Summer Values Research Articles

Empirical analysis of the influence mechanism of vegetation and environment on negative air ion in warm temperate forest ecosystems

Air pollution presents a significant threat to public health in megacities globally. Negative air ions (NAI), often referred to as “air vitamins,” are recognized for their effectiveness in alleviating the harmful effects of air pollution. Forest ecosystems serve as natural generators of NAI, with both vegetation and environmental conditions playing critical roles in the formation and persistence of NAI. Gaining a comprehensive understanding of how forest ecosystems regulate NAI production is essential for leveraging their potential to enhance air quality. However, the intricate dynamics of forest ecosystems, along with seasonal fluctuations in vegetation and environmental factors, introduce uncertainties in NAI generation. This study utilized long-term observational data to explore the relationships between environmental variables, vegetation photosynthetic capacity (using solar-induced chlorophyll fluorescence, SIF), and NAI concentrations. By employing machine learning algorithms, we analyzed the spatiotemporal distribution of NAI, identifying the key contributing factors and their relative influence within forest ecosystems. The results revealed distinct seasonal variations in NAI levels, with higher values in summer and lower in winter. SIF and PM2.5 primarily influenced NAI through direct effects across seasons, whereas ambient temperature (TA), relative humidity, photosynthetically active radiation (PAR), and soil moisture predominantly impacted SIF on NAI through indirect effects in summer. TA was the primary influencing factor in spring and winter, contributing 28% and 25%, respectively, while PAR played a more significant role in summer and autumn, accounting for 37% and 27%. Vegetation had a greater impact on NAI levels during spring and summer, contributing 66% and 62%, whereas environmental factors dominated in autumn and winter, with contributions of 83% and 89%. This study offers both a theoretical foundation and technical guidance for enhancing the role of forest ecosystems in improving air quality and human living environments.

Characterization of drought propagation over the Tibetan Plateau

Study regionThis study was carried out on the Tibetan Plateau (TP), which contains multiple important ecosystems, is the source of many rivers in China, and is experiencing significant climate change. Study focusClarifying drought propagation characteristics is crucial for understanding the mechanism of drought development and benefiting drought mitigation and early warning schemes. However, there is currently a notable lack of research on droughts on the TP and drought propagation characteristics on the TP have yet to be investigated. In this study, we investigated drought propagation time, probability, threshold, and the climatic factors associated with drought development based on the copula probability model and correlation, Bayesian network, and attribution analyses, allowing us to fill current research gaps. New hydrological insights for the regionThe research framework proposed in this study effectively reflected the characteristics of drought propagation. Our results showed that seasonality and aridity controlled the propagation time from meteorological drought (MD) to agricultural drought (AD), i.e., the time was shortest in summer (2.311.0 months) and in the humid zone (2.37 months); the same pattern was found for the propagation of MD to hydrological drought (HD), with the propagation time being 2.33.0 months in summer and 2.36 months in humid zones. The propagation probability for both AD and HD generally increased synchronously with the severity of MD, and also exhibited seasonal patterns, with the highest probability values in summer (0.590.90 for AD and 0.510.82 for HD). The highest propagation thresholds were also found in summer (−1.68 to −1.09 for AD and −1.68 to −1.36 for HD). The trends of both propagation time and probability were significant, and the probability of HD exhibited significant downward trends (−0.074 to −0.030/decade) across the TP. Precipitation was the dominant factor controlling the development of drought in most cases; however, other climatic factors, such as maximum temperature, solar radiation, and specific humidity, contributed 14.0 %43.9 % of the variances of AD and HD.

Medium‐range predictability of temperature extremes and biases in Rossby‐wave amplitude

AbstractThis study investigates the medium‐range predictability of warm and cold extremes in the Northern Hemisphere and the role that upper‐tropospheric circulation biases play in this regard. Deterministic ERA5 reforecasts for the period 1979–2019 are evaluated based on the ERA5 reanalysis of the respective period, thus providing a large sample for verification and bias identification. The predictability of temperature extremes at 850 hPa is assessed based on the Gilbert Skill Score and other metrics and is shown to exhibit regional and seasonal variations. Summer is generally characterized by lower forecast skill scores than winter for both warm and cold extremes. Moreover, cold extremes in summer have slightly lower skill scores than warm extremes, while the opposite is true in winter. Biases in the frequency of temperature extremes are, to some extent, consistent with biases in mean temperature and indicate an underestimation in the total amount of extremes for much of the hemisphere in summer. Associated with the latter, biases also emerge in the standard deviation of the daily temperature distribution, with the summer values being largely underestimated over most of the hemisphere. The role of upper‐tropospheric circulation in these biases is then assessed by verifying the representation of Rossby‐wave packet (RWP) properties. It is found that the amplitude of RWPs is systematically underestimated in most of the hemisphere in summer, while it is overestimated in many parts of the midlatitudes in winter. Overall, the results suggest that the underestimation of RWP amplitude in summer hinders the medium‐range predictability of temperature extremes in the explored retrospective and operational forecasts. Although operational European Centre for Medium‐Range Weather Forecasts (ECMWF) forecasts gradually improve between 2013 and 2022 in terms of the 850‐hPa temperature and 300‐hPa RWP amplitude absolute errors, the aforementioned summer biases remain qualitatively similar.

Seasonal Changes in the Oxidative Potential of Urban Air Pollutants: The Influence of Emission Sources and Proton- and Ligand-Mediated Dissolution of Transition Metals.

The inhalation of fine particulate matter (PM2.5) is a major contributor to adverse health effects from air pollution worldwide. An important toxicity pathway is thought to follow oxidative stress from the formation of exogenous reactive oxygen species (ROS) in the body, a proxy of which is oxidative potential (OP). As redox-active transition metals and organic species are important drivers of OP in urban environments, we investigate how seasonal changes in emission sources, aerosol chemical composition, acidity, and metal dissolution influence OP dynamics. Using a kinetic model of the lung redox chemistry, we predicted ROS (O2 •-, H2O2, •OH) formation with input parameters comprising the ambient concentrations of PM2.5, water-soluble Fe and Cu, secondary organic matter, nitrogen dioxide, and ozone across two years and two urban sites in Canada. Particulate species were the largest contributors to ROS production. Soluble Fe and Cu had their highest and lowest values in summer and winter, and changes in Fe solubility were closely linked to seasonal variations in chemical aging, the acidity of aerosol, and organic ligand levels. The results indicate three conditions that influence OP across various seasons: (a) low aerosol pH and high organic ligand levels leading to the highest OP in summer, (b) opposite trends leading to the lowest OP in winter, and (c) intermediate conditions corresponding to moderate OP in spring and fall. This study highlights how atmospheric chemical aging modifies the oxidative burden of urban air pollutants, resulting in a seasonal cycle with a potential effect on population health.

Spatiotemporal patterns and drivers of extreme fire severity in Spain for the period 1985–2018

Extreme fire severity patterns driven by climate change have deep consequences on vegetation, subsequent fire regimes and have consequences on the effectiveness of extinction. In this work, we aimed to determine if extreme fire severity defined as the 90th percentile of RdNBR has changed in Spain in the last 3 decades, if extreme fire severity patterns have differed among the different vegetation types and what drivers have influenced extreme fire severity in both summer and non-summer fires. We have used perimeters of large wildfires (≥100 ha, n = 1719) from 1985 to 2018 in four pyroregions and the main dominant vegetation types. We have analyzed time series for each pyroregion and vegetation type to determine if there were significant trends and breakpoints in extreme fire severity. We have also analyzed the effects of drought, weather, topography and vegetation on extreme fire severity in seasonal wildfires.Extreme fire severity increased in summer fires from 1985 to 2018, especially in the East and North pyroregions, while the Southwest pyroregion reached highest values in summer. There has been an increase of severity in shrubland, mosaic vegetation and conifer forests in summer. Broadleaved forests had the lowest values of fire severity and did not show any trend in the period considered. The most important drivers of extreme fire severity are, in order of importance, pyroregion, elevation, slope, vapor pressure deficit (VPD) and vegetation type for summer fires, and VPD, vegetation types, pyroregion, windspeed and drought for non-summer fires. Global change is increasing climate-related events. Our results indicate that extreme fire severity in summer has been on the rise in recent decades in Spain, suggesting that, in a climate warming context, without strategic management of these increasingly flammable landscapes, further increases may be likely.

Varying photosynthetic quotients strongly influence net kelp primary production and seasonal differences increase under warming

Reliable net primary production (NPP) estimations of kelp forests are important to evaluate their C-fixation potential. Photosynthetic oxygen measurements can be converted to C-fixation using photosynthetic quotients (PQs). Although there is a known high variability in PQs, the extent and the consequences for NPP is understudied in kelp species. Thus, the present study aimed (i) to quantify the variability of PQs, (ii) to model NPP and (iii) to assess the impact of warming on both. The kelp, Laminaria hyperborea, was studied near the island of Helgoland (North Sea, Germany) along a depth gradient (2, 4, 6 m below mean low water spring tide) across all four seasons. Blade discs were cultivated during at least 6 days per season under simulated ambient photosynthetic photon flux density (PPFD) and temperature conditions and, in parallel, in a warming scenario (+ 4°C). PQs were calculated from parallel oxygen production and 14C-fixation measurements at saturating PPFD at the end of the incubation period. Seasonal PQs varied between 1.7 and 4.4, with highest values in summer due to increased oxygen production. The warming scenario stimulated C-fixation in most seasons, lowering the PQ in comparison to ambient temperature conditions, while collection depth had no significant effect on PQs. The seasonal PQs were used to model daily NPP rates for kelp standing stock at 4 m depth. These daily NPP rates were compared between temperature treatments and with daily NPP rates based on fixed PQs. The warming scenario had a stimulating effect on daily NPP rates in the high-light season spring. In the low-light season autumn, warming resulted in negative daily NPP rates, as the high respiration rates could not be compensated by gross photosynthesis. Overall, annual NPP rate under warming conditions (347 g C m–2 yr–1) was 14% higher than the annual NPP rate under ambient conditions (303 g C m–2 yr–1). Modelling daily NPP with fixed PQs, which neglects the seasonal variation of the PQs, led to a high overestimation of up to 255%. We, therefore, recommend modelling NPP rates not with a fixed PQ, but with seasonal PQs determined under different temperature scenarios in order to obtain reliable future predictions.

CHARACTERIZATION OF FINE CARBONACEOUS AEROSOLS FROM THE EASTERN MEDITERRANEAN: CONTRIBUTIONS OF FOSSIL AND NON-FOSSIL CARBON SOURCES

ABSTRACT In order to better characterise carbonaceous components in atmospheric aerosols and to assess the contributions of fossil carbon (FC) and non-fossil carbon (NFC) sources and their seasonality in the Eastern Mediterranean, we collected fine (PM1.3) aerosols at a remote marine background site, the Finokalia Research Station, Crete, Greece, over a period of one-year. PM1.3 samples were analysed for elemental carbon (EC), organic carbon (OC), water-soluble OC (WSOC), and stable carbon isotope ratio (δ13CTC) and radiocarbon content (14CTC) (pMC) of total carbon (TC). All the parameters, i.e., PM1.3, δ13CTC and 14CTC showed a clear temporal pattern with higher values in summer and lower values in autumn. The 14CTC ranged from 54.7 to 99.1 pMC with an average of 74.5 pMC during the entire year. The FC content in TC (FCTC) was found to be slightly lower in winter and almost stable in other seasons, whereas the NFC contents (NFCTC) showed a clear seasonality with the highest level in summer followed by spring and the lowest level in winter. Based on these results together with the seasonal distributions of organic tracers, we found that biomass burning (BB) and soil dust are two major sources of the fine aerosols in winter. Although biogenic emissions of VOCs followed by subsequent secondary oxidation processes are significant in summer followed by spring and autumn, pollen is a significant contributor to TC in spring. This study showed that emissions from fossil fuel combustion are significant (25.5%) but minor compared to NFC sources in the eastern Mediterranean.

Retrieval of total suspended matter concentration in the yellow river estuary offshore area based on QAA-RF model

ABSTRACT Total suspended matter is one of the crucial water quality parameters for both inland and marine environments, and a key role in evaluating the water quality of estuaries and offshore areas. Each year, the Yellow River carries a significant amount of sediment into the semi-enclosed Bohai Sea, results in a prolonged high concentration of total suspended matter in the offshore areas of the Yellow River Estuary. This study focuses on the offshore region of the Yellow River Estuary in China. Utilizing Sentinel-2 satellite imagery data from 2020 to 2023 and in-situ measured data from August 2020 to August 2022, to address the lack of physical mechanisms currently studied in machine learning retrieval methods, a model that integrates the physics-driven Quasi-Analytical Algorithm (QAA) and data-driven Random Forest (RF) is employed for the retrieval of total suspended matter concentration in the study area. The fused model (QAA-RF) is compared and analysed against regression models and standalone machine learning models. The results indicate that the accuracy of machine learning retrieval models is consistently higher than that regression models. The QAA-RF model demonstrates the highest accuracy (R 2 = 0.87, MAE = 5.01 mg L−1, RMSE = 6.39 mg L−1). Based on the QAA-RF model and the imagery data, monthly total suspended matter concentration is conducted in the study area. The retrieval results indicates that: (1) the total suspended matter concentrations is primarily concentrated in the near estuary region, with concentrations decreasing as distance from the estuary increases. (2) the total suspended matter concentration exhibits a distribution pattern with higher values in spring and winter, and lower values in summer and autumn. (3) the concentration of total suspended matter shows relatively small fluctuations at the annual scale from 2020 to 2023.

Spatiotemporal Variation and Influences of Acidification in the North Pacific, 1995–2019

The continuous rise in atmospheric CO2 levels has led to persistent ocean acidification, which negatively impacts marine environments crucial for marine life and alters the chemical composition of seawater. This phenomenon carries significant implications for human society. Utilizing surface seawater pH data from the North Pacific spanning 1995 to 2019, this study investigates the overall and localized spatiotemporal variations in pH within the region, as well as the factors influencing these variations. Additionally, it conducts a quantitative analysis of the different influencing factors. The findings reveal a consistent downward trend in surface seawater pH in the North Pacific, decreasing from 8.073 to 8.029, with notable seasonal variations. The highest pH values are recorded in winter, followed by spring, with lower values in autumn and summer. Spatially, the pH values are higher in the northwest and lower in the southeast, with the most pronounced acidification occurring in the central and western regions, while other areas exhibit more uniform acidification levels. Spatial correlation analysis indicates that surface seawater pH in the North Pacific generally shows a negative correlation with sea surface temperature (SST), salinity (SSS), and chlorophyll-a concentration (chl a) and a positive correlation with dissolved oxygen (DO). Among these factors, SST exerts the greatest influence on seawater pH, followed by DO and SSS. The degree of acidification varies across different regions, and the dominant influencing factors differ accordingly. In the equatorial central region (A), the primary factors are chl a and SST; in the eastern regions of China and Japan (B) and the western region of Canada (C), DO and SSS are the main controlling factors. An interaction analysis of each pair of dominant factors using the geodetector shows that their respective contributions to regions A, B, and C are 70%, 90%, and 50%, respectively. Understanding the primary factors driving acidification in different regions can aid in comprehending the biological and environmental impacts of acidification in those areas and provide valuable insights for mitigating marine acidification.

Assessing ecological status using phytoplankton functional groups in three urban rivers in Hainan Island, China.

The urban rivers, including Changwang, Meishe, and Wuyuan in Haikou City, Hainan Island, are vital water sources for agricultural production and support industrial and domestic activities. Despite the rivers experiencing anthropogenic impacts, limited studies have assessed their water quality. Accordingly, this study assessed the phytoplankton community structure, utilized the river phytoplankton assemblage index (Qr index) to evaluate the ecological status, and compared its performance with the comprehensive trophic level index (TLI). Sample collection and microscopy analysis was conducted seasonally in 2019. Two hundred ninety-eight phytoplankton species belonging to 8 phyla were identified, predominated by Chlorophyta, Bacillariophyta, and Cyanophyta. The phytoplankton biomass ranged from 0.04 to 34.98mg L-1, with averages of 3.06 ± 0.71, 5.16 ± 1.92, and 2.70 ± 0.76mg L-1 in Changwang, Meishe, and Wuyuan, respectively. The phytoplankton biomass varied seasonally, recording the highest and lowest values in summer and autumn, respectively. The phytoplankton species were classified into 26 functional groups, which exhibited spatial and seasonal differences in their biomass and composition. The redundancy analysis (RDA) revealed that NH3-N, TP, CODMn, Chl-a, salinity, and temperature were the main environmental factors influencing phytoplankton functional groups. The average Qr index values in Changwang, Meishe, and Wuyuan were 3.39 ± 0.61, 3.44 ± 0.51, and 3.22 ± 0.67, and all the rivers were rated "good" in status. Seasonally, the Qr index and TLI revealed that the rivers' ecological condition was better in autumn and winter compared to spring and summer. Generally, the Qr index performed better, indicating that parameters such as NH3-N, CODMn, TP, and Chl-a decreased with improving ecological conditions from "poor" to "excellent" status. In addition, the Qr index exhibited a significant negative relationship with TLI, suggesting that low Qr index values may indicate increased eutrophication or deteriorated water quality. Thus, the ecological condition of the urban rivers could be adequately assessed using the Qr index to guide their water quality monitoring and management.

4E Analysis of a new cogeneration system coupling heat pumps and PEMFC in summer and winter modes

In response to the ongoing optimization of energy systems and the promotion of clean energy, this paper introduces a new high-efficiency cogeneration system based on proton exchange membrane fuel cells (PEMFC). Named the Transcritical Combined Cooling Heating and Power with Subcooling Coupled ORC (CPTSO) system, it undergoes energy, exergy, economic, and environmental (4E) assessments to evaluate its performance in both summer and winter modes. This paper also analyzes the effects of key factors on the new system's performance. The results indicate that the new system performs more effectively overall and achieves faster cost recovery during winter operations. With varying degrees of subcooling (ΔTsubcooling), the system's average energy efficiency, fuel energy saving ratio (FESR), exergy efficiency, and pollutant reduction in winter are 60.97 %, 4.51 %, 17.16 %, and 33.35 % higher, respectively, than in summer. Changes in the main evaporation temperature (Te) result in winter improvements of 74.37 % in energy efficiency, 16.86 % in FESR, 17.6 % in exergy efficiency, and 45.5 % in pollutant reduction compared to summer. Similarly, adjustments to the outlet temperature of the gas cooler (Tg) lead to winter increases of 56.75 % in energy efficiency, 0.49 % in FESR, 17.1 % in exergy efficiency, and 29.3 % in pollutant reduction over summer values.

Effects of vegetation types on soil wetting pattern and preferential flow in arid mountainous areas of northwest China

Understanding the mechanisms governing the infiltration of precipitation into soil is crucial in eco-hydrological processes. However, the effect of vegetation types on the wetting front depth and velocity is poorly understood. Here, we analyzed 1234 infiltration events based on a large-scale long-term in-situ soil moisture monitoring network in arid mountainous area of northwest China. Our results show that the proportion of preferential flow was the largest in shrub (52.38 %), followed by alpine meadow (36.55 %), grassland (11.51 %), and barren (0.70 %). The wetting front velocity was consistent with the order of the proportion of preferential flow, with values of 11.42, 4.96, 2.32, and 1.16 cm/h, respectively. The mean velocity of preferential flow events was 2.05 times (0.06–71 times) higher in the shallow soil layer and 3.86 times (0.3–68 times) higher in the deep soil layer compared to matrix flow events. The wetting front depth was shallowest in alpine meadow (14.31 cm), followed by barren (15.70 cm), grassland (18.95 cm), and shrub (39.81 cm). Moreover, the wetting front depth and velocity reach their peak values in summer, primarily influenced by precipitation. Random Forests analysis results demonstrate that preferential flow is the primary factors influencing the profile wetting front depth, with control factors varying across different soil depths, soil water characteristic curve in shallow soil layers, and vegetation in deep soil layers, respectively. Meanwhile, soil organic carbon emerged as the most important factor impacting wetting front velocity. These findings contribute to a deeper understanding of infiltration processes in arid mountainous areas and offer a theoretical foundation for refining and enhancing mountain hydrological models.

Sclerochronology of the large scallops Gigantopecten latissimus and Pecten jacobaeus in a Pliocene warmer Mediterranean Sea

Here we apply a sclerochronological approach to reconstruct the life-history of two stenohaline bivalves of the family Pectinidae, Gigantopecten latissimus and Pecten jacobaeus from the Pliocene of Italy. The specimens come from the locality of Torrita di Siena (Siena-Radicofani Basin, Tuscany), dated to the late Zanclean-Piacenzian with nannoplankton biostratigraphy and Sr-isotope stratigraphy. After measuring the width of micro-growth increments and verifying that the shells were not diagenetically altered, we sampled them at high resolution for carbon and oxygen stable isotopes. δ13C and δ18O shell values allowed to distinguish between specimens that lived above or below the thermocline. Those influenced by surface waters indicate temperatures (for δ18Oseawater = 1.5‰) with winter minima of 16–18 °C and summer values up to 28–29 °C, close to present temperature conditions in the tropical west-African climate belt. In line with this, we found that the two species had similar seasonal growth patterns, with faster growth during colder months and summer slowdown, a typical adaptation of bivalves of tropical affinity suffering from summer temperature extremes. Despite this similar adaptation, G. latissimus, with large and heavy shells (length up to 30 cm) became extinct around 3.0 Ma, while the smaller P. jacobaeus survived Plio-Pleistocene cooling. Different growth rates between the two species and, therefore, different metabolic costs, might explain such differential response, together with differences in reproduction strategies. Habitat loss and fragmentation, due to the decrease of shelf margins and organogenic substrates caused by cooling and sea level fall, are abiotic factors that could have also contributed to the extinction of G. latissimus. P. jacobaeus adaptation to live across a larger bathymetric range, which indicates the ability to thrive in a wider range of temperatures, most likely played a role in its survival. Further studies, including more specimens across multiple localities, will help verifying these hypotheses.

Environmental controls on bioluminescent dinoflagellate density, in Laguna Grande, Fajardo, Puerto Rico

Introduction: Bio bays in Puerto Rico play an important socio-economic role and declines in dominant bioluminescent dinoflagellate Pyrodinium bahamense are concerning. Studies show erratic blooms with is weak correlation to in situ environmental factors. Our study examines shorter field and longer proxy records on dinoflagellate density at Laguna Grande de Fajardo (LGF). Objectives: To quantify temporal changes in dinoflagellate density in a long-term monitoring study, understand how the marine environment modulates those changes, and determine the wider impacts of a fluctuating climate and extreme events on proxies for dinoflagellate density. Methods: Bimonthly samples were collected from 2016 to 2021 at three sampling sites in LGF. Dinoflagellates density was estimated by Sedgewick Rafter counting cells. Environmental conditions were obtained from Rio Fajardo 5007100 station and NOAA buoy 41056. Marine climate and biotic proxies were obtained from remote sensing measurements. Kruskal Wallis, Spearman correlations and cross-correlations in the shorter field and longer proxy records were used to evaluate environmental controls on LGF dinoflagellate blooms. Results: Six years of field monitoring densities found a low period in 2016-2017, frequent and intense blooms in 2018-2021 punctuated by hurricanes. Generally low values were recorded in late winter in contrast with higher values in late summer (Aug-Nov). Light winds and mixed layer response to seasonal warming in the form of high tides and low salinity, were found to sustain dinoflagellate reproduction. Conclusions: Bioluminescent dinoflagellates are vital to coastal tourism and require resource management. LGF results show that: 1) dinoflagellate counts fluctuate widely, 2) fluorescing dinoflagellates are sensitive to environmental conditions because of limited seasonality and narrow physiological range, 3) hurricanes play a role by ‘raking and refreshing’ the coastal lagoon for subsequent biotic reproduction, and 4) intra-seasonal fluctuations of density and proxies relate to air-sea thermodynamic conditions, the salinity budget and sea level.

Performance Evaluation of Horizontal Flow Constructed Wetland for Removal of Pharmaceuticals from Synthetic Wastewater

The removal efficiency of pharmaceutical compounds in wastewater treatment can be significantly influenced by seasonal variations and the presence of vegetation. This study evaluates the removal efficiencies of five pharmaceutical compounds – Cefadroxil (CFL), Ciprofloxacin (CIP), Cefpodoxime (CFD), Atenolol (ATN) and Avil-25 (AVL) – in non-planted (CW2) and planted (CW1) constructed wetlands across various parameters including Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), Alkalinity, Nitrate, and Phosphate during winter and summer seasons. Results indicate that CW1 consistently outperforms CW2 in all parameters and seasons. For example, CW1 achieved 54.28% BOD removal for CFL in winter compared to CW2's 39.67%, with summer values reaching 79.6% and 69.7%, respectively. The superior performance of CW1 was also observed for COD and other parameters, with phosphate removal reaching 94% in summer. The results of HPLC analysis indicated that CW1 showed better removal efficiencies of Cefadroxil (56.94%), Ciprofloxacin (90%), and Avil-25 (99.7%) than CW2. Even though Cefpodoxime showed low removal efficiency in both systems, CW1 still performed slightly better (13.99% vs. 0.7%). Atenolol removal was particularly notable in CW1 (93.79%), significantly outperforming CW2. Hazard quotient assessments revealed lower risks associated with pharmaceutical residues in CW1. For example, Ciprofloxacin's hazard quotient was reduced from 16% in CW2 to 10% in CW1, underscoring the effectiveness of vegetation in mitigating environmental risks. Atenolol showed a significant hazard quotient reduction from 2% in CW2 to less than 0.5% in CW1, while Avil-25's hazard quotient was negligible in CW1 compared to 4% in CW2. It was also concluded that vegetation positively influenced the treatment efficacy of constructed wetlands for pharmaceuticals with reduced eco-toxicity and the associated risks.

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.

Stable isotopic characterization and sources of ammonium in wet deposition at the Danjiangkou Reservoir

Ammonium nitrogen (NHx) in atmospheric wet deposition is a primary external nitrogen source for reservoir-type water sources, and identifying its sources is crucial for controlling nitrogen pollution in water. This study aimed to examine the NHx characteristics and sources in wet deposition in the Xichuan reservoir area of the Danjiangkou Reservoir, the South-to-North Water Diversion Project (SNWDP) water source, from September 2019 to August 2020. Major inorganic nitrogen concentrations in precipitation and ammonia-nitrogen isotope (δ15N–NH4+) values were measured, and the sources were analyzed using the Bayesian mixing model. The results showed that NH4+ was the main inorganic nitrogen form in wet deposition, with a concentration ranged of 0.16–5.26 mg L−1. The δ15N–NH4+ values ranged from −14.7‰ to +6.3‰, with significant isotopic effects from agricultural sources and climatic conditions, showing higher values in summer and lower values in winter. The release of ammonia (NH3) from agricultural sources was the primary NHx source (58.0%–76.6%), with fertilizer application being the most significant contributor (32.1%–46.6%). Seasonally, the relative contribution of agricultural sources to NH4+ in wet deposition was higher in autumn and winter. Spatially, agricultural activities significantly impacted atmospheric nitrogen accumulation across the reservoir area. This study quantified NHx sources in wet deposition, providing isotopic evidence and scientific references for nitrogen control measures and atmospheric nitrogen cycling studies.

The regional characteristics of the occurrence rate of ionospheric anomalies in 2011–2018

This paper presents the regional characteristics of the occurrence rate of ionospheric anomalies of total electron content derived from global position system (GPS) observations. The area of concern spans 70° of longitude, from 70° E to 140° E, and 40° of latitude, from 15° N to 55° N. We introduced the 27 days moving window method to automatically detect anomalies that are caused by various sources. The spatial, diurnal, seasonal, and yearly distribution of the occurrence rate of extreme anomalies in 2011–2018 were provided. The spatial distribution of the occurrence rates of positive and negative anomalies had clear patterns in latitude and it did not change much in longitude at a certain local time over this area. The occurrence rates of positive and negative anomalies at the middle latitudes had significantly different diurnal variations from those at low latitudes. The maximum and minimum of the occurrence rates of positive anomalies occurred at about 17:00 local time (LT) and about 13:00 LT over the region from 36° N to 45° N. The maximum and minimum of the occurrence rates of negative anomalies in the same area occurred at about 07:00 LT and 18:00 LT over the region from 36° N to 45° N. There was no clear pattern in the seasonal variations of occurrence rates of positive and negative anomalies over [70° E-140° E, 15° N-55° N] in 2011–2018. The mean O/N2 had low values in summer and comparable high values in other seasons in 2015, and the O/N2 may not be the main reason for irregular seasonal characteristics of occurrence rate of anomalies. The occurrence rates of positive and negative anomaly in the year when the F10.7 index is relatively low, such as 2018, may be larger than the occurrence rates in the year with relatively large F10.7 index, such as 2014.

Difference of habitat suitability and the influencing variables between winter and summer of Procapra picticaudata in the Three-River-Source region, China.

Procapra picticaudata is an ungulate endemic to the Tibetan Plateau and is widely distributed in the Three-River-Source region. Predicting the seasonal variations in habitat suitability and understanding the effects of environmental variables on habitat use by this species will help formulate effective conservation strategies and clarify its niche characteristics. Based on point records of the occurrence collected during repeated field surveys in winter (January 2019) and summer (August 2019), we used MaxEnt model to predict the differences in habitat suitability and the distribution pattern of the P. picticaudata in the Three-River-Source region using eight preselected environmental variables. We further explored the influence of those variables on the P. picticaudata' distribution pattern using environmental response curves. The results showed that the average area under the receiving operator curve values in winter and summer was 0.901±0.023 and 0.882±0.024, respectively, with a good accuracy of fitness. The total area of suitable habitat for P. picticaudata in winter and summer was 6.83×104 and 9.78×104 km2, respectively. The area of suitable habitats in summer increased significantly compared with winter. There was a tendency for P. picticaudata to spread to the south of the Yangtze River Source Park and the Yellow River Source Park in summer. The spatial patterns of habitat suitability in both winter and summer took Three-River-Source National Park as the high-value center and decreased around it. The seasonal average temperature, altitude, population density, and slope were the main environmental variables affecting the distribution of P. picticaudata both in winter and summer. The higher temperatures in summer allowed the suitable P. picticaudata habitats to extend into areas above 5000 m in altitude, and to areas with slopes of less than 25°, compared with winter. The expansion of human activities in summer encroached on the suitable habitat of P. picticaudata.

Assessment of seasonal impacts on Water Quality in Yamuna river using Water Quality Index and Multivariate Statistical approaches

This study analyzed the water quality of the Yamuna river in Prayagraj across nine locations where the sampling was done upstream, downstream and middle stream from May 2019 to April 2020 using fourteen water quality parameters. Quarterly samples showed good Water Quality Index (WQI) values for summer (95.19), monsoon (77.28), and winter (90.77), but a decline in spring (102.11) due to religious activities was observed. Inductively coupled plasma mass spectroscopy suggested high concentration of Ca2+, Mg2+, K, and P in the river. Principal Component Analysis revealed 9 significant factors (eigen value >0.5) covering 25.13 – 93.89 % variance. Strong correlations included TDS-EC (0.853) and Ca2+ – Mg2+ (1.00) was observed. The correlation between water quality parameters generated by principal component analysis showed that the main parameters affecting the water quality vary in all the seasons. Based on the water quality indicators, anthropogenic activities are accountable to deteriorate the quality of river water. Therefore, the pollution status of the river need to be made publicly.