Search Results (141)

The inter-provincial border region in eastern China, encompassing the junction of Jiangsu, Anhui, Shandong, and Henan provinces, serves as a crucial zone that connects the important economic zones of Beijing–Tianjin–Hebei and the Yangtze River Delta. It is of great significance to study the temporal variation characteristics, spatial distribution patterns, and driving factors of PM_2.5 concentrations in this region. Based on the PM_2.5 concentration observation data, ground meteorological data, environmental data, and socio-economic data from 2022 to 2024, this study conducted in-depth and systematic research by using advanced methods, such as spatial autocorrelation analysis and geographical detectors. The research results show that the concentration of PM_2.5 rose from 2022 to 2023, but decreased from 2023 to 2024. From the perspective of seasonal variations, the concentration of PM_2.5 shows a distinct characteristic of being “high in winter and low in summer”. The monthly variation shows a “U”-shaped distribution pattern. In terms of spatial changes, the PM_2.5 concentration in the inter-provincial border region of eastern China (Jiangsu, Anhui, Shandong, Henan) forms a gradient difference of “higher in the west and lower in the east”. The high-concentration agglomeration areas are mainly concentrated in the Henan part of the study region, while the low-concentration agglomeration areas are distributed in the eastern coastal parts of the study region. The analysis of the driving factors of the PM_2.5 concentration based on geographical detectors reveals that the average temperature is the main factor affecting the PM_2.5 concentration. The interaction among the factors contributing to the spatial differentiation of the PM_2.5 concentration is very obvious. Temperature and population density (q = 0.92), temperature and precipitation (q = 0.95), slope and precipitation (q = 0.97), as well as DEM and population density (q = 0.96), are the main combinations of factors that have continuously affected the spatial differentiation of the PM_2.5 concentration for many years. The research results from this study provide a scientific basis and decision support for the prevention, control, and governance of PM_2.5 pollution. Full article

With the acceleration of global urbanization, cropland loss and fragmentation due to construction land expansion have become critical threats to food security and ecological sustainability, particularly in rapidly developing coastal regions. Understanding urban–rural differences in these processes is essential as divergent governance policies, socioeconomic pressures, and land use transition pathways may lead to uneven impacts on agricultural systems. However, past comparisons of urban–rural differences regarding this issue have been insufficient. Therefore, this study takes Jiangsu Province, China, as an example. Based on 30 m-resolution land use data, Geographic Information System (GIS) spatial analysis, and landscape pattern indices, it delves into the urban–rural differences in cropland loss and fragmentation caused by construction land expansion from 1990 to 2020. The results show that cropland in urban and rural areas decreased by 44.14% and 5.97%, respectively, while the area of construction land increased by 2.61 times and 90.14%, respectively. 94.36% of the newly added construction land originated from cropland, with the conversion of rural cropland to construction land being particularly prominent in northern Jiangsu, while the conversion of urban cropland to construction land is more pronounced in southern Jiangsu. The expansion of construction land has led to the continuous fragmentation of cropland, which is more severe in urban areas than in rural areas, while construction land is becoming increasingly agglomerated. There are significant differences in the degree of land use change between urban and rural areas, necessitating the formulation of differentiated land management policies to balance economic development with agricultural sustainability. Full article

Saline–alkali land is a critical factor limiting agricultural production and ecological restoration. Utilizing salt-tolerant plants for bioremediation represents an environmentally friendly and sustainable approach to soil management. This study employed the highly salt-tolerant crop Portulaca oleracea L. cv. “Su Ma Chi Xian 3” as the test material. A plot experiment was established in coastal saline soils with planting P. a- oleracea (P) and no planting (CK) under three blocks with the different salt levels (S1: 2.16 g/kg; S2: 4.08 g/kg; S3: 5.43 g/kg) to systematically evaluate its salt accumulation capacity and effects on soil physicochemical properties. The results demonstrated that P. oleracea exhibited adaptability across all three salinity levels, with aboveground biomass following the trend PS2 > PS3 > PS1. The ash salt contents removed through harvesting were 1.29, 2.03, and 1.74 t/ha, respectively, in PS1, PS2, and PS3. Compared to no planting, a significant reduction in bulk density was observed in the 0–10 and 10–20 cm soil layers (p < 0.05). A significant increase in porosity by 9.72%, 16.29%, and 12.61% was found under PS1, PS2, and PS3, respectively, in the 0–10 cm soil layer. Soil salinity decreased by 34.20%, 50.23%, and 48.26%, in the 0–10 cm soil layer and by 14.43%, 32.30%, and 26.42% in the 10–20 cm soil layer under PS1, PS2, and PS3, respectively. The pH exhibited a significant reduction under the planting treatment in the 0–10 cm layer. A significant increase in organic matter content by 13.70%, 12.44%, and 13.55%, under PS1, PS2, and PS3, respectively, was observed in the 0–10 cm soil layer. The activities of invertase and urease were significantly enhanced in the 0–10 and 10–20 cm soil layers, and the activity of alkaline phosphatase also exhibited a significant increase in the 0–10 cm layer under the planting treatment. This study indicated that cultivating P. oleracea could effectively facilitate the improvement of coastal saline soils by optimizing soil structure, reducing salinity, increasing organic matter, and activating the soil enzyme system, thereby providing theoretical and technical foundations for ecological restoration and sustainable agricultural utilization of saline–alkali lands. Full article

The coastal tidal flat area of Jiangsu Province, China, is vast and has great potential for carbon sequestration. Planting oat in saline–alkaline land can increase carbon sequestration from the atmosphere into soil and, thus, improve soil quality. Harvesting oats can act as a biological desalination mechanism, and long-term planting may transform saline–alkaline land into high-quality arable land. Our experiment selected two oat varieties, Caesar (V1) and Menglong (V2), and used urea, organic fertilizer, microbial inoculant, and biochar as experimental factors to investigate the effects of fertilizers and soil amendments on soil improvement and carbon sequestration when cultivating oats. The results showed that when planting V1, the carbon sequestration of the farmland ecosystem was the highest with microbial inoculant and organic fertilizer treatments, and the soil salinity decreased the most with biochar treatment. When planting V2, the carbon sequestration of the farmland ecosystem was the highest with the urea + biochar treatment, the soil salinity decreased the most with organic fertilizer + microbial inoculant treatment, and the soil organic carbon content increased the most with organic fertilizer + biochar treatment. We found that the application of organic fertilizer and biochar significantly increased soil organic carbon (SOC) content by 22.03% compared to the control treatment. Additionally, the combined treatment of urea and biochar resulted in the highest agricultural carbon sink, with a 74.62% increase in oat carbon storage compared to conventional fertilization. Full article

Taking the coastal area of Binhai County, Jiangsu Province, as an example, this study first investigated the basic natural geography and the regional geological and hydrogeological conditions of the study area, and then carried out in-depth geophysical prospecting, hydrogeological tests, geothermal temperature monitoring, hydrochemistry and isotope analyses, and other studies based on the results to comprehensively and systematically reveal the genesis mechanism of the geothermal water resources of this coastal area from multiple perspectives. The results showed the following: the geothermal water in this area mainly comes from atmospheric precipitation; the deep east–northwest interlaced fracture is the recharge and transportation channel; the Cambrian–Ordovician carbonate rock layer, enriched by the development of cavernous fissures, forms the thermal storage layer; the underground heat mainly comes from the upward heat flow along the deep fracture and the natural warming of the strata; and the thermal reservoir cover comprises Paleozoic and Mesozoic clastic rocks that have a high mud content and form a thick layer. The genesis mode of this area is as follows: the atmospheric precipitation infiltrates and is recharged through the exposed alpine carbonate fissures in the Lianyungang area, and then it is transported to the south along the large deep fracture under the action of a high hydraulic pressure head; meanwhile, it is heated by the heat flow in the deep part of the fracture and water–rock interactions with the strata occur. Geothermal water with a calculated thermal storage temperature of 83.6 °C is formed at a depth of 2.9 km, which is blocked by the intersection of the northeast and northwest fractures to form a stagnant zone in the coastal area. Full article

Biofertilizers play a crucial role in promoting sustainable agriculture in China; however, comprehensive quantification of their effects and limitations in field conditions remain unclear. In this study, a meta-analysis encompassing 1818 comparisons from 107 studies was conducted to quantify their systematic effects in field conditions in China. The results demonstrated that biofertilizers enhanced crop yields across 21 of the 23 investigated crops, with notable increases in millet (+65.42%), vegetables (e.g., Chinese cabbage +35.57%, ginger +39.18%), and legumes (kidney beans +54.03%), while cotton and rapeseed showed non-significant improvements. Nutritional quality was also improved, as evidenced by elevated levels of vitamin C (14.61%), protein (16.61%), and carotenoids (15.18%), alongside a reduction in nitrate content (21.94%). Soil health was significantly improved through increased organic matter (16.64%), enhanced enzymatic activities (urease: 57.60%; phosphatase: 43.51%), and a proliferation of beneficial microbes (bacteria: 157.10%; fungi: 30.28%), while pathogenic organisms were suppressed by 51.81%. The observed yield improvements were attributed to enhanced nutrient availability (total nitrogen: 16.67%; available phosphorus: 10.98%), optimized root growth (19.23% increase in volume), and a reduction in disease incidence (42.52%). The efficacy of biofertilizers was maximized when they were used in conjunction with organic amendments, resulting in a 29.20% increase in yield, particularly when applied prior to planting. These results show that biofertilizers boost productivity, quality, and soil functionality, depending on their production and field management practices. Their effectiveness is tied to optimizing soil properties and suppressing pathogens, providing strategies for sustainable agriculture in China. Full article

Sesbania cannabina (Retz.) Pers., as a legume, has strong waterlogging tolerance, but the lack of genomic information limits the exploration of key genes and molecular mechanisms. In this study, single-molecule real-time technology was used to sequence stems RNA of two Sesbania varieties at five time points under waterlogging stress through the PacBio Iso-Seq platform. The full-length transcriptome information contained 42 Gb raw data, 32,503 transcripts with an average length of 1912.28 nt, N50 length of 2059 nt and GC content of 42.69%. A total of 32,143 coding sequences (CDSs), 1745 transcription factors (TFs), 282 long non-coding RNAs (LncRNAs), 7497 simple sequence repeats (SSRs) and 202 alternative splicing (AS) events were identified through sequence alignment and software analysis. The analysis showed that 10,075 transcripts were enriched in 137 KEGG pathways, and 519 transcripts were included in plant hormone signal transduction, of which 103 and 123 transcripts were, respectively, involved in the ethylene and auxin pathways. The assembly and annotation of full-length transcriptome data of Sesbania provided reliable and accurate genomic information for the exploration of key genes and the study of molecular mechanisms in stem response to waterlogging stress. Full article

Balancing regional disparities in non-grainization is vital for stable grain production and sustainable urbanization. This study employs geospatial analysis to examine the spatiotemporal patterns and driving factors of non-grainization in Jiangsu Province from 2001 to 2020. By integrating geospatial data from 77 county-level units and employing spatial autocorrelation analysis, multiple linear regression, and mixed geographically weighted regression (MGWR), this study reveals the spatial heterogeneity and key driving factors of non-grainization. The results indicate strong spatial dependence, with persistent high–high clusters in economically developed southern/coastal areas and low–low clusters in northern regions. Furthermore, the driving mechanism shifted significantly over the two decades. Early constraints from natural endowments (e.g., elevation’s positive impact significantly weakened post 2010) and individual economics diminished with technological progress, while macroeconomic development became dominant, influencing both scale and structure. Infrastructure improvements (reflected by rural electricity use) consistently limited non-grainization; some factors showed phased effects, and annual mean precipitation emerged as a significant influence in 2020. MGWR revealed substantial, dynamic spatial heterogeneity in these drivers’ impacts across different periods. These findings highlight the importance of geoinformation tools in managing regional disparities. Integrating spatial and socio-economic analysis offers practical insights for policymakers to develop targeted strategies that balance food security with agricultural diversification. Full article

This study investigates the spatiotemporal distribution of carbon emissions and the decoupling relationship between emissions and innovation-driven urban development in six coastal provinces and municipalities in China from 2008 to 2022. The main questions of this paper are as follows: What are the spatial and temporal distribution characteristics of carbon emissions in the study area? What is the decoupling relationship between carbon emissions and innovation-driven urban development? What key variables contribute significantly to carbon emissions and urban development? Carbon emissions increased overall, with higher levels in northern regions such as Shandong, northern Jiangsu, and the Yangtze River Delta. Meanwhile, innovation levels rose but disparities widened, with northern cities leading and those in western Fujian and Guangdong lagging behind. The green economy and industrial transformation were key drivers of rapid development in some cities. To identify the driving factors, the SHAP (SHapley Additive exPlanations) model was employed to quantify the contributions of key variables, including energy structure, technological innovation, and industrial upgrading, to both carbon emissions and urban development. This study found that decoupling between carbon emissions and smart city development improved, transitioning from negative to strong decoupling, particularly in coastal cities. These insights can assist governments in formulating sustainable development strategies. High-emission cities should focus on integrating low-emission measures to mitigate their carbon footprint. High-carbon cities need to transition to low-carbon pathways, enhancing resource efficiency and reducing emissions. Low-emission cities should prioritize improving carbon sinks. Cities with weak economies but rich ecological resources should develop tertiary and ecological economies. Developed cities should optimize resource allocation, digitize industries, and pursue low-carbon growth. Additionally, adjustments in transportation and industry can further boost innovation and urbanization. Full article

Siltation around the harbour entrance poses significant challenges to the navigational safety and operational stability of coastal ports. Previous research has predominantly focused on sedimentation mechanisms in sandy coastal environments, while studies on silt-muddy coasts remain scarce. This paper investigates the causes of siltation around the entrance of Binhai Port in Jiangsu Province, China, utilising field observation data and a two-dimensional tidal current numerical model, with emphasis on hydrodynamic variations and sediment dynamics. Observations reveal that tidal currents induce sediment deposition in the outer harbour entrance area, whereas pronounced scouring occurs near breakwater heads. During extreme weather events, such as Typhoons Lekima (2019) and Muifa (2022), combined wind–wave interactions markedly intensified sediment transport and accumulation, particularly amplifying siltation at the entrance, with deposition thicknesses reaching 0.5 m and 1.0 m, respectively. The study elucidates erosion–deposition patterns under combined tidal, wave, and wind forces, identifying two critical mechanisms: (1) net sediment transport directionality driven by tidal asymmetry, and (2) a lagged dynamic sedimentary response during sediment migration. Notably, the entrance zone, functioning as a critical conduit for water– sediment exchange, exhibits the highest siltation levels, forming a key bottleneck for navigational capacity. The insights gleaned from this study are instrumental in understanding the morphodynamic processes triggered by artificial structures in silt-muddy coastal systems, thereby providing a valuable reference point for the sustainable planning and management of ports. Full article

Owing to the abundant land resources in the intertidal zone, the central coastal area of Jiangsu Province, China, has implemented large-scale activities such as tidal flat reclamation, aquaculture, and harbor construction, which have strongly affected the local hydrodynamic environment and the evolution of the mudflat. In this study, based on the 1984–2022 multisource remote sensing image data, an enhanced waterline method (EWM) combined with an average slope method (ASM) were adopted to obtain the spatial–temporal evolution characteristics of the continental coastline and intertidal zone in central Jiangsu Province for six typical years, exhibiting the coastal variations at critical year intervals in response to former large-scale coastal development and subsequent coastal zone protection. Results showed that the coastlines significantly advanced toward the sea. The deposited coast moved toward the seaside at an annual rate of 85.91 m, and the reclaimed coast advanced toward the seaside at a yearly rate of 129.25 m, which were dominated by natural siltation and reclamation activities of mudflats. In the past forty years, the coast’s erosion and siltation transition node has gradually moved southward from the Sheyang Estuary to the Simaoyou Estuary. Affected by reclamation and coastal erosion, the most drastic changes in the slope of the erosive intertidal zone occurred in the section from Binhai Port to the Biandan Estuary, ranging from 2‰ to 14‰. The silted coastal section from the Sheyang Estuary to the Xinyang Estuary increased in average slope from 0.89‰ to 2.43‰ as a result of the continuous intensification of erosion. The area of the intertidal mudflat decreased by 47.76% from 1378.59 to 720.11 km², whereas the mean width of the intertidal zone decreased by 48.02%, from 5518.44 m to 2868.36 m. This study provides current situations of the dynamic changes in the muddy coast of the central Jiangsu coast, which could be a comparison and reference for the sustainable development, utilization, and protection of similar muddy coasts globally. Full article

Coastal areas are essential for global ‘blue carbon’ burial, significantly impacting the global carbon cycle. To better understand the carbon burial capacity, impact factors, and response mechanisms of surface sediments in different coastline regions, this study investigated the surface sediments of the Spartina alterniflora vegetation, transition, and bare flat areas along Jiangsu coast in China. The results indicated significant changes in organic carbon (OC), inorganic carbon (IC), and various physicochemical property indicators between the three coastal environments. There were also significant differences in the important impact factors of OC and IC in each region. In areas of vegetation, OC and IC influenced each other, while nitrogen (N), clay, and sand were common impact factors. The pH only had a significant impact on OC. In the bare flat area, the important impact factors of OC and IC were identical: OC/IC, clay, salinity (SAL), and sand. However, the important impact factors of OC and IC in the transition area have undergone significant changes. The important impact factors of OC were N, total phosphorus (TP), total sulfur (TS), SAL, and sand. The partial least squares regression analysis results of IC were poor, and there were no important impact factors. This study refined the spatial distribution patterns and response mechanisms to the important impact factors of carbon in different coastal subregions, providing a basis for accurately evaluating the role of coastal wetlands in mitigating global climate change. Full article

In coastal saline–alkali regions, the intrusion of saline water exacerbates the nutrient depletion in the plow layer, posing a significant challenge to agricultural productivity. Given the limited understanding of soil fertility in these areas and the inconsistent results among different assessment methods, this study aims to develop a more accurate and reliable soil fertility evaluation system. To achieve this objective, 108 topsoil samples were systematically collected from saline–alkali lands in Jiangsu Province. Several key soil fertility indicators, including soil pH, total salinity (TS), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkaline-hydrolyzable nitrogen (AN), available phosphorus (AP), and available potassium (AK), were comprehensively evaluated. Four advanced methods, namely principal component analysis indexing–linear scoring (SQI_PCAL), principal component analysis indexing–nonlinear scoring (SQI_PCANL), modified Nemerow–linear scoring (SQI_NemeroL), and modified Nemerow indexing–nonlinear scoring (SQI_NemeroNL), were employed to conduct a multi-dimensional examination of soil fertility. Additionally, principal component analysis (PCA) was utilized to establish a minimum data set (MDS), which was then compared with the total data set (TDS) for a more precise assessment of soil fertility. Linear scoring methods (SQI_PCAL and SQI_NemeroL) had higher semi-variogram R² values compared to nonlinear methods. Moreover, under the SQI_PCAL and SQI_NemeroL evaluation methods, a strong correlation was observed between the TDS and MDS, with R² values reaching 0.63 and 0.65, respectively. Based on these findings, the SQI_NemeroL method, integrated with MDS, is recommended as an effective approach for soil fertility assessments in coastal saline–alkali regions in Jiangsu Province. This research not only enriches the theoretical understanding of soil fertility in such regions but also provides practical insights for sustainable agricultural management. Full article

Total nitrogen (TN) and total phosphorus (TP) are essential indicators for assessing water quality. This study systematically analyzes the spatial and temporal distribution of TN and TP in China’s surface waters and examines the influence of natural factors and human activities on their concentrations. Utilizing data from 1387 monitoring sites (2020–2021) and employing K-means clustering and geographically weighted regression (GWR), we found that the national average concentrations were 3.89 mg/L for TN and 0.096 mg/L for TP. Spatially, higher TN and TP levels were observed in northern regions, coastal areas, and plains compared with southern, inland, and mountainous areas. Notably, TN concentrations reached up to 29.49 mg/L in the Haihe River basin and related plains, while TP peaked at 0.497 mg/L in the southeastern Shandong and northern Jiangsu coastal zones. Temporally, TN levels were approximately 50% higher in winter than summer, whereas TP levels were about 40% higher in summer. Key influencing factors included rainfall, elevation, fertilizer use, and population density, with spatial heterogeneity observed. Rainfall was the primary factor for TN change and the secondary factor for TP change. Soil type positively correlates with TN and TP changes, affecting non-point source pollution. Human activities such as land use, fertilizer application and population density had a significant effect on the nitrogen and phosphorus concentrations, while woodland had a significant impact on the improvement of water quality. The geographically weighted regression analysis showed spatial heterogeneity in the effects of each factor on TN and TP concentrations, and the best fit was at the watershed scale. The findings highlight the need for enhanced control of agricultural runoff, improved sewage treatment, and region-specific management strategies to inform effective water environment policies in China. Full article

This study on soil salinity inversion in coastal tidal flats based on Sentinel-2 remote sensing imagery is significant for improving saline–alkali soils and advancing tidal flat agriculture. This study proposes an improved approach for soil salinity inversion in coastal tidal flats using Sentinel-2 imagery and a new enhanced chaotic mapping adaptive whale optimization neural network (CIWOABP) algorithm. Novel spectral indices were developed to enhance correlations with salinity, significantly outperforming traditional indexes. The CIWOABP model achieved superior validation accuracy (R² = 0.815) and reduced root mean square error (RMSE) and mean absolute error (MAE) compared to other machine learning models. The results enable the precise mapping of salinity levels, aiding salt-tolerant crop cultivation and sustainable agricultural management. This method offers a reliable framework for rapid salinity monitoring and precision farming in coastal regions. Full article