Yangtze River Delta Region Research Articles

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China.

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Sources apportionments of heavy metal(loid)s in the farmland soils close to industrial parks: Integrated application of positive matrix factorization (PMF) and cadmium isotopic fractionation

Understanding the source identification and distribution of heavy metal(loid)s in soil is essential for risk management. The sources of heavy metal(loid)s in farmland soil, especially in areas with rapid economic development, were complicated and need to be explored urgently. This study combined geographic information system (GIS) mapping, positive matrix factorization (PMF) model and cadmium (Cd) isotope fingerprinting methods to identify heavy metal(loid) sources in a typical town in the economically developed Yangtze River Delta region of China. Cd, As, Cu, Zn, Pb, Ni and Co in different samples were detected. The results showed that Cd was the most severely contaminated element, with an exceedance rate of 78.0 %. GIS mapping results indicated that the hotspot area was located in the northeastern area with prolonged operational histories of electroplating and non-ferrous metal smelting industries. The PMF model analysis also identified emissions from smelting and electroplating enterprises as the main sources of Cd in the soil, counted for 49.28 %, followed by traffic (25.66 %) and agricultural (25.06 %) sources. Through further isotopic analysis, it was found that in soil samples near the industrial park, the contribution of electroplating and non-ferrous metal smelting enterprises to cadmium pollution was significantly higher than other regions. The integrated use of various methodologies allows for precise analysis of sources and input pathways, offering valuable insights for future pollution control and soil remediation endeavors.

Nontarget screening analysis of organic compounds in river sediments: a case study in the Taipu River of the Yangtze River Delta Region in China.

Sediments are the vital fate of organic compounds, and the recognition of organic compounds in sediments is constructive in providing comprehensive and long-term information. In this study, a three-step nontarget screening (NTS) analysis workflow using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) revealed the extensive existence of organic compounds in the Taipu River sediment. Organic compounds (705) were detected and divided into four structure-related groups or eight use-related classes. In the Taipu River's mainstream, a significant difference was found in the composition profiles of the identified organic compounds among various sites, demonstrating the organic compounds were more abundant in the midstream and downstream than in the upstream. Meanwhile, the hydrodynamic force was recognized as a potential factor influencing organic compounds' occurrence. Based on multiple statistical analyses, the shipping and textile printing industries were considered the significant contributors to the identified organic compounds. Considering the principles of the priority substances and the current status of the substances, two traditional pollutants and ten emerging organic compounds were recognized as the priority organic compounds for the Taipu River. Conclusively, this study established a workflow for NTS analysis of sediment samples and demonstrated the necessity of NTS analysis to evaluate the impact of terrestrial emissions of organic compounds on the aquatic environment.

On the Path of Increasing Farmer Income in the Yangtze River Delta Region under the Background of Digital Economy

The Yangtze River Delta is one of the most active economic development areas in China, accounting for only 2.1% of China's regional area, concentrating 1/4 of China's total economic output and more than 1/4 of industrial added value, and is regarded as an important engine of China's economic development. The analysis and discussion of the influencing factors of farmers' growth in the Yangtze River Delta region under the background of digital economy has great reference significance for the income growth of farmers in other regions. This paper first analyzes the current situation of farmers' income in Anhui Province, Jiangsu Province, Shanghai Municipality and Zhejiang Province in the Yangtze River Delta region, and then analyzes the impact of the industrial index, integration index and infrastructure index on the income of farmers in the digital economy index through regression model, and tests and corrects them. The results show that the integration index and infrastructure index have a significant impact on the income of farmers in Anhui Province, the spillover index has a significant impact on the income of farmers in Jiangsu Province, the industrial index has a significant impact on the income of farmers in Shanghai, and the integration index and infrastructure index have a significant impact on the income of farmers in Zhejiang Province. Based on this, corresponding suggestions are put forward in order to effectively increase the income of farmers in the four regions and provide corresponding reference for other regions.

Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region

Abstract Based on land use classification data for the Yangtze River Delta region in 2000, 2015, and 2020, this study aims to explore the spatial and temporal evolution of ecosystem services value (ESV) in the region. By analyzing the land use structure and its dynamic changes, an ESV model is constructed. Furthermore, the study utilizes a geodetector to analyze the driving factors of ESV in the Yangtze River Delta region. The findings are as follows: (1) From 2000 to 2020, arable land was the predominant land use type in the Yangtze River Delta region. (2) The ESV in the region showed an upward trend followed by a decline from 2000 to 2020. Regulating services and supporting services have always been the core functions of ecosystem services in the region, with hydrological regulation contributing the most. (3) From a spatial perspective, there were significant differences in the spatial distribution of AESV (aggregated ecosystem services value) in the Yangtze River Delta region. The AESV changes in various cities within the region were evident, with a decreasing trend observed in most cities. (4) The sensitivity index of each land use type was less than 1, with forest land exhibiting the highest sensitivity and having the greatest impact on ESV. (5) Geodetector analysis revealed that the AESV in the Yangtze River Delta region is influenced by a combination of regional natural factors, economic factors, and social factors, and the interaction among different driving forces significantly enhances the spatial heterogeneity of AESV in the region.

Source-specified atmospheric age distribution of black carbon and its impact on optical properties over the Yangtze River Delta

Black carbon (BC) exerts a profound and intricate impact on both air quality and climate due to its high light absorption. However, the uncertainty in representing the absorption enhancement of BC in climate models leads to an increased range in the modeled aerosol climate effects. Changes in BC optical properties could result either from atmospheric aging processes or from variations in its sources. In this study, a source-age model for identifying emission sources and aging states presented by University of California at Davis/California Institute of Technology (UCD/CIT) was used to simulate the atmospheric age distribution of BC from different sources and to quantify its impact on the optical properties of BC-containing particles. The results indicate that regions with greater aged BC concentrations do not correspond to regions with higher BC emissions due to atmospheric transport. High concentrations of aged BC are found in northern Yangtze River Delta (YRD) regions during summer. The chemical compositions of particles from different sources and with different atmospheric ages differ significantly. BC and primary organic aerosols (POA) are dominating in Traffic-dominated source while other components dominate in Industry-dominated source. As the atmospheric age increases, the mass fraction of secondary inorganic aerosols rises. Compared to the original model, the simulated mass absorption cross section of BC particles in the source-age model decreases while the single scattering albedo increases. This compensates for ~11 % of the overestimation of the simulated BC direct radiative forcing. Our study highlights that incorporating atmospheric age and source information into models can greatly improve the estimation of optical properties of BC-containing particles and deepen our understanding of their climate effects.

Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies.

Photochemical ozone (O3) formation in the atmospheric boundary layer occurs at both the surface and elevated altitudes. Therefore, the O3 formation sensitivity is needed to be evaluated at different altitudes before formulating an effective O3 pollution prevention and control strategy. Herein, we explore the vertical evolution of O3 formation sensitivity via synchronous observations of the vertical profiles of O3 and proxies for its precursors, formaldehyde (HCHO) and nitrogen dioxide (NO2), using multi-axis differential optical absorption spectroscopy (MAX-DOAS) in urban areas of the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions in China. The sensitivity thresholds indicated by the HCHO/NO2 ratio (FNR) varied with altitude. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude, particularly on heavily polluted days. The NOx-limited and transition regimes played more important roles throughout the entire boundary layer than at the surface. The feasibility of extreme NOx reduction to mitigate the extent of the O3 pollution was evaluated using the FNR-O3 curve. Based on the surface sensitivity, the critical NOx reduction percentage for the transition from a VOC-limited to a NOx-limited regime is 45-72%, which will decrease to 27-61% when vertical evolution is considered. With the combined effects of clean air action and carbon neutrality, O3 pollution in the YRD and PRD regions will transition to the NOx-limited regime before 2030 and be mitigated with further NOx reduction.

Can Financial Agglomeration Development Reduce Carbon Emissions? Evidence from the Yangtze River Delta Region of China

Reducing carbon emissions is a crucial measure for achieving sustainable development. The financial industry exhibits remarkable spatial agglomeration characteristics, which play a pivotal role in advancing carbon emission reduction and facilitating energy transformation. Using panel data from 41 cities in the Yangtze River Delta from 2008 to 2019, this study employed a spatial econometrics model to investigate the impacts and spatial spillover effects from the development of financial agglomeration on carbon emissions and the associated underlying mechanisms. The research shows that (1) there is an uneven spatial distribution of carbon emissions and financial development within the Yangtze River Delta region of China; (2) an inverted U-shaped relationship exists between financial agglomeration and carbon emissions, and only Shanghai’s level of financial agglomeration exceeds the extremum point; (3) financial agglomeration shows a negative spatial spillover effect on carbon emissions; and (4) financial agglomeration can promote industrial movement toward reducing carbon emissions. The study suggests some strategies for carbon reduction in China.

Differential response of various pollutant-meteorology factors on O3 in key regions of China: Based on multiple methods and datasets

Scientific control is urgently required to address O3 pollution in key regions of China. Therefore, based on air pollutant concentrations and meteorological datasets, the methods including distributed lag nonlinear models, Kolmogorov–Zurbenko filter and stepwise multiple linear regression (SMLR) were applied to analyze and clarify the response of pollution and meteorological factors to O3, as well as the comprehensive impact under different time dimensions in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Chengdu-Chongqing regions (CY). Results indicate O3 concentrations in the study area fluctuated at high pollution levels. The effects of various air pollutants and meteorological factors on O3 varied among cities. Temperature is the dominant driver for O3, followed by solar radiation and relative humidity. The influence of wind vector indicates different transport sources of O3 and its precursors. Direct photochemical process based on SMLR fitting coefficient calculation is the main pathway for O3 generation, with contribution of 68.7%–93.8%. In terms of air-pollutant factors, U-shaped response between PM2.5 and O3 in all cities highlighted the interaction of the two air pollutants. The undeniable impact of NO2 on O3 is reflected in its range of effect. Meteorological adjustments led to −10.4–15.1 μg/m3 variations on O3 during 2014–2021, but performed obvious spatiotemporal differences. The changes in anthropogenic emissions deteriorated O3 pollution from 2014 to 2017, while have fluctuated effect since 2018. From the actual cases in special periods, in order to alleviate O3 pollution, it is necessary to strengthen the understanding of the synergistic contribution of meteorology and anthropogenic emissions.

A pathway to coordinated regional development: Energy utilization efficiency and green development - Evidence from China's major national strategic zones

According to the new economic geography hypothesis, this study establishes an analytical framework to assess the efficiency of energy use and the progress of green development. The framework is based on panel data collected from 254 cities at the prefecture level in China. The spatial Durbin model is employed to examine the influence and spatial spillover effect of energy utilization efficiency on green development in major national strategic zones. The results show that: improving energy utilization efficiency promotes green development in major national strategic regions, with a stronger intra-regional transfer effect than inter-regional. This is confirmed by robustness and endogeneity analyses. The spillover intensity of energy utilization efficiency on green development varies across regions. It shows an inverted U-shape curve in the Yangtze River Economic Belt, a U-shape curve in the Yellow River Basin and Yangtze River Delta region, a diminishing margin in the Beijing-Tianjin-Hebei region, and a growing margin in the Guangdong-Hong Kong-Macao Greater Bay Area. There is significant spatial heterogeneity within these regions. Different mediating mechanisms affect green development in different regions. The knowledge spillover effect mediates energy utilization efficiency's impact on green development in the Guangdong-Hong Kong-Macao Greater Bay Area, the industry linkage effect in the Yangtze River Economic Belt and Beijing-Tianjin-Hebei region, the environmental improvement effect in the Yellow River Basin, and the market linkage effect in the Yangtze River Delta region. To promote regional coordinated development with energy utilization efficiency, the country should not only consider differences between national strategic areas but also focus on the effects of different paths to realize the complementarity between energy utilization efficiency and green development.

Urban green and blue infrastructure: unveiling the spatiotemporal impact on carbon emissions in China's Yangtze River Delta.

Blue-green infrastructure (BGI) plays a crucial role in regulating urban carbon cycles. Nonetheless, the spatiotemporal effect of BGI on carbon emissions has not received extensive attention. This study used the Yangtze River Delta (YRD) region as the study area and quantified the landscape patterns of BGI. Using a spatiotemporal geographically weighted regression model, we analyzed the impact of evolving spatiotemporal characteristics of BGI on carbon emissions. Additionally, we constructed a spatiotemporal weight matrix using the Moran index ratio to examine the spillover effects of BGI among different regions. Our results show that the aggregation effect of carbon emissions in the YRD region is gradually increasing while BGI has a dynamic impact on carbon emissions. In terms of spatial and temporal spillovers, under the influence of economic connections between regions, patch fragmentation and distance exert a persistent positive influence on carbon emissions, while shape complexity has a negative impact, with area and layout characteristics showing no significant effects. However, area and patch distance have a persistent positive influence on carbon emissions in adjacent areas, while shape complexity exhibits a negative impact. Therefore, optimizing urban BGI through a regional synergistic governance system is important to promote low-carbon urban development.

Research on the collaborative development of digital logistics, new urbanization and ecological environment governance: taking the Yangtze River Delta region as an example

Research on the collaborative development of digital logistics, new urbanization and ecological environment governance: taking the Yangtze River Delta region as an example

Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta (YRD), China from 2015 to 2022

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015–2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov–Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O3 (O3–8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O3–8 hr, and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O3–8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission—the contribution of Shanghai, the maximum accounting for 3.6%.

Multi-scale carbon emission characterization and prediction based on land use and interpretable machine learning model: A case study of the Yangtze River Delta Region, China

Carbon emissions are a significant factor contributing to global climate change, and their characterization and prediction are of great significance for regional sustainable development. This study proposes a novel carbon emission characterization and prediction model based on interpretable machine learning and land use. It does not rely on socio-economic indicators, thus enabling carbon emission predictions after the decoupling effect. It can also reflect spatial distribution characteristics of carbon emissions, and demonstrates high accuracy and interpretability. The Yangtze River Delta (YRD) region serves as the application case for the model. Utilizing GIS-Kernel Density for land-use subdivision and Optimized Extra Tree Regression, the model achieves high precision (R2 = 0.99 for training, R2 = 0.86 for testing). Shapley Additive exPlanations (SHAP) model was employed to interpret the model, revealing the impact curves of different land areas on carbon emissions. Optimized Land Expansion Analysis Strategy (Opti-LEAS) and Cellular Automaton based on Multiple Random Seeds (CARS) models simulated land use under baseline scenarios, confirming an overall accuracy exceeding 85%. The total carbon emissions in the YRD in 2030 are projected to reach 1580.70 million tons, with Shanghai leading at 223.84 million tons, followed by Suzhou at 172.20 million tons. County-level carbon emissions were characterized, and a spatial econometrics model was employed to reveal the spatial distribution characteristics of future carbon emissions, indicating a clustering effect (Moran's I = 0.6076). As industrial land disperses, clustering shifts towards regional centers, with areas like Wuzhong District identified as 99% confident carbon emission hotspots.

Spatial–Temporal Characteristics and Influencing Factors of Eco-Efficiency of Cultivated Land Use in the Yangtze River Delta Region

The sustainable utilization of regional cultivated land systems in the Yangtze River Delta (YRD) region over the past 40 years has been severely impacted by rapid urbanization processes. Improving the eco-efficiency of cultivated land use (ECLU) plays a significant role in achieving the sustainable utilization of farmland and high-quality development of agriculture and rural areas. In this study, the spatial–temporal features and influencing factors of the ECLU in the YRD are investigated by various methods, such as a super-efficient SBM model, hot spot analysis, Dagum Gini coefficient, and panel tobit model. The findings indicate the following: the ECLU showed an overall high level from 2000 to 2020; the ECLU varied significantly over time and space in the YRD. The ECLU presented obvious spatial agglomeration in the YRD: southern regions exhibited a concentration of cold spots, while hot spots were primarily found in the east and north of the YRD. The trend of regional differences in ECLU during the research period fluctuated upwards in the YRD, and the density difference super-variable was the main source of regional differences. Increases in urbanization level and GDP per capita contributed to ECLU enhancement in the YRD, and agricultural intensity levels and agricultural industrial structures played a negative role in ECLU improvement. Finally, we suggest that different regions should adapt to local conditions, scientifically and reasonably allocate cultivated land production resources, and promote the coordinated improvement of ECLU. This study could provide a reference for policymakers to formulate better decisions on cultivated land utilization and management.

Evolutionary Game Analysis of Ecological Governance Strategies in the Yangtze River Delta Region, China

Under integrated ecological and green development in the Yangtze River Delta, the regional ecology is adversely affected by ineffective synergistic governance. Regional environmental governance is a collaborative process involving multiple stakeholders and mutual engagement, with each participant pursuing their interests and common goals simultaneously. This study employed stakeholder theory. A tripartite evolutionary game model of the public, enterprises, and local governments was constructed to analyze the behavioral strategies and influencing factors for the parties involved, and the impacts of key factors on the stability of the evolutionary game system were evaluated. The results indicate that ecological environmental governance in the Yangtze River Delta region is a complex and evolving system involving multiple stakeholders, within which system stability is influenced by stakeholders’ behavioral strategies. The interests of each party are affected by the cost of public involvement in ecological environment governance and the benefits and subsidies that enterprises receive for active environmental governance. The costs and penalties paid by local governments for lax regulations impact their behavioral strategies. This study provides policy recommendations for ecological governance in the study region, including the government–enterprise co-construction of liquid regulatory funds, government–enterprise–public partnerships in low-cost regulatory models, and the sharing of high-quality regulatory outcomes.

Middle to late Holocene hydroclimate instability in the Yangtze River Delta region of China inferred from phytolith records, and its implications for societal disruption

The decline of ancient societies has been often associated with hydroclimate instabilities. In this paper, we report phytolith records from the Yangtze River Delta of China, to reconstruct middle and late Holocene climate dynamics, and understand societal impacts. Our findings reveal that the area experienced a consistent decline in temperature and humidity punctuated by several rapid climate shifts. A distinct dry episode from 7000 to 6000 cal yr BP likely developed in response to weakened Atlantic Meridional Overturning Circulation (AMOC) and a southward shift of the intertropical convergence zone (ITCZ), resulting in a weakened East Asian summer monsoon (EASM) and a strengthened East Asian winter monsoon (EAWM). This dry condition would have favoured the emergence of dryland and facilitated rice cultivation in the lower Yangtze region. Another dry episode at 4500–4000 cal yr BP, which was probably associated with the widespread 4.2 ka climate event, and linked to a further retreat of the ITCZ and highly variable ENSO intensity, led to highly unstable hydroclimate conditions in the region. We argue that this event disrupted social resilience and culminated in the cultural collapse at the end of Liangzhu Culture.

Quantitative analysis of ecological compensation in the Yangtze River Delta region based on the value of ecosystem services and ecological footprint

IntroductionThe Yangtze River Delta is where “the Belt and Road” and China’s Yangtze River Economic Belt converge, which plays a crucial strategic location. However, with the demands of economic growth, environmental issues are frequently present in the Yangtze River Delta as a result of human and exploitation of ecological resources, and there is an urgent need to coordinate the relationship between human development and ecology.MethodsThe Yangtze River Delta region is used as the research subject, quantitatively analyzing various ecosystems within the region from three dimensions: ecosystem services value, ecological carrying capacity, and ecological footprint, and analyzing various factors that affect economic and environmental balance. Then calculate eco-compensation and its payment order based on this information, in order to build a foundation for coordinating ecological interests and safeguarding the environment in the Yangtze River Delta region.Results and discussion(1) Jiangsu Province was the main provider of ecosystem services in the Yangtze River Delta; the Yangtze River Delta’s three main ecosystems-waters, forests, and wetlands-accounted for 90% of the ecosystem services valued in the area and must be preserved. (2) The Yangtze River Delta as a whole belonged to an ecological deficit area, showing varying degrees of unsustainable development; In terms of ecological deficits, cultivated land and fossil energy had the worst, and both need to be treated severely. (3) The Yangtze River Delta was a region that paid ecological compensation. The payment order and total amount was 6825.596 billion yuan in Shanghai, 6412.264 billion yuan in Jiangsu, 12088.852 billion yuan in Zhejiang, and 3675.637 billion yuan in Anhui. At the same time, considering the current state of Anhui, the amount of eco-compensation can be appropriately reduced. Finally, recommendations are made based on the findings above, in order to improve the overall ecological benefits of the Yangtze River Delta region and foster ecological integration, all provincial and municipal governments should take reasonable action to reverse the ecological deficit of fossil energy and cultivated land, and also aim to achieve an ecological surplus in both land uses.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer.

Colorectal cancer (CRC) is a serious threat worldwide. Although early screening is suggested to be the most effective method to prevent and control CRC, the current situation of early screening for CRC is still not optimistic. In China, the incidence of CRC in the Yangtze River Delta region is increasing dramatically, but few studies have been conducted. Therefore, it is necessary to develop a simple and efficient early screening model for CRC. To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC. Data of 64448 participants obtained from Ningbo Hospital, China between 2014 and 2017 were retrospectively analyzed. The cohort comprised 64448 individuals, of which, 530 were excluded due to missing or incorrect data. Of 63918, 7607 (11.9%) individuals were considered to be high risk for CRC, and 56311 (88.1%) were not. The participants were randomly allocated to a training set (44743) or validation set (19175). The discriminatory ability, predictive accuracy, and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic (ROC) curves and calibration curves and by decision curve analysis. Finally, the model was validated internally using a bootstrap resampling technique. Seven variables, including demographic, lifestyle, and family history information, were examined. Multifactorial logistic regression analysis revealed that age [odds ratio (OR): 1.03, 95% confidence interval (CI): 1.02-1.03, P < 0.001], body mass index (BMI) (OR: 1.07, 95%CI: 1.06-1.08, P < 0.001), waist circumference (WC) (OR: 1.03, 95%CI: 1.02-1.03 P < 0.001), lifestyle (OR: 0.45, 95%CI: 0.42-0.48, P < 0.001), and family history (OR: 4.28, 95%CI: 4.04-4.54, P < 0.001) were the most significant predictors of high-risk CRC. Healthy lifestyle was a protective factor, whereas family history was the most significant risk factor. The area under the curve was 0.734 (95%CI: 0.723-0.745) for the final validation set ROC curve and 0.735 (95%CI: 0.728-0.742) for the training set ROC curve. The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population. The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age, BMI, WC, lifestyle, and family history exhibited high accuracy.

Insights into PM2.5 pollution of four small and medium-sized cities in Chinese representative regions: Chemical compositions, sources and health risks

Fine particles (PM2.5) pollution is still a severe issue in some cities in China, where the chemical characteristics of PM2.5 remain unclear due to limited studies there. Herein, we focused on PM2.5 pollution in small and medium-sized cities in key urban agglomerations and conducted a comprehensive study on the PM2.5 chemical characteristics, sources, and health risks. In the autumn and winter of 2019–2020, PM2.5 samples were collected simultaneously in four small and medium-sized cities in four key regions: Dingzhou (Beijing-Tianjin-Hebei region), Weinan (Fenwei Plain region), Fukang (Northern Slope of the Tianshan Mountain region), and Bozhou (Yangtze River Delta region). The results showed that secondary inorganic ions (43.1 %–67.0 %) and organic matter (OM, 8.6 %–36.4 %) were the main components of PM2.5 in all the cities. Specifically, Fukang with the most severe PM2.5 pollution had the highest proportion of SO42− (31.2 %), while the dominant components in other cities were NO3− and OM. The Multilinear Engine 2 (ME2) analysis identified five sources of PM2.5 in these cities. Coal combustion contributed most to PM2.5 in Fukang, but secondary sources in other cities. Combined with chemical characteristics and ME2 analysis, it was preliminarily determined that the primary emission of coal combustion had an important contribution to high SO42− in Fukang. Potential source contribution function (PSCF) analysis results showed that regional transport played an important role in PM2.5 in Dingzhou, Weinan and Bozhou, while PM2.5 in Fukang was mainly affected by short-range transport from surrounding areas. Finally, the health risk assessment indicated Mn was the dominant contributor to the total non-carcinogenic risks and Cr had higher carcinogenic risks in all cities. The findings provide a scientific basis for formulating more effective abatement strategies for PM2.5 pollution.