Taiwan Area Research Articles

Exploring the Impact of Regional Environment and Institutional Factors on Operation Period of Nursing Facilities in Taiwan.

This study examines factors influencing the operational durations of nursing facilities in Taiwan. It departs from previous closure-focused research by analyzing the duration of facility operation. A Cox regression model was employed to assess the impact of regional, governmental, and individual institutional factors on 199 facilities across diverse areas in Taiwan from 2011 to 2019. Results demonstrate closure hazards associated with rising property prices, particularly for rented facilities, with metropolitan locations exhibiting superior survival rates and lower institutional appraisal grades significantly increasing closure. Additionally, operator background, facility type, and bed occupancy emerged as influential factors. These findings underscore the financial vulnerability of rented facilities to market fluctuations and the challenges associated with adjusting resident fees. Furthermore, the study highlights the unique challenges faced by facilities in low-density areas regarding resident access to resources. Policymakers should closely monitor regional factors and consider proactively implementing early warning systems to address these challenges.

Estimating monthly NO2, O3, and SO2 concentrations via an ensemble three-stage procedure with downscaled satellite remote sensing data and ground measurements

The gaseous air pollutants nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), in addition to particulate matter (PM2.5), are known to be associated with many adverse health effects. However, exposure estimates may not be available in rural or mountainous areas without monitoring stations. In this study, we retrieved satellite remote sensing data for NO2, O3, and SO2 from the Ozone Monitoring Instrument (OMI) L3 products. Together with ground measurements (air monitoring stations and meteorological and land use data), we estimated the monthly NO2, O3, and SO2 concentrations with a spatial resolution of 3×3 km across Taiwan from 2005 to 2019. A three-stage estimation procedure was utilized: in Stage 1, an ensemble generalized additive model (GAM) and machine learning method were used to determine the spatiotemporal variations; in Stage 2, the remote sensing data were downscaled; and in Stage 3, the downscaled concentrations were reused in the Stage 1 procedure for fine-tuning estimations. We obtained overall leave-one-out cross-validation (LOOCV) R2 values ranging from 0.927-0.950, 0.704-0.721, and 0.601-0.716, and root-mean-square-errors (RMSEs) ranging from 1.59-2.28, 3.81-4.18, and 0.67-1.32 ppb for NO2, O3, and SO2, respectively, via the random forest procedure. The annual NO2 and SO2 concentrations greatly improved from 2005-2019, especially in the western residential area of Taiwan. However, despite these improvements in air quality, the annual O3 concentrations tended to increase from 2015–2019. This might be due to the complex mixtures of precursors (e.g., NO2), atmospheric circulation, barriers of the Central Mountain Ridge, and increasing ground temperatures over the past decade. The proposed multistage estimation procedure performed well over the whole island with complex terrain and topography. The study outcomes may provide epidemiological information for long-term ambient exposure estimates and guidance for future administrative policies.

Visualization of commuting areas and examination of jobs-housing balance with the adoption of excess commuting

Rapid urban growth extends the boundaries of urbanized areas and makes people spend extra travel cost on the journey to work. Scholars have examined commuting behaviors between residence and work places within a region, and suggested the conceptual theory of jobs-housing balance to evaluate if there are sufficient job opportunities for residents in the region. A quantitative measurement of excess commuting is proposed to reflect the degree of jobs-house balance. However, current studies focus on the evaluation of excess commuting and the causality of spatial restructuring between residence and workplace, the spatial extend of excess commuting in an urban region is not visually delineated. In addition, conventional studies acquire static data such as statistic data or other survey data to analyze impacts of commuting patterns on urban formation. Today the emergence of spatial big data sheds light on the causality of urban commuting from higher spatial and temporal resolutions. This study aims to examine the degree of jobs-housing balance through the calculation of excess commuting and represent the spatial extent of excess commuting of Taichung metropolitan area in Taiwan. Electronic Toll Collection (ETC) data, the spatial big data which is publicly accessible in Taiwan, is introduced as the commuting data and to calculate three key parameters of excess commuting, Tmin, Tobs, and Tmax. The three parameters are used to visualize the extent of commuting zones and examine commuting patterns of Taichung metropolitan area and observe the spatial relationship between those patterns and land-use types. The evaluation of excess commuting indicates that the degree of jobs-housing imbalance in Taichung metropolitan area is similar to Los Angeles metropolis in US. The analytical results explain how ETC data can be successfully used for the calculation of excess commuting, and visualization of the extent of commuting regions. In addition, after the cluster analysis of residential areas, it is intuitive to observe spatial correlation between hot zones of residential areas and the spatial extent of theoretical maximum commuting, and shows that the scenarios of commuting can be considered as an indicator to explain the possibility of urban expansion in the future.

Determinants of Forest Recreation Visitors’ Environmentally Responsible Behavior: The Moderating Role of Family Structure

This research aims to verify the relationships between destination ij3dentity, environmental concern, and environmentally responsible behavior (ERB), based on the Cognition–Affect–Behavior (C–A–B) model, in the Sun-Link-Sea Forest Recreation Area (SLSFRA) in Taiwan. This study also aims to address the gap in understanding whether tourists’ family structure, with or without children, influences the impact of destination identity on their environmental concerns and ERB. A total of 431 samples were collected through convenience sampling and analyzed using structural equation modeling. The findings indicated that destination identity significantly influenced environmental concern, which in turn affected the general and specific ERB. Environmental concern acted as a mediator between destination identity and ERB. Specifically, tourists who strongly identified with the destination were more inclined to be concerned that its environmental condition influenced their travel experience, encouraging them to take action to protect the environment. Families with children who had greater environmental concern exhibited stronger general and specific environmentally responsible behavior (ERB) compared to families without children, who were more influenced by the impact of forest destination identity on their ERB. Practical implications for management and future research suggestions are proposed for relevant organizations and researchers.

Rapid identification of the predominant azole-resistant genotype in Candida tropicalis.

Candida tropicalis is a leading cause of non-albicans candidemia in tropical/sub-tropical areas and a predominant genotype of azole-resistant C. tropicalis clinical isolates belongs to clade 4. The aim of this study was to reveal markers for rapidly identifying the predominant azole-resistant Candida tropicalis genotype. We analysed XYR1, one of the six genes used in the multilocus sequence typing analysis, and SNQ2, an ATP-binding cassette (ABC) transporter in 281 C. tropicalis, including 120 and 161 from Taiwan and global areas, respectively. Intriguingly, the first 4-mer of codon sequences ATRA of CTRG_05 978 (96/119vs. 21/162, p<0.001, at phi=0. 679) and the SNQ2 A2977G resulting in amino acid I993V alternation (105/118vs.12/163, p<0.001, at phi=0.81) was significantly associated with the clade 4 genotype. The sensitivity and specificity of the clade 4 genotype detection with a combination of SNPs of CTRG_05 978 and SNQ2 were 0.812 and 0.994, respectively, at phi=0.838. Furthermore, we successfully established a TaqMan SNP genotyping assay to identify the clade 4 genotype. Our findings suggest that to improve the management of C. tropicalis infections, rapidly identifying azole-resistant C. tropicalis by detecting SNPs of CTRG_05 978 and SNQ2 is promising.

A cloud 15kV-HDPE insulator leakage current classification based improved particle swarm optimization and LSTM-CNN deep learning approach

Real-time insulator leakage current classification is crucial in preventing the pollution flashover phenomenon and providing appropriate maintenance schedules in high-voltage transmission towers. However, current methodologies only utilize traditional artificial neural networks, which have limitations when performing big data analysis. This research developed a novel cloud 15kV-HDPE insulator leakage current classified framework, utilizing a long short-term memory convolutional neural network (LSTM-CNN). The hybrid model structure is optimized through hyperparameter fine-tuning based on improved particle swarm optimization (IPSO), which reduces human effort and considerable time compared with PSO and random search (RS) techniques. The IPSO-LSTM-CNN model can productively identify correlations between selected weather features and target leakage current levels of 15kV-HDPE insulators. LSTM efficiently captures long-term patterns in sequential data, while CNN layers competently extract high-level dependency in time-invariant information. Four 15kV-HDPE insulators’ datasets, collected in high-voltage transmission lines in the coastal area of Taiwan for more than one year, are deployed for analyzing and comparing classified performance. Other conventional models are developed to evaluate and compare classified performance with the proposed IPSO-LSTM-CNN approach, which acquires the most significant enhancement of 48.08 % loss, 45.91 % validating loss, 52.57 % MAE, 35.47 % validating MAE, 47.34 % MSE, 27.02 % validating MSE, 9.15 % PRE, 3.40 % validating PRE, 4.76 % REC, and 6.17 % validating REC. The experiment outcomes demonstrate that the developed IPSO-LSTM-CNN model acquires improved robustness and accuracy in the leakage current classified capability of 15kV-HDPE insulators.

Influence of increasing noise at the offshore wind farm area on fish vocalization phenology: A long-term marine acoustical monitoring off the foremost offshore wind farm in Taiwan

The rapid increase of offshore projects at Taiwan Strait in recent decade has been debated for elevated noise levels. However, there are no studies on long-term assessment of noise levels and impact of noise on marine organisms. The passive acoustic monitoring was conducted at the foremost wind farm area in Taiwan to assess the sound levels and the impact of noise on fish vocalization behavior. Predominately, in the soundscape around the Taiwan Strait, two chorusing types (Type 1 and Type 2) from the Sciaenid family of fishes exist. Ambient sound levels significantly increased from 2014 to 2019, while the chorusing Types 1 and 2 were observed in a lower percentage of the recordings. Additionally, chorusing peak intensity and duration significantly reduced over the years for both choruses. This is the first field-based evidence to demonstrate the consequences of increasing anthropogenic noise having the potential to alter the vocalization behavior of the fish.

Investigating the mechanisms of an intense coastal rainfall event during TAHOPE/PRECIP-IOP3 using a multiscale radar ensemble data assimilation system

Abstract The joint Taiwan-Area Heavy Rain Observation and Prediction Experiment (TAHOPE)/Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) field campaign between Taiwan and the United States took place from late May to mid-August in 2022. The field campaign aimed to understand the dynamics, thermodynamics, and predictability of heavy rainfall events in the Taiwan area. This study investigated the mechanisms of a heavy rainfall event that occurred on 6–7 June during the intensive observation period-3 (IOP3) of the field campaign. Heavy rainfall occurs on Taiwan’s western coast when a Meiyu front hovers in northern Taiwan. A multiscale radar ensemble data assimilation system based on the successive covariance localization (SCL) method is used to derive a high-resolution analysis for forecasts. Two numerical experiments are conducted with the use of convective-scale (RDA) or multiscale (MRDA) corrections in the assimilation of the radial velocity from operational radars at Chigu and Wufen, and the additional S-Pol radar deployed at Hsinchu during the field campaign. Compared with RDA, MRDA results in large-area wind corrections, which help reshape and relocate a low-level mesoscale vortex, a key element of this heavy rainfall event, offshore of western central Taiwan and enhances the front intensity offshore of northwestern Taiwan. Consequently, MRDA improves the 6-h heavy rainfall prediction over the coast of western Taiwan and better represents the elongated rainband in northern Taiwan during the 3- to 6-h forecast. Sensitivity experiments demonstrate the importance of assimilating winds from Chigu and S-Pol radar in establishing low-level mesoscale vortex and convergence zones.

Long-term monitoring dataset of plankton assemblages in western Taiwan coastal water

Plankton plays important roles in the marine ecosystems as important producers for primary production, major components in the global biogeochemical cycles, and the foundation of the marine food web. Despite their importance, long-term monitoring data about marine plankton are fairly limited, especially in the Asia-Pacific region. We fill this knowledge gap by providing a 29-year long-term monitoring data on the coastal areas of western Taiwan quarterly from 1993 to 2021. This long-term monitoring data can be used to set proper baseline for detecting human-induced impacts on the plankton, as well as modelling future scenarios under global changes.

First Report of Grovesinia moricola Causing Zonate Leaf Spot on Hernandia nymphaeifolia in Taiwan.

Hernandia nymphaeifolia (C. Presl) Kubitzki, a native tree of Taiwan, is a sea drift plant (Yang and Lu 1996). It is a salt- and wind-tolerant tree (Bezona et al. 2009) and was selected for the afforestation of badlands in coastal areas of Taiwan. In December 2022, all H. nymphaeifolia seedlings at a nursery in Wu-Lai, Taiwan were diseased and wilted with a similar progression. The initial symptom was small zonate white or gray lesions with water-soaked periphery on leaves. Then, expansion and fusion of leaf spots which caused leaf blight and defoliation were observed. Seedlings eventually wilted. Sporophores found on the host were generally hypophyllous, solitary, erect, and easily detachable. The upper portion of the sporophore was considered an individual conidium and consisted of a pyramidal head that was fusiform to ventricose, 206.3 to 501.8 μm (average: 378.0 ± 75.3 μm) long, and 63.6 to 104.5 μm (average: 85.0 ± 16.2 μm) wide at the broadest point (n=30). Branches within the pyramidal head were short, compact, and di- or trichotomously branched. The central stipe was hyaline, broad, septate, tapering toward an acute apex, and sometimes constricted at the basal septum. Sclerotia were gray or black, spherical, and 1.0 to 2.5 mm (n=10) in diameter and observed on older lesions. The fungus was isolated from infected tissue and sporophores and maintained on potato dextrose agar (PDA) at 20°C in darkness. Sclerotia were produced on PDA after 4 to 5 weeks and were irregular or spherical, but no sporophore was developed. The fungus was identified as Grovesinia moricola (I. Hino) Redhead based on morphological characteristics (Tomoko et al. 2006). Three DNA samples was obtained from the cultures isolated from the diseased leaf, sporophores and sclerotia. They were then amplified by PCR with primers for the internal transcribed spacer region (ITS; primers ITS5/ITS4) and the large subunit nuclear ribosomal RNA gene (LSU; primers LR0R/LR5) (Cho et al. 2017), and then sequenced respectively. The sequences were deposited into GenBank with accession nos. PP727191 to PP727193 and PP748518 to PP748520. BLAST analysis of the three isolates showed 100% identity to the sequences of G. moricola from Taiwan (OP550202, OP550203) for the ITS region and 99.9% identity to the sequence of G. moricola from the USA (MW013804) for the LSU rRNA gene. The specimens (FS2022-140) and the culture (Asco-0109) in this study were deposited into the herbarium of Taiwan Forestry Research Institute in Taiwan. Koch's postulates were performed by inoculating four 8-month-old, asymptomatic, potted H. nymphaeifolia plants; every plant was inoculated with sporophores from infected leaves on the upper surface of each of five leaves. Four uninoculated plants were kept in separate pots and served as controls. All plants were covered with transparent plastic bags individually and incubated in a growth chamber at 18 to 20°C with 8 h of light. Similar leaf spots and sporophores were observed after 2 to 4 days and 10 days on every inoculated plant but not on uninoculated plants. The pathogen with a similar colony on PDA was reisolated from the leaf spots of the inoculated plants. Molecular identification of the reisolated pathogen by the above method was carried out. The sequences showed 99.9% identity to the sequence of G. moricola, and were deposited into GenBank with accession nos. PQ157896 to PQ157897 (ITS region) and PQ157701 to PQ157702 (LSU rRNA gene). The pathogenicity test was repeated once. G. moricola is known to cause severe defoliation on woody and annual plants, including at least 73 host species and 36 families distributed in the eastern United States and Japan (Trolinger et al. 1978). This is the first report of G. moricola on H. nymphaeifolia in the world. Control of the disease would play an important role in maintaining healthy seedlings for the afforestation in Taiwan.

Exploring the characteristics and source-attributed health risks associated with polycyclic aromatic hydrocarbons and metal elements in atmospheric PM2.5 during warm and cold periods in the northern metropolitan area of Taiwan

Polycyclic aromatic hydrocarbons (PAHs) and metal elements are commonly considered hazardous air pollutants due to their toxic, mutagenic, and carcinogenic properties. However, few studies have simultaneously examined their potential sources and health effects. This study aimed to quantify the PAHs and metal elements in atmospheric PM2.5, investigating their characteristics and potential sources to assess associated health risks in the northern metropolitan area of Taiwan. The measurements indicated that the mean concentrations of total PAHs and metal elements in PM2.5 were 0.97 ± 0.52 ng m−3 and 590 ± 200 ng m−3, respectively. Utilizing the positive matrix factorization profiles, the PAH pollution was classified into two sources: industrial emissions, traffic emissions, and coal combustion (69%) were the predominant sources of PAHs, with petroleum volatilization and biomass burning (31%) making a lesser contribution. Similarly, we traced metal elements to three potential sources: natural sources (48%), a combined source of industrial emissions, coal combustion, and traffic exhaust (32%), and a blend of non-exhaust emissions from traffic and waste incineration sources (20%). Results from the potential source contribution function model suggested that the emissions of PAHs and metals could be influenced by the eastern regions of China, although local sources, including waste incinerators, traffic, shipping, and harbor activities, were identified as the primary contributors. Source-attributed excess cancer risk revealed that industry, traffic, and coal combustion had the highest cancer risk posed by PAHs in the cold period (1.0 × 10−5), while the greatest cancer risk among metal elements was linked to non-exhaust emissions from traffic and waste incineration emissions (2.0 × 10−5). This research underscores the importance of considering source contributions to health risk and emission reduction when addressing PM2.5 pollution. These findings have direct implications for policymakers, providing them with valuable insights to develop strategies that protect public health from the detrimental effects of PAH and metal element exposure.

Strontium Isotopic Composition as Tracers for Identifying Groundwater Recharge Sources in the Choushui River Alluvial Plain, Western Taiwan

Groundwater is a vital resource in the Chuoshui River alluvial plain (CSAP), a key agricultural area in Taiwan. Understanding groundwater recharge is crucial for sustainable water management amidst changing climatic conditions and increasing water demand. This study investigates the major ion composition, solute Sr concentrations, and 87Sr/86Sr ratios in groundwater and stream water from the Choushui River (CSR) to trace groundwater recharge sources. The Piper diagram reveals that most groundwater samples are of the freshwater Ca–HCO3 type, aligning with the total dissolved solids (TDS) classification. TDS and major ion compositions indicate that groundwater near Baguashan Terrace (BGT) and Douliu Hill (DLH) primarily derives from stream water and rainwater. Na+ and Cl− enrichment in some aquifers of BGT and DLH is attributed to the dissolution of paleo-sea salt and mixing with paleo-seawater from sedimentary porewater. Elevated dissolved Sr concentrations and lower 87Sr/86Sr ratios in these aquifers further support the intrusion of paleo-seawater. Groundwater in the proximal fan shows high TDS due to intensive weathering, complicating the use of TDS as a tracer. Sr isotopic compositions and solute Sr2+ concentrations effectively distinguish recharge sources, revealing that the CSR mainstream primarily recharges the proximal fan and BGT region, while CSR tributaries and rainwater mainly recharge the DLH region. This study concludes that Sr isotopic compositions and solute Sr2+ concentrations are more reliable than TDS and major ion compositions in identifying groundwater recharge sources, enhancing our understanding of groundwater origins and the processes affecting water quality.

Empirical Study on the Usage of Telemedicine by Rural and Urban Health Care Consumers in Taiwan: Integrating the Perspectives of Technology Acceptance Model and Theory of Planned Behavior.

Introduction: The outbreak of the novel coronavirus disease-19 posed significant challenges globally, impacting various sectors and health care systems profoundly. In response, telemedicine has emerged as a vital solution to address health care demands and resource shortages. However, there is a lack of comprehensive research on telemedicine usage among health care consumers in urban and rural areas of Taiwan. Methods: This study aimed to investigate the usage, attitudes, and intentions of telemedicine utilization among health care consumers in Taiwan, integrating the Technology Acceptance Model and Theory of Planned Behavior. A cross-sectional study was conducted from April 2023 to May 2024, involving 1,053 participants who utilized telemedicine services. Structured questionnaires were used for data collection, and statistical analyses were performed using SPSS 21.0 software. Results: The results revealed significant disparities in telemedicine utilization between urban and rural areas, with urban residents exhibiting higher levels of perceived ease of use, perceived usefulness, attitude toward use, trust, and intention to use telemedicine. Regression analysis indicated a significant association between urban residence and male gender with telemedicine utilization, contrary to previous research findings. These disparities may stem from differences in health care accessibility and cultural norms prevalent in urban and rural areas. Conclusions: Further investigation into gender differences and interventions to promote telemedicine usage among females, particularly in urban areas, are recommended. This study provides valuable insights for future research and health care policy formulation.

Quantitative analysis of aeolian dust incidence and diagnosis using a dynamic Bayesian network model: A case study of estuary area in central Taiwan

The presence of high concentrations of PM10 in aeolian dust within the estuary area of central Taiwan has been a focal point for air quality protection and remediation efforts over the past 15 years. This study explores the quantitative analysis of aeolian dust occurrences concerning various levels of PM10 concentration, aiming to offer early warning information to local communities and government agencies. Employing Dynamic Bayesian network (DBN) models, the research interrelates conditional probability dependencies among air quality and meteorological factors monitored in the downstream area of the Jhuoshuei River, predicting the probability distribution of aeolian dust events. The constructed DBNs demonstrate the inference of probability distributions of meteorological factors' states based on PM10 concentrations, enabling diagnostic analysis of meteorological conditions during high PM10 concentration dust events. The DBN models exhibit robust predictive ability, achieving an overall accuracy of 85.72% in validation and 85.8% in testing, with high discriminatory capacity that the area under the receiver operating characteristic curve (AUC) values of 0.924 and 0.915 during validation and testing, respectively. Sensitivity analysis highlights wind direction, wind speed, relative humidity as significant factors affecting PM10 concentrations. The probability of low PM10 concentrations was notably higher compared to higher concentrations, indicating effective aeolian dust remediation efforts. However, attention is warranted toward the 10% incidence of aeolian dust events deemed unhealthy or hazardous to human health. Diagnosis of meteorological conditions during high PM10 concentration events suggests low temperature, high wind speeds, and dry conditions, particularly with northeastern or southwestern winds, as conducive factors. This study underscores the physical relationship between meteorological factors and PM10 concentrations, employing DBNs to consider temporal relationships and uncertainties in data, aligning with human health impact standards proposed by the Ministry of Environment. Future research should incorporate soil and land surface conditions to provide a more comprehensive understanding of aeolian dust dynamics and mitigation strategies.

Phytochemical Evaluation and Anti-angiogenic Activity of Alingatong (Dendrocnide meyeniana Walp.) Root Extracts Using the Chorioallantoic Membrane Assay on Duck Embryo

Dendrocnide meyeniana (Walp.), known as "Alingatong" in the Visayas region of the Philippines, is a plant from the Urticaceae family. It is commonly found in the mountain areas of Taiwan and the Philippines. This study aims to determine the Dendrocnide meyeniana root extract's anti-angiogenic activity. The methanolic extracts of Dendrocnide meyeniana were subjected to preliminary phytochemical screening. Cytotoxicity test using Brine Shrimp Lethality Assay was conducted with different plant concentrations to determine the concentration to use for the anti-angiogenic activity of the root extracts. The anti-angiogenic activity was observed by calculating blood vessel percent inhibition using chorioallantoic membrane assay or CAM assay. Phytochemical screening reveals that the plant contains varying levels of detection of bioactive compounds, including saponins, flavonoids, alkaloids, and steroids. Brine Shrimp Lethality Assay showed that the ethyl acetate and hexane extracts from Dendrocnide meyeniana were highly toxic as their LC50 values were lower than 100 ppm. CAM assay results showed that hexane with 250 ppm concentration has the highest percent inhibition with 34.98% followed by hexane at 125 ppm with 34.07% inhibition. Both concentrations of ethyl acetate showed low percentage inhibition, where 250 ppm was at 19.05% and 125 ppm at 15.93%. One-way ANOVA indicates that the different treatments have significant differences (p-value&lt; 0.0001) in the number of branches present using the CAM assay. Therefore, based on the results, Dendrocnide meyeniana root extracts have anti-angiogenic properties and these findings will help to understand the efficacy of the traditional medicine used by the local people.

Wastewater-based epidemiology to monitor 68 NPS/conventional drug use in Taipei metropolitan area in Taiwan during and after COVID-19 pandemic

Amidst far-reaching COVID-19 effects and social constraints, this study leveraged wastewater-based epidemiology to track 38 conventional drugs and 30 new psychoactive substances (NPS) in northern Taiwan. Analyzing daily samples from four Taipei wastewater plants between September 2021 and January 2024—encompassing club reopenings, holidays, Lunar New Year, an outbreak, and regular periods—thirty-one drugs were detected, including 5 NPS. Tramadol, zolpidem tartrate, CMA, and MDPV were newly detected in Taiwanese sewage with frequency of 1.4 %− 89.0 %. Conventional drug use typically increased post-pandemic, aside from benzodiazepines and methadone. Methamphetamine showed 100 % frequency, indicating ongoing daily consumption despite COVID-19 measures. Methamphetamine and morphine's consumption dipped then rose around club reopening, hinting at limited access. The consumption trend of methadone appeared to compensate for the use of morphine. Ketamine and NPS demonstrated similar patterns throughout the entire period. NPS as party drugs seemed influenced by an unstable supply chain and complexities in implementation. Benzodiazepines, commonly abused alongside synthetic cathinones in Taiwan exhibited an opposing trend to NPS while aligned with acetaminophen, suggesting elevated stress and anxiety levels during the pandemic. No significant differences were observed in drug consumption between weekdays and weekends, potentially indicating that COVID-19 measures blurred the traditional distinctions between these timeframes. Environmental ImplicationNew psychoactive substances refer to chemically modified variants of controlled drugs designed to mimic the effects of the original drugs while evading modern detection methods, categorizing them as hazardous materials. The study presents a sewage monitoring project conducted from 2021 to 2024, collecting samples from four WWTPs to analyze NPS and conventional drug trends during and after the COVID-19 pandemic. The findings uncovered connections between drug consumption patterns and pandemic-related policies. In light of the persistent drug abuse and their environmental presence, the results bear critical importance for both environmental and public health. We provide a thorough assessment of these relationships and prioritize areas for future research.

Chemical characteristics and formation mechanism of secondary inorganic aerosols: The decisive role of aerosol acidity and meteorological conditions

In recent years, there has been a growing concern about air pollution and its impact on the air quality and human health, especially for fine particulate matter (PM2.5) and its associated secondary aerosols in urban areas. This study conducted a year-long field campaign to collect PM2.5 samples day and night in an urban area of central Taiwan. Higher PM2.5 mass concentrations were observed in winter (27.7 ± 9.7 μg/m3), followed by autumn (22.5 ± 8.3 μg/m3), spring (19.2 ± 6.4 μg/m3), and summer (11.0 ± 3.1 μg/m3). The dominant formation mechanism of secondary inorganic aerosols was heterogeneous reactions of NO3− at night and homogeneous reactions of SO42− during the day. Additionally, significant correlations were observed between aerosol liquid water content (ALWC) and NO3− during nighttime, indicating the importance of aqueous-phase NO3− formation. The role of aerosol acidity was explored and a unique alkaline condition was found in spring and summer, which showed lower PM2.5 concentrations than the neutralized condition. Under the neutralized condition, higher PM2.5 concentrations were commonly found when combining the ammonium-rich regime with molar ratios of [NO3−]/[SO42−] exceeding 1.6, suggesting the importance of reducing both NH3 and NOx. Furthermore, the results showed that reducing NH3 should be prioritized under high temperature conditions, while reducing NOx became important under low temperature conditions. Clustering of backward trajectories showed that long-range transport could enhance the formation of secondary aerosols, but local emissions emerged as the main factor driving high PM2.5 concentrations. This study provides insights for policymakers to improve air quality, suggesting that different mitigation strategies should be formulated based on meteorological variables and that using clean energy for vehicles and electricity generation is important to alleviate air pollution.

Exploring groundwater depletion and land subsidence dynamics in Taiwan’s Choushui river alluvial fan: insights from integrated GNSS and hydrogeological data analysis

The Choushui River Alluvial Fan (CRAF) is a major agricultural area in Taiwan with heavy groundwater usage. The extraction of groundwater here has caused land subsidence, which is now a significant global environmental issue. This study analyzes land subsidence in the CRAF by integrating hydrogeological data from 233 groundwater monitoring stations across four aquifers (CRAF Groundwater_NET) and data from 50 continuous GNSS stations (CRAF GNSS_NET). We developed an automated processing flow for GNSS static surveying within CRAF GNSS_NET, and further employed a time-series fitting method to examine the long-term trends and annual changes for both GNSS and groundwater level data. Our analysis of the time-series data from the past decade identifies areas of significant groundwater level depletion and subsidence hotspots. We explore the relationship between groundwater level variations and surface displacements within CRAF, utilizing GNSS data to analyze horizontal and vertical displacement trends, as well as annual changes. We integrate these findings with hydrogeological data to understand regional subsidence patterns. Our results indicate that CRAF is characterized by distinct hydrogeological features. The study finds that the amplitudes of annual changes in both groundwater level and vertical displacement generally increase from northeast to southwest in the analyzed region. One particular area shows significant groundwater level decline, with the most severe rate recorded at 0.54 m/year. Similarly, GNSS analysis indicates pronounced subsidence trends in the same area, with rates ranging from 4.2 to 5.2 cm/year. These findings highlight the critical need for the development of effective groundwater management strategies to ensure sustainable use of groundwater resources and to implement mitigation measures against land subsidence in similar multiple-aquifer settings.

Enhanced shear and veer in the Taiwan Strait during typhoon passage

During typhoon passage extreme wind conditions pose a challenge to the structural integrity of wind turbines. Particularly, wind shear and wind veer can influence wind turbine loads. This study investigates how Taiwan’s central mountain range affects wind shear and wind veer in the Taiwan Strait during three westward-moving typhoon cases. The typhoons are simulated with the Weather Research and Forecasting (WRF) model. We find that wind speed, shear, and veer vary over different regions in the Taiwan Strait. In large areas, the simulated wind shear is larger than modeled over the open ocean. In particular, mountain blockage leads to a spatially confined area of several 1000 km2 downstream of Taiwan, that exhibits over several hours strongly modified shear and veer in all three analyzed cases. Shear exponents up to 0.75 and veer between 0.2 and 0.6° m−1 suggest that turbine loads are impacted by the vertical change in the wind field in this area. The shear exponent and wind veer vary strongly with height in the downstream area of Taiwan’s central mountain range. The location of the area with large wind shear and wind veer differs between the three simulated typhoon cases and primarily depends on the latitude of the typhoon track relative to the central mountain range.

Microhabitat association and resistance of Tanaidacea (Crustacea) to tropical cyclones in rocky intertidal areas of central-eastern Taiwan

Microhabitat association and resistance of Tanaidacea (Crustacea) to tropical cyclones in rocky intertidal areas of central-eastern Taiwan