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Road dust carries various contaminants and causes urban non-point source pollution in waterbodies through runoff. Road dust samples were collected in each month in two years and then sieved into five particle size fractions. The concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in each fraction were measured. The particle size fraction load index, coefficient of divergence, and Nemerow integrated risk index were used to analyze the temporal variation of pollution load and ecological risk in different particle size fractions. The advanced three-way model and wavelet analysis were used in quantitative identification and time-series analysis of sources. Results showed that both the pollution load and ecological risk of most heavy metals showed a decreasing trend from the finest fraction (P1) to the coarsest fraction (P5). The frequency of heavy metals in P1 posing extreme risk was about two times that of P5. Main types of heavy metal sources were similar among different fractions, whereas the impact intensity of these sources varied among different fractions. Traffic exhaust tended to accumulate in finer particles, and its contribution to Cu in P5 was only 35–55% of that in other fractions. Construction contributed more to coarser particles, and its contribution to Pb was increased from 45.34% in P1 to 65.35% in P5. Wavelet analysis indicated that traffic exhaust showed periodicities of 5–8 and 10–13 months. Fuel combustion displayed the strongest periodicity of 12–15 months, peaking in winter. [ABSTRACT FROM AUTHOR]

Trees and their morphology can mitigate the urban heat island (UHI) effect, but the impacts of tree species and their two-dimensional (2D) and three-dimensional (3D) morphological characteristics on the thermal environment of residential spaces at the building scale have not been effectively evaluated. This research extracted the data of trees in the spatial range of a 50 m radius of the sampling sites located in a subtropical humid city's residential area based on unmanned aerial vehicle (UAV) imagery and field measurements. It included Ficus microcarpa L. f., Cinnamomum camphora (L.) J. Presl, and Alstonia scholaris (L.) R. Br. as three typical evergreen tree species and six quantitative indicators of trees, with the number of trees (N) serving as fundamental indicator and mean canopy width (MCW), mean canopy height (MCH), mean tree height (MTH), canopy biomass (CV), and mean canopy biomass (MCV) as morphological characteristic indicators. We analyzed the impact of the six indicators above on two thermal environment parameters: Air temperature (AT) and relative humidity (RH), by correlation analysis and multiple linear regression analysis. Results showed that: (1) F. microcarpa, as a dominant local species, provided more than 65% of the tree canopy volume within the study area (50 m radius buffer zones), and its contribution to cooling and humidification effects was superior to those of C. camphora and A. scholaris. (2) The MTH and CV of F. microcarpa are the key factors influencing daytime AT and RH, respectively, with temporal fluctuation in impact intensity during the spring (May) daytime. (3) The MTH and N of F. microcarpa show the best cooling effect (adjusted R2 = 0.731, p < 0.05) during midday (13:00–14:00 p.m.), while its CV and MTH have the best humidification effect (adjusted R2 = 0.748, p < 0.05) during the morning (9:00–10:00 a.m.) among three typical tree species. The 2D and 3D morphological characteristic indicators effectively describe the impact and variation of tree species on the spring microclimate within small-scale residential spaces. This work provides new insights into the thermal benefits brought by the spatial growth features of trees at the building scale and offers reference for urban residential areas in the planning and management related to tree species selection, canopy maintenance, and the improvement of thermal comfort for inhabitants. [ABSTRACT FROM AUTHOR]

Due to the impact of global warming, drought has caused serious damage to China's ecological environment and social status. This article selects Laibin City in the Guangxi Zhuang Autonomous Region as the research area, utilizing multispectral remote sensing data as the data source and Landsat series image data for relevant preprocessing. It calculates the monthly normalized vegetation index (NDVI) and surface temperature (LST) data for Laibin City. Based on the ecological environment and surface coverage conditions of the research area, the ratio vegetation index (RVI), normalized vegetation moisture index (NDWI), temperature vegetation drought index (TVDI), and conditional vegetation temperature drought index (VTCI) were selected to calculate and invert the drought monitoring results of Laibin City. The drought monitoring results were obtained and overlaid with the vegetation area map to generate the vegetation drought monitoring results of Laibin City. Based on the climate, geography, and ecological characteristics of the monitored area in Laibin City, a specific analysis will be conducted to develop an appropriate TVDI index drought level, and generate vegetation drought level result maps for Laibin City in 2021, 2022, and 2023. Then, a detailed analysis of the vegetation drought situation in Laibin City is conducted according to time and space. Among them, in the past three years, the vegetation areas in Laibin City have experienced drought seasons mostly in summer and autumn. The interannual drought is mainly mild drought, and the proportion of areas with mild drought shows a relatively stable trend. In conclusion, TVDI proves to be a valuable tool for monitoring vegetation drought in Laibin City, offering insights for efficient water resource management strategies. [ABSTRACT FROM AUTHOR]

Light use efficiency (LUE) characterizes the efficiency of vegetation in converting photosynthetically active radiation (PAR) into biomass energy through photosynthesis and is a critical parameter for gross primary productivity (GPP) in terrestrial ecosystems. Based on the eddy covariance measurements of a Chinese cork oak plantation ecosystem in northern China, the temporal variations in LUE were investigated, and biophysical factors were examined at time scales ranging from hours to years. Our results show that diurnal LUE first increased sharply before 8:30 and then decreased gradually until 12:00, thereafter increasing gradually and reaching the maximum value at sunset during the growing season. The daily and monthly LUE first increased and then decreased within a year and showed a substantial drop around June. The annual LUE ranged from 0.09 to 0.17 g C mol photon−1, and the multiyear mean maximal LUE was 0.30 g C mol photon−1 during 2006–2019. Only GPP (positive) and clearness index (CI) (negative) had consistent effects on LUE at different time scales, and the effects of the remaining biophysical factors on LUE were different as the time scale changed. The effects of air temperature, vapor pressure deficit, precipitation, evaporative fraction, and normalized difference vegetation index on LUE were mainly indirect (via PAR and/or GPP). When CI decreased, an increased ratio of diffuse PAR to PAR produced a more uniform irradiance in the canopy, which ultimately resulted in a higher LUE. Due to climate change in our study area, the annual LUE may decrease in the future but improving management practices may slow or even reverse this trend in the annual LUE in the studied Chinese cork oak plantation. [ABSTRACT FROM AUTHOR]

Traditionally, for indoor radon testing, predominantly passive measurements have been used, typically applying the solid-state alpha track-etch method for long-term and the charcoal method for short-term measurements. However, increasingly, affordable consumer-grade active monitors have become available in the last few years, which can generate a concentration time series of an almost arbitrary duration. Firstly, we argue that consumer-grade monitors can well be used for quality-assured indoor radon assessment and consequent reliable decisions. Secondly, we discuss the requirements of quality assurance, which actually allow for reliable decision-making. In particular, as part of a rational strategy, we discuss how to interpret measurement results from low-cost active monitors with high and low sensitivity with respect to deciding on conformity with reference levels that are the annual average concentration of indoor radon. Rigorous analysis shows that temporal variations in radon are a major component of the uncertainty in decision-making, the reliability of which is practically independent of monitor sensitivity. Manufacturers of low-cost radon monitors already provide sufficient reliability and quality of calibration for their devices, which can be used by both professional inspectors and the general public. Therefore, within the suggested measurement strategy and metrologically assured criteria, we only propose to clarify the set and values of the key metrological characteristics of radon monitors as well as to upgrade user-friendly online tools. By implementing clear metrological requirements as well as the rational measurement strategy for the reliable conformity assessment of a room (building) with radon safety requirements, we anticipate significant reductions in testing costs, increased accessibility, and enhanced quality assurance and control (QA/QC) in indoor radon measurements. [ABSTRACT FROM AUTHOR]

Cloud cover and shadows often hinder the accurate analysis of satellite images, impacting various applications, such as digital farming, land monitoring, environmental assessment, and urban planning. This paper presents a new approach to enhancing cloud-contaminated satellite images using a novel variational model for approximating the combination of the temporal and spatial components of satellite imagery. Leveraging this model, we derive two spatial-temporal methods containing an algorithm that computes the missing or contaminated data in cloudy images using the seamless Poisson blending method. In the first method, we extend the Poisson blending method to compute the spatial-temporal approximation. The pixel-wise temporal approximation is used as a guiding vector field for Poisson blending. In the second method, we use the rate of change in the temporal domain to divide the missing region into low-variation and high-variation sub-regions to better guide Poisson blending. In our second method, we provide a more general case by introducing a variation-based method that considers the temporal variation in specific regions to further refine the spatial–temporal approximation. The proposed methods have the same complexity as conventional methods, which is linear in the number of pixels in the region of interest. Our comprehensive evaluation demonstrates the effectiveness of the proposed methods through quantitative metrics, including the Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Metric (SSIM), revealing significant improvements over existing approaches. Additionally, the evaluations offer insights into how to choose between our first and second methods for specific scenarios. This consideration takes into account the temporal and spatial resolutions, as well as the scale and extent of the missing data. [ABSTRACT FROM AUTHOR]

The nitrogen-stable isotopes of plants can be used to verify the source of fertilizers, but the fertilizer uptake patterns in tea (Camellia sinensis) plants are unclear. In this study, potted tea plants were treated with three types of organic fertilizers (OFs), urea, and a control. The tea leaves were sampled over seven months from the top, middle, and base of the plants and analyzed for the δ15N and nitrogen content, along with the corresponding soil samples. The top tea leaves treated with the rapeseed cake OF had the highest δ15N values (up to 6.6‰), followed by the chicken manure, the cow manure, the control, and the urea fertilizer (6.5‰, 4.1‰, 2.2‰, and 0.6‰, respectively). The soil treated with cow manure had the highest δ15N values (6.0‰), followed by the chicken manure, rapeseed cake, control, and urea fertilizer (4.8‰, 4.0‰, 2.5‰, and 1.9‰, respectively). The tea leaves fertilized with rapeseed cake showed only slight δ15N value changes in autumn but increased significantly in early spring and then decreased in late spring, consistent with the delivery of a slow-release fertilizer. Meanwhile, the δ15N values of the top, middle, and basal leaves from the tea plants treated with the rapeseed cake treatment were consistently higher in early spring and lower in autumn and late spring, respectively. The urea and control samples had lower tea leaf δ15N values than the rapeseed cake-treated tea and showed a generalized decrease in the tea leaf δ15N values over time. The results clarify the temporal nitrogen patterns and isotope compositions of tea leaves treated with different fertilizer types and ensure that the δ15N tea leaf values can be used to authenticate the organic fertilizer methods across different harvest periods and leaf locations. The present results based on a pot experiment require further exploration in open agricultural soils in terms of the various potential fertilizer effects on the different variations of nitrogen isotope ratios in tea plants. [ABSTRACT FROM AUTHOR]

Knowledge of wind field characteristics and variation principles in complex topographical regions is of great importance for the development of numerical prediction models, aviation safety support, and wind energy utilization. However, there has been limited research focused on the lower-tropospheric wind fields in the Qinghai-Tibet Plateau. This paper aims to study the wind characteristics, vertical distributions, and temporal variations in the northeast of the plateau by analyzing a four-year continuous dataset collected from a Doppler wind LiDAR deployed in Xining, Qinghai Province of China. The results indicate that the prevailing horizontal wind direction in the low levels is primarily influenced by the mountain-valley wind circulation. However, as the altitude increases, the prevailing winds are predominantly affected by the westerlies. From a diurnal perspective, noticeable transition processes between up-valley and down-valley winds can be observed. The west-northwest wind (down-valley wind) dominates from late night to morning, while the east-southeast wind (up-valley wind) prevails from afternoon to early evening. The vertical winds in the low levels exhibit a downward motion during the daytime and an upward motion during the nighttime. In this plateau valley, the wind shear exponent is found to be highest in spring and lowest in winter, and it is generally lower during the daytime compared to the nighttime. [ABSTRACT FROM AUTHOR]

In 2023, this study monitored nine types of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in the urban and suburban areas of Tangshan. The total antibiotics concentration detected in influent WWTPs was highest in winter, followed by spring, summer, and autumn. The antibiotics concentration in influent and effluent urban WWTPs was higher than that in the suburban WWTPs in spring, summer, and winter, while the trend was reversed in autumn. Roxithromycin and oxytetracycline had a risk quotient (RQ) value of ≥0.1 in the effluent of WWTPs in winter, indicating that they are medium-risk antibiotics that pose a risk to the aquatic ecosystem after discharge. In the study area, the per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole, while it was highest in winter for ofloxacin. In the urban area, the use of roxithromycin, sulfamethoxazole, sulfamethoxazole, and ofloxacin was highest in spring, summer, autumn, and winter, respectively, while in suburban areas, the use of sulfamethoxazole, norfloxacin, sulfamethoxazole, and ofloxacin was highest during the same period. The use of antibiotics in the urban area was one order of magnitude higher than that in suburban areas, indicating a possible overuse of antibiotics in urban environments. [ABSTRACT FROM AUTHOR]

Elevated atmospheric reactive nitrogen (Nr) emissions and the subsequent nitrogen (N) deposition have negatively impacted the global environment, particularly in China. In order to assess the long-term trends in atmospheric N deposition in the south of China, Taojiang County in Hunan Province was selected as a representative rural area for study. We analyzed interannual variation in atmospheric Nr, including gaseous ammonia (NH3), nitrogen dioxide (NO2), nitrate acid (HNO3) vapor, particulate ammonium (NH4+), and nitrate (NO3−) in air and NH4+-N and NO3−-N in precipitation from 2011 to 2020. The 10-year average atmospheric wet-plus-dry N deposition was 41.9 kg N ha−1 yr−1, which decreased by approximately 24% after 2012, indicating that NH3 and NOx emissions were effectively reduced by emission controls introduced in 2013. Wet deposition accounted for approximately 74% of the total N deposition and was significantly influenced by annual precipitation amount. Reduced N (NH3, pNH4+, and NH4+ in rainwater) was the dominant form, comprising approximately 58% of the total N deposition, while oxidized N (pNO3−, NO2, HNO3, and NO3− in rainwater) accounted for 42% of the total N deposition. Atmospheric HNO3, NO2, and NH3 concentrations and deposition declined by 30–80% over the decade, while particulate NH4+ and NO3− concentrations and deposition remained at relatively stable levels, which suggests that ongoing research and policy should focus on rural particulate pollution. Future strategies must concentrate on the integrated control of NH3 and NOx emissions to mitigate air pollution and protect human health, particularly in rural areas because current abatement efforts are primarily directed toward urban areas and the industrial sector, whereas non-point source NH3 pollution, influenced mainly by agricultural activities, dominates in rural regions. [ABSTRACT FROM AUTHOR]

Air pollution in the developed regions of eastern China has been intensively investigated in the past decade. However, there is a relative dearth of air pollution studies on the northwest of inland China (e.g., Xinjiang). In this work, hourly measurement data of six criteria air pollutants (PM2.5, PM10, CO, NO2, O3, and SO2) for the past five years (2018–2022) from Hami and Turpan cities of eastern Xinjiang were analyzed to reveal air pollution characteristics and the distribution of potential sources. Hami and Turpan had the highest AQI values in winter due to increased coal combustion for domestic heating and unfavorable meteorological conditions. The slight elevations of AQI values in spring were caused by frequent dust storms. PM10 was the most frequent main pollutant in both Hami (63.1%) and Turpan (74.1%), followed by PM2.5 and O3. Except for O3, PM2.5, PM10, SO2, NO2, and CO exhibited a generally decreasing pattern in annual average values. But the annual average concentrations of PM10 in Hami (83.5 μg·m−3) and Turpan (139 μg·m−3) in 2022 were still higher than those in eastern China. Diurnal and monthly variations of the six criteria pollutants were influenced by a combination of emission sources and meteorological conditions. The air masses in eastern Xinjiang mainly originated from the west and north and were affected by both inter-regional and intra-regional transport. Analysis of the distribution of potential sources showed that local emissions strongly impacted particulate matter pollution in winter, while regional transport played a dominant role in other seasons. O3 showed a broad distribution of potential sources across all four seasons. Considering that the trend that O3 pollution increased year by year, eastern Xinjiang might face a similar pollution situation as eastern China, i.e., the combined pollution of particulate matter and O3. [ABSTRACT FROM AUTHOR]

The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical factor limiting the positioning performance. The conventional strategy adopts a fixed sound velocity profile (SVP) to correct the spatial variation, especially in the vertical direction. However, SVP is actually time-varying, and ignoring this kind of variation will lead to a worse estimation of ARVs'coordinates. In this contribution, we propose a two-step sound speed correction method, where, firstly, the deviation due to the acoustic ray bending effect is corrected by the depth-based ray-tracing policy with the fixed SVP. Then, the temporal variation of SVP is considered, and the fixed SVP is adaptively adjusted according to the in situ sound velocity (SV) measurements provided by the conductivity–temperature–depth (CTD) sensor equipped at the ARV. The proposed method is verified by semi-physical simulation and sea-trail dataset in the South China Sea. When compared to the fixed-SVP method, average positioning accuracy with the resilient SVP be improved by 8%, 21%, and 26% in the east, north, and up directions, respectively. The results demonstrate that the proposed method can efficiently improve the adaptability of sound speed observations and deliver better performance in USBL real-time positioning. [ABSTRACT FROM AUTHOR]

The grout pressure in the shield tunnel tail void during synchronous grouting is the key to controlling ground settlement and restraining the segment. However, the circumferential, longitudinal, and radial distribution of grout pressure considering the temporal variation in grout viscosity has not been well explored yet. In this study, a theoretical model of grout pressure distribution and dissipation considering the temporal variation in Bingham grout viscosity was established. The simulation results of the pressure model were verified by field-measured data. The results showed that the radial and longitudinal distributions of grout pressure considering the temporal variation in grout viscosity were closer to the field-measured data. The impacts of the main parameters on the pressure distribution and dissipation were analyzed. Compared with the effect of the shield tail void thickness, tunnel radius and yield shear stress have greater effects on grout pressure during the circumferential filling phase. During the longitudinal and radial diffusion phases, the increase in soil porosity and permeability coefficient was conducive to grout diffusion. The increase in the grout viscosity reduces the pressure loss during the grout flow process. The results of this research can provide a theoretical basis for the grout design process in shield tunnels. [ABSTRACT FROM AUTHOR]

Ambient atmospheric concentrations of isoprene and monoterpenes were measured at two forest sites, one deciduous and one coniferous, over the year 2022. Both sites in a regional area were sampled monthly between April and September. The samples were taken using sorbent tubes and analyzed with thermal desorption–gas chromatography–mass spectrometry. The highest concentrations were determined in August at both sites. While isoprene is the most abundant compound at the deciduous forest with an average concentration of 5.59 µg m−3 in August, α-pinene and β-pinene dominate throughout the year at the coniferous forest with the highest concentrations also in August (3.44 µg m−3 and 1.51 µg m−3). Because other monoterpenes (camphene, sabinene, 3-carene, p-cymene and limonene) are also emitted in significant amounts, the total concentration measured in the coniferous forest is higher (7.96 µg m−3 in August) in comparison to the deciduous forest (6.08 µg m−3). Regarding the detected monoterpenes in the deciduous forest, sabinene is the dominant monoterpene in addition to α-pinene and is sometimes present in higher (July) or equal (August) concentrations. The seasonal and diurnal concentrations of all monoterpenes correlate very well with each other at both sites. An exception is sabinene with a diurnal concentration profile similar to isoprene. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) and their derivatives have received extensive attention due to their negative effects on the environment and on human health. However, few studies have performed comprehensive assessments of PAHs emitted from pesticide factories. This study assessed the concentration, composition, and health risk of 52 PM2.5-bound PAHs during the daytime and nighttime in the vicinity of a typical pesticide factory. The total concentration of 52 PAHs (Σ52PAHs) ranged from 53.04 to 663.55 ng/m3. No significant differences were observed between daytime and nighttime PAH concentrations. The average concentrations of twenty-two parent PAHs, seven alkylated PAHs, ten oxygenated PAHs, and twelve nitrated PAHs were 112.55 ± 89.69, 18.05 ± 13.76, 66.13 ± 54.79, and 3.90 ± 2.24 ng/m3, respectively. A higher proportion of high-molecular-weight (4–5 rings) PAHs than low-molecular-weight (2–3 rings) PAHs was observed. This was likely due to the high-temperature combustion of fuels. Analysis of diagnostic ratios indicated that the PAHs were likely derived from coal combustion and mixed sources. The total carcinogenic equivalent toxicity ranged from 15.93 to 181.27 ng/m3. The incremental lifetime cancer risk from inhalation, ingestion, and dermal contact with the PAHs was 2.33 × 10−3 for men and 2.53 × 10−3 for women, and the loss of life expectancy due to the PAHs was 11,915 min (about 0.023 year) for men and 12,952 min (about 0.025 year) for women. These results suggest that long-term exposure to PM2.5 emissions from a pesticide factory has significant adverse effects on health. The study results support implementing the characterization of PAH emissions from pesticide factories and provides a scientific basis for optimizing the living environment around pesticide factories. [ABSTRACT FROM AUTHOR]

Exposure to air pollution will pose a serious threat to human health. Accurate air pollution forecasting can help people to reduce exposure risks and promote environmental pollution control, and it is also an extremely important part of smart city management. However, the current deep-learning-based models for air pollution forecasting usually focus on prediction accuracy improvement without considering the model interpretability. These models usually fail to explain the complex relationships between prediction targets and external factors (e.g., ozone concentration (O 3 ), wind speed, temperature variation, etc.) The relationships between variables in air pollution time series prediction problems are very complex, with intricate relationships between different types of variables, often with nonlinear multivariate dependencies. To address these problems mentioned above, we proposed a hybrid autoformer network with a genetic algorithm optimization to predict air pollution temporal variation as well as establish interpretable relationships between pollutants and external variables. Furthermore, an elite variable voting operator was designed to better filter out more important external factors such as elite variables, so as to perform a more refined search for elite variables. Moreover, we designed an archive storage operator to reduce the effect of neural network model initialization on the search for external variables. Finally, we conducted comprehensive experiments on the Ma'anshan air pollution dataset to verify the proposed model, where the prediction accuracy was improved by 2–8%, and the selection of model influencing factors was more interpretable. [ABSTRACT FROM AUTHOR]

Improving air quality in the Yellow River Golden Triangle Demonstration Area (YRGTDA) is an important practice for ecological protection and high-quality development in the Yellow River Basin. Preventing and controlling PM2.5 pollution in this region will require a scientific understanding of the spatiotemporal patterns and characteristics of PM2.5 pollution. PM2.5 data from different sources were combined in this study (the annual average of PM2.5 concentrations were obtained from the Atmospheric Composition Analysis Group of Dalhousie University, and the daily PM2.5 concentration data were obtained from the China National Environmental Monitoring Centre). Then, the temporal variation of PM2.5 concentrations at annual, seasonal, and monthly scales, the spatial variation of PM2.5 concentrations, and the variation of PM2.5 pollution classes were analyzed. Results showed that: (1) at the annual scale, the PM2.5 concentrations showed a decreasing trend from 2000 to 2021 in the study area. The variation of PM2.5 concentrations were divided into two different stages. (2) At the seasonal scale, high PM2.5 concentrations occurred mainly in winter, low PM2.5 concentrations occurred in summer. At the monthly scale, PM2.5 concentrations showed a U-shaped variation pattern from January to December each year. (3) The hotspot analysis of the PM2.5 concentrations in the study area showed a cyclical variation pattern. (4) The PM2.5 concentrations exhibited a spatial pattern of high values in the central and low values in the northern and southern parts of YRGTDA. (5) The number of days for different PM2.5 pollution classes from 2015 to 2021 followed the order of Good > Excellent > Light pollution > Moderate pollution > Heavy pollution > Severe pollution in YRGTDA. The results of this study have great theoretical and practical significance because they reveal the spatiotemporal patterns and pollution characteristics of PM2.5 and will lead to the development of scientifically based measures to reasonably prevent and control pollution in YRGTDA. [ABSTRACT FROM AUTHOR]

Understanding the normal variation of the sugarcane rhizosphere fungal community throughout its life cycle is essential for the development of agricultural practices for fungal and ecological health associated with the microbiota. Therefore, we performed high-throughput sequencing of 18S rDNA of soil samples using the Illumina sequencing platform for correlation analysis of rhizosphere fungal community time series, covering information from 84 samples in four growth periods. The results revealed that the sugarcane rhizosphere fungi possessed the maximum fungal richness in Tillering. Rhizosphere fungi were closely associated with sugarcane growth, including Ascomycota, Basidiomycota, and Chytridiomycota, which showed high abundance in a stage-specific manner. Through the Manhattan plots, 10 fungal genera showed a decreasing trend throughout the sugarcane growth, and two fungal genera were significantly enriched at three stages of sugarcane growth (p < 0.05) including Pseudallescheria (Microascales, Microascaceae) and Nectriaceae (Hypocreales, Nectriaceae). In addition, soil pH, soil temperature, total nitrogen, and total potassium were critical drivers of fungal community structure at different stages of sugarcane growth. We also found that sugarcane disease status showed a significant and strong negative effect on selected soil properties by using structural equation modeling (SEM), suggesting that poor soil increases the likelihood of sugarcane disease. In addition, the assembly of sugarcane rhizosphere fungal community structure was mainly influenced by stochastic factors, but after the sugarcane root system became stable (Maturity), the stochastic contribution rate decreased to the lowest value. Our work provides a more extensive and solid basis for the biological control of sugarcane potential fungal diseases. [ABSTRACT FROM AUTHOR]

Ground-level ozone pollution causes adverse health effects, and the detailed influences of meteorological factors and precursors on ozone at an hourly scale need to be further understood. We conducted an in-depth analysis of the phase relationships and periods of ground-level ozone in Shunyi station, Beijing, and contributing factors using wavelet analysis and geographic detectors in 2019. The combined effects of different factors on ozone were also calculated. We found that temperature had the strongest influence on ozone, and they were in phase over time. NO2 had the greatest explanatory power for the temporal variations in ozone among precursors. The wavelet power spectrum indicated that ozone had a periodic effect on multiple time scales, the most significant being the 22–26 h period. The wavelet coherence spectrum showed that in January–March and October–December, NO2 and ozone had an antiphase relationship, largely complementary to the in-phase relationship of temperature and ozone. Thus, the main influencing factors varied during the year. The interactions of temperature with NO2 significantly affected the temporal variations in ozone, and explanatory power surpassed 70%. The findings can deepen understanding of the effects of meteorological factors and precursors on ozone and provide suggestions for mitigating ozone pollution. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) is the most developed region in China. Influenced by intensive and complex anthropogenic activities, atmospheric pollution in this region is highly variable, and reports are sparse. In this study, a seven-year history of the atmospheric O3 and NOx mixing ratios over a typical city, Hangzhou, was presented to enrich the studies on air pollution in the YRD region. Our results revealed that the diurnal variation in NOx corresponded to traffic rush hours, while O3 was mainly impacted by photochemical reactions in the daytime. The weekend effect was significant for NOx, but inapparent for O3. Two O3 peaks in May and September were caused by seasonal atmospheric stability and climatic conditions. The lower NOx and higher O3 levels observed suggested direct effects from traffic restrictions and large-scale industrial shutdowns during the COVID-19 lockdown in 2020 compared with those in the periods before and after lockdown. The model simulation results showed that O3 mixing ratios were not only related to regional anthropogenic emissions but were impacted by air mass transportation from surrounding provinces and the China shelf seas. The NOx mixing ratios showed a decreasing trend, while the O3 mixing ratios showed the opposite trend from 2015 to 2021, which is indicative of the implementation of the Air Pollution Prevention and Control Acton Plan issued by the Chinese government in 2013. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? Variations in the form of trends and abrupt changes are distinguished. What is the implication of the main finding? Using the single-test method produced large uncertainty. Trend tests were performed separately from abrupt change tests to assess the long-term changes in rainfall erosivity series, which would result in the wrong conclusion. Rainfall erosivity is commonly used to estimate the probability of soil erosion caused by rainfall. The accurate detection of temporal changes in rainfall erosivity and the identification of abrupt changes and trends are important for understanding the physical causes of variation. In this study, a detection framework is introduced to identify temporal changes in rainfall erosivity time series as follows: (i) The significance of time series variation of rainfall erosivity is assessed based on the Hurst coefficient and divided into three levels: None, medium, and high. (ii) The detection of abrupt changes (Mann–Kendall, Moving T, and Bayesian tests) and trends (Spearman and Kendall rank correlation tests) of variate series and the correlation coefficient between the variation component and the original series is calculated. (iii) The modified series is obtained by preferentially eliminating the variation component (trend or change point) with larger correlation coefficients. (iv) We substituted the modified series into steps i to iii until the correlation coefficient was not significant. This framework is used to analyze the variation of rainfall erosivity in the Three Gorges Reservoir, China. The results showed that by using traditional methods, both an increasing trend and an upward change point were observed in Zigui station. However, after the upward change point was deducted from the annual rainfall erosivity series R(t), the resultant Rm(t) showed no statistically significant trend. Trend analysis should be performed considering the existence of an abrupt change to assess the long-term changes in rainfall erosivity series; otherwise, it would result in the wrong conclusion. In addition, the change points detected in the Rm(t) varied with the methods. Compared with the single-test method, the proposed framework can effectively reduce uncertainty. [ABSTRACT FROM AUTHOR]

To highlight the characteristics of PM2.5–O3 pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental monitoring stations in seven major cities of the agglomeration. The results revealed the following: (1) Spatially, the PM2.5–O3 pollution days were aggregated in the central area of Xinxiang and decreased toward the north and south. Temporally, during the 2014–2020 period, 50 days of PM2.5–O3 pollution were observed in the major cities of the Central Plains Urban Agglomeration, with an overall decreasing trend. (2) A low-temperature, high-pressure environment appeared unfavorable for the occurrence of PM2.5–O3 pollution days. Wind speeds of 2.14–2.19 m/s and a southerly direction increased the incidence of PM2.5–O3 pollution days. (3) The external transport range in summer was smaller and mainly originated from within Henan Province. These results can provide important reference information for achieving a synergistic control of PM2.5–O3 pollution, determining the meteorological causes, as well as the potential sources, of PM2.5–O3 pollution in polluted areas and promoting air pollution control. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of thermal stratification and complete mixing conditions on the bacterial diversity of a deep alkaline lake. For this purpose, the water and sediment samples were collected during the winter turnover and stratification periods, and bacterial communities were assessed by metabarcoding. The results showed that temperature shaped the bacterial community patterns in the lake. While the bacterial communities of the water samples showed high similarity during the mixing period, communities had distinctive patterns in the epilimnion and hypolimnion during stratification. The diversity and evenness of the bacterial communities increased with depth, whereas the bacterial communities of sediments were more even and diverse than in water. Proteobacteria members dominated the sediment communities representing 41% to 62% of the total reads in the samples. Particularly, Gammaproteobacteria was the major class found in the sediment; higher abundances were recorded in the mixing period representing 33–51%. Additionally, Actinobacteria species were more abundant in the water samples representing 22–52% of all reads during the stratification period. Due to the complete mixing conditions in the lake, a homogenized bacterial community structure was observed in the lake with minor spatial changes, and a clear divergence was observed between epilimnion and hypolimnion. On the other hand, the sediment bacterial community showed a more stable profile. [ABSTRACT FROM AUTHOR]

This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents. [ABSTRACT FROM AUTHOR]

It is crucial to understand the spatial-temporal variation of water quality for the water safety and eutrophication migration in plateau lakes. To identify the variation property and the main causes of eutrophication and continuous water quality deterioration, the water quality, including the water temperature (WT), dissolved oxygen (DO), pH, Chl-a, turbidity, total nitrogen (TN) and total phosphorus (TP), of Lake Xingyun was monitored from 2016 to 2021, and their spatial and temporal distribution characteristics were analyzed. The results show that there is no obvious thermal stratification in the vertical direction; pH and DO decrease with depth, which is caused by both physical and biochemical processes, especially at the bottom of Lake Xingyun, which has an anaerobic environment. The chlorophyll content was higher during the high-flow periods and varied significantly in the vertical direction; the spatial variation of water quality in Lake Xingyun was more obvious in the low-flow period and alkaline throughout the year. The average content of total phosphorus (TP) ranged between 0.33 and 0.53 mg/L during the high-flow periods and between 0.22 and 0.51 mg/L during the low-flow periods, while the average content of total nitrogen (TN) ranged between 1.92 and 2.62 mg/L and 1.36 and 2.53 mg/L during the high- and low-flow periods, respectively. The analysis of the inflow samples shows that exogenous nitrogen and phosphorus is the main pollution source affecting the nitrogen and phosphorus content of Lake Xingyun. The trophic level index (TLI) shows that Lake Xingyun is in eutrophication all year round, and even in areas less affected by the exogenous nutrient, there are still conditions for cyanobacterial blooms. This study shed new light on the water quality, eutrophication status and changes in Lake Xingyun, providing suggestions for controlling lake pollution and eutrophication mitigation. [ABSTRACT FROM AUTHOR]

The temporal variability and abrupt change analysis of temperature and precipitation in Turpan was investigated and examined based on a monthly data set of temperature, precipitation and drought indices (1960–2019) from three meteorological stations over the study area. The Yamamoto method, Mann–Kendall test, Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), and Reconnaissance Drought Index (RDI) were applied to reveal temperature, precipitation and drought indices trends in their annual volumes. The conclusions were as follows: (1) in the past 60 years, the annual average temperature in the Turpan region has increased at a rate of 0.33 °C·(10a)−1. Whereas the temperature has accelerated since the 1980s, the annual average minimum temperature has increased more than the annual average maximum temperature, and the temperature difference between winter and summer has increased since the 1990s. (2) The inter-annual, inter-decadal and normal value changes in precipitation in the Turpan region and its three meteorological stations indicated a decreasing trend during 1960–2019. Though the normal value of summer and autumn precipitation decreased and increased as a whole, the normal values of spring, summer, winter and annual precipitation in the Turpan region displayed downward trends. (3) Abrupt changes in temperature were observed in the mid-1990s, and abrupt changes in precipitation were not obvious. (4) The SPI and RDI responded quickly to precipitation and temperature, and the overall characteristics of dry and wet trend changes were consistent. When the SPEI considered the combined effect of temperature and precipitation, the SPI and SPEI are better correlated, and the SPI and RDI are better correlated than the SPEI and RDI. On the whole, the occurrence of drought has obvious regional and seasonal characteristics. These conclusions not only provide scientific data for sustainable development in Turpan but also offer scientific information to further understand the trends and periodicity of climate change and drought conditions in hyper-arid regions around the world. [ABSTRACT FROM AUTHOR]

Much of our understanding of factors influencing stream chemistry comes from studies of montane forests, whereas far less work has focused on streams of coastal areas that integrate a homogeneous, flat topography and interactions with the bodies of water into which they drain, especially involving tidal fluxes. Fewer still do so in the context of an urban interface, especially that of a college campus. This study assessed the water quality of Thompson Bayou, a freshwater stream entering the University of West Florida campus in a wetland after flowing through the urban property with impacted water quality. We measured temperature, pH, dissolved O2 (DO), and specific conductivity (SC) for one year at eight sites along Thompson Bayou from campus to the Escambia River. All variables, except temperature, varied spatially, with consistent increases in DO and SC toward the river of 10% and 75%, respectively. Variables exhibited temporal patterns of significant seasonal variation, especially temperature, increasing from a January minimum of 14 °C to a summer maximum of 28 °C. These results suggest that, in general, the biogeochemistry of coastal streams such as Thompson Bayou can be influenced by numerous factors, including (1) wetland processes, (2) interactions of the stream channel with forested uplands, and (3) tidal fluxes. [ABSTRACT FROM AUTHOR]

To investigate the microwave radiation characteristics of different vegetation types, the "pure pixels" of 12 typical vegetated land types were selected and corresponding emissivity was retrieved under clear sky based on L1C AMSR2 observed brightness temperatures (TBs). According to the retrieved values for the 12 types, the spectral features in summer from 10.65 to 89 GHz were analyzed first. Then, the temporal variations in emissivity at 10.65, 18.7, and 36.5 GHz H-polarized (hereinafter 10H, 18H and 36H) are shown for the period from January 2018 to September 2020. Finally, the responses of 10H emissivity to surface skin temperature (SKT), the normalized differential vegetation index (NDVI), and soil moisture content (SMC) were quantitatively evaluated using a step-by-step analysis method. The general results are as follows: H-polarized (H-pol) emissivity increases with frequency and vegetation biomass, while the polarization differences decrease with frequency and vegetation biomass. The responses of V-pol emissivity to frequency and biomass are different from those of H-pol emissivity, and there are negative correlations with frequency and unusually high low-frequency values in grasslands and open shrublands (OS). The temporal variation amplitude of emissivity seems to be negatively correlated with vegetation biomass, and evergreen broadleaf forests show little variation. In general, the seasonal changes in emissivity are consistent with those of NDVI for most vegetation types. Nevertheless, in some cases, the change in emissivity is obviously ahead or behind that of NDVI, revealing that NDVI and emissivity may be sensitive to different vegetation elements that do not change in sync. In addition, variations in emissivity at different frequencies also show different amplitudes and turning points. Generally, the response of the 10H emissivity to SKT is weak, regardless of whether the response is positive or negative. The relatively large negative responses can be attributed to other indirect causes. NDVI plays a positive role in emissivity of the low-biomass vegetation in drier environments and medium- or high-biomass vegetation with clear seasonal variation. SMC is a complex factor that can have a positive or negative effect on emissivity. [ABSTRACT FROM AUTHOR]

In-depth studies on the effect of size and period in the diet of the hollow-snout grenadier Coelorinchus caelorhincus in the Mediterranean Sea are scant and incomplete. We obtained 75 specimens of this species from the discard of deep trawl fishing on the slope of the central Tyrrhenian Sea. As corollary data, we estimated the length–weight relationship, the size frequency distribution, and composition of sexual maturity stages of the sampled individuals. We deepened stomach content analysis aiming at the evaluation of size and period's effect in the fish diet by Costello's interpretation of dietary indexes and correspondence analysis. The corollary results suggested negative allometric growth (b = 2.69), an asynchronous reproductive strategy (paucity of mature individuals) and a size-related bathymetrical distribution for this species (prevalence of small and intermediate-sized specimens). The prey importance index (PII) revealed that the hollow-snout grenadier is a generalist feeder on cephalopods (PII: 0–1200), fish (PII: 0–1000), crustaceans (PII: 4000–6000), and polychaetes (PII: 400–1800), and a light specialist at population level on the dominant prey among them. At the micro-taxa level, the species was found to be a generalist feeder on 10 groups of rare prey and a light specialist at population level on amphipods (PII: 1300–3200). Overall, results indicated the presence of two feeding gradients that determined an intermingled effect of size and period on fish diet. In particular, intraspecific competition and stability of food resources appeared as the factors that significantly harmonize the diet of Coelorinchus caoelorhincus in the context of the ecotrophic constraints of a deep-sea species. [ABSTRACT FROM AUTHOR]

Assessment of benthic diversity and estuarine ecological quality is becoming increasingly important. Estuaries are not only highly productive and variable environments, but they are also areas of high anthropogenic perturbations. In this study, benthic macrofauna were sorted, identified and analyzed from a freshwater-dominated tropical estuary along the Bay of Bengal to assess their community structure, distribution and functional guilds, and to uncover the environmental drivers influencing their distributional patterns. Results revealed that the studied physio-chemical variables (DO, pH, alkalinity and temperature) were significantly varied (p < 0.05) among the sites. Capitella sp. was dominant (18%) of the forty morphospecies recorded, indicating organic richness of the area. The ANOVA results revealed that macrobenthic density differed significantly (p < 0.01) between the study locations, and diversity indices (Shannon diversity index, H′) also differed significantly (F4,12 = 5.89; p = 0.02). The benthic density decreased from the head to the mouth, which could be related to salinity fluctuations and large freshwater discharges. Upstream sites were completely segregated from downstream and mid-estuarine sites, according to cluster analysis (CA). The SIMPER results clarified the site grouping pattern, showing that Mysis-1 spp., Capitella spp. and Nephtys-1 were the most significant contributors. From the communities, five functional trophic groups were identified where deposit feeders were the most dominant (66.44%). Most of the macrobenthos had strong positive correlations with DO (r = 0.92) and water temperature (r = 0.86) and a negative correlation with soil pH (r = −0.28), per correlation and CCA analyses. Individually, soil pH (r = 0.88) and alkalinity (r = 0.898) showed strong positive correlation with Capitella sp. and Chironomus sp.2. The above results indicate that macrobenthos of this estuary do not follow the usual pattern of spatial distribution, and they are structured by DO, alkalinity and soil pH. In addition, dominance of some pollution indicator species (Capitella sp. and Chironomus sp.) and deposit feeders indicates a poor ecological condition of the estuary. [ABSTRACT FROM AUTHOR]

The WHO has classified carbapenem-resistant Enterobacteriaceae in most critical priority pathogens that pose a threat to human health. The present study investigated the prevalence of meropenem-resistant Escherichia coli (E. coli) in relation to its temporal variation in different seasons along with its resistance markers in sewage water. E. coli was selected on MacConkey agar containing meropenem (3 µg/mL). There were 27% of sites/sewage samples carrying meropenem-resistant E. coli. All E. coli were confirmed through the amplification of the uidA gene. All isolated E. coli were multidrug-resistant (MDR), and among them, 51% were extensively drug-resistant (XDR). An antibiogram determined against 15 antibiotics showed the highest resistance to ampicillin and cefotaxime (98% each) and lowest resistance to fosfomycin (2%). Phylogenetic groups and resistance gene analysis through PCR showed a significant co-occurrence of carbapenemases with extended spectrum beta lactamases (ESBLs), plasmid encoded quinolone, and colistin resistance genes. The higher number of resistance genes in E. coli isolates in community sewage indirectly indicate that these isolates circulate abundantly in the community. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations. [ABSTRACT FROM AUTHOR]

Industrialization and urbanization have led to continuous urban development. The rapid change in land-use type and extent has a significant impact on the capacity of ecosystem services. Changes in the landscape pattern of roads, rivers, railway stations, and expressway entrances and exits have evident geographical proximity effects. We used landscape pattern indices and ecosystem service value (ESV) to evaluate the landscape pattern and ESV spatial differentiation of the Pearl River Delta region and its typical transportation infrastructure and rivers in 1990, 2000, and 2017. The results show that rapid urbanization and industrialization have led to changes in urban land use along the Pearl River Estuary. Urban land changes on the east bank of the Pearl River are greater than urban land changes on the west bank of the Pearl River; the landscape diversity of the Pearl River Delta has increased, the connectivity of the landscape has decreased, and the degree of fragmentation has increased. Second, the city size of the Pearl River Delta was negatively correlated with the ESVs. The ESVs in the core areas of the Pearl River Delta urban agglomeration were smaller than those in the fringe areas. With the gradient change in urban land use, ESVs showed a growing trend from the city center to the surrounding areas. The key areas for ecological protection and restoration should be central urban areas and suburbs. Third, the siphoning effect of the buffer zones of railway stations and expressway entrances and exits was very strong and drove the development and utilization of the surrounding land. As the degree of land development in the buffer zone decreased, the ESVs increased. Fourth, different grades of roads in the Pearl River Delta had different impacts on the regional landscape and ESVs. County roads had a greater interference effect than expressways, national roads, and provincial roads, and the riverside plains of the Pearl River Delta have a large development space, low urban development costs, and multiple land-use activities that have profoundly changed the landscape of the river buffer zone. [ABSTRACT FROM AUTHOR]

This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen's slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = -0.37) and Adet (Z = -0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980-2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies. [ABSTRACT FROM AUTHOR]

Water quality patterns in two adjacent embayments of the tidal freshwater Potomac River were compared using continuously monitored data. The two embayments, the tidal Occoquan and Gunston Cove, are shallow embayments fed by tributaries which vary in their watershed attributes. The tidal Occoquan has a larger watershed and a dam just upstream from the head of tide whereas Gunston Cove has a large wastewater treatment plant just upstream of the embayment. Water temperature, specific conductance, dissolved oxygen (DO), and pH were collected at 15 min intervals at representative locations in the two embayments from April through November of 2012. Mean daily values of water quality variables exhibited similar seasonal patterns at both sites which were related to seasonal patterns of forcing functions such as temperature, light and freshwater inflows. Three two-week intervals were examined in great detail. During a mid-summer period of stable conditions and low flow, both embayments exhibited strong and consistent diel (light cycle-based) periodicity in temperature, DO, and pH. Specific conductance exhibited semi-diel (tidal cycle-based) periodicity. The two other two-week intervals were punctuated by substantial flow events which resulted in major changes in daily mean values and disruptions to the typical diel or semi-diel cycles. The large rainfall event related to Hurricane Sandy caused a major disruption in diel and semi-diel cycles. Some cycles were quickly re-established and others took a week or more. The two embayments exhibited similar behavior in most aspects. Site-specific factors such as differences in the frequency and magnitude of tributary flow pulses and the presence of treated sewage discharge at Gunston Cove helped explain some of the differences observed between the two embayments. [ABSTRACT FROM AUTHOR]

Various multivariate methods were used to analyze datasets of river water quality for 11 variables measured at 20 different sites surrounding Lake Taihu from 2006 to 2010 (13,200 observations), to determine temporal and spatial variations in river water quality and to identify potential pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into two periods (May to November, December to the next April) and the 20 sampling sites into two groups (A and B) based on similarities in river water quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only three variables (water temperature, dissolved oxygen (DO) and five-day biochemical oxygen demand (BOD5)) to correctly assign about 94% of the cases and five variables (petroleum, volatile phenol, dissolved oxygen, ammonium nitrogen and total phosphorus) to correctly assign >88.6% of the cases. In addition, principal component analysis (PCA) identified four potential pollution sources for Clusters A and B: industrial source (chemical-related, petroleum-related or N-related), domestic source, combination of point and non-point sources and natural source. The Cluster A area received more industrial and domestic pollution-related agricultural runoff, whereas Cluster B was mainly influenced by the combination of point and non-point sources. The results imply that comprehensive analysis by using multiple methods could be more effective for facilitating effective management for the Lake TaihuWatershed in the future. [ABSTRACT FROM AUTHOR]

Qiandao Lake (Xin’an Jiang reservoir) plays a significant role in drinking water supply for eastern China, and it is an attractive tourist destination. Three multivariate statistical methods were comprehensively applied to assess the spatial and temporal variations in water quality as well as potential pollution sources in Qiandao Lake. Data sets of nine parameters from 12 monitoring sites during 2010–2013 were obtained for analysis. Cluster analysis (CA) was applied to classify the 12 sampling sites into three groups (Groups A, B and C) and the 12 monitoring months into two clusters (April-July, and the remaining months). Discriminant analysis (DA) identified Secchi disc depth, dissolved oxygen, permanganate index and total phosphorus as the significant variables for distinguishing variations of different years, with 79.9% correct assignments. Dissolved oxygen, pH and chlorophyll-a were determined to discriminate between the two sampling periods classified by CA, with 87.8% correct assignments. For spatial variation, DA identified Secchi disc depth and ammonia nitrogen as the significant discriminating parameters, with 81.6% correct assignments. Principal component analysis (PCA) identified organic pollution, nutrient pollution, domestic sewage, and agricultural and surface runoff as the primary pollution sources, explaining 84.58%, 81.61% and 78.68% of the total variance in Groups A, B and C, respectively. These results demonstrate the effectiveness of integrated use of CA, DA and PCA for reservoir water quality evaluation and could assist managers in improving water resources management. [ABSTRACT FROM AUTHOR]

In this communication, we report the springtime variation of the composition of aristolochic acids (AAs) in Aristolochia chilensis leaves and stems. The dominant AA in the leaves of all samples, which were collected between October and December, was AA-I (1), and its concentration varied between 212.6 ± 3.8 and 145.6 ± 1.2 mg/kg and decreased linearly. This decrease occurred in parallel with the increase in AA-Ia (5) concentration from 15.9 ± 0.8 mg/kg at the beginning of October to 96.8 ± 7.8 mg/kg in mid-December. Both acids are enzymatically related by methylation-demethylation reactions. Other AAs also showed important variations: AA-II (2) significantly increased in concentration, reaching a maximum in the first two weeks of November and subsequently decreasing in mid-December to approximately the October levels. The principal component in the AA mixture of the stems was also AA-I (1); similar to AA-II (2), its concentration increased beginning in October, peaked in the second week of November and subsequently decreased. The concentrations of AA-IIIa (6) and AA-IVa (7) in the leaves and stems varied throughout the study period, but no clear pattern was identified. Based on the variation of AAs in A. chilensis leaves and stems during the study period, the reduced contents of non-phenolic AAs and increased concentrations of phenolic AAs are likely associated with a decrease in this plant's toxicity during the spring. [ABSTRACT FROM AUTHOR]

In an effort to minimize complex urban microclimatic variability within high-resolution (H-Res) airborne thermal infrared (TIR) flight-lines, we describe the Thermal Urban Road Normalization (TURN) algorithm, which is based on the idea of pseudo invariant features. By assuming a homogeneous road temperature within a TIR scene, we hypothesize that any variation observed in road temperature is the effect of local microclimatic variability. To model microclimatic variability, we define a road-object class (Road), compute the within-Road temperature variability, sample it at different spatial intervals (i.e., 10, 20, 50, and 100 m) then interpolate samples over each flight-line to create an object-weighted variable temperature field (a TURN-surface). The optimal TURNsurface is then subtracted from the original TIR image, essentially creating a microclimatefree scene. Results at different sampling intervals are assessed based on their: (i) ability to visually and statistically reduce overall scene variability and (ii) computation speed. TURN is evaluated on three non-adjacent TABI-1800 flight-lines (∼182 km2) that were acquired in 2012 at night over The City of Calgary, Alberta, Canada. TURN also meets a recent GEOBIA (Geospatial Object Based Image Analysis) challenge by incorporating existing GIS vector objects within the GEOBIA workflow, rather than relying exclusively on segmentation methods. [ABSTRACT FROM AUTHOR]

We report an active surveillance study of the occurrence of specific antibodies to European Bat Lyssavirus Type 1 (EBLV-1) in bat species, scarcely studied hitherto, that share the same refuge. From 2004 to 2012, 406 sera were obtained from nine bat species. Blood samples were subjected to a modified fluorescent antibody virus neutralization test to determine the antibody titer. EBLV-1-neutralizing antibodies were detected in six of the nine species analyzed (Pipistrellus pipistrellus, P. kuhlii, Hypsugo savii, Plecotus austriacus, Eptesicus serotinus and Tadarida teniotis). Among all bats sampled, female seroprevalence (20.21%, 95% CI: 14.78%-26.57%) was not significantly higher than the seroprevalence in males (15.02%, 95% CI: 10.51%-20.54%). The results showed that the inter-annual variation in the number of seropositive bats in T. teniotis and P. austriacus showed a peak in 2007 (>70% of EBLV-1 prevalence). However, significant differences were observed in the temporal patterns of the seroprevalence modeling of T. teniotis and P. austriacus. The behavioral ecology of these species involved could explain the different annual fluctuations in EBLV-1 seroprevalence. [ABSTRACT FROM AUTHOR]

Ozone (O 3 ) has attracted considerable attention due to its harmful effects on the ecosystem and human health. The Yangtze River Delta (YRD), China in particular has experienced severe O 3 pollution in recent years. Here, we conducted a long-term observation of O 3 in YRD to reveal its characteristics. The O 3 concentration in autumn was the highest at 72.76 ppb due to photochemical contribution and local convection patterns, with its lowest value of 2.40 ppb in winter. O 3 exhibited strong diurnal variations, showing the highest values in the early afternoon (15:00-16:00) and the minimum in 07:00-08:00, specifically, peroxyacetyl nitrate (PAN) showed similar variations to O 3 but PAN peak usually occurred 1 h earlier than that of O 3 due to PAN photolysis. A generalized additive model indicated that the key factors to O 3 formation were NO 2 , PAN, and temperature. It was found that a certain temperature rise promoted O 3 formation, whereas temperatures above 27 °C inhibited O 3 formation. An observation-based model showed O 3 formation was VOCs-limited in spring and winter, was NO x -limited in summer, and even controlled by both VOCs and NO x in autumn. Thus, prevention and control strategies for O 3 in the YRD are strongly recommended to be variable for each season based on various formation mechanisms., Competing Interests: Author Dongfeng Shi was employed by the company Hangzhou Xufu Detection Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Based on surface energy balance and the assumption of fairly invariant evaporative fraction (EF) during daytime, this study proposes a new parameterization scheme of directly estimating daily EF. Daily EF is parameterized as a function of temporal variations in surface temperature, air temperature, and net radiation. The proposed EF parameterization scheme can well reproduce daily EF estimates from a soil-vegetation-atmosphere transfer (SVAT) model with a root mean square error (RMSE) of 0.13 and a coefficient of determination (R²) of 0.719. When input variables from in situ measurements at the Yucheng station in North China are used, daily EF estimated by the proposed method is in good agreement with measurements from the eddy covariance system corrected by the residual energy method with an R² of 0.857 and an RMSE of 0.119. MODIS/Aqua remotely sensed data were also applied to estimate daily EF. Though there are some inconsistencies between the remotely sensed daily EF estimates and in situ measurements due to errors in input variables and measurements, the result from the proposed parameterization scheme shows a slight improvement to SEBS-estimated EF with remotely sensed instantaneous inputs. [ABSTRACT FROM AUTHOR]

Animal husbandry is an important source of carbon emissions. As a large country, China must measure the carbon emissions from animal husbandry to reveal the spatial and temporal characteristics and determine the influencing factors to realize low-carbon animal husbandry and carbon emission reduction. In this paper, the carbon emissions of the livestock industry in each province of China were calculated with the emission coefficient method, considering the temperature change factor. The spatial and temporal characteristics and influencing factors of livestock industry carbon emissions were analyzed using the kernel density model, the spatial autocorrelation model, and the Tobit model. The results indicated that: (1) From 2000 to 2020, carbon emissions from the livestock industry in China experienced four stages: rapid rise, rapid decline, slow rise, and fluctuating decline, with an overall downward trend. Carbon emissions in the eastern and central regions showed a downward trend, while carbon emissions in the western regions showed an upward trend. (2) In terms of time, the relative gap in carbon emissions among the provinces narrowed first and then widened; the spatial agglomeration of carbon emissions from livestock farming in China increased, gradually forming the characteristics of "high agglomeration, low agglomeration", and showing a gradually decreasing pattern from northwest to southeast. (3) Nationwide, industrial structure, population, and farmers' income levels have had significantly promoting effects on animal husbandry carbon emissions, and the urbanization and agricultural mechanization levels have had significant inhibitory effects on carbon emissions. Finally, based on the above factors, it can be concluded that recognizing the location conditions, promoting the upgrading of industrial structures, and adopting differentiated strategies will help to promote the reduction in carbon emissions in animal husbandry and achieve its high-quality development.

A number of studies have found associations between the short-term exposure to ambient air pollution and hospital admissions. However, little is known about the temporal variations in ambient air pollution associated with health exposure, especially in China. We evaluated whether the risks of allergic rhinitis (AR) outpatient visits from short-term exposure to air pollution varied over time (2014-2020) in Beijing, China. A quasi-Poisson generalized additive model was used to evaluate the relative risks (RRs) and 95% confidence intervals (CIs) associated with the pollutant concentrations during the entire study period and three specific periods. We also analyzed the temporal variations of the period-specific associations and tested the trend of change using the Mann-Kendall test. The concentration-response relationships for the specific periods were further investigated. The RRs (95%CI) for an interquartile range (IQR) increased in PM 10 (70 μg/m 3 ) and CO (0.5 mg/m 3 ) decreased from period 1 to period 3. However, The RRs (95%CI) of PM 2.5 (55 μg/m 3 ), SO 2 (7 μg/m 3 ) and NO 2 (27 μg/m 3 ) increased from 1.015 (0.978, 1.054), 1.027 (1.009, 1.044) and 1.086 (1.037, 1.137) in period 1 to 1.069 (1.005, 1.135), 1.074 (1.003, 1.149) and 1.214 (1.149, 1.282) in period 3, respectively. A statistically significant temporal change and the stable effects were observed between the NO 2 exposure and AR visits over time. Despite a substantial reduction in ambient air pollution, the short-term effects on AR outpatient visits remained significant. Our findings provide a rationale for continued air pollution control efforts in the future to minimize air pollution and to protect the public.

Although particulate matter (PM) is a major risk factor for stroke, its effects on hospital outpatients admitted for stroke have not been documented in Korea. In addition, recent studies have reported that the effects of PM 10 on circulatory mortality changed over time. We aimed to estimate the effects of PM 10 on stroke and their temporal heterogeneity in seven major cities of Korea during the period 2002-2015. The study period was divided into five years of moving time windows, and city-specific PM 10 effects on ischemic and hemorrhagic stroke outpatients were calculated. We pooled the estimates using meta-analysis and plotted them into a sequence to identify their temporal trends. A 10 µg/m 3 increase of PM 10 was significantly associated with increments in hospital outpatients admitted for ischemic stroke (0.24%, 95% CI: 0.04%, 0.44%), but not for hemorrhagic stroke (0.33%, 95% CI: -0.06%, 0.73%). Effect estimates for strokes increased during the period 2003-2013 but decreased after. For the first time, we have estimated the effects of PM 10 on hospital outpatients admitted for stroke in Korea. The observed temporal trend in PM 10 effects was similar to patterns of circulatory mortality, suggesting that the temporal heterogeneity in PM 10 effects might be due to systematic causes rather than random fluctuations.

Several studies report temporal, geographical, and intra-individual variation in sponge metabolite yields. However, the internal and/or external factors that regulate the metabolite production remain poorly understood. Dysidea avara is a demosponge that produces sesquiterpenoids (avarol and derivatives) with interesting medical properties, which has prompted addressed studies to obtain enough amounts of these metabolites for research on drug discovery. Within this framework, specimens of Dysidea avara from a population of the Northwest Mediterranean were sampled and their secondary metabolites quantified to assess their variability and the possible relationship with external (seasonality, interactions with neighbors) and internal (reproductive stages) factors. The results show a variation of the amount of both avarol and its monoacetate derivative with time, with no clear relationship with seawater temperature. A trade-off with sponge reproduction was not found either. However, our results showed for the first time that sponges are able to increase production or accumulation of secondary metabolites in their peripheral zone depending on the nature of their neighbors. This finding could explain part of the high variability in the amount of secondary metabolites usually found in chemical ecology studies on sponges and opens new biotechnological approaches to enhance the metabolite yield in sponge cultures. [ABSTRACT FROM AUTHOR]

Species composition and abundance of the phytoplankton community in Acapulco Bay, Mexico, were studied from May to December 2009. Samples were collected at 5 stations (4 coastal and one oceanic) at 3 depths (1, 5 and 10 m). Eighty-seven species were identified: 54 dinoflagellates, 32 diatoms and one silicoflagellate. The community was structured mainly by adiaphoric species, that is species adapted to both neritic and oceanic environments. Species abundance and composition varied significantly during the sampling period due to increased nutrient concentrations in the rainy season. Dinoflagellate species were more abundant during the dry season, and diatom species dominated numerically during the rainy season. [ABSTRACT FROM AUTHOR]

As aerosols in the air have a great influence on the health of residents of coal resource-based cities, these municipalities are confronting the dilemma of air pollution that is caused by the increase of suspended particles in the atmosphere and their development process. Aerosol optical thickness could be used to explore the aerosol temporal and spatial variations and to develop accurate prediction models, which is of great significance to the control of air pollution in coal resource-based cities. This paper explored the temporal spatial variation characteristics of aerosols in coal resource-based regions. A total of 11 typical coal-resource prefecture-level cities in the Shanxi Province were studied and inverted the aerosol optical thickness (AOT) among these cities based on MODIS (Moderate Resolution Imaging Spectroradiometer) data and analyzed the significant factors affecting AOT. Through inputting significant correlation factors as the input variables of NARX (nonlinear auto regressive models with exogenous inputs) neural network, the monthly average AOTs in the Shanxi Province were predicted between 2011 and 2019. The results showed that, in terms of time series, AOT increased from January to July and decreased from July to December, the maximum AOT was 0.66 in summer and the minimum was 0.2 in autumn, and it was related to the local monsoon, temperature, and humidity. While as far as the space alignment is concerned, the figure for AOT in Shanxi Province varied significantly. High AOT was mainly concentrated in the centre and south and low AOT was focused on the northwestern part. Among the positively correlated factors, the correlation coefficient of population density and temperature exceeded 0.8, which was highly positive, and among the negatively correlated factors, the correlation coefficient of NDVI exceeded -0.8, which was highly negative. After improving the model by adding the important factors that were mentioned before, the error between the predicted mean value and the actual mean value was no more than 0.06. Considering this charge, the NARX neural network with multiple inputs can contribute to better prediction results. [ABSTRACT FROM AUTHOR]