian kernel machine regression (BKMR) to analyze the association of nine PFAS mixtures with 14 liver function indices. PFAS mixtures were positively associated with apolipoprotein B (APOB) and gamma-glutamyltransferase (GGT) and negatively associated with direct bilirubin (DBIL) and total bilirubin (TBIL) in both the WQS and BKMR analyses. In addition, Spearman's correlation test showed individual PFAS correlated with APOB, GGT, TBIL, and DBIL, while there's little correlation between individual PFAS and other liver function indices. In linear regression analysis, PFHxS, PFOS, PFHpS, PFNA, PFDA, and PFUdA were associated with APOB; PFOA, PFDA, PFOS, PFNA, and PFUdA were associated with GGT. Subsequently, a metabolome-wide association study and mediation analysis were combined to explore metabolites that mediate these associations. The mechanisms linking PFAS to APOB and GGT are mainly related with amino acid and glycerophospholipid metabolism. High-dimensional mediation analysis showed that glycerophospholipids are the main markers of the association between PFAS and APOB, and that (R)-dihydromaleimide, Ile Leu, (R)-(+)-2-pyrrolidone-5-carboxylic acid, and L-glutamate are the main markers of the association between PFAS and GGT. In summary, overall associations between PFAS and specific indices of liver function were found using two statistical methods; the metabolic pathways and markers identified here may serve to prompt more detailed study in animal-based systems, as well as a similar detailed analysis in other populations. [ABSTRACT FROM AUTHOR]

With the notion of intelligent pipelines gaining ground in natural gas pipe networks, the requirements for fully automated daily operations are increasing. The flow control problem, especially in the complex station-level process piping network (SLPPN), has become the main challenge. This paper proposed a machine learning-based surrogate model that used the precise SLPPN flow control. A hybrid modeling method that uses data-driven method to surrogate numerical model was adopted to reveal the flow characteristics in the SLPPN, retaining the accuracy of the numerical simulation model while increasing its calculation speed simultaneously. Then, a two-step controller combining open-loop optimal control and closed-loop feedback control was designed to replace the classic proportional-integral-differential (PID) controller. First, genetic algorithms (GA) were used to determine the optimal control scheme of the surrogate model for fast simulation. Second, the follow-up PID controller was employed to compensate for the gap between the setpoint and the flow after the first control step. The controller was verified using the actual calibration station of a natural gas flowmeter in Guangzhou, China. The results showed that this two-step control method based on the surrogate model outperformed the conventional PID control technique regarding control duration and time, highlighting its potential in automating and intellectualizing the natural gas transportation industry. • The surrogate approach was proposed as a solution to the inverse problem in piping flow control. • The first principle simulation model was replaced by a data-driven model to significantly improve simulation speed. • A two-step controller combining open-loop optimal control and closed-loop feedback control was designed to regulate flow. • A case study was performed with actual data from the Guangzhou natural gas flowmeter calibration station. [ABSTRACT FROM AUTHOR]

Previous studies have indicated that chlorinated polyfluorinated ether sulfonic acids (Cl-PFESAs), when used as an alternative to per- and polyfluoroalkyl substances (PFASs), result in kidney toxicity. However, their co-exposure with heavy metals, has not yet been described. To explore the joint effects of Cl-PFESAs and heavy metal exposure on renal health in Chinese adults, and identify specific pollutants driving the associations. Our sample consists of 1312 adults from a cross-sectional survey of general communities in Guangzhou, China. We measured Cl-PFESAs, legacy PFASs (perfluorooctanoic acid [PFOA] and perfluorooctane sulfonated [PFOS]), and heavy metals (arsenic, cadmium, and lead). The relationship between single pollutant and glomerular filtration rate (eGFR) and the odds ratio (OR) of chronic kidney disease (CKD) was studied using Generalized additive models (GAMs). Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint effects of Cl-PFESAs and heavy metals. Additionally, we conducted a sex-specific analysis to determine the modification effect of this variable. In single pollutant models, CI-PFESAs, PFOA, PFOS and arsenic were negatively associated with eGFR. Additionally, PFOA and heavy metals were positively correlated with the OR of CKD. For example, the estimated change with 95% confidence intervals (CI) of eGFR at from the highest quantile of 6:2 Cl-PFESA versus the lowest quantile was −5.65 ng/mL (95% CI: −8.21, −3.10). Sex played a role in modifying the association between 8:2 Cl-PFESA, PFOS and eGFR. In BKMR models, pollutant mixtures had a negative joint association with eGFR and a positive joint effect on CKD, especially in women. Arsenic appeared to be the primary contributing pollutant. We provide epidemiological evidence that Cl-PFESAs independently and jointly with heavy metals impaired kidney health. More population-based human and animal studies are needed to confirm our results. [Display omitted] • We conducted a study of the general adult population of urban communities in southern China. • For the first time, Cl-PFESAs was reported to be associated with human kidney health. • Interactions exist between Cl-PFESAs and heavy metals. • Cl-PFESAs and heavy metals impaired kidney function, especially in women. [ABSTRACT FROM AUTHOR]

The magnitudes of toxicities and effects of the ambient concentration of total mass (weight) of particulate matter with aerodynamic diameter less than 2.5 μm (PM 2.5) on adverse health outcomes manifest regional- and temporal-specific heterogeneity due to the variability of embedded chemical components. To explore acute hazards of 39 chemical components of PM 2.5 on cause-specific emergency department visits (EDVs) in the Guangzhou, China, we firstly applied geographical detector method to quantify the individual and interactive effects of PM 2.5 chemical components on the variability of EDVs. Then, a causal inference framework based on the Bayesian Additive Regression Trees (BART) was developed to estimate the causal impacts that would have had on cause-specific EDVs, under an assumptive intervention via setting median concentration of as the predefined threshold for each PM 2.5 component. We found that the pairwise interactions of components play a more important role in explaining the variability of cause-specific EDVs than single factor separately. PM 2.5 chemical components combined with gaseous pollutants as well as meteorological factors affect cause-specific diseases. We obtained robust causal estimates that exposures to high levels of vanadium and fluoranthene caused an increase in EDVs for neurological diseases (4.39%; 95% CI: 0.65%, 8.23%) and circulatory diseases (4.72%; 95% CI: 0.12%, 9.63%), respectively. A comprehensive strategy to reduce the hazards of toxic chemical components of PM 2.5 is urgently needed. • Acute hazards of PM 2.5 components on emergency department visits (EDVs) were assessed. • The relationships between components and EDVs were evaluated within a causal inference framework. • The impact of pairwise interactions of components on human health was identified. • High levels of vanadium and fluoranthene were linked to neurologic and circulatory EDVs, respectively. [ABSTRACT FROM AUTHOR]