City In Southeast China Research Articles

Occurrence, distribution and health risk assessment of quinolone residues in cultured fish in southeast China

Quinolone antibiotics are widely utilized in aquaculture, but little is known about the health effects of their residues. This study used UPLC-MS/MS to analyze the distribution of 11 quinolone antibiotics in cultured fish sold in a coastal city in southeast China - Fujian Province and to assess their health risks. The study found 35.77% of 260 cultured fish samples detected quinolones, with three exceeding the MRL and one containing the banned drug ofloxacin. Of the 11 quinolones tested, three were found in cultured fish, with enrofloxacin at up to 246.0 μg kg−1, followed by ciprofloxacin and ofloxacin. The distribution of antibiotic detection rates showed no significant differences across regions or time periods; however, notable variations were observed among different fish species. The dietary exposure assessment revealed that consuming cultured fish does not pose a health risk to residents. Nevertheless, there are still instances that exceed regulatory limits. Therefore, routine monitoring and risk assessment are essential for enhancing regulatory measures and protecting public health.

Machine learning exploring the chemical compositions characteristics and sources of PM2.5 from reduced on-road activity

Particulate nitrate pollution has emerged as a major contributor to haze events in urban environment, due to the rapid increase of vehicle emissions. However, a comprehensive formation mechanisms of PM2.5 responses to vehicle emissions control still remains high uncertainties. In our study, hourly criteria air pollutants, meteorological parameters and chemical compositions of PM2.5 were continuously measured with or without reduced on-road activity at the coastal city in southeast China. XG Boost-SHAP models analysis showed that increasing concentrations of NO3−, NH4+, and BC contribute to elevated PM2.5 levels, due to the influence of vehicle emissions. Based on PMF model results, there was a notable increase in the contributions of traffic-related emissions, industrial activities, and dust sources to PM2.5, with increments of 13%, 4%, and 7%, respectively. In addition, metal elements such as Mn emerged as the primary contributor to hazard quotient (HQ) values, originated from non-exhaust emissions of vehicles, which might cause the potential toxic risks on human health, particularly during haze events. Hence, this study improve the understanding of air quality and human health both direct and indirect responses to vehicle emissions control in future urban management.

Predicting Crime Hotspots using Machine Learning Techniques

This research delves into the application of machine learning algorithms for forecasting crime hotspots by leveraging historical data of public property crime in a major coastal city in southeast China. The study conducts a comparative analysis, emphasizing the predictive efficacy of various machine learning models. Results indicate that the LSTM model surpasses other methods including KNN, random forest, support vector machine, naive Bayes, and convolutional neural networks when utilizing solely historical crime data. Moreover, integrating built environment data such as points of interest (POIs) and urban road network density as covariates into the LSTM model enhances predictive accuracy. These findings bear significance for shaping policing strategies and implementing measures for crime prevention and control.

Evaluating 15-minute walkable life circles for the senior: a case study of Jiande, China

ABSTRACT Walking is the primary travel mode for daily errands, leisure, and accessing local services, particularly for most seniors. Sufficient and diverse facilities within walking distance help improve seniors’ well-being. Countries today face the challenge of providing enough facilities for more seniors and adopt some possible solutions, such as China’s 15-minute community life circle. Focused on Jiande, a medium-sized city in southeast China, we propose an assessment framework with three dimensions: availability, diversity, and balance among medical, living, and leisure facilities. Using GIS network analysis, this study reveals disparities in facility provision at the household-level between earlier and newer developed urban areas, which are closely related to geographical factors and gated communities. This is common in Chinese cities, suggesting the cumulative effects of urban development sequences. To alleviate and prevent serious service inequity, we propose the following two strategies to achieve an equally walkable city: increasing landscape services to overcome geographical obstacles and implementing open-gated community strategies. Furthermore, the limitations of relying solely on big data to calculate walking routes were noted. This diagnostic framework for assessing city environments for seniors is straightforward yet comprehensive and potentially promotes cooperation between planning professionals, policymakers, and the public.

Nitrate contamination in groundwater and its health risk assessment: a case study of Quanzhou, a typical coastal city in Southeast China

Nitrate contamination in groundwater and its health risk assessment: a case study of Quanzhou, a typical coastal city in Southeast China

Growing Up with Anne: A Chinese Adolescence

This article explores my encounter with Anne of Green Gables as an adolescent living in a coastal city in Southeast China. The character of Anne was a unique addition to my childhood repertoire of favourite heroines, as I gradually began getting to know the imaginative girl, first by reading the translations and then the original, unabridged versions. My private journey of reading the Anne books offers a lens through which to observe the publication, adaptation, and reception of L.M. Montgomery’s most famous work in China.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1–2.5, and coarse particles (PM2.5–10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015–2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 μg/m3 for PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10. An inter-quartile range increase for PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3–51.9%), 53.7% (22.4–93.1%), 32.6% (15.0–53.0%), 35.1% (17.7–55.0%) and 25.9% (13.0–40.3%) in MD-related deaths at lag 0–3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75–84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Explaining Theft Using Offenders’ Activity Space Inferred from Residents’ Mobile Phone Data

Both an offender’s home area and their daily activity area can impact the spatial distribution of crime. However, existing studies are generally limited to the influence of the offender’s home area and its immediate surrounding areas, while ignoring other activity spaces. Recent studies have reported that the routine activities of an offender are similar to those of the residents living in the same vicinity. Based on this finding, our study proposed a flow-based method to measure how offenders are distributed in space according to the spatial mobility of the residents. The study area consists of 2643 communities in ZG City in southeast China; resident flows between every two communities were calculated based on mobile phone data. Offenders’ activity locations were inferred from the mobility flows of residents living in the same community. The estimated count of offenders in each community included both the offenders living there and offenders visiting there. Negative binomial regression models were constructed to test the explanatory power of this estimated offender count. Results showed that the flow-based offender count outperformed the home-based offender count. It also outperformed a spatial-lagged count that considers offenders from the immediate neighboring communities. This approach improved the estimation of the spatial distribution of offenders, which is helpful for crime analysis and police practice.

Spatiotemporal simulation, early warning, and driving factors of soil heavy metal pollution in a typical industrial city in southeast China

Spatiotemporal simulation, early warning, and driving factors of soil heavy metal pollution in a typical industrial city in southeast China

Exploring the amplified role of HCHO in the formation of HMS and O3 during the co-occurring PM2.5 and O3 pollution in a coastal city of southeast China

Abstract. To develop effective strategies for controlling both PM2.5 and O3 levels, it is crucial to understand their synergistic mechanisms and key precursors and the atmospheric physiochemical processes involved. In this study, a wintertime co-occurring O3 and PM2.5 pollution event in a coastal city in southeast China was investigated based on high-time-resolution measurements of criteria air pollutants and chemical compositions of PM2.5, and O3 precursors, such as NOx, HCHO, and volatile organic compounds (VOCs). The results of this study revealed the characteristics of positively correlated PM2.5 and MDA8 O3 concentrations, and an increase in atmospheric oxidation capacity (AOC) during the cold seasons. Strong correlations (R2= 0.415–0.477) between HCHO, Fe, Mn, and sulfate concentrations were observed, suggesting the influence of catalyzed oxidation processes in the coastal city. Through an observation-based model (OBM) analysis coupled with the Regional Atmospheric Chemistry Mechanism, version 2 (RACM2) and the Chemical Aqueous-Phase Radical Mechanism, version 3.0 (CAPRAM 3.0), we found that high concentrations of precursors (SO2 and HCHO), high relative humidity, and moderately acidic pH conditions enhanced the heterogeneous formation of hydroxymethanesulfonate (HMS) in PM2.5. Furthermore, by employing an OBM coupled to the Master Chemical Mechanism (OBM-MCM), we verified that disabling the HCHO mechanism could decrease daytime net O3 production rates by reducing the production rates of HO2 + NO. These results were consistent with the daily values of AOC, OH, HO2, and RO2 concentrations. This study contributes to a better understanding of the significance of HCHO in photochemical reactions and the formation of HMS in a coastal city.

The effects of caregivers' responsiveness and situational stress levels on children's expectations of caregivers' support-giving behavior and willingness.

Children develop expectations of caregivers' support-giving during early-life interactions. The present study examined whether caregivers' responsiveness would influence young children's expectations of caregivers' support-giving behavior and willingness under different situational stress levels. We manipulated the caregivers' responsiveness and situational stress levels. Children were tested to determine their expectations of caregivers' support-giving behavior and willingness. Sixty-four (33 boys, Mage = 5.34) and 68 (34 boys, Mage = 5.25) Chinese Han children from a city in Southeast China participated in Studies 1 and 2, respectively. In Study 1, we created a separation condition (i.e., a moderate level of stress) and found that children's expectations of caregivers' support-giving behavior and willingness were significantly lower in the unresponsive condition than in the responsive condition. The expectations in the unresponsive condition decreased significantly compared with the initial expectations. In Study 2, we created a danger condition (i.e., a high level of stress) and found that caregivers' responsiveness had no significant effect on children's expectations of caregivers' support-giving behavior and willingness. These results imply that both caregivers' responsiveness and situational stress levels affect children's expectations of caregivers' support-giving. They further suggest that children aged 4-6 can simultaneously assess caregivers' responsiveness and situational stress levels while forming support-giving expectations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sleep quality, frailty and overall health among community-dwelling older people: A longitudinal study.

The aims of the study were to describe sleep quality among community-dwelling older people; determine the association between sleep quality (total and multidimensional), frailty and overall health; study frailty as a mediator in the association between sleep quality and overall health. This longitudinal, correlative study used data from 2020 to 2022. A total of 181 community-dwelling older people in a city in Southeast China were assessed twice. Sleep quality was measured using the Pittsburgh Sleep Quality Index at Time 1 (year 2020); frailty was measured using the FRAIL scale, and overall health was measured using the EuroQol visual analogue scale at Time 1 and 2 (1 year later). Associations and indirect effects were examined using linear regression analyses using the PROCESS Macro (Model 4). Poor sleep quality (higher scores) was associated with increased frailty over time (total scale), as well as subjective sleep quality, sleep duration, sleep efficiency and daytime dysfunction. Mediation analyses indicated that frailty change had an indirect effect on the association between sleep quality total score Time (T) 1 and overall health T2 and between the dimensions subjective sleep quality, sleep duration, sleep efficiency and daytime dysfunction and overall health. All analyses were adjusted for age, multimorbidity and overall health T1. Poor sleep quality is a common problem associated with poor overall health after 1 year, and the progression of frailty mediates this association. The findings provide a better understanding of the association between sleep quality and overall health and elucidate the mediating effect of frailty. Regular screening and effective treatment by healthcare providers for sleep problems and frailty in older people are necessary to improve their overall health and enhance healthy ageing. Participants in the study provided the data used for all data analysis in the manuscript. Patient or public were not involved in data analysis, interpretation or manuscript preparation. Staff in the community health centre helped with data collection.

A New Technique for Impervious Surface Mapping and Its Spatio-Temporal Changes from Landsat and Sentinel-2 Images

Accurately mapping and monitoring the urban impervious surface area (ISA) is crucial for understanding the impact of urbanization on heat islands and sustainable development. However, less is known about ISA spectra heterogeneity and their similarity to bare land, wetland, and high-rise-building shadows. This study proposes a feature-based approach using decision tree classification (FDTC) to map ISAs and their spatio-temporal changes in a coastal city in southeast China using Landsat 5 TM, Landsat 8 OLI/TIRS, and Sentinel-2 images from 2009 to 2021. Atmospheric correction using simplified dark object subtraction (DOS) was applied to Landsat imagery, which enabled faster computation. FDTC’s performance was evaluated with three sensors with different spectral and spatial resolutions, with parameter thresholds held constant across remote-sensing images. FDTC produces a high average overall accuracy (OA) of 94.53%, a kappa coefficient (KC) of 0.855, and a map-level image classification efficacy (MICE) of 0.851 for ISA mapping over the studied period. In comparison with other indices such as BCI (biophysical composition index), PISI (automated built-up extraction index), and ABEI (perpendicular impervious surface index), the FDTC demonstrated higher accuracy and separability for extracting ISA and bare land as well as wetland and high-rise buildings. The results of FDTC were also consistent with those of two open-source ISA products and other remote sensing indices. The study found that the ISA in Xiamen City increased from 16.33% to 26.17% over the past 13 years due to vegetation occupation, encroachment onto bare land, and reclamation of coastal areas. While the expansion significantly reduced urban vegetation in rapidly urbanizing areas of Xiamen, ambitious park greening programs and massive redevelopment of urban villages resulted in a modest but continuous increase in urban green space.

How do inpatients’ costs, length of stay, and quality of care vary across age groups after a new case-based payment reform in China? An interrupted time series analysis

ContextA patient classification-based payment system called diagnosis-intervention packet (DIP) was piloted in a large city in southeast China in 2018.ObjectiveThis study evaluates the impact of DIP payment reform on total costs, out-of-pocket (OOP) payments, length of stay (LOS), and quality of care in hospitalised patients of different age.MethodsAn interrupted time series model was employed to examine the monthly trend changes of outcome variables before and after the DIP reform in adult patients, who were stratified into a younger (18–64 years) and an older group (≥ 65 years), further stratified into young-old (65–79 years) and oldest-old (≥ 80 years) groups.ResultsThe adjusted monthly trend of costs per case significantly increased in the older adults (0.5%, P = 0.002) and oldest-old group (0.6%, P = 0.015). The adjusted monthly trend of average LOS decreased in the younger and young-old groups (monthly slope change: -0.058 days, P = 0.035; -0.025 days, P = 0.024, respectively), and increased in the oldest-old group (monthly slope change: 0.107 days, P = 0.030) significantly. The changes of adjusted monthly trends of in-hospital mortality rate were not significant in all age groups.ConclusionImplementation of the DIP payment reform associated with increase in total costs per case in the older and oldest-old groups, and reduction in LOS in the younger and young-old groups without deteriorating quality of care.

Study of deformation characteristics and a strain calculation model for pipelines impacted by landslides

It is not uncommon to see pipelines damaged by landslides. If the maximum strain that landslides exert on pipelines can be calculated from available survey data, then pipeline damage can be more accurately predicted and the safety of the pipeline can be improved. Furthermore, this information can assist targeted prevention and control measures, which should greatly reduce the risk that landslides pose to pipelines. However, although researchers have conducted considerable research on landslide-induced pipeline deformation, there is no model that can calculate the change in pipeline strain under the displacement of landslide material. Based on geological data collected from a buried crude oil pipeline damaged by a landslide near a city in southeast China, this work uses numerical simulations to obtain the deformation parameters of pipelines affected by landslides at different orientations and for different landslide and pipeline parameters. This work also summarizes the deformation characteristics of pipelines affected by landslides under these different variables. A model is then constructed and verified that simulates the change in pipeline strain with soil displacement while considering the characteristics of the landslide mass and the pipeline itself. The results show that the model can sufficiently reflect the influence of various factors that act on pipeline deformation and can accurately calculate the maximum strain that landslides exert on pipelines.

Water Quality Evaluation and Pollution Source Apportionment of Surface Water in a Major City in Southeast China Using Multi-Statistical Analyses and Machine Learning Models

The comprehensive evaluation of water quality and identification of potential pollution sources has become a hot research topic. In this study, 14 water quality parameters at 4 water quality monitoring stations on the M River of a city in southeast China were measured monthly for 10 years (2011-2020). Multiple statistical methods, the water quality index (WQI) model, machine learning (ML), and positive matrix factorisation (PMF) models were used to assess the overall condition of the river, select crucial water quality parameters, and identify potential pollution sources. The average WQI values of the four sites ranged from 68.31 to 77.16, with a clear trend of deterioration from upstream to downstream. A random forest-based WQI model (WQIRF model) was developed, and the results showed that Mn, Fe, faecal coliform, dissolved oxygen, and total nitrogen were selected as the top five important water quality parameters. Based on the results of the WQIRF and PMF models, the contributions of potential pollution sources to the variation in the WQI values were quantitatively assessed and ranked. These findings prove the effectiveness of ML in evaluating water quality, and improve our understanding of surface water quality, thus providing support for the formulation of water quality management strategies.

Person-Centered Climate, Garden Greenery and Well-Being among Nursing Home Residents: A Cross-Sectional Study

Nursing home residents' well-being is often proxy-rated in studies, and few studies have explored the association between resident-rated person-centered climate, garden greenery, and resident-rated well-being. A cross-sectional study was conducted. Questionnaire data from a convenient sample of 470 nursing home residents in a city in Southeast China in 2021 were analyzed using multiple linear regressions, with block-wise models. The instruments used were the Person-centered Climate Questionnaire-Patient version, the Nursing Home Greenery Index, and, for well-being, the EuroQol-Visual Analogue Scale, the Life Satisfaction Questionnaire, and the 9-item Patient Health Questionnaire (depression symptoms). In the unadjusted models, the person-centered climate was positively associated with general health (β 0.29, p < 0.001), person-centered climate and greenery with life satisfaction (β 0.39, and 0.18; both p < 0.001), and negatively with depression (β -0.28, and β -0.23, both p < 0.001). After adjusting for personal and nursing home characteristics, the associations between person-centered climate, greenery, and well-being remained statistically significant. The three models explained 36%, 35%, and 21% of the variance in general health, life satisfaction, and depression, respectively. This study provides knowledge on person-centered climate in long-term care and the access to greenery.

Characteristics and Meteorological Effects of Ozone Pollution in Spring Season at Coastal City, Southeast China

Surface ozone (O3) pollution has become one of the top environmental issues in recent years around the world and can be influenced by meteorological processes on multiple scales. Understanding the meteorological mechanism and contributions of O3 pollution is of great importance for O3 mitigation. In this study, we explored the impacts of meteorological conditions on O3 concentrations in a coastal city in Southeast China, with a particular focus on O3 pollution episodes inspringtime. A significant increase in the O3 pollution ratefrom 2015 to 2020 was observed (41.7% year−1) and the seasonal characteristics of O3 concentrations showed a two-peak pattern. We selected 12 pollution episodes during the springtime of 2015 to 2020 and identified four dominant synoptic weather patterns (SWPs) that could cause O3 pollution. The local meteorological conditions and vertical dynamic structures under different SWPs were analyzed. The results showed that high O3 levels tend to be associated with high temperature, weak wind, low relative humidity, and deep vertical sinking motion. We also established a quantitative linkage between the O3 values and meteorological factors. Based on meteorological conditions, 60.8~80.8% of the variation in O3 can be explained.

Higher education and regional development of Shenzhen municipality in China’s greater bay area

Shenzhen City in Southeast China has developed from a small fishing village into a modern metropolis since China adopted an open-door policy in 1978. In accordance with its national plan and strategy, China has been striving to develop its international Guangdong–Hong Kong–Macau Greater Bay Area (GBA). Owing to its rapidly developing economy, industries and innovative technologies, Shenzhen is an important city in the GBA. Shenzhen’s higher education (HE) is supposedly crucial for its advancement as an innovation hub. However, the HE in Shenzhen is reportedly not adept with the city’s economic development. Although some Chinese studies have focused on Shenzhen’s HE-related issues, such as integration of and co-operation with the GBA’s policies, not many international studies have assessed how universities can help to ensure overall regional development. Thus, in this study, using Shenzhen’s case in the GBA, we explore the roles of universities in regional development. We review several policy documents and literature based on the glonacal framework to collect relevant data in text and generated themes. The study findings address the critical roles of Shenzhen universities in regional development such as promoting research capacity, fostering international collaboration and upgrading the GBA’s HE sector.

Quantifying the source and formation of nitrate in PM2.5 using dual isotopes combined with Bayesian mixing model: A case study in an inland city of southeast China

Atmospheric nitrate has been attracting increasing attention because it is one of the important components of PM2.5. Understanding the sources and formation mechanism of nitrate in PM2.5 is essential to take effective measures to prevent and control the emission of nitrogen oxides in the atmosphere and reduce the formation of haze. In this study, PM2.5 samples were collected from Ganzhou, an inland city in southeast China, during summer and winter. The concentrations of PM2.5 and NO3− were determined, and the isotopic compositions of NO3− (δ15N–NO3− and δ18O–NO3−) were analyzed in order to quantify the relative contributions of different emission sources and formation pathways of nitrate in PM2.5. The results showed that PM2.5 and NO3− concentrations were lower in summer (39.80 ± 11.10 μg·m−3 and 1.79 ± 0.70 μg·m−3) while higher in winter (69.85 ± 29.58 μg·m−3 and 10.83 ± 9.89 μg·m−3). The values of δ18O–NO3- and δ15N–NO3- ranged from 42.84‰ to 56.80‰ and from −11.17‰ to −2.08‰ in summer, while from 55.86‰ to 78.66‰ and from −10.63‰ to −1.88‰ in winter, respectively. The results of δ15N–NO3− combined with Bayesian isotope mixing model showed that the relative contributions of vehicle exhaust, soil microbial activity, biomass combustion and coal fired power plants were 59.3%, 28.5%, 8.7% and 3.4% in summer, while 65.1%, 20.1%, 10.6% and 4.1% in winter, respectively. The results of δ18O–NO3- combined with Bayesian isotope mixing model showed that the possible relative contributions of pathway 1 (P1) (NO2 + ·OH), pathway 2 (P2) (NO3 + HC) and pathway 3 (P3) (N2O5 + H2O) were 73.5%, 12.4% and 14.1% in summer, while 41.6%, 28.9% and 29.5% in winter, respectively. Moreover, P2 and P3 contributed more when NO3− concentrations were higher, suggesting that P2 and P3 were of significance to the formation of nitrate in PM2.5, especially during winter.