Coastal Regions Research Articles

Regional distribution of anaplastic thyroid cancer in the United States

Abstract Introduction/Objective Anaplastic thyroid cancer (ATC) is an aggressive rare malignancy found in less than 2% of thyroid cancer patients. Its low occurrence rate presents challenges for collecting sufficiently large cohorts at a single institution, making statistical analysis about the disease’s spread, geographical distribution, and prevalence difficult. Nationwide data lakes such as Oracle EHR Real-World Data (ORWD, formerly Cerner Real World Data) offer a boost in cohort sizes and an opportunity to study ATC’s geographical distribution and assess regional differences. Methods/Case Report We searched ATC distribution across US regions defined by ZIP codes recorded in ORWD using multiple coding parameters, including ICD9, ICD10, and SNOMED as well as direct text searches for “anaplastic thyroid carcinoma”. We analyzed the geographical associations defined by ORWD (region) with sex, race, and age of ATC onset using the Fisher’s exact test. We combined 10 regions into 4 representative groups because of the small sample size. The groups are West Coast including the Rockies, Midwest from North Dakota to Texas, East Coast, and New England. Results (if a Case Study enter NA) Search for ATC condition codes in ORWD produced only 200 region-coded patient records across the US using multiple methods to try and identify cases. The mid-section of the US and coastal regions shows the highest numbers of ATC patients while New England and South regions show the lowest. While more women have ATC overall, the East Coast group has significantly more males (p value = 0.04). ATC is a predominantly white disease (79.8% overall) with black population increasing in East Coast group and other races (Asian/Undeclared) in West Coast (p-value < 0.001). There appears to be no significant association between age of ATC onset and the geographical groups. Conclusion The data shows geographic differences in distribution of ATC although this preliminary analysis neither explains the nature of these differences nor allows for a clearer view. The rarity of the disease complicates data analysis. This study was also limited by number of cases retrievable from the database itself and lack of granularity in coding available for ATC to find cases of interest, highlighting the difficulty of accurate tumor classifications in large data lakes. Further research into geographical distribution and environmental factors (radioactivity, pollution) of thyroid cancer using more advanced tools, such as GeoSpark, are planned.

Regulation of Physiological and Biochemical Mechanisms Related to Water Stress Tolerance in Barley and Improvement of Growth and Productivity Using Salicylic Acid and Chitosan

The present investigation aimed to assess the impacts of three Salicylic Acid (SA) concentrations (T2=100, T3=200, T4=300ppm), three Chitosan concentrations (T5=150, T6=225, T7=300ppm) and T8= Salicylic Acid (100 ppm) with Chitosan (150 ppm) mixture in comparison to control treatment (T1) on two barley cultivars Giza126 and Giza 134 under rainfed conditions. Some vegetative and yield traits were recorded, plant height, spike length, number of gains spike-1, number of spikes/m2, 1000 grain weight, biological and grain yield. A split plot design was performed with three replications. The field experiment was conducted in the northern west coast region of Egypt (Marsa Matruh government) under the rainfed condi­tions during 2019/2020 and 2020/2021 growing seasons. The results showed a direct relationship between increased foliar application and increased yield attributes. Results indicated that Giza 126 cultivar as affected by T4 showed the most desirable values for grains spikes-1 in first season, spikes/m2, biological yield and grain yield during the first and second seasons respectively. In addition, barley cultivar Giza 126 as affected by T3 showed the highest values for grains spikes-1 in second season. On the other hand, barley cultivar Giza 134 as affected by T4 showed the highest values for plant height, spike length and 1000-grain weight in first and second seasons respectively. From results, it can be concluded that the Salicylic Acid (SA) concentration 300 ppm is recommendable for improving the productivity of barley under rainfed conditions of Egypt. To study the potential role of SA and Chitosan on water stress tolerance mechanisms some biochemical and physiological parameters were recorded. Application of SA and Chitosan decreased significantly Reactive Oxygen Species (ROS) measuring by determined the concentrations of MDA and H2O2 especially SA with concentrations 300 ppm (T4). For osmolytes (proline, SSC and SPC), all treatments using SA and Chitosan induced significant increase in osmolytes content compared with control under water stress only in the two studied barley genotypes, except for treatment with Chitosan 225 and 300 ppm in Giza 126 for proline content. Similar results were recorded for antioxidant enzymes activity (CAT, POX and PPO) which showed up-regulation for all treatments compared with control under water stress for the two studied genotypes. On contrast, APX antioxidant enzyme recorded the highest activity in control treatment under water stress only. In general, for all studied treatments comparing with control, application of SA300 ppm and the mixture between SA100 and Chitosan150 ppm were the best treatment for induction of up and down regulation of biochemical and physiological component in the barley cells which is known as defense system against water stress damage.

Glomerular Filtration Rate and Blood Urea Nitrogen Levels between Coastal and Desert Regions within Libya

Background: Limited research exists on how geographic location and environmental factors influence kidney function. This study investigates potential variations in Glomerular Filtration Rate (GFR) and Blood Urea Nitrogen (BUN) levels between individuals residing in the coastal and desert regions of Libya. Methods: An observational, retrospective analysis was conducted using medical records. Participants (n=260) were recruited from Benghazi (coastal) and Jalu/Samnu/Sabha (desert) regions. Inclusion criteria included age range (18-90 years) and residency in the designated location. Exclusion criteria focused on factors affecting GFR (e.g., pre-existing kidney disease). GFR was estimated using the CKD-EPI formula. BUN levels were obtained from medical records. T-tests and Mann-Whitney U tests were used for statistical analysis. Results: The final sample size (after exclusions) and participant demographics was 134 participants. The study found no statistically significant difference in GFR between the coastal and desert groups (p-value = 0.238). However, BUN levels were significantly higher in the desert group (mean = 28.2 SD = 30.5) compared to the coastal group (mean = 15.5, SD = 10.5) with a p-value of (p-value = 0.026). Conclusion: This study did not identify a significant association between GFR and geographic location (coastal vs. desert) within Libya. However, BUN levels were significantly higher in the desert population, suggesting potential differences in kidney function or contributing factors that warrant further investigation.

Demographic influences on digital service perceptions and satisfaction at World Heritage Sites in Chinese coastal cities: An empirical analysis

This study investigates how digital transformation influences visitor satisfaction at 12 World Heritage Sites (WHS) across eight coastal provinces in Eastern and Southern China. Utilizing 402 valid survey responses, it explores the impact of demographic factors—education, age, and income—on visitors’ perceptions of digital services, particularly focusing on usability, quality, and overall experience. The findings reveal that younger, higher-income, and STEM-educated visitors express significantly higher satisfaction with digital services, while older, lower-income visitors report lower levels of engagement and satisfaction. This research highlights the need for tailored digital strategies that cater to diverse demographic groups, ensuring the balance between technological innovation and the preservation of cultural authenticity at heritage sites. The originality of this study lies in its focus on non-Western contexts, particularly China’s rapidly developing coastal regions, which have been largely overlooked in the global discourse on digital tourism. By applying established theoretical frameworks—such as the Technology Acceptance Model (TAM) and Expectation-Confirmation Theory (ECT)—to a non-Western setting, this research fills a crucial gap in the literature. The insights provided offer actionable recommendations for heritage site managers to enhance visitor engagement, adapt digital services to demographic variations, and promote sustainable tourism development.

Willingness to Pay for Nature Protection: Crowdfunding as a Payment Mechanism

AbstractIn this study, we use a discrete choice experiment to elicit the willingness-to-pay (WTP) for preventing and mitigating the effects of oil spills on marine and coastal ecosystem services, along a particularly vulnerable coastal region of mainland Portugal. We used a split-sample design to analyze the differences between two payment vehicles (PV): a mandatory extra income tax and a voluntary contribution collected by a crowdfunding campaign with a provision point mechanism and a money-back guarantee. The difference between the two PVs is examined in a setting where the local population has a negative perception of the quality of institutions. We find that respondents are more willing to contribute when presented with the crowdfunding version. Also, regardless of the payment vehicle, respondents who express a mistrust in institutions are more likely to choose the status quo. These results suggest the potential of using crowdfunding to support ecosystem services’ conservation initiatives.

Experimental Implementation of Reinforcement Learning Applied to Maximise Energy from a Wave Energy Converter

Wave energy has the potential to provide a sustainable solution for global energy demands, particularly in coastal regions. This study explores the use of reinforcement learning (RL), specifically the Q-learning algorithm, to optimise the energy extraction capabilities of a wave energy converter (WEC) using a single-body point absorber with resistive control. Experimental validation demonstrated that Q-learning effectively optimises the power take-off (PTO) damping coefficient, leading to an energy output that closely aligns with theoretical predictions. The stability observed after approximately 40 episodes highlights the capability of Q-learning for real-time optimisation, even under irregular wave conditions. The results also showed an improvement in efficiency of 12% for the theoretical case and 11.3% for the experimental case from the initial to the optimised state, underscoring the effectiveness of the RL strategy. The simplicity of the resistive control strategy makes it a viable solution for practical engineering applications, reducing the complexity and cost of deployment. This study provides a significant step towards bridging the gap between the theoretical modelling and experimental implementation of RL-based WEC systems, contributing to the advancement of sustainable ocean energy technologies.

Decoding China's new-type industrialization: Insights from an XGBoost-SHAP analysis

Integrating machine learning and explainable artificial intelligence offers superior interpretability for indicator selection compared with traditional evaluation models. This study utilizes the XGBoost-SHAP model to assess the influencing factors, development trends, and spatiotemporal evolution of China's new-type industrialization. The results demonstrate that digitalization emerges as the most critical factor, contributing 41.23% to the weight of indicators, followed by innovation drive at 34.31%, greenization at 16.38%, and aspects of servitization and fusion. China's new industrialization level shows a positive trend, with an accelerated growth rate post-2020, despite significant regional disparities in industrial indices. A spatiotemporal evolution identified a three-tier regional distribution: the eastern coastal, central plain, and western plateau regions. Notably, the improvement in new-type industrialization has expanded from coastal to inland regions, with significant progress observed in the southwestern region, represented by Sichuan Province. Additionally, the analysis revealed that China's level of new industrialization is converging toward the Hu Huanyong Line, suggesting that it may be influenced by population distribution density and natural environmental factors. The research results provide a scientific basis and decision-making guidance for evaluating the dynamics of China's new industrialization.

Fragility estimation for performance-based structural design of floating offshore wind turbine components

This study proposes a computational and mathematical framework aimed at assessing the reliability of structural components within Floating Offshore Wind Turbines (FOWT) that reflects the various sources of uncertainties coupled between structural analyses, hydrodynamics, and aerodynamics. The limit state functions are represented through structural capacity and environmental demand models for selected structural failure modes that incorporate fully coupled aero-hydro-servo-elastic analysis. The fragility surfaces are developed for a selected benchmark wind turbine for both operating and parking conditions. The fragilities are also estimated under 50-year and 100-year environmental conditions in the selected U.S. coastal regions. It is found that the wind speed variations largely affect the fragility during non-operation, while wave height variations are significant during operation. Increased uncertainties in environmental parameters raised failure probabilities, especially in lower fragility ranges targeted by design codes. Analyses in U.S. coastal environments show both parking and operating conditions can be critical, challenging the previous focus on parking. Sensitivity studies reveal that under mild conditions, structural reliability is influenced by moment of inertia and material strength, but as environmental loads increase, these parameters become equally significant. Increased uncertainties in parameters lead to higher failure risks, especially below 25 m/s wind speeds.

Comparative Seasonal Variability of the Atmospheric Boundary Layer over Gangetic Plain (Varanasi) and Coastal Region (Goa), India

Comparative Seasonal Variability of the Atmospheric Boundary Layer over Gangetic Plain (Varanasi) and Coastal Region (Goa), India

Sea-Air Transfer of Ostreopsis Phycotoxins Is Driven by the Chemical Diversity of the Particulate Fraction in the Surface Microlayer.

Blooms of Ostreopsis cf. ovata pose an emerging health threat, causing respiratory disorders in various coastal regions. This dinoflagellate produce potent phycotoxins named ovatoxins that can be transferred from the seawater to the atmosphere. However, the biotic and abiotic conditions affecting their transfer are still unknown. In this study, we investigate the sea-to-air transfer of O. cf ovata phycotoxins using a process study in an aerosol reference tank (MART) and field observations. The process study exhibited a positive correlation between the phycotoxin content in sea spray aerosol (up to 832.59 ng m-3) and the particulate phycotoxin fraction in the water column and surface microlayer. In contrast, in the natural system, aerosolized phycotoxins were only observed in one out of six air collection (total toxins 0.59 ng m-3) despite optimal wind conditions. In both the process study and the natural system, ovatoxins represented only a minor fraction of the total toxin content, which was comprised of up to 90% liguriatoxins. In seawater, while no solubilized ovatoxins were detected, the concentration in dissolved liguriatoxin-a reached up to 19.07 μg L-1. These results underscore the need for future research on the liguriatoxins, and on their toxicity to establish safe exposure thresholds for beachgoers.

The complete mitochondrial genome of the endangered Atlantic Pygmy Devil Ray, Mobula hypostoma (Bancroft, 1831), from Brazil.

Mobulidae is a monophyletic family within the Myliobatiformes that comprises pelagic species represented by manta and devil rays. Among the genus Mobula, the Atlantic Pygmy Devil Ray - Mobula hypostoma - is reported in coastal regions exclusively in tropical and subtropical Atlantic Ocean from 1 to 100m deep. In Brazil, M. hypostoma is one of the least studied Mobula species. It is regularly misidentified, especially as Mobula thurstoni, and is commonly listed as bycatch, in fishery inventories, or related to opportunistic sightings in the national territory. Here, we describe the complete nucleotide sequence of the mitochondrial genome (mitogenome) from Mobula hypostoma, which is 18,141bp in length and comprises 13 protein-coding, two ribosomal RNA, and 22 transfer RNA genes. The M. hypostoma mitochondrial genes organisation and mitochondrial genome length are similar to other Mobula species, and the phylogenetic reconstruction indicates M. hypostoma as closely related to Mobula munkiana. The Brazilian mitogenome of M. hypostoma is expected to be a valuable resource for molecular-based species identification, and evolutionary and phylogeography studies.

Tides in Complex Coastal Regions: Early Case Studies From Wide‐Swath SWOT Measurements

AbstractStudying ocean tides with satellite altimetry has traditionally been difficult in coastal regions. The 1 day repeat of the Cal/Val phase of SWOT provides a unique dataset that can be exploited for tidal analysis. In this work, KaRIn data from the SWOT Cal/Val phase are analyzed in two coastal regions to present a first look at the possibilities for tidal analysis from SWOT. The areas are: (a) Bristol Channel and (b) Great South Bay. When benchmarked against in situ measurements in these regions, substantial improvements over tide models, which typically report errors exceeding tens of centimeters and degrees, are seen. Specifically, the SWOT ocean‐tide estimates exhibit amplitude discrepancies ranging from 1.75 to 3 cm and phase lag discrepancies between 1.75° and 2.75° when compared with in situ tide gauge data. These findings underscore the value of SWOT for tidal research in complex coastal regions.

Assessing the Techno-enviro-economic viability of wind farms to address electricity shortages and Foster sustainability in Palestine

This study critically examines the feasibility of wind turbines in addressing electricity shortages in the coastal region of Palestine. Assessing technical, economic, and environmental aspects offers vital insights for sustainable energy solutions. Hence, 10 turbines with different rated powers were selected to determine the optimal and economically viable solution. Wind velocities were assessed at altitudes of 10, 65, and 80 m. Various performance indicators such as wind power density, capacity factor (Cf), anticipated energy yield, cost of wind-generated electricity, benefit-cost ratio (BCR), and simple payback period were examined. The findings indicate that the Siemens SWT-2.3-93 turbine yields an annual energy production of 3910.3 MWh. The Lagerwey-LW58/750 turbine boasts the highest capacity factor at 20.5 % making it the most cost-effective option with generation costs of $0.0604/kWh to $0.0825/kWh. It exhibited the highest benefit-cost ratio, ranging from 1.287 to 1.758, and payback period of 6.33 years. Consequently, the Lagerwey-LW58/750 turbine emerges as the optimal choice for implementing the wind power plant project in Palestine's coastal region. The use of wind turbines to generate electricity leads to 3323.75 ton/year of emissions reduction. This research provides crucial insights for decision-makers aiming to tackle electricity shortages and enhance environmental sustainability in Palestine's energy sector.

Construction, assessment, and protection of green infrastructure networks from a dynamic perspective: A case study of Dalian City, Liaoning Province, China

The green infrastructure (GI) network, an important nature-based solution (NBS) strategy, is pivotal for sustainable urban development. However, current research perspectives focus on constructing a static GI network, and research on evaluating and protecting GI networks in the context of spatiotemporal changes has been limited. This research aims to comprehensively characterise the spatio-temporal changes in the GI network and protect its efficiency. We selected Dalian City as a case study and applied the Future Land-use Simulation (FLUS) model to predict its land use for 2030 and 2040. Based on predicted and historical land-use data, the 1990–2040 GI network of Dalian City was constructed utilising the Integrated valuation of ecosystem services and trade-offs (InVEST), morphological spatial pattern analysis (MSPA) and minimum cumulative resistance (MCR) model, while its spatiotemporal changes were evaluated. The results revealed that the hub area exhibited positive growth over time, whereas the link lengths showed an opposite trend. Furthermore, the overall position of the GI network shifted toward the southwest. The flatness indicator detected that the direction of the GI network shape gradually became less pronounced. Consequently, the structure of the GI network shifted from multi-centre to mono-centre. Additionally, priority protection for hubs is mainly in the northeast, while links are primarily in the coastal regions. The urgency of protection for both increases over time. This research developed a dynamic GI network construction and assessment method, providing a scientific basis and reference for future rational GI network planning, ecological protection planning, and related land policy formulation.

Regional differences and catch-up analysis of energy efficiency in China’s manufacturing industry under environmental constraints

For coordinated regional growth and the development of high-quality manufacturing, China must narrow its regional energy efficiency gap and catch up inter-regionally. This paper focuses on whether China’s inter-provincial manufacturing energy efficiency has technological diffusion and a catch-up effect and explores its possible influencing factors, which are important for narrowing the differences in China’s manufacturing energy efficiency and promoting the improvement of the overall level of efficiency. Between 2011 and 2020, 30 Chinese manufacturing industries will be evaluated using a non-radial distance function model under environmental conditions. By employing the Dagum Gini coefficient method, regional disparities were analyzed, with hyper-variable density and efficiency discrepancies between regions making a noteworthy contribution. This paper evaluated a catch-up effect by constructing a frontier productivity model that considered the influence of China’s manufacturing energy efficiency. Results show a general rise in energy efficiency, particularly in coastal regions, higher than inland ones. The Gini coefficient of energy efficiency in manufacturing experienced a slight increase; however, when comparing it to the regional efficiency frontier, the catch-up effect and technology diffusion effect of China’s provincial manufacturing energy efficiency become more pronounced when taking into account the national efficiency frontier; the sub-regional manufacturing energy efficiency catch-up effect has different performances; the catch-up and technology diffusion effect is more evident after controlling for Economic development, innovation levels, the environmental regulation, and the proportion of high-energy-consumption output value and other influencing factors.

Identifying groundwater characteristics and controlling factors in Jiaozhou Bay’s northern coastal region, China: a combined approach of multivariate statistics, isotope analysis, and field empirical investigations

Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings.

Parametric study for shear failure of bearing pads due to hurricane-induced wave loadings

The increasing frequency of extreme weather events, such as hurricanes and rising sea levels due to climate change, presents significant challenges to coastal infrastructure. With 42% of bridges in the United States exceeding 50 years of age, which surpasses their intended service life, there is a pressing need to assess their structural integrity, especially in coastal regions. This study focuses on evaluating the structural performance of bearing pads in coastal bridges under hurricane-induced wave loadings. Utilizing a combination of physics-based models (PBM), nonlinear modal time history analysis, and numerical validation, the research examines the hysteresis response of eight distinct bearing pad configurations. The findings indicate that reinforced circular bearing pads exhibit significantly greater shear displacements compared to plain elastomeric pads, underscoring the critical influence of shape factors on shear response. Fragility functions developed in the study illustrate the probability of shear failure, with reinforced circular pads showing a 28% higher likelihood of exceedance compared to rectangular plain pads. These results highlight the necessity for advanced design methodologies specifically for bearing pads to enhance the resilience of coastal infrastructure against severe hydrodynamic forces induced by hurricanes.

Stark seasonal contrast of fine aerosol levels, composition, formation mechanism, and characteristics in a polluted megacity.

In this study, we investigated the temporal variation of organic and inorganic aerosol with its optical properties in Mumbai (India), an urban coastal region. Mean PM2.5concentrations during the sampling period were 175μg/m3 (winter) and 90μg/m3 (summer). During winter, the average concentrations of organic (OC), elemental (EC), and water-soluble organic carbon (WSOC) were three times higher than in summer. Secondary organic carbon (SOC) contribution in OC was higher in summer (78%) than in winter (53%), and strong solar radiation in summer likely caused this outcome. Aerosols were slightly acidic in both seasons, with an average pH of 5.7 (winter) and 6.0 (summer). A correlation was observed between SOC and the acidity of particles in summer (R2 = 0.6), indicating some amount of acid-catalysed SOC formation. In both seasons, the sulphate oxidation ratio (SOR) was higher than the nitrate oxidation ratio (NOR), which may reflect a preference for SO2 oxidation over NO2 or the difference in partitioning ammonium nitrate into ammonium sulphate under high RH. The dominant mechanism of SOC formation (gas vs aqueous phase oxidation) also showed seasonal variation. In winter, a relatively steep reduced major axis (RMA) slope of O3/CO suggests gas phase oxidation was the dominant mechanism of SOC production. Winter has more BrC fraction than summer, indicating higher absorbing aerosols, though the efficiency of absorbing the light was higher in summer. To assess the radiative forcing of PM2.5 on a local scale, an effective carbon ratio (ECR) was computed. The findings pointed to a local radiative heating impact caused by PM2.5. The spectral slope ratio and MAE at 250 to 300nm ratio (E2/E3) revealed a higher abundance of high molecular weight species in WSOC during summer than in winter.

Spatial distribution and risk assessment of heavy metal pollution from enterprises in China

Heavy metal pollution (HMP) directly affects the safety of agricultural products, thereby impacting human health. Industrial emissions, as the main source of soil HMP in China, require in-depth research on their pollution risks. Based on national heavy metal (HM) enterprise data, this paper analyzes the spatial distribution characteristics of key enterprises involved in the HMP across the country. It constructs the risk assessment index system of enterprise HMP based on the “source-pathway-receptor” (SPR) process of the HMP, evaluates and partitions the risk of the HMP from enterprises nationwide. The results show that: (1) Enterprises and pollutant discharge outlets are mainly distributed in the eastern and southeastern coastal regions. Jiangxi, Yunnan, Guangdong, and Hunan Province are the main distribution regions of smelting enterprises, with the most types of HM pollutants. The hazard of pollution sources shows a spatial distribution pattern of higher risk in the southwest and north, and lower risk in the central region. Counties with high-risk pollution sources are mainly distributed in Yunnan, Hunan, Guangdong, Inner Mongolia, and Jiangxi Province. (2) The hazard of pollutant transmission pathways shows a spatial distribution pattern of higher risk in the southeast and lower risk in the central region. About 31.5 % of counties are at extremely high risk, mainly distributed in the southeastern coastal regions of Guangdong, Jiangsu, Zhejiang, Jiangxi, Shandong, and Fujian Province. (3) The vulnerability of the receptors shows significant clustering characteristics in the northeast and central regions. About 3.3 % of counties have a receptor vulnerability level of “extremely high,” mainly distributed in Inner Mongolia, Jilin, Heilongjiang, Liaoning Province in the northeast, as well as Hubei and Jiangsu Province. (4) About 1.55 % of counties nationwide have a comprehensive risk level of the HMP classified as “extremely high,” mainly distributed in Guangdong Province and Inner Mongolia. Additionally, some counties in Yunnan, Hunan, Jiangsu, Jiangxi, and Zhejiang Province have a risk of exceeding pollution standards, requiring further preventive measures to reduce pollution risks in the future. This paper can provide a scientific basis for the prevention and control (P&C) of the HMP in China.

Spatial Variability of Ground Deformation of Coastal Regions of the Krishna Delta, East Coast of India Using SAR Interferometry

Spatial Variability of Ground Deformation of Coastal Regions of the Krishna Delta, East Coast of India Using SAR Interferometry