The degradation effect, degradation mechanism, oxidation kinetics, and degradation products of Atrazine (ATZ) by Ultrasound/Peroxymonosulfate (US/PMS) in phosphate buffer (PB) under different conditions were studied. It turned out that the degradation rate of US/PMS to ATZ was 45.85% when the temperature of the reaction system, concentration of PMS, concentration of ATZ, ultrasonic intensity, and reaction time were 20 °C, 200 μmol/L, 1.25 μmol/L, 0.88 W/mL, and 60 min, respectively. Mechanism analysis showed that PB alone had no degradation effect on ATZ while PMS alone had extremely weak degradation effect on ATZ. HO• and SO₄⁻• coexist in the US/PMS system, and the degradation of ATZ at pH7 is dominated by free radical degradation. Inorganic anion experiments revealed that Cl⁻, HCO₃⁻, and NO₃⁻ showed inhibitory effects on the degradation of ATZ by US/PMS, with Cl⁻ contributing the strongest inhibitory effect while NO₃⁻ showed the weakest suppression effect. According to the kinetic analysis, the degradation kinetics of ATZ by US/PMS was in line with the quasi-first-order reaction kinetics. ETA with concentration of 1 mmol/L reduced the degradation rate of ATZ by US/PMS to 10.91%. Product analysis indicated that the degradation of ATZ by US/PMS was mainly achieved by dealkylation, dichlorination, and hydroxylation, but the triazine ring was not degraded. A total of 10 kinds of ATZ degradation intermediates were found in this experiment.

Background: With the acceleration of aging and urbanization, how to make cities more age-friendly has become a hot topic. During the long-term demographic transition, the health of the elderly has become an important consideration in urban planning and management. The health of the elderly is a complex issue. However, previous studies have mainly focused on the health defects related to disease incidence, loss of function, mortality, etc., yet a comprehensive evaluation of health status is lacking. The Cumulative Health Deficit Index (CHDI) is a composite index that combines psychological and physiological indicators. Health deficits can reduce the quality of life of the elderly and increase the burden on families, cities and even society, so it is indispensable to understand the individual factors and regional factors that affect CHDI. The research on the spatial differentiation of CHDI and its driving factors can provide scientific geographic information basis for the construction of age-friendly cities and healthy city planning. It also has great significance in narrowing the differences in the health status among regions and reducing the overall burden of the country. Methods: This research analyzed a nationwide dataset, the China Longitudinal Aging Social Survey in 2018 conducted by the Renmin University of China, which contained 11,418 elderly aged 60 years and older from 28 provinces/municipalities/autonomous regions that represent 95% of the population in mainland China. The Cumulative Health Deficit Index (CHDI) was the first time constructed using the entropy-TOPSIS method to evaluate the health status of the elderly. Entropy-TOPSIS is to quantify the importance of each indicator by calculating the entropy value to improve the reliability and accuracy of the results and avoid the influence of previous researchers’ subjective assignments and model assumptions on the results. The selected variables include physical health 27 indicators (self-rated health, basic mobility assessment, daily activity ability, disease and treatment) and mental health 36 indicators (cognitive ability, depression and loneliness, social adjustment, and filial piety concept). The research used the Geodetector methods (factor detection and interaction detection) that combined individual and regional indicators to analyze the spatial variation characters and reveal the driving factors of CHDI. Results: The weight of mental health indicators (75.73) is three times that of physical health indicators (24.27), and its composition formula is: CHDI value = (14.77% disease and treatment + 5.54% daily activity ability + 2.14% health self-assessment + 1.81% basic mobility assessment) + (33.37% depression and loneliness + 25.21% cognitive ability + 12.46% social adjustment + 4.7% filial piety). Individual CHDI was more associated with age and was more evident in females than males. CHDI average values show the distribution trend of Hu Line (HL) in the geographic information graph that the CHDI in West HL regions are lower than in the East HL regions. The highest CHDI cities are in Shanxi, Jiangsu, and Hubei, whereas the lowest CHDI cities are Inner Mongolia, Hunan and Anhui. The geographical distribution maps of the 5-levels of CHDI levels show very different CHDI classification levels among the elderly in the same region. Further, the top three influential factors are personal income, empty nest, aged 80+, and regional factors also obviously affect CHDI values, such as the proportion participating in insurance, population density, and GDP. The two different factors in individual and regional factors all show a two-factor interaction effect, and enhancement or nonlinear enhancement. The top three ranks are personal income ∩ quality of air (0.94), personal income ∩ GDP (0.94), and personal income ∩ urbanization rate (0.87). Conclusions: CHDI is a subjective and objective comprehensive index, and mental indicators are primary factors. Thus attaching importance to the psychological care of the elderly is the key to building a healthy aging society. The large individual heterogeneity and spatial differentiation of CHDI in the elderly were demonstrated by map visualization. The analysis of the influencing factors of CHDI by the Geodetector method proves that spatial differentiation is mainly affected by individual economic and social security factors, but also by the interaction with regional factors such as quality of air, GDP, and urbanization rate. This research fills a gap in the elderly health status in the field of spatial geography. The results can provide empirical evidence for policymakers to take measures according to local conditions to improve the health status of the elderly according to regional differences in physical and mental conditions. It also plays a guiding role for the country in balancing regional economic development, promoting healthy and sustainable urban development, and creating age-friendly cities.

The Asia-Pacific region has gradually become a driver of global economic growth, with economic integration agreements (EIAs) and climate distance playing increasingly important roles in the agri-food trade in the 21st century. The recent signing and implementation of the Regional Comprehensive Economic Partnership (RCEP) and the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) have garnered global attention. This study examines the roles of different types of regional trade agreements and climate distance in the agri-food trade in the Asia-Pacific region and constructs a trade system involving 19 member countries of the RCEP and the CPTPP by analyzing panel data from 2003 to 2022. The Poisson pseudo-maximum likelihood estimator is employed to estimate an augmented gravity model that considers domestic trade flows, endogeneity issues, reverse causality, globalization effects, long-term effects, and overlapping membership. The empirical findings demonstrate that partial scope agreements and EIAs significantly promote bilateral agri-food trade, whereas temperature distance acts as a barrier and precipitation distance has a negligible effect. Overlapping members of the RCEP and CPTPP exhibit cumulative positive effects three years after the implementation of EIAs, resulting in an approximately 52.1% increase in the bilateral agri-food trade after ten years. Additionally, overlapping membership mitigates the long-term negative impact of temperature distance. This study reveals that the seven overlapping members of the RCEP and CPTPP in the Asia-Pacific region achieve greater benefits more quickly through EIAs, suggesting that overlapping membership can be an effective adaptive strategy for dealing with climate change.

Since the 1970s, neoliberalism has transformed the global economy, replacing full-time, long-term employment with flexible work arrangements, contributing to precarious employment (PE). PE has been linked to negative health outcomes, but research on the multiple dimensions of PE remains limited. This study employed a longitudinal cohort design using data from the Japanese Panel Study of Employment Dynamics (JPSED) from 2017 to 2023, focusing on individuals aged 16-65 who were employed but not on full-time permanent contracts. We developed a modified Employment Precariousness Scale (EPRES-JP) for evaluation. The entropy-based TOPSIS method with adjustable weight coefficients (Ea-TOPSIS) method was applied to calculate the Precarious Employment Index (PEI), and logistic regression analyzed its association with health outcomes, while Structural Equation Modeling (SEM) explored potential mediating pathways. The study found that the "Rights" dimension (social insurance and leave access) had the highest average weight at 40.2 %, with the impact of COVID-19 (introduced in 2021) significantly contributing to the PEI. Higher PEI was associated with greater risks of headaches (OR_0.1 = 1.11, 95 % CI [1.06, 1.16]), fatigue (OR_0.1 = 1.09, 95 % CI [1.04, 1.14]), anxiety (OR_0.1 = 1.12, 95 % CI [1.07, 1.17]), depression (OR_0.1 = 1.18, 95 % CI [1.13,1.24]), loss of appetite (OR_0.1 = 1.22, 95 % CI [1.16, 1.28]), and sleep disturbances (OR_0.1 = 1.20, 95 % CI [1.15, 1.25]). SEM identified mediating pathways between PE, job and life satisfaction, and health outcomes. These findings deepen our understanding of how PE affects worker health. Enhancing job characteristics and life satisfaction may mitigate the health risks of PE. Broader labor policies are essential to improve job security and worker well-being.