An assessment of atmospheric concentrations and spatiotemporal variation of BTEX and associated pollutants in India.

Benzene, toluene, ethylbenzene, and xylene (BTEX) pollution poses a serious threat to public health and the environment because of its respiratory and neurological effects, carcinogenic properties, and adverse effects on air quality. BTEX exposure is a matter of grave concern in India owing to the growing vehicular and development activities, necessitating the assessment of atmospheric concentrations and their spatial variation. This paper presents a comprehensive assessment of ambient concentrations and spatiotemporal variations of BTEX in India. The study investigates the correlation of BTEX with other criteria pollutants and meteorological parameters, aiming to identify interrelationships and diagnostic indicators for the source characterization of BTEX emissions. Additionally, the paper categorizes various regions in India according to the Air Quality Index (AQI) based on BTEX pollution levels. The results reveal that the northern zone of India exhibits the highest levels of BTEX pollution compared to central, eastern, and western regions. In contrast, the southern zone experiences the least pollution with BTEX. Seasonal analysis indicates that winter and post-monsoon periods, characterized by lower temperatures, are associated with higher BTEX levels due to the accumulation of localized emissions. When comparing the different zones in India, high traffic emissions and localized activities, such as solvent use and solvent evaporation, are found to be the primary sources of BTEX. The findings of the current study aid in source characterization and identification, and better understanding of the region's air quality problems, which helps in the development of focused BTEX pollution reduction and control strategies.

[Spatiotemporal Variation Characteristics of Ozone and Identification of Key Influencing Factors Based on Random Forest Model： A Case Study of Chuzhou City].

The cause of ozone pollution is a complex scientific problem. Studying the spatiotemporal variation characteristics of O3 at different time scales and analyzing the key influencing factors of O3 concentration is of great significance for the precise formulation of urban air pollution control measures and the improvement of urban air quality. Based on the analysis of the spatiotemporal variation characteristics of O3 concentration in Chuzhou City, we studied the 12 ozone-influencing factors of meteorology and pollutants at multiple time scales using Spearman correlation analysis and a random forest model. The results showed that： ① The O3 pollution level of Chuzhou City showed an aggravating trend, and the O3 concentration distribution showed a spatial pattern of "high in the southeast and low in the northwest." ② From February to May, SO2 concentration had a strong impact on the increase in O3 concentration. From June to September, PM2.5 and PM10 were significantly positively correlated with ozone and had a greater impact. ③ Relative humidity, temperature, and wind speed had a significant impact on O3, whereas barometric pressure and hourly rainfall had a weak impact. ④ The O3 pollution mechanism in Chuzhou City changed from "pollutant-controlled" to "meteorology-controlled." ⑤ Among meteorological and pollutant factors, the three influencing factors that had the greatest influence on O3 concentration were temperature, wind speed, and relative humidity, with PM10 concentration, PM2.5 concentration, and SO2 concentration also contributing. All of the above six influencing factors had a significant nonlinear relationship with the O3 concentration.

Evaluating background and local contributions and identifying traffic-related pollutant hotspots: insights from Google Air View mobile monitoring in Dublin, Ireland.

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022. One-second data were aggregated to 377,113 8 s road segments, and 8 s rolling medians were aggregated to hourly and daily levels for further analysis. We assessed the temporal variability of fine particulate matter (PM2.5), nitrogen monoxide (NO), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and carbon dioxide (CO2) concentrations at hyperlocal levels. The average daytime median concentrations of NO2 (28.4 ± 15.7 µg/m3) and PM2.5 (7.6 ± 4.7 µg/m3) exceeded the WHO twenty-four hours (24 h) Air Quality Guidelines in 49.4% and 9% of the 1-year sampling time, respectively. For the diurnal variation of measured pollutants, the morning (8:00) and early evening (18:00) showed higher concentrations for NO2 and PM2.5, mostly happening in the winter season, while the afternoon is the least polluted time except for O3. The low-percentile approach along with 1-h and daytime minima method allowed for decomposing pollutant time series into the background and local contributions. Background contributions for NO2 and PM2.5 changed along with the seasonal variation. Local contributions for PM2.5 changed slightly; however, NO2 showed significant diurnal and seasonal variability related to traffic emissions. Short-lived event enhancement (1 min to 1 h) accounts for 36.0-40.6% and 20.8-42.2% of the total concentration for NO2 and PM2.5. The highly polluted days account for 56.3% of total NO2, highlighting local traffic is the dominant contributor to short-term NO2 concentrations. The longer-lived events (> 8 h) enhancement accounts for 25% of the monitored concentrations. Additionally, conducting optimal hotspot analysis enables mapping the spatial distribution of "hot" spots for PM2.5 and NO2 on highly polluted days. Overall, this investigation suggests both background and local emissions contribute to PM2.5 and NO2 pollution in urban areas and emphasize the urgent need for mitigating NO2 from traffic pollution in Dublin.

Linking divergence in phenotypic selection on floral traits to divergence in local pollinator assemblages in a pollination-generalized plant.

Divergent patterns of phenotypic selection on floral traits can arise in response to interactions with functionally distinct pollinators. However, there are a limited number of studies that relate patterns of phenotypic selection on floral traits to variation in local pollinator assemblages in pollination-generalized plant species. We studied phenotypic selection on floral traits of Viscaria vulgaris, a plant that interacts with a broad range of diurnal and nocturnal pollinators, and related divergence in phenotypic selection on floral traits to the expected level of divergence in local pollinator assemblages. We detected phenotypic selection on floral traits involved in the attraction of pollinators and the mechanics of pollen removal and deposition, and demonstrated that floral traits are subject to spatiotemporal variation in the strength and direction of phenotypic selection. We revealed that diurnal and nocturnal pollinators, when considered in isolation, mediated divergent patterns of phenotypic selection on floral traits. Consistent with the Grant-Stebbins model, we observed that divergence in phenotypic selection on floral traits increased with the expected level of divergence in local pollinator assemblages. Thus, generalized plant-pollinator interactions can mediate phenotypic selection on floral traits and distinct local pollinator assemblages can generate a geographic mosaic of divergent patterns of phenotypic selection. We underscore that these outcomes are not exclusive to specialized plant-pollinator interactions and can emerge at a local geographic scale.

Assessment of the Restoration Potential of Forest Vegetation Coverage in the Alxa Desert Region of China.

To scientifically evaluate the sustainability of tree planting and afforestation in the Alxa Desert region, this study, grounded in the principles of water balance within the natural water cycle, employed multi-source remote sensing products and ground-based measurements to construct a quantitative response relationship model. This model links evapotranspiration (ET) with meteorological variables and the Enhanced Vegetation Index (EVI). Furthermore, the study estimated the recovery thresholds and potential of forest and grassland vegetation coverage in the Alxa Desert region under various precipitation scenarios. The findings reveal that ET exhibited an increasing trend in 84.17% of the Alxa Desert region, with a significant increase observed in 61.53% of the area, indicating positive outcomes from the implementation of the Three-North Shelterbelt Forest Program. Notably, however, ET in the southeastern plain region demonstrated a decreasing trend, which is strongly associated with human activities. The response relationship model demonstrated that linear relationship areas constituted 47.52%, while nonlinear relationship areas accounted for 45.51% of the total. The overall model exhibited an R2 value of 0.69, indicating a high level of predictive accuracy. Analysis of forest and grassland coverage revealed that, under wet year scenarios, the vegetation coverage showed a significant trend of recovery, with an average recovery threshold of (75.4 ± 12.5)% and an average recovery potential of (8.5 ± 3.6)%. It is noteworthy that the vegetation coverage in 31.25% of the area had already surpassed the recovery threshold. The outcomes of this study provide a theoretical foundation for the formulation of more scientifically rigorous ecological restoration strategies in the future.

Spatiotemporal variation of microplastics along the long-distance raw water pipeline.

Raw water pipelines are considered a significant pathway for human exposure to microplastics (MPs, <5 mm) in surface water. However, there is currently very limited information on the longitudinal distribution characteristics of microplastics in raw water pipelines. This study assessed the abundance and distribution characteristics of microplastics in surface water from two different water sources in Jiangsu Province during different seasons. The correlation between conventional water quality indicators and microplastics was also explored. Specifically, the longitudinal variation of microplastics in raw water pipelines was investigated. Results showed that microplastics were detected in both basins during different seasons. In Basin 1, the abundance of MPs ranged from 34 ± 1 to 58 ± 2 n/L in March and from 3 ± 1 to 6.7 ± 4 n/L in June. In Basin 2, the abundance ranged from 6.5 ± 1 to 14 ± 1 n/L in March and from 2 ± 1 to 7.7 ± 1 n/L in June. The abundance of microplastics showed a decreasing trend along the pipeline. Polymethyl methacrylate (PMMA) was the main polymer type detected in both basins. Polyethylene terephthalate (PE) and polyurethane (PU) showed higher removal rates in the pipeline due to their higher density. The predominant size ranges of microplastics in the raw water were 10-50 µm and 50-100 µm. Additionally, the average particle size of MPs increased with the transportation distance, likely due to microbial colonization. This study is the first comprehensive investigation of the distribution characteristics of microplastics in raw water pipeline systems. The removal of microplastics in raw water pipelines contributes significantly to the elimination of microplastics at the source. This research helps to fill the knowledge gap regarding the fate of microplastics in raw water pipeline systems.

Limited Impacts of Water Diversion on Micro-eukaryotic Community along the Eastern Route of China's South-to-North Water Diversion Project.

The Eastern Route of the South-to-North Water Diversion Project (ER-SNWDP) represents a crucial initiative aimed at alleviating water scarcity in China's northern region. Understanding the dynamics governing the composition and assembly processes of micro-eukaryotic communities within the canal during different water diversion periods holds paramount significance for the effective management of the ER-SNWDP. Our study systematically tracks the dynamics of the micro-eukaryotic community and its assembly processes along the 1045.4 km of canals and four impounded lakes, totaling 3455 km2, constituting the ER-SNWDP during a complete water diversion cycle, utilizing high-throughput sequencing, bioinformatics tools, and null modeling algorithms. The primary objectives of this study are to elucidate the spatial-temporal succession of micro-eukaryotic communities as the water diversion progresses, to delineate the relative importance of deterministic and stochastic processes in community assembly, and to identify the pivotal factors driving changes in micro-eukaryotic communities. Our findings indicate notable variations in the composition and diversity of micro-eukaryotic communities within the ER-SNWDP across different water diversion periods and geographic locations (P < 0.05). This variation is influenced by a confluence of temporal and environmental factors, with limited impacts from water diversion. In essence, the assembly of micro-eukaryotic communities within the ER-SNWDP primarily stemmed from heterogeneous selection driven by deterministic processes. Water diversion exhibited a tendency to decrease community beta diversity while augmenting the influence of stochastic processes in community assembly, albeit this effect attenuated over time. Furthermore, our analysis identified several pivotal environmental parameters, notably including nitrite-nitrogen, nitrate-nitrogen, orthophosphate, and water temperature, as exerting significant effects on micro-eukaryotic communities across different water diversion periods. Collectively, our study furnishes the inaugural comprehensive exploration of the dynamics, assembly processes, and influencing factors governing micro-eukaryotic communities within the ER-SNWDP, thus furnishing indispensable insights to inform the water quality management of this important project.

Spatial and temporal characteristic of PM2.5 and influence factors in the Yellow River Basin.

The Yellow River Basin has been instrumental in advancing ecological preservation and fostering national high-quality development. However, since the advent of China's reform and opening-up policies, the basin has faced severe environmental pollution issues. This study leverages remote sensing data from 1998 to 2019. As per the "Basin Scope and Its Historical Changes" published by the Yellow River Conservancy Commission of the Ministry of Water Resources, the Yellow River Basin is categorized into upstream, midstream, and downstream regions for analysis of their spatial and temporal distribution traits using spatial autocorrelation methods. Additionally, we employed probes to study the effects of 10 factors, including mean surface temperature and air pressure, on PM2.5. The study findings reveal that (1) the annual average concentration of PM2.5 in the Yellow River Basin exhibited a fluctuating trend from 1998 to 2019, initially increasing, then decreasing, followed by another increase before ultimately declining. (2) The air quality in the Yellow River Basin is relatively poor, making it challenging for large-scale areas with low PM2.5 levels to occur. (3) The PM2.5 concentration in the Yellow River Basin exhibits distinct high and low-value concentration areas indicative of air pollution. Low-value areas are predominantly found in the sparsely populated central and southwestern plateau regions of Inner Mongolia, characterized by a better ecological environment. In contrast, high-value areas are prevalent in the inland areas of Northwest China, with poorer natural conditions, as well as densely populated zones with high energy demand and a relatively developed economy. (4) The overall population density in the Yellow River Basin, as well as in the upstream, midstream, and downstream regions, serves as a primary driving factor. (5) The primary drivers in the middle reaches and the entire Yellow River Basin remain consistent, whereas those in the upper and lower reaches have shifted. In the upstream, air pressure emerges as a primary driver of PM2.5, while in the downstream, NDVI and precipitation become the main influencing factors.

Both nutrients and macrophytes regulate organic carbon burial: Insights from high-resolution spatiotemporal records of a large shallow lake (Baiyangdian) in eastern China.

Both ecological regime shifts and carbon cycling in lakes have been the subject of global debates in recent years. However, the direct linkage between them is poorly understood. Lake Baiyangdian, a representative large shallow lake with the coexistence of a macrophyte-dominated area (MDA) and an algae-dominated area (ADA) in eastern China, allowing better understanding of the relationship between regime shifts and organic carbon (OC) burial in lakes. On the basis of Bayesian isotopic mixing modelling of C/N ratios and δ13C values, the sediment OC is primarily of autochthonous origin. The mean OC burial rate (OCBR) was 39 g C m-2 yr-1 before eutrophication occurred in 1990 and increased approximately 2.7-fold to 106 g C m-2 yr-1 after eutrophication. Partial least squares path modelling revealed that this change can be largely attributed to enhanced primary productivity and rapid burial as a result of intensified human perturbation. In terms of spatial patterns, the OCBR was greater in the MDA than in the ADA, which may be related to the different burial and mineralization processes of debris from macrophytes and algae. It then deduced that a decrease in the OCBR and an increase in the mineralization rate might have occurred after a shift from a macrophyte-dominated state to an algae-dominated state. Our findings highlight that eutrophication generally increases OC burial by enhancing lake primary productivity. However, once nutrient levels reach a critical range, lake ecosystems may shift from a macrophyte-dominated state to an algae-dominated state, which can lead to a significant reduction in the carbon burial capacity of lakes. Therefore, more attention should be given to avoiding shifts in eutrophic lakes, as such shifts can alter carbon cycling.

[Antibiotic Pollution and Its Effects on the Spatiotemporal Variation in Microbial Community Structure and Functional Genes in Sediment of Baiyangdian Lake].

Microbial communities play an important role in water quality regulation and biogeochemical cycles in lakes, and their community structure and function are affected by environmental factors. Therein, antibiotics affect the abundance, diversity, composition, and function of microbial communities. In this study, Baiyangdian Lake was selected as the study area. Sediment samples of 16 sites were collected in August 2018 and April 2019, respectively. Ultra-high performance liquid chromatography-mass spectrometry （HPLC-MS/MS） was used to determine the content of typical antibiotics-quinolones （QNs） in sediment. Through high-throughput sequencing technology, the structure and function of microbial communities was analyzed in the sediments to explore the spatiotemporal variation. Thereinto, redundancy analysis （RDA） was used to identify the key influencing factors of spatiotemporal variation of microbial communities. The results showed that： ① From August to April, the average ω（QNs） showed an increasing trend, and its mean value changed from 3.91 ng·g-1 to 6.34 ng·g-1, with significant seasonal differences in oxolinic acid （OXO） and total QNs content （P < 0.05）. ② In terms of temporal variation, the dominant bacteria were Proteobacteria and Chloroflexi. The relative abundance of Proteobacteria showed a decreasing trend, whereas Chloroflexi showed an increasing trend； at the genus level, the dominant bacteria genera in August were norank_ f__Anaerolineaceae and Thiobacilus, and the dominant bacteria genera in April were Acinetobacter and norank_ f_Anaerolineaceae, and the dominant bacteria genera had significant seasonal differences （P < 0.05）. ③ In terms of temporal variation, the index of Simpson, Chao, Ace, and OTU number all showed an increasing trend, and the seasonal differences were significant （P < 0.05）. ④ In terms of spatial variation, there were no significant spatial differences among functional genes of COG. In terms of temporal variation, there were significant seasonal differences in functional genes of energy production and conversion, carbohydrate transport and metabolism, transcription, cell wall/membrane/envelope biogenesis, and signal transduction mechanisms （P < 0.01 and P < 0.05）. ⑤ Microbial community structure and functional genes were significantly correlated with QNs （P < 0.01 and P < 0.05）, and QNs were the main influencing factors. Therefore, QNs were the main factor affecting the changes in microbial community structure and functional genes in sediments of Baiyangdian Lake. Thus, comprehensive control of antibiotic pollution in sediments should be further strengthened.

Spatiotemporal variations of fossil fuel CO2 emissions in China: A sectoral allocation approach based on multi-source data.

Fossil fuel (FF) CO2 emissions account for the largest portion of human-related CO2 emissions. It is essential to accurately understand the spatial distribution of high-resolution FFCO2 emissions to formulate different carbon emission reduction policies in different regions. Therefore, a sectoral allocation approach was proposed to estimate FFCO2 emissions in China from 2000 to 2021 based on multi-source data. Furthermore, the spatiotemporal characteristics of FFCO2 emissions in different sectors were analyzed at different scales, and the spatial correlation of FFCO2 emissions in the service sector and industrial sector was also evaluated through Moran's index. The results showed that the mean R2 value of the sectoral allocation approach (0.89) exceeds that of the approach using only nighttime light (0.72). Moreover, the calculated results were utilized to analyze the Spatiotemporal variation of FFCO2 emissions. The analysis revealed that China's FFCO2 emissions increased from 3173 Mt in 2000-10662 Mt in 2021. The high emissions of FFCO2 mainly come from the industrial sectors in North China and Central China, as well as the service sectors in the eastern coastal cities and other provincial capital cities. The spatial dependence of FFCO2 emissions in the industrial sector was stronger than that in the service sector, but the spatial dependence of FFCO2 emissions in the service sector showed an increasing trend from 2000 to 2021. These results have important references and implications for region-specific carbon emission reduction policies.

[Analysis of Spatiotemporal Variation and Driving Factors of Water Quality in the Xiangjiang River Basin from 1990 to 2016].

In order to explore the spatiotemporal variation characteristics and driving mechanism of water quality in the Xiangjiang River Basin, the data of 16 water quality parameters at 113 stations over 26 years from 1990 to 2016 in the Xiangjiang River Basin were collected for synthetically assessing the water quality and identifying its main pollutants through the water quality index and other methods. The causal mechanism of water quality, especially the driving effect of water level and land use pattern, was analyzed. The results showed that： ① The overall water quality grade of the Xiangjiang River Basin during the study period was "good." However, the water quality deteriorated first （from 1990 to 2003） and then improved （from 2004 to 2016）. The season variation in water quality was not obvious, but the water quality fluctuation of the wet season was larger. The water pollution load of the main stream decreased successively from the middle reaches, downstream reaches, and upstream reaches. The upstream tributaries had the best water quality, whereas areas with poor water quality were mainly distributed at the mouth of the middle and downstream tributaries, especially in areas where multiple tributaries converged. ② Toxic heavy metals had the characteristics of toxicity, persistence, and bioaccumulation. If they exceeded a certain concentration in water, they were difficult to purify, posing great harm to the natural environment and human health. The toxic metal index （CI1） was the leading factor affecting water quality, in which Hg and Cd were the main parameters affecting the overall water quality of the Xiangjiang River Basin. ③ The water level had a positive impact on the water quality of the Xiangjiang River by diluting environmental parameters. Land type had little effect on heavy metal concentration, whereas forest land could improve water quality. Grassland had a negative correlation with permanganate index over a large scale range （≥ 5 km）. The increase in water bodies, arable land, and impermeable surface areas within the watershed increased the probability of high fecal coliform concentration in the water body. ④ With the increase in buffer distance, the water quality explained by the land use pattern increased. On the scale of 10 km buffer zone in the riparian zone, the explanation degree by land use pattern on water quality was the highest, which was an effective scale for water quality control of the Xiangjiang River. This research showed that the driving factors of heavy metal pollution and other pollution were different, but their regional differences were all obvious in the Xiangjiang River Basin. Therefore, pollution control should be classified and taken according to local conditions.

Occurrence and potential hazard posed by pharmaceutically active compounds in coastal waters in Cape Town, South Africa.

The occurrence of 58 pharmaceutically active compounds (PhACs) in surface water at 28 coastal and five river sites, and in two stormwater flows in Cape Town, South Africa, was investigated in winter and summer. After accounting for quality assurance and control data, 33 PhACs were considered in detail. In winter, 25 PhACs were found at one or more sites and 27 in summer. Salicylic acid was the most widespread PhAC in each season. At least one PhAC was found at each site in each survey. The largest number found at a site was 22 at Lifebox23 Beach in winter and 23 at Macassar Beach and in the Black and Diep Rivers in summer. These sites are strongly directly or indirectly affected by wastewater treatment plant discharges. The range in ΣPhAC concentrations was 41 ng L-1 to 9.3 µg L-1 in winter and 109 ng L-1 to 18.9 µg L-1 in summer. The hazard posed by PhACs was estimated using Predicted No Effect Concentrations (PNEC) from several sources. Hazard Quotients (HQs) for numerous PhACs were >1, and for several even >10, including azithromycin, cimetidine, clarithromycin, erythromycin, and ibuprofen. The highest hazards were at coastal sites strongly indirectly affected by wastewater treatment plant discharges. Azithromycin, trimethoprim, and sulfamethoxazole at some sites may have promoted antibiotic resistance in bacteria, while irbesartan at some sites might have posed a hazard to fish according to the fish plasma model. The concentrations of several PhACs at some coastal sites are higher than concentrations reported in estuarine, coastal, and marine waters in other parts of the world.

[Spatiotemporal variation and driving factors of vegetation coverage in Shanxi Province, China]. / å±±è¥¿çœæ¤è¢«è¦†ç›–åº¦çš„æ—¶ç©ºå˜åŒ–åŠé©±åŠ¨å› å­.

Understanding the spatiotemporal variations and driving factors of regional vegetation coverage is crucial for developing scientific plans for ecological environment protection and maintaining regional ecological balance. Based on the Google Earth Engine (GEE) platform and using Landsat Collection 2 data, we investigated the spatiotemporal variation and driving factors of vegetation coverage in Shanxi Province, China, from 1990 to 2020, by employing methods such as pixel-based binary model, trend analysis, zonal statistics, and geodetector. The results showed that vegetation coverage in Shanxi Province showed a fluctuating upward trend from 1990 to 2020. Vegetation coverage in 44.4% of this region had been significantly improved, and the area with significant degradation accounted for 7.4%. Vegetation coverage in Shanxi Province was positively correlated with elevation, slope, and mountain terrain relief. The area proportion of vegetation coverage growth was the highest in the plateau and hilly regions. Factor detection results showed that land use type, landform type, annual average precipitation, and soil type were the main influencing factors of the spatial differentiation of vegetation coverage in Shanxi Province. Results of the interaction detection showed that the interaction between driving factors all showed enhancement. The interaction between natural factors showed a downward trend, while the interaction results of social factors showed an upward trend, reflecting that the impacts of human activities on vegetation coverage in Shanxi Province were gradually increasing.

Analysis of the temporal and spatial evolution of turbidity in Tonle Sap Lake and its influencing factors.

Turbidity is a crucial indicator of water quality. The European Commission's Copernicus Land Monitoring Service Platform provides free turbidity data for large lakes to monitor the global water quality of lakes. However, the data were missing from April 2012 to April 2016, severely limiting long-term analysis. Based on MODIS and turbidity data, Random Forest and XGBoost models are used to invert Tonle Sap Lake's turbidity. Random Forest outperformed the XGBoost model. Based on Random Forest model, missing data were filled in to construct long-term series data of Tonle Sap Lake turbidity (2004-2021). Trend, persistence and correlation analyses were conducted to reveal spatiotemporal characteristics and driving mechanism of turbidity. The results showed that: (1) spatially, the average annual, monthly, and seasonal turbidity was higher in the north but lower in the south, with regions of higher turbidity exhibiting more significant changes; (2) temporally, the annual turbidity mean was 53.99 NTU and showed an increasing trend. Monthly, turbidity values were higher from March to August and lower from September to February, with the highest and lowest recorded in June and November at 110.06 and 5.82 NTU, respectively. Seasonally, turbidity was higher in spring and summer compared to autumn and winter, with mean turbidity values of 84.16, 93.47, 15.33 and 23.21 NTU, respectively; (3) In terms of sustainability, the Hurst exponent for annual turbidity was 0.23, indicating a reverse trend in the near future; (4) Dam construction's impact on turbidity was not significant. Compared with natural factors (permanent wetlands, grasslands, lake surface water temperature, and remote sensing ecological index), human activities (barren, urban and built-up lands, croplands and population density) had a more significant impact on turbidity. Turbidity was highly correlated with croplands (r = 0.76), followed by population density (r = 0.71), and urban and built-up lands (r = 0.69).

Spatiotemporal Dynamics of COVID-19 Pandemic City Lockdown: Insights From Nighttime Light Remote Sensing.

The global COVID-19 outbreak severely hampered the growth of the global economy, prompting the implementation of the strictest prevention policies in China. Establishing a significant relationship between changes in nighttime light and COVID-19 lockdowns from a geospatial perspective is essential. In light of nighttime light remote sensing, we evaluated the spatiotemporal dynamic effects of COVID-19 city lockdowns on human activity intensity in the Zhengzhou region. Prior to the COVID-19 outbreak, nighttime light in the Zhengzhou region maintained a significant growth trend, even under regular control measures. However, following the October 2022 COVID-19 lockdown, nighttime light experienced a substantial decrease. In the central area of Zhengzhou, nighttime light decreased by at least 18% compared to pre-lockdown levels, while in the sub-center, the decrease was around 14%. The areas where nighttime light decreased the most in the central region were primarily within a 15 km radius, while in the sub-center, the decrease was concentrated within a 5 km radius. These changes in both statistical data and nighttime light underscored the significant impact of the COVID-19 lockdown on economic activities in the Zhengzhou region.

Spatiotemporal distribution patterns and coupling effects of aquatic environmental factors in the dry-wet season over a decade from the Beibu Gulf, South China Sea.

Since the 21st century, the Beibu Gulf area has been affected by increasing anthropogenic activities, which makes the coastal aquatic ecosystem extremely concerning. However, the comprehensive exploration and analysis of the long-term scale behavior change characteristics of various water quality environment factors is still limited. Through comprehensively detecting coastal surface water environmental behavior information from 33 locations in the Beibu Gulf from 2005 to 2015, we revealed and quantified mutual response characteristics and patterns of various environmental indicators. The main environmental pollution indicators (e.g., COD, NH4+, NO3-, and DIP) showed a gradual decrease in concentration from the coast to the offshore sea area, and significantly increases during the wet season. The semi-enclosed Maowei Sea exhibited the most prominent performance with significant differences compared to other regions in Beibu Gulf. The average Chlorophyll-a (Chla) content in the coastal area of the Beibu Gulf during the wet season was more than twice that of the dry season, yet the interaction pattern between Chla and environmental factors in the two seasons was opposite to its concentration behavior, accompanied by a closely significant relationship with thermohaline structure and the input of nitrogen and phosphorous nutrients. The multivariate statistical analysis results of total nutrient dynamics suggested that the Beibu Gulf was clearly divided into different regions in both dry and wet season clusters. The present study can provide a comprehensive perspective for the spatial and temporal migration patterns and transformation laws of coastal water environmental factor, which should contribute to improve the prevention countermeasure of nutrient pollution in coastal environment.

Spatiotemporal patterns and deposition of organophosphate esters (OPEs) in air, foliage and litter in a subtropical forest of South China.

Recent studies revealed the un-negligible impact of airborne organophosphate esters (OPEs) on phosphorus (P)-limited ecosystems. Subtropical forests, the global prevalence P-limited ecosystems, contain canopy structures that can effectively sequester OPEs from the atmosphere. However, little is known about the behavior and fate of OPEs in subtropical forest ecosystem, and the impact on the P cycling in this ecosystem. OPE concentrations in the understory air (at two heights), foliage, and litterfall were investigated in a subtropical forest in southern China. The median ∑OPE concentrations were 3149 and 2489 pg/m3 in the upper and bottom air, respectively. Foliage exhibited higher ∑OPE concentrations (median = 386 ng/g dry weight (dw)) compared to litter (median = 267 ng/g dw). The air OPE concentrations were ordered by broadleaved forest > mixed forest > coniferous forest, which corresponds to the results of canopy coverage or leaf area index. The spatial variation of OPEs in foliage and litter was likely caused by the leaf surface functional traits. Higher OPE concentrations were found in the wet season for understory air while in the dry season for foliage and litter, which were attributed to the changes in emission sources and meteorological conditions, respectively. The inverse temporal variation suggests the un-equilibrium partitioning of OPEs between leaf and air. The OPE concentrations during the litter-incubation presented similar temporal trends with those in foliage and litter, indicating the strong interaction of OPEs between the litter layer and the near-soil air, and the efficient buffer of litter layer played in the OPEs partitioning between soil and air. The median OPEs-associated P deposition fluxes through litterfall were 270, 186, and 249 µg P/m2·yr in the broadleaved, mixed, and coniferous forests, respectively. Although the fluxes accounted for approximately 0.2% of the total atmospheric P deposition, their significance to this P-limited ecosystem may not be negligible.

Ecological and anthropogenic drivers of waterfowl productivity are synchronous across species, space, and time.

Knowledge of interspecific and spatiotemporal variation in demography-environment relationships is key for understanding the population dynamics of sympatric species and developing multispecies conservation strategies. We used hierarchical random-effects models to examine interspecific and spatial variation in annual productivity in six migratory ducks (i.e., American wigeon [Mareca americana], blue-winged teal [Spatula discors], gadwall [Mareca strepera], green-winged teal [Anas crecca], mallard [Anas platyrhynchos] and northern pintail [Anas acuta]) across six distinct ecostrata in the Prairie Pothole Region of North America. We tested whether breeding habitat conditions (seasonal pond counts, agricultural intensification, and grassland acreage) or cross-seasonal effects (indexed by flooded rice acreage in primary wintering areas) better explained variation in the proportion of juveniles captured during late summer banding. The proportion of juveniles (i.e., productivity) was highly variable within species and ecostrata throughout 1961-2019 and generally declined through time in blue-winged teal, gadwall, mallard, pintail, and wigeon, but there was no support for a trend in green-winged teal. Productivity in Canadian ecostrata declined with increasing agricultural intensification and increased with increasing pond counts. We also found a strong cross-seasonal effect, whereby more flooded rice hectares during winter resulted in higher subsequent productivity. Our results suggest highly consistent environmental and anthropogenic effects on waterfowl productivity across species and space. Our study advances our understanding of current year and cross-seasonal effects on duck productivity across a suite of species and at finer spatial scales, which could help managers better target working-lands conservation programs on both breeding and wintering areas. We encourage other researchers to evaluate environmental drivers of population dynamics among species in a single modeling framework for a deeper understanding of whether conservation plans should be generalized or customized given limited financial resources.

Dynamics of antibiotic resistance genes in the sediments of a water-diversion lake and its human exposure risk behaviour.

The dynamics and exposure risk behaviours of antibiotic resistance genes (ARGs) in the sediments of water-diversion lakes remain poorly understood. In this study, spatiotemporal investigations of ARG profiles in sediments targeting non-water (NWDP) and water diversion periods (WDP) were conducted in Luoma Lake, a typical water-diversion lake, and an innovative dynamics-based risk assessment framework was constructed to evaluate ARG exposure risks to local residents. ARGs in sediments were significantly more abundant in the WDP than in the NWDP, but there was no significant variation in their spatial distribution in either period. Moreover, the pattern of ARG dissemination in sediments was unchanged between the WDP and NWDP, with horizontal gene transfer (HGT) and vertical gene transfer (VGT) contributing to ARG dissemination in both periods. However, water diversion altered the pattern in lake water, with HGT and VGT in the NWDP but only HGT in the WDP, which were critical pathways for the dissemination of ARGs. The significantly lower ARG sediment-water partition coefficient in the WDP indicated that water diversion could shift the fate of ARGs and facilitate their aqueous partitioning. Risk assessment showed that all age groups faced a higher human exposure risk of ARGs (HERA) in the WDP than in the NWDP, with the 45-59 age group having the highest risk. Furthermore, HERA increased overall with the bacterial carrying capacity in the local environment and peaked when the carrying capacity reached three (NWDP) or four (WDP) orders of magnitude higher than the observed bacterial population. HGT and VGT promoted, whereas ODF covering gene mutation and loss mainly reduced HERA in the lake. As the carrying capacity increased, the relative contribution of ODF to HERA remained relatively stable, whereas the dominant mechanism of HERA development shifted from HGT to VGT.