Gaseous air pollutants emitted from anthropogenic sources are diverse and form secondary products through photochemical reactions, complicating the regulatory analysis of anthropogenic emissions in the atmosphere. Here, we used an environmental chassis dynamometer and a photochemical smog chamber to conduct a parameter sensitivity experiment to investigate the formation of secondary products from a direct-injection gasoline passenger car. To simulate the mitigation of ammonia (NH3) emissions from gasoline vehicle exhausts assuming future emission controls and to allow photochemical oxidation and aging of the vehicle exhaust, NH3 was selectively removed by a series of five denuders installed between the vehicle and the photochemical smog chamber. Overall, there were no differences in the formation of secondary organic aerosols and ozone with or without NH3 mitigation. However, the secondary particle formation potential of ammonium nitrate (NH4NO3) was significantly reduced with NH3 mitigation. In addition, NH3 mitigation resulted in increased particle phase acidity due to HNO3 in the gas phase not being neutralized by NH3 and condensing onto the liquid particle phase, indicating a potentially important secondary effect associated with NH3 mitigation. The present study provides new insights into the effects of NH3 mitigation on secondary emissions from gasoline vehicle exhaust and the experimental approach.

A method is proposed for analyzing the tremor of the earth's surface, measured by GPS, in order to highlight prognostic effects. The method is applied to analysis of daily time series of vertical displacements in Japan. The network of 1047 stations is divided into 15 clusters. The Huang Empirical Mode Decomposition (EMD) is applied to the time series of principal components from clusters with subsequent calculation of instantaneous amplitudes using the Hilbert transform. To ensure the stability of estimates of the waveforms of the EMD decomposition, 1000 independent additive realizations of white noise of limited amplitude were averaged before the Hilbert transform. Using a parametric model of the intensities of point processes, we analyze the connections between the instants of sequences of times of the largest local maxima of instantaneous amplitudes averaged over the number of clusters and the times of earthquakes in the vicinity of the Japan with minimum magnitude thresholds of 5.5 for the time interval 2012-2023. It is shown that part of the intensity of the sequence of times of seismic events, due to the influence of the times of the most expressive local extrema of instantaneous amplitudes, significantly exceeds the reverse influence.

Warsaw is among European cities with the worst atmospheric air quality, mainly due to very high pollution emitted by the residential sector and road traffic. This results in high concentrations of particulate matter and nitrogen oxides, often exceeding WHO standards. The paper discusses the current and expected effects of actions taken by the Warsaw authorities, to significantly improve air quality in the city. The Clean Air Program currently implemented mainly involves the reduction, and ultimately the total elimination, of coal combustion in all heat sources of the municipal sector, which is identified in numerous publications as the main source of air quality degradation in cities. The program's goal, which timeframe covers the years 2018-2029, is a definite reduction in particulate pollution. The second part of the remedial activities, covering the years 2024-2034, mainly concerns the reduction of nitrogen oxide pollution, the main source of which is urban road traffic. In the latter case, the expected effects of introducing Low-Emission Zone (launched July 2024) in the city center are considered. According to the project, the zone's implementation will consist of five two-year stages, in which the car emission limits will gradually tighten. The paper compares the effectiveness of two being considered versions, differing in size zones.

Concern over microplastics (MPs) in the environment is rising. Microplastics are generally known to exist in aquatic settings, but less is known about their occurrence in soil ecosystems. When plastic waste builds up in agricultural areas, it can have a negative impact on the environment and food sources, as well as have an indirect effect on all trophic levels of the food chain. This paper addresses the relationship between microplastics and the management of plastic waste, which contributes to their accumulation, and it describes the sources and primarily the movement processes of microplastics in agricultural soils as a result of natural events. Evaluating the impact of weather on coastal microplastic contamination is critical, as extreme weather events have become more frequent in recent years. This study sheds light on how weather patterns affect the dispersion of plastic waste in terrestrial habitats, including the impacts of seasonality and extreme weather. According to our data, typhoons, monsoons, rainfall, and floods all contribute significantly more microplastics to the surface sediment through surface runoff and wind transport, particle redistribution caused by agitated waves, and fragmentation under intense abrasion forces. Severe weather conditions have the potential to disperse larger and more varied kinds of microplastics.

A composite is a material formed from the combination of two or more constituent materials through a non-homogeneous mixture. This research aims to determine the effect of volume fraction and fiber orientation angle of the hybrid polyester-ulin wood powder (Eusideroxylon zwageri)-wire mesh composite on bending strength. The bending test was conducted using ASTM D-790 standard with a three-point bending test method. The composite was made using the hand lay-up method with various compositions of particles and polyester. The results showed that the composition with less ulin wood powder and finer mesh size with a 45° wire mesh angle orientation had the highest bending strength and high deformation capability. The addition of wire mesh did not significantly increase the bending strength but could reduce the effect of decreased deformation capability.

Seedling establishment is often a critical bottleneck to revegetation of mine tailings and similar substrates with a low capacity to retain water and plant nutrients. Biochar and deactivated yeast are potential sustainable, low-cost materials with high nutrient- and water-holding capacity that could be used in this context as seed coatings to aid in seedling establishment on challenging sub-strates. We conducted a greenhouse study to assess the effectiveness of biochar and deactivated yeast, applied alone in a factorial combination, as seed coatings, on the germination, establish-ment, and early growth of white clover (Trifolium repens) and purple prairie clover (Dalea pur-purea). Coated seeds were applied to a mine tailing, a coarse granitic sand, and potting soil mix substates; seedling establishment and growth were monitored over 75 days. Results indicate strong interactive effects of seed coatings with species and substrate. Biochar coatings enhanced seedling establishment of Trifolium, with biochar or biochar plus yeast coatings giving the best results. In some cases, these effects persisted throughout the experiment: biochar coatings resulted in a ~5-fold increase in Trifolium biomass at harvest for plants in the potting soil mix but had neutral effects on sand or tailings. Biochar seed coatings also enhanced Dalea germination in some cases, but benefits did not persist. Our results indicate that biochar-based seed coatings can have lasting effects on plant growth well beyond germination, but also emphasize highly spe-cies-specific responses that highlight the need for further study of broader patterns and mecha-nisms.

The Arabian Desert is characterised by very low rainfall and high evaporation, yet on its northeastern edge in central Iraq are 210 springs along the Abu Jir lineament, which represents the western depositional margin of a foreland basin infilled by the floodplain sediments of the Tigris and Euphrates Rivers; there is little evidence of faulting. The springs discharge from gently east-dipping Paleocene-Eocene limestones, either where groundwater flowpaths intersect the ground surface or where groundwater flow is forced to the surface by confining aquitards. Calculated annual recharge to the aquifer system across the Arabian Desert plateau (130-500 million m3) is enough to sustain the Abu Jir springs provided groundwater extraction is not excessive. The hydrochemistry of the springs is determined by evaporation, rainfall composition (high SO4 concentrations are due to dissolution of wind-blown gypsum in the rainfall), and plant uptake of Ca and K (despite the sparse vegetation). Limestone dissolution has relatively little impact; many of the springs are undersaturated with respect to calcite and lack tufa/travertine deposits. The springs at Hit-Kubaysa contain tar and high levels of H2S that probably seeped upwards along subvertical faults from underlying oil reservoirs; the presence of hydrocarbons makes the water reducing and converts the dissolved SO4 to H2S.

Monitoring and protecting flowing watercourses is a complex and challenging task that requires the collaboration and coordination of various stakeholders such as governments, industries, farmers, consumers and environmental groups. The study of the dynamics of the concentration of polluting factors and especially the concentrations of heavy metals and highlighting a seasonal variation is a necessary element from this point of view. In this article, we present the results of our analyzes carried out in two measurement campaigns executed in 10 monitoring points along the Danube River, between Braila city and Isaccea city in the pre-deltaic area, during the summer season and autumn season 2022. The importance of this area is given by the fact that the Dan-ube Delta is part of the UNESCO heritage and the monitoring of polluting factors is a necessity in the desire to protect this area. The data measured during the July and August 2022 campaign co-vers a wide range of chemical species: Phosphate, CCO, CBO5, NH4+, N-NO2, N-NO3-, N-Total, P-PO4 3-, SO42-, Cl-, phenols, as well as metals with a harmful effect: Aluminum, Arsenic, Cad-mium, Chromium, Iron. The study includes an evaluation based on the statistical approach of the results to highlight the significant correlations and differences identified between the two data sets. Next, to highlight the obtained results, a numerical model was considered using HEC-RAS and ESRI ArcGis applications in a two-dimensional unsteady flow model in order to get the non-homogenous concentrations’distributions in the studied area. These two-dimensional models have been less studied in the specialized literature. In this way, interesting results could be ob-tained and prediction methods regarding the dynamics of metal concentrations could be struc-tured. The data obtained was used for the terrain model from the USGS service and the flows of the Danube and its two tributaries were simulated using the data provided by the national ser-vices. In this work, we present the results obtained for the dynamics of the concentrations of the metals Aluminum, Arsenic, Cadmium, Chromium and Iron and the evaluation of the specific ab-sorption coefficients for the explanation and correlation with the results of the measurements. The study is part of a more complex project in which the spatio-temporal distribution of the polluting factors in the water was evaluated and the habitats in the study area were inventoried - especially those of community interest. the aspects related to the influence of the distribution of polluting factors on the state of health will be the subject of another article.

Fluoride (iF) is important inorganic pollutant in groundwater in central México. The aim of this study was estimated environmental risk exposure of iF in residents of Jerez Zacatecas México. Fifty-five tap water samples were collected from households to determine iF concentrations using the ion-selective electrode method. Based on these environmental values, the Hazard Quotient (HQ) was estimated following the methodology of the Pan American Health Organization (PAHO). Subsequently, risk maps were generated from these values to visualize the spatial distribution of high-risk areas within the city. iF in tap water ranger in concentration from 1.3 – 7.3 mg/L (ppm). We estimated HQ in a range of 0.63 to 3.73. iF ex-posure in tap water is a health problem that must be addressed, carrying out risk communication actions that allow the population to take care of their health through simple actions, avoiding future health costs.

Evaluating the economic and environmental effects of farmers' green production behaviors holds important reference value for promoting sustainable agricultural development, alleviating agricultural non-point source (NPS) pollution, and achieving the organic combination of environmental protection and economic development. This paper utilizes survey data from 1,345 farm households in the main rice production areas of Jiangxi Province, China, using the example of reduced fertilizer application (RFA) among rice farmers. By constructing a DEA—SBM model with undesirable outputs to measure environmental effects, and applying an endogenous switching model to test the economic and environmental effects of farmers' adoption of green production technologies. The study found that: (1)The behavior of RFA by farmers has a significant positive impact on their net profit per mu(NPPA), helping farmers increase their income, with the increase ranging from 2.05% to 6.54%. (2)The behavior of RFA by farmers has a significant positive impact on agricultural green productivity(AGP), contributing to the improvement of the environment, with the improvement ranging from 44.09% to 45.35%. (3)Heterogeneity analysis found inconsistencies in the income-enhancing and environmental-enhancing effects at different quantiles of NPPA and AGP. Therefore, attention should be placed on improving the agricultural product quality supervision system under the market circulation mechanism, creating land scale conditions conducive to the promotion and application of fertilizer reduction technologies, and promoting the implementation of externality internalization compensation systems.

Environmental responsibility is crucial in both consumption and production processes. Increasing environmental concerns of societies require eco-innovative and nature-based solutions (NBS) for entrepreneurs. Young people's intentions as potential innovators and entrepreneurs on eco-entrepreneurship with mediating effects have not been investigated is a shortcoming in the literature. This study was conducted with 920 respondents from a public university (Düzce University) students to determine the underlying motivations of eco-entrepreneurship intentions using structural equation modeling (SEM) and bootstrap methodology. SEM results show that environmental concerns have a positive direct effect (β=0.62) on students’ eco-entrepreneurship intention. This study can serve the several sustainable development goals (SDGs) making suggestions for the efficient and effective use of production factors in terms of environmentally responsible behavior. Study results provide data for sustainable business applications and eco-innovative thinking. Study results intend the direction of modern environmental governance, policy makers and SEM developers.

The yield of logging in a forest management area using only the volume variable is not sufficient to assess effective wood productivity. The objective was to evaluate production using different logging variables to point out possible divergences between what was planned and what was actually carried out, in order to indicate adjustments to annual operating plans (AOPs) in the Amazon. The database comes from a community forest management area in the Tapajós National Forest, con-sidering three sources: 100% inventory, AOP planning and the post-exploration report. The pro-duction yield considering the number of trees felled and the effective volume were compared with the AOP planning. The volume estimated by the generic equation was compared with the cubed volume and the commercial height variable was evaluated. Of the 6,267 trees selected, 5,090 trees were harvested (3.2 trees.ha-1), indicating a yield of 85.0% of the estimated volume. Of the 25 commercial species logged, the most representative were: Manilkara huberi, Vochysia maxima, Lec-ythis lurida, Couratari guianensis and Hymenaea courbaril. It can be concluded that the number of trees, cubed volume and commercial height are post-exploration yield response variables and not just volume, as is currently used in SFMPs.

The present study aimed to date the death of Korean red pine (Pinus densiflora Siebold & Zucc.) at Sogwang-ri, where is famous for the Korean red pine forests in Korea, using a dendrochronological method, and to investigate the effect of climatic factors on the death and growth decline of the pine trees. For the study, 51 Korean red pines were selected from three stands (Jungmi-gol A, Jungmi-gol B, and Neonam-gol) in the study area, and for the ring-width measurement the increment cores were extracted from the selected trees. The stand chronologies for the Jungmi-gol and Neonam-gol were established using the mean values of individual time series of the living trees from each site, and the chronologies were further used for cross-dating with individual time series of the dead trees to date their death. The abrupt growth reduction was also investigated based on the consecutive ring-width growth decline trend to know the vitality during the living. Results revealed that the red pines at Jungmi-gol A were dead in 2020, at Jungmi-gol B in 2012 or 2013, and at Neonam-gol in 2019. So, it was verified that the death of the red pines at the study sites occurred from high to low elevations. In the analysis of the role of climate in the annual ring growth, the trees at Jungmi-gol A and B located on the southwest slope showed more ring-width growth when precipitation in April, July, and August were increasing, at Neoman-gol located on the north slope when precipitation only in July was increasing. Although the correlations of the ring-width growths at the sites with temperature and precipitation were somehow different from each other, Drought Stress Index (DSI) from May to September at all sites were all negative. Therefore, water stress caused by increased temperature and decreased precipitation is the most significant climatic parameter for the death or growth decline of the pine trees in the study area.

Climate change is an important threat to orchard production at Mediterranean basin. Diversification seems to be implemented at a farm level as an important strategy to face these challenges. This paper aims to analyse farmer’s perceptions on crop diversification as a way to enhance farm’s adaptive capacity in a context of current and future climate changes impacts. Our case study is focused in orchards growers from French department of Vaucluse recently diversifying their activities through pistachio (Pistacia vera L.). We did in-depth semi-structured farmers’ interviews in 2021. The results show that diversification is supposed to enhance 3 main components of farms adaptative capacity: (1) strengthening robustness through improvement of buffering capacities to climate impacts (trough robust and adapted plants), economic uncertainties (by exploring local/niche markets) and labour scarcity (by lowering workforce requirements and mechanization); (2) Learning by experimenting, monitoring and exchanging with pairs and advisors (3) Cope with change related with societal demands and helps to increase personal satisfaction. Finally, promote farm’s diversification can contribute to enhance farm’s adaptive capacity under climate change impacts.

Recently, the concept of participatory democracy developed in the early 1970s has come back into fashion to revitalize the public involvement in political decision-making processes. Public par-ticipation in forest policy has been fully conceptualized by the scientific community in the late 1990s and early 2000s, but in many contexts the practical application remains unfulfilled. The aim of this study is to identify and analyze the participatory techniques used in literature to increase knowledge and facilitate its transferability into forest policies and strategies. A literature review was carried out to offer an overview of the participatory techniques adopted in the deci-sion-making process. At the end of literature review, 25 participatory techniques were identified based on over 2,000 publications. Afterwards, the participatory techniques were assessed using seven indicators (degree of participation, type and number of participants, time scale, cost, po-tential influence on policy). The results showed that the type of actors involved in the participa-tory technique is a key variable for the complexity and usefulness of the process, while the number of participants influences how information is disseminated. The Principal Component Analysis highlighted that the participatory techniques can be divided in three groups: the first group includes those techniques with a high degree of participation and a contextual high po-tential influence on policies, the second one includes techniques with a costs in terms of re-sources, while the third one consists of those with a large number of participants and reduced time requirements.

The diel variations of viruses (< 0.2 μm), picoplankton (0.2—2 μm; heterotrophic bacteria, Syn-echococcus spp., Prochlorococcus spp. and picoeukaryotes) and nanoplankton (2—20 μm; hetero-trophic nanoflagellates and pigmented nanoflagellates) were investigated for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. A period of wind change associated with rain and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. The abundance of bacteria did not follow a consistent diel pattern, while viral abundance positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nano-flagellate grazing could control their abundances and may explain temporally varying picocyanobacteria abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

At the end of the dry season in early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass burnings period, smoke aerosols blanket the whole regions and were transported and dispersed by predominant westerly and south westerly winds to southern China, Taiwan and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperature making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burnings period to the exposed population and their health impact. The Weather Research Forecast- Chemistry (WRF-Chem) model was used to predict the PM2.5 concentration over the simulating domain and health impacts are then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia and Vietnam. Using the health impact based on log-linear concentration response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 314 deaths respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact and associated economic cost of agricultural waste burnings in Southeast Asia at the end of the dry season. And hence policy makers should take these into account to design measures to reduce the negative impact of widespread burnings on exposed population in the region.

Coppicing has been neglected in recent decades leaving gaps in knowledge on silvicultural interventions, especially the long-term effects on coppices of South-East Europe. Thus, our work aims to define the long-term effects of thinning in sessile oak (Quercus petraea (Matt.) Liebl.) and European beech (Fagus sylvatica L.) sub-mountainous thermophilic low coppices in the Croatian Dinarides. The experiment includes two localities with thinning plots and control plots. Thinning was done in 2002 with 17.71% of wood volume removed in the European beech coppice and 26.09% in the sessile oak coppice. 1276 trees were marked, measured (DBH, tree height, number of stems per stump) and assessed for vitality, origin and six silvicultural features revealing tree quality. Descriptive statistics for all variables, RMANOVA for DBH and height and for continuous variables mean+-+ standard deviation for categorical frequency and relative frequency variables were carried out. The results show a statistically significant positive long-term effect of thinning on tree growth, stem and crown features and support findings that thinning, by increasing growth and quality, is a necessary intervention in European beech and sessile oak low coppices. The recent economic crisis, the sudden increase in energy prices, and the increased demand for assorted wood products have initiated higher interest in coppices in Croatia.

The study delves into the Zaalklapspruit valley-bottom wetland in South Africa, a site designed through ecological engineering and currently impacted by acid mine drainage due to an upstream defunct coal mine. The research conducted in 2022, aimed to uncover the dynamics of contaminant dispersal within such a wetland setting, focusing on the origins, routes, and ultimate recipients of various metals and sulfur compounds. Analysis revealed that the bottom sediment is rich in organic material, with pH levels observed between 6.05 and 6.59, and exhibited notably low oxidation-reduction potentials, reaching down to −219.67 mV at sample point S3. Notably, Manganese displayed the highest adsorption rates, whereas Iron was predominantly absorbed by the roots of Typha capensis and the algae Klebsormidium acidophilum. The wetland's macrophyte rhizospheres hosted a rich array of microbiota, including families like Helicobacteraceae and Hydrogenophilaceae, which are crucial in metal and sulfur processing. This investigation sheds light on the intricate biogeochemical processes taking place involving the wetland's sediment, macrophyte root systems, periphyton, and microbial populations, underscoring the potential of ecologically engineered wetlands in the remediation of waters affected by acid mine drainage.

Since the 1960s, forest planners have used linear programming models to develop management plans for large, forested areas. Hundreds of academic papers have presented such models, incorporating multiple objectives, a growing diversity of management interventions, and uncertainty, among other things. Three basic ways to formulate these models have been used: Model I, III, and III. We define these models based on the sequence of management unit states represented by the variables. In Model I, variables represent a sequence of states from the beginning of the planning horizon to the end. In Model II, variables represent a sequence of states from one intervention to the next. Finally, in Model III, variables represent a single arc in a management unit’s decision tree, including only a beginning and an ending state. We formulate each type of model for a case study with three increasingly complex scenarios incorporating additional ecosystem services. Our results indicate that, despite requiring more variables and constraints, Model III requires the least time to formulate, largely because it has the least dense parameter matrix. Model II has the shortest solution times, with Model III close behind. Model I requires both the longest formulation and solution times.

The sustainable development of the country, particularly in hilly regions, encounters formidable challenges attributed to the gradual degradation of environmental conditions in these areas. Over time, disputes have arisen concerning forests, water sources, and other natural assets. The present analysis focuses on the environmental conflicts surrounding the Chamera Stage-I hydroelectric project in the Chamba region of Himachal Pradesh. This analysis is based on perception surveys conducted within local communities and field studies examining ecological and environmental parameters. These parameters include the loss of green cover, decline in biodiversity, depletion of natural resources, disruption of access to common property, disturbances in the ecological cycle, alterations in microclimate, changes in land use patterns, and the loss of ethnobotanical and wild edible fruit plants. Local communities overwhelmingly assert that these conflicts have arisen due to the construction of the dam. They firmly hold the view that higher authorities disregard the environmental and ecological impact as a crucial consideration in any project. Consequently, as communities grapple with survival challenges, conflicts with authorities emerge over environmental issues. The analysis also highlights measures to mitigate these adverse impacts and proposes an enhanced collaborative approach in handling such projects to address conflicts more effectively.

This study was conducted to investigate heavy metal contamination and potential health risk of ground water of selected municipal solid waste (MSW) disposal sites of Khyber Pakhtunkhwa (KP) Pakistan. For this purpose a total of 30 composite samples of both surface and ground water were collected from dumpsites of Abbottabad, Bannu and Peshawar. The collected samples were analyzed for physico-chemical parameters and heavy metals by following standard methods. Results indicated that pH values were found within the acceptable limits specified by national environmental quality standards (NEQS) and world health organization (WHO). Mean concentrations of heavy metals were within NEQS and WHO limits, except for Ni which exceeded the NEQS and WHO limit of 0.02 mg/L in all samples, Similarly, Mn exceeded the limit set by NEQS and WHO (0.5 mg/L) in the ground water samples collected from Bannu dumpsite. The multivariate analysis indicated that the heavy metal contamination of the groundwater of the selected dumpsites was anthropogenic. The pollution index (PI) values (PI≥100) of Mn and Ni indicated very high pollution at individual levels while collectively based on heavy metals pollution index (HPI) values (HPI ≥ 200) the ground water of all the selected dumpsites were found highly polluted. Whereas, the hazard index (HI) values (HI ≥ 5) suggested adverse health effects. It was concluded that the ground water of all the dumpsites was highly polluted with heavy metals particularly Ni and Mn thus, posing a high health risk.

Like many coastal lagoons in several countries, “Navío Quebrado” lagoon (La Guajira-Colombia) is a very delicate and precious environment; indeed, it is a nationally recognized Flora and Fauna Sanctuary. Several factors, amongst which climate change, are threatening its existence because of changes in the governing hydro-morphological processes. A first step to address this problem certainly is to understand its hydrological behavior and to be able to replicate via simulation its recent history and then infer likely futures. These potential futures will be marked by changes in the water input by its tributary, the Camarones River, and by a modified water exchange with the sea, according to a foreseen sea level rise pattern, as well as by a different evaporation from the free surface, according to temperature changes. In order achieve the required ability to simulate future scenarios, data on the actual behavior have to be gathered, i.e. a monitoring system has to be set up, which to date is not existent. Conceptually, designing a suitable monitoring system is not a complex issue and seems easy to implement. However, the environmental and socio-cultural and socio-economic context makes every little step a hard climb. An extremely simple –almost “primitive”- monitoring system has been set up in this case which is based on very basic measurements of current velocity and water levels and a direct participation of local stakeholders, first of all the National Park unit of the Sanctuary. All this may clash with the latest groovy advances of science, like in situ automatized sensors, remote sensing, machine learning and digital twins, and certainly several improvements are possible and desirable. But it has strong positive points: it is providing surprisingly reasonable data and…it is working at almost zero additional cost. Several technical difficulties made this exercise interesting in itself and worth being shared. Its novelty lies in showing how old, simple methods may offer a working solution to new challenges. This humble experience may be of help in several other similar situations across the world.

This study investigates the anthropogenic activities, water quality, and ichthyofaunal diversity of the Navotas Riverine Ecosystem. It examines the anthropogenic influences, analyzes the physicochemical and microbiological properties of water, identifies fish species, evaluates the water quality index, and determines ichthyofaunal diversity using various indices. Water samples and fish collections were conducted from January to April 2024 at three sites. Key findings indicate that water quality parameters such as temperature (23.20-37.5°C), dissolved oxygen (6.22-7.84 mg/L), phosphate concentration (0.55-3.72 mg/L), and fecal coliform (350-160,000 MPN/100 mL) failed to meet DENR standards for Class C water. The TDS (1153.33-10700 ppm) and conductivity (17653.33-21333.33 µS/cm) were also elevated, indicating significant pollution. The study identified low ichthyofaunal diversity, with six native and one invasive fish species. A total of 269 fish were collected: 161 from Site 1, 46 from Site 2, and 62 from Site 3. The most abundant species was Scatophagus argus (19% occurrence), while the invasive Sarotherodon melanotheron ranked third (17% occurrence). Notably, pH (r = 0.753) correlated highly with nitrate concentration. S. melanotheron significantly correlated with pH (r = 0.602, p = 0.019) and nitrates (r = 0.555, p = 0.031). Lutjanus argentimaculatus also had significant correlations with pH (r = 0.527, p = 0.039) and nitrates (r = 0.651, p = 0.011). Conversely, S. argus had a negative moderate correlation with temperature (r = -0.529, p = 0.039) and conductivity (r = -0.536, p = 0.036). These correlations suggest that the water parameters significantly influence the diversity and abundance of fish in the river. The study concludes that the river's water quality is heavily influenced by anthropogenic activities which negatively affect ichthyofaunal diversity. Recommendations include continuous monitoring, gut and heavy metal analysis of fish, assessment of avifauna diversity, and strict implementation of conservation regulations.

This study investigates the anthropogenic activities, water quality, and ichthyofaunal diversity of the Navotas Riverine Ecosystem. It examines the anthropogenic influences, analyzes the physicochemical and microbiological properties of water, identifies fish species, evaluates the water quality index, and determines ichthyofaunal diversity using various indices. Water samples and fish collections were conducted from January to April 2024 at three sites. Key findings indicate that water quality parameters such as temperature (23.20-37.5°C), dissolved oxygen (6.22-7.84 mg/L), phosphate concentration (0.55-3.72 mg/L), and fecal coliform (350-160,000 MPN/100 mL) failed to meet DENR standards for Class C water. The TDS (1153.33-10700 ppm) and conductivity (17653.33-21333.33 µS/cm) were also elevated, indicating significant pollution. The study identified low ichthyofaunal diversity, with six native and one invasive fish species. A total of 269 fish were collected: 161 from Site 1, 46 from Site 2, and 62 from Site 3. The most abundant species was Scatophagus argus (19% occurrence), while the invasive Sarotherodon melanotheron ranked third (17% occurrence). Notably, pH (r = 0.753) correlated highly with nitrate concentration. S. melanotheron significantly correlated with pH (r = 0.602, p = 0.019) and nitrates (r = 0.555, p = 0.031). Lutjanus argentimaculatus also had significant correlations with pH (r = 0.527, p = 0.039) and nitrates (r = 0.651, p = 0.011). Conversely, S. argus had a negative moderate correlation with temperature (r = -0.529, p = 0.039) and conductivity (r = -0.536, p = 0.036). These correlations suggest that the water parameters significantly influence the diversity and abundance of fish in the river. The study concludes that the river's water quality is heavily influenced by anthropogenic activities which negatively affect ichthyofaunal diversity. Recommendations include continuous monitoring, gut and heavy metal analysis of fish, assessment of avifauna diversity, and strict implementation of conservation regulations.

Small and Medium Enterprises (SMEs) are recognized as the main drivers of economic growth and development in many countries throughout the world. SMEs represent about 90% of the manufacturing sector and contribute about 14% of the total manufacturing contribution to GDP. Despite SMEs’ potential to change Nigeria’s status from a consumer economy to a production economy, policies that will ensure that environmentally- friendly manufacturing processes and production technology are not implemented or complied with. SMEs’ operational activities may be deleterious to human health and the ecosystem if environmental management practices are not adopted or prioritized. This paper evaluated the perception and adoption of the Environmental Management System, mainly ISO 14001, by SMEs in Nigeria. One hundred and fifty (150) SMEs in the manufacturing sector in Lagos and Ogun State, Southwestern Nigeria, were randomly selected for this study. The paper posits that environmental management literacy and advocacy should be carried out in SMEs. Environmental management practices involve engaging both industries and product end-users in sustainable practices. The paper concludes that the implementation of environmental management practices and culture by SMEs will abate environmental pollution and its concomitant health risks to humans, the environment, flora, and fauna. Mandatory and voluntary environmental measures are suggested as a means of engendering eco-friendly innovation for sustainable development, triggering employment, job security, and gross domestic product.

Crop coefficient (Kc), the ratio of crop evapotranspiration (ETc) to reference evapotranspiration (ETo), is used to schedule an efficient irrigation regime. This research was conducted to investigate variations of ETc and growth-stage-specific Kc in a flood-irrigated winter wheat as a forage crop from 2021 to 2023 in the Lower Rio Grande Valley of southern New Mexico, USA, and evaluate the performances of the two temperature-based ETo estimation methods of Hargreaves-Samani and Blaney-Criddle with the widely used Penman-Monteith method. Results indicated that the total ETc over the whole growth stage for flood-irrigated winter wheat was 556.4 mm on a two-year average, while the average deep percolation (DP) was 2.93 cm and 2.77 cm, accounting for 28.8% and 27.2% of applied irrigation water, respectively in the 2021-22 and 2022-23 growing seasons. The ETo over the growing season computed by Penman-Monteith, Hargreaves-Samani, and Blaney-Criddle equations were 867.0 mm, 1015.0 mm, and 856.2 mm in 2021-22, and 785.6 mm, 947.0 mm, and 800.1 mm in 2022-23, respectively. The Hargreaves-Samani method performed better than the Blaney-Criddle method with higher statistical indicators of model efficiency coefficient (CE), and smaller mean bias error (MBE), mean absolute error (MAE), and the root mean square error (RMSE) in both growing seasons. The result of a global sensitivity analysis showed that the mean temper-ature is main driving factor for estimated ETo based on Blaney-Criddle and Hargreaves-Samani, but the sensitivity percentage for Blaney-Criddle was 76.9%, which was much higher than that of 48.9% for Hargreaves-Samani, given that Blaney-Criddle method is less accurate in ETo estimation for this area especially during the hottest season from May to August. In contrast, wind speed and maximum temperature were the main driving factors for the Penman-Monteith method, with sensitivity percentages of 70.9% and 21.9%, respectively. The two-year average crop coefficient (Kc) values at the initial, mid, and late growth stage were 0.54, 1.1, and 0.54 based on Penman-Monteith, 0.51, 1.0 and 0.46 based on Blaney-Criddle, and 0.52, 1.2 and 0.56 based on Hargreaves-Samani. Results showed that the Hargreaves-Samani equation serves as an alternative tool to predict ETo when fewer meteorological variables are available. The calculated local growth-stage-specific Kc can help improve irrigation water management in this region.

This study investigates the utilization of Eco-Innovation practices within Nigerian industries to mitigate urban soil contamination. Soil samples were collected from various urban land uses in Ijebu Ode town, specifically mechanic workshops (MW), roadsides (RD), industrial areas (IL), and market zones (MT). Ten composite soil samples were randomly gathered from each land use at a depth of 0-30cm and subjected to analysis for heavy metal concentrations (copper Cu, iron Fe, lead Pb, zinc Zn, cadmium Cd, manganese Mn) using an Atomic Absorption Spectrophotometer. This facilitated the calculation of contamination levels and pollution load index. The findings indicate that the concentration of Cu, Zn, Fe, and Mn is highest in soils from mechanic workshops, with the degree of soil contamination ranking as follows: Mechanic Workshop > Industrial land use > Roadside > Market land use. The study concludes that elevated levels of heavy metals in the sampled urban soil are closely linked to improper land use practices and other human activities. It advocates for the promotion of sustainable environmental practices through comprehensive stakeholder engagement aimed at educating the populace on the management and preservation of urban soils against harmful practices.

Keywords: emerging pollutants; pharmaceuticals; plant uptake; soil behavior; soil remediation.

This study aimed to evaluate the effects of plasma treated metal contaminated water, used for irrigation, on plant growth. Zinc (Zn) is one of the more commonly used metals. It can enter the environment from industrial processes as particles released into the atmosphere or as wastewater discharged into waterways or the ground. Exposure to large amounts of zinc, even for a short time, can seriously affect human health. In this experiment, three different DBD O2 plasma treated zinc contaminated water and a control (tap water) were used, with Arabidopsis thaliana as the model plant. The treatments were: i) Control, ii) Zn water, iii) Zn+O3(30 min), and iv) Zn+O3(60 min). Arabidopsis plant exhibited maximum growth in the Zn+O3(30 min) treatment. All growth parameters, except leaf area, followed this trend: Zn+O3(30 min) > Control > Zn water > Zn+O3(60 min). Gene expression analysis revealed that reduced metal ion stress and controlled oxidation due to active oxygen species contributed to favorable/improved growth of Arabidopsis in the Zn+O3(30 min) treatment. Therefore, 30 minutes of DBD O2 plasma treated zinc contaminated water [Zn+O3(30 min)] can mitigate the adverse effects of excess zinc ions and promote the growth of Arabidopsis plants.

Greenhouse gas (GHG) emission-induced climate change, particularly occurring since the mid-20th century has been considerably affecting short-term weather conditions, such as increasing weather variability, and incidence of extreme weather-related events. Milk production is sensitive to such changes. In this study, we use spatial panel econometric models, Spatial Error Model (SEM) and Spatial Durbin Model (SDM), with a panel dataset at the state-level varying over seasons, to estimate the relationship between weather indicators and milk productivity, in an effort to reduce the bias of omitted climatic variables that can be time-varying and spatially correlated and cannot be directly captured by conventional panel data models. We find an inverse U-shaped effect of summer heat stress on milk production per cow (MPC), indicating that milk production reacts positively to a low-level increase in summer heat stress, and then MPC declines as heat stress continues increasing beyond a threshold value of 72. Additionally, fall precipitation exhibits an inverse U-shaped effect on MPC, showing that milk yield increases at a decreasing rate until fall precipitation rises to 14 inches and then over that threshold milk yield declines at an increasing rate. We also find that, relative to conventional panel data models, spatial panel econometric models could improve prediction performance by leading to smaller in-sample and out-sample root mean squared errors. Our study contributes to the literature by exploring the feasibility of promising spatial panel models and resulting in estimating weather influences on milk productivity with high model predicting performance.

The exponential growth of user-contributed data provides a comprehensive basis for assessing collective perceptions of landscape change. A variety of possible public data sources exist, such as geospatial data from social media or Volunteered Geographic Information (VGI). Key challenges with such ‘opportunistic’ data sampling are variability in platform popularity and bias due to changing user groups and contribution rules. In this study, we use five case studies to demonstrate how intra- and inter-dataset comparisons can help to assess the temporality of landscape scenic resources, such as identifying seasonal characteristics for a given area, or testing hypotheses about shifting popularity trends observed in the field. By focusing on the consistency and reproducibility of temporal patterns for selected scenic resources and comparisons across different dimensions of data, we aim to contribute to the development of systematic methods for disentangling the perceived impact of events and trends from other technological and social phenomena included in the data. The proposed techniques may help to draw attention to overlooked or underestimated patterns of landscape change, fill in missing data between periodic surveys, or corroborate and support field observations. Despite limitations, the results already provide a comprehensive basis for developing indicators with a high degree of timeliness for monitoring perceived landscape change over time.

This manuscript reviews three case studies from Brazil, Panama, and Portugal that illustrate Nature-based Solutions. The Tijuca Forest in Rio de Janeiro is a remarkable story of centuries of forest management that today is recognized as a UNESCO World Heritage Site. The Panama Canal Watershed produces water for Canal operations, electricity generation, and drinking water for half the country´s population. Traditional windmills and weirs near streams in the Alentejo Region, Portugal, have largely been abandoned due to the damming of the Guadiana River. Yet today, weirs are increasingly recognized for their important contribution to water provisioning in this dry region. All have a primary goal related to water provisioning, yet their ecosystem benefits are multiple. The cases offer important lessons for adaptation to climate change, cultural benefits from traditional human activities, and concerns about social equity.

The Third U.S. National Marine Environmental DNA Workshop on June 2–5, 2024 brought together researchers, practitioners, and policymakers to overview and discuss: (1) environmental (e)DNA – defined as “DNA in the environment” – as a strategic U.S. national priority, (2) eDNA tool readiness and approaches to support decision-making, (3) emerging eDNA technologies, and (4) plans for implementation and adoption for environmental monitoring and ecosystem assessment “from microbes through whales”. Uses and applications of eDNA have been revolutionizing exploration, measurement, and monitoring of biodiversity across ecosystems, including the marine and freshwater aquatic environments emphasized in the Workshop, as well as terrestrial and aerial systems. The Workshop featured the launch of the new U.S. National Aquatic Environmental DNA Strategy from the White House Office of Science and Technology Policy (2024), with aquatic defined as freshwater to ocean waters, across all salinities; the Strategy was developed using outputs and a taskforce from the 2022 Second Workshop. The 2.5-day Third Workshop included speaker presentations, panel discussions, and networking on eDNA tools, applications, use, upscaling, and their future. The Workshop led into Capitol Hill Ocean Week (CHOW) events (June 5–6, 2024), during World Ocean Week. Note that this summary paper represents the author’s take-away view and interpretation, and not necessarily the overall views or consensus of the U.S. Government, Smithsonian Institution, workshop organizers, or speakers.

The article adds new policy insights to the way in which formal teaching methods of environmental stewardship education areas are evaluated in Tuvalu. We aimed to answer three questions: 1. What are the formal policies shaping environmental stewardship education in Tuvalu? 2. Are national educational and environmental policies mutually consistent? and 3. Are these national policies consistent with regional and global policies? These questions were addressed using a study of Tuvaluan online-available documentary assessments of national policies, frameworks, and curricula in conjunction with those obtained from the Education Department. Our findings revealed limitations and weaknesses regarding the provisions of environmental stewardship education at the national scale, including misaligned curricula, policy documents, and formal educational provisions with Tuvalu’s national environmental policy. We also found inconsistencies with regional and global policies such as the Pacific Islands Framework for Nature Conservation, the Framework for Resilient Development in the Pacific, and international strategic plans for biodiversity and climate change. These cross-scalar policy weaknesses and limitations highlight the need for the Tuvaluan government to align educational and environmental policies at different scales. We recommend a multi-pronged strategy where modes of informal environmental education can support and complement formal government policymaking on education and the environment.

In this study the distribution of heavy metal in the agricultural soils in the vicinity of 3 large mine-landfills around Kizhnica mine in Kosovo was investigated. The mining sector is one of the most important sectors of the economic development of Kosovo. The Kizhnica mine is one of the main ore producers in Kosovo. In addition to the positive aspects of production development it has its own side effects such as: industrial waste and the possibility of contamination of sur-rounding areas including the agricultural lands in the surrounding region. Ten sampling sites close to the Kizhnica mining complex were selected. These sampling sites have been characterized and evaluated as the most critical points, due to the anthropogenic influences of the discharge of industrial water from mining flotation and open tailing dumps in the Kizhnica. Concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in selected samples was carried out by inductively coupled plasma–optical emission spectrometry (ICP–OES). Obtained data were used in order to generate geochemical maps and for calculatation the contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo). The statistical clustering analysis (CA), Pearson correlation coefficient (r) and air spatial distribution patterns using AERMOD View-Gaussian air dispersion model are used to perform evaluation within the area. The results demonstrated higher contents of the heavy metals in the vicinity of the mining area. It may be concluded that the heavy metal contents are impacted by anthropogenic nature of the contamination that confirms a current eco-logical threat of the mining activities in the region. Finally, a paper proposes the potential reas-signment of the deposed waste material into different combinations in construction in order to enhance the waste management and reduce the continued risk to: residents, lands and all living beings in the region.

This study examined local communities' perceptions of mangroves in coastal southeastern Cuba. A variety of methods were employed, including mixed and structured questionnaire surveys, interviews with key informants, and document reviews. Data were gathered from 334 respondents living in communities adjacent to four mangrove social-ecological systems (SESs). The analysis focused on five variables: community use of mangrove resources, ecosystem services, threats to the ecosystem, management activities, and social-ecological relationships. To qualitatively assess the influence of social-ecological relationships and governance, a matrix was created based on anthropogenic activities identified by respondents and their perceptions of ecosystem services. The results indicated that while local people recognize the uses and ecosystem services of mangroves, they do not rely on them for their livelihoods. They also showed moderate to full awareness of management responsibilities and activities at each site. The most commonly identified threats were climate change, drought, and deforestation. Three types of social-ecological relationships were identified based on the characteristics of the communities, their economic activities, and their impacts on the mangroves: urban-industrial, rural-agricultural, and rural-agricultural/tourism. Finally, the research proposed a set of five recommendations and eight associated indicators to ensure that mangrove management framework become more inclusive and participatory, thereby contributing to the articulation of mangrove SES governance in the southeastern region of Cuba.

AbstractLarge numbers of urban lakes are facing issues related to cyanobacteria, commonly known as blue-green algae, resulting in significant threats to humans and animal health due to their production of microtoxins and Anatoxin-A. These toxins induce acute effects including gastrointestinal distress, and respiratory problems, underscoring the need to protect urban lakes to safeguard community health and ecosystem well-being. A comprehensive monitoring program is a critical step to address cyanobacteria-related issues. Monitoring results of dissolved phosphorous, nitrates(N), Total Kjeldahl Nitrogen (TKN), total phosphorous (TP), TSS, and Escherichia coli (E. coli) concentrations, are used to understand the importance of different pathways events during dry conditions (no prior rainfall) and wet events (rainfall during or proceeding monitoring events) plus a microbial source tracking procedure, to understand impacts on growth characteristics of cyanobacteria and microtoxins. The Mann-Kendall Trend Test is used to characterize trends of various parameters (using transitions of ‘wet’ and ‘dry’ to the Lake and within the Lake), to identify the impact of various management strategies and/or the impact of various sources from overland land uses for a) wet events to the Lake, b) dry events to the Lake, c) wet events in the Lake, and d) dry events within the Lake. Microbial source tracking methods are used along the shoreline of Fairy Lake to interpret elevated levels of fecal pollution and E. coli bacteria in water samples, aiding in the identification of pollution sources. Blue-green algae have been observed at least once each year from 2018 to 2023. Microtoxins and Anatoxin-A were present in nine samples with a maximum of 1.72 mg/L and 0.02 mg/L, respectively. Frequent beach closures have occurred every year, raising public concerns regarding both ecological and recreational aspects for Fairy Lake.

Source water quality is a key determinant of drinking water quality. The recast European Union 2020/2184 drinking water directive (DWD) introduced the obligation for comprehensive risk assessment in drinking water supplies, including the water source and incorporated new elements of natural origin in the list of parameters to be monitored. The current study is the first comprehensive assessment of 15 natural elements (B, Ba, Be, Ca, Co, K, Li, Mg, Mo, Na, Se, Sr, Ti, U and V) in 1155 (82%) Hungarian drinking water sources, including surface water, bank filtered and groundwater sources. Parameters posing a risk to health (Se, V and U) were typically below the lower limit of quantification (LOQ), but higher concentrations (max. 7.0, 17 and 41 µg/L, respectively) may occur in confined locations, the latter exceeding the DWD parametric value in one water supply. Li in a small geographical area, Mg and Ca in the majority of the water supplies reached the concentration range assumed to be protective to health. Water sources were grouped in 6 clusters based on their element distribution, some of them also showing clear geographical patterns. Water types were not differentiated, with the exception of karstic waters (dominated by Ca and Mg). None of the investigated parameters are expected to be a source of public health concern.

Previous studies on the water-energy nexus mainly focused on the calculation and comparison of resource consumption at the national or regional level, lacking interprovincial sector-sector transfer analysis. In this study, the intensity of water and energy consumption of various sectors in China were calculated, the key nodes and paths of resource networks were identified, and countermeasures for resource conservation were proposed from the new perspective of the “dual saving” and “bidirectional saving” of water and energy. The results showed that the metallurgical industry (Me) in Jiangsu and the chemical industry (Ch) in Hebei and Jiangsu had high node strength in the water and energy network and were key sectors in China with “dual saving” effects of water and energy. The construction industry, Ch, Me in Jiangsu, electricity and hot water production and supply industry in Beijing, and Me in Hebei had high node strength in the water-related energy network and energy-related water network, significantly supporting the “bidirectional saving” effect of water and energy in China. The electrical equipment industry (El) in Jiangsu→El in Zhejiang, El in Zhejiang→El in Shanghai frequently appeared in key paths, which could effectively reduce the resource consumption of the entire network.

Recent omics technologies have revolutionized the study of molecular plant responses to air pollution, overcoming previous limitations. This review synthesizes the latest advancements in molecular plant responses to major air pollutants, emphasizing ozone (O3), nitrogen oxides (NOX) and particulate matter (PM) research. These pollutants induce stress responses common to other abiotic and biotic stresses, including the activation of reactive oxygen species (ROS)-scavenging enzymes and hormone signaling pathways. New evidence showed the central role of antioxidant phenolic compound biosynthesis via phenylpropanoids pathway in air pollution stress responses. Transcription factors like WRKY, AP2/ERF, and MYB, which connect hormones signaling to antioxidant biosynthesis, were also affected. To date, research has predominantly focused on laboratory studies analyzing individual pollutants. This review highlights the need for comprehensive field studies and the identification of molecular tolerance traits, which are crucial for the identification of tolerant plant species aimed to the development of sustainable Nature Based Solutions (NBS) to mitigate urban air pollution.

The effects of climate change are already being felt around the world; however, data on its socio-economic impacts in regions such as the Amazon are still insufficient. Thus, this article aims to reveal the socio-environmental vulnerability of riverine communities to climate change through an analysis carried out in the middle Juruá region, Brazil, focusing on the loss of agricultural production that occurred after the extreme flooding in 2021. Data were collected through semi-structured questionnaires with the participation of 638 agro-extractivists from traditional riverine communities in the municipality of Carauari in the Brazilian Amazon, as well as the collection of documentary information and field visits to quantify and qualify the damage caused by the flood. The loss of agricultural production in the territory exceeded the value of US$ 1,300,000 with greater losses in the production of cassava flour, an essential food for the riverine communities. Production chains of non-timber products, such as the case of rubber tapping and the harvesting of oilseeds, were also directly impacted. The damages caused by climate change to the Amazonian riverine sociological systems are already being experienced by the traditional communities of the middle Juruá region. Governments need to assist these populations in building adaptive measures and strengthening local resilience.

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers novel insights into the causative mechanisms of ground fissures in the northern North China Plain, providing valuable scientific evidence for mitigating ground fissure disasters during the urbanization process in the region.

The article addresses the complex climatic situation faced by the state of Rio Grande do Sul, Brazil, which began on April 27, 2024, and extended for weeks. This unprecedented extreme weather event is yet another chapter in the global climate crisis. Initially, this rainfall seemed typical for the season. However, it quickly escalated into one of the worst climatic catastrophes in Brazil's history. In recent years, there has been a global increase in extreme weather events, including heavy precipitation, flooding, landslides, cyclones, and heatwaves, highlighting the ongoing climate crisis as one of the most serious threats we face today. In light of this, our study aims to elucidate the impact of climate change by examining one of Brazil's most severe climate disasters. We investigate the complex situation in Rio Grande do Sul, analyzing the ongoing climate crisis and projecting what can be expected in the near future.

This research provides an in-depth analysis of drought impacts in West Pokot, Kenya, utilizing both remote sensing surveys and focus group discussions. The study commenced by assessing the impact of drought on vegetation health via spatial sensors. It then utilized surveys and focus group discussions (FGDs) to engage farmers from the most drought-affected areas in Kacheliba and Sigor sub-counties. The analysis of remote sensing data from 1990 to 2022 highlighted that Sigor and Kacheliba experienced significant drought events during the years 1995, 2000, 2002, 2005, and 2009, and 1991, 1995, 2000, 2005, and 2019, respectively. This study delves into both the meteorological and socio-economic effects on local communities. Using the Multinomial Logistic Regression (MLR) model with the glm function, the research uncovered the impacts of so-cio-economic factors and agricultural practices on household livestock production. Additionally, the study employed Multiple Correspondence Analysis (MCA) to explore the dynamics between livestock production, community resilience, and crop production. The findings underscore the urgent need for tailored interventions to enhance community resilience in the face of increasing climatic extremes, serving as a blueprint for similar arid and semi-arid regions worldwide.

Hydrokinetic energy constitutes a significant promise as a renewable energy source, yet many regions experience flow velocities insufficient to support conventional turbine installations. According to this, the present work proposes a vertical axis hydrokinetic turbine aimed to environments where conven-tional turbines may not be feasible due to insufficient water velocity. This turbine is based on a biologi-cally inspired design which improves the traditional Savonius turbine. This innovative configuration is inspired by the Fibonacci spiral. The turbine's performance was analyzed through Computational Fluid Dynamics. A notable improvement was found in comparison with the traditional Savonius turbine, providing a 15.1% increment in the power coefficient.

This research investigates the exposure of plant species to extreme drought events in the Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across the region. Meteorological indicators derived from hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized to quantify past, current, and future drought conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window and exhibits a modest percentage of missing data. Missing data were excluded from analysis, aligning with the decision to refrain from imputation methods due to potential bias. Drought quantification involved the computation of the Aridity Index, the analysis of consecutive hours without precipitation, and the classification of wet and dry days per month. Mann-Kendall trend analysis was applied to assess trends in evapotranspiration and maximum air temperature, considering their significance. The hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated the ranking of meteorological indicators to identify regions most exposed to drought events. The results revealed consistent occurrences of extreme rainfall events, indicated by positive outliers in monthly precipitation values. However, significant trends were observed, including an increase in daily maximum temperature and consecutive hours without precipitation, coupled with a decrease in daily precipitation across the Brazilian Atlantic Forest. No significant correlation between vulnerability ranks and weather station latitudes and elevation were found, suggesting geographical location and elevation does not strongly influence observed dryness trends.

Fish kills in Southeast Asia are frequently associated with harmful algal blooms (HABs) and cause significant ecological and economic impacts. This paper serves as a review of fish kill events with focus on those related to HABs within the region. It examines the causative algal species, known mechanisms of fish mortality, and socio-economic consequences. Fish kills have been reported across multiple countries within Southeast Asia, with notable hotspots in the Philippines, Malaysia, Singapore, Indonesia, and Thailand. The common harmful microalgal species span a diverse group including dinoflagellates (Karenia spp., Karlodinium spp., Margalefidinium polykrikoides, Noctiluca scintillans), raphidophytes (Chattonella spp.), diatoms (Skeletonema spp. and Chaetoceros spp.), and cyanobacteria (Trichodesmium spp.). These microalgae lead to fish kills through mechanisms such as hypoxia, physical gill damage, and ichthyotoxin production. Freshwater fish kills linked to HABs have also been documented for the Philippines, but there is no or limited information for the region. Our review highlights the widespread and recurring nature of fish kills, their impact on fisheries and aquaculture, and challenges in managing and mitigating their effects. There are efforts at enhancing management and mitigation using clay and early-warning systems. However, it is essential to further improve monitoring efforts, the development and deployment of early-warning systems, and viable and holistic mitigation strategies to protect the region’s aquatic resources and dependent communities, especially as aquaculture and coastal development are increasing concurrent with a changing climate that can exacerbate the risks of fish kills and HABs in Southeast Asia.

Modeling the reaction time required for the removal of chemical oxygen demand (COD) from wastewater is important because can be an indicator of harmful pollutants that may pose risks to human health.. Here, we evaluate the use of an inverse artificial neural network (ANNi) to optimize the removal of COD from aqueous herbicide solutions using sonophotocatalysis as the treatment process.. This algorithm takes the operating conditions as input and estimates the optimal reaction time to reach the required effluent COD. This model was validated by comparison with both experimental measurements and simulated analysis, resulting in low error (0.5%), high Pearson correlation (R2 = 0.9956), and short computing time (less than one minute). The results for the proposed methodology (ANNi-GAs) were efficient and attractive in a reasonable way providing a satisfactory picture of the relationships between the optimal input parameters. Such parameters control the degradation process of herbicides online and can be used to predict the behavior of COD removal, thus taking actions to reduce the impact of aqueous treatment with alazine and gesaprim herbicides on aquatic, soil biota, and human health. Therefore, this technique constitutes a promising framework for predicting the environmental impact of herbicides within a tolerable degree of error.

Arsenic is a prevalent environmental pollutant with recognized carcinogenic properties. Liver fibrosis is a frequent consequence of arsenic poisoning, with the activation of hepatic stellate cells (HSCs) being a central event. Solute Carrier Family 7 Member 11 (SLC7A11), a pivotal regulator of ferroptosis, may be involved in the process of arsenic-induced liver fibrosis. This study utilized lentiviral vector-mediated SLC7A11 silencing in LX-2 cells (a type of human hepatic stellate cells) to establish an SLC7A11 knockout cell model, which was then exposed to sodium arsenite (NaAsO2). Protein interactions were assessed through Protein Immunoprecipitation (IP), and protein levels were evaluated via Western blot analysis. It was found that NaAsO2 decreased cellular Fe2+ levels and nuclear receptor co-activator 4 (NCOA4) expression, with SLC7A11 silencing reversing these effects. Additionally, IP analysis revealed an interaction between Beclin1 and SLC7A11 proteins in LX-2 cells exposed to NaAsO2. Silencing SLC7A11 attenuated the reduction in Tumor Protein p53(P53), and p-mammalian target of rapamycin (p-mTOR) protein levels, along with the rise in Beclin1, Phosphorylated adenosine monophosphate activated protein kinase (p-AMPK), α-smooth muscle actin (α-SMA) and Fibroblast activation protein-α (FAP) induced by NaAsO2. Consequently, SLC7A11 silencing promoted cellular ferroptosis, reduced autophagy levels through the P53/AMPK/mTOR pathway, and inhibited HSC activation by NaAsO2, potentially mitigating liver fibrosis.

The studied area (the Ionian Islands: Paxoi, Lefkas, Kefalonia and Zakynthos), is situated in the western ends of Ionian Basin (IB) in contact with the Apulian Platform (AP) and named as Apulian Platform Margins (APM). The proposed model is based on fieldwork, previously published data and balanced geologic cross-sections. Late Jurassic characterizes Ionian Basin to Early Eocene NNW–SSE extension followed by Middle Eocene to Middle Miocene compression (NNW–SSE directed). The space availability, the distance of Ionian Thrust from the Kefalonia strike-slip fault (KSSF) and the altitude between Apulian platform and Ionian basin that produced during extensional regime were the main factors for the produced structures due to inversion tectonic. In Zakynthos Island, the space availability (far from KFT), and the reactivation of normal bounding faults formed an open geometry anticline (Vrachionas anticline) and a foreland basin (Kalamaki thrust foreland basin). In Kefalonia Island, the space from FKT was limited and the tectonic inversion formed anticline geometries (Aenos Mountain), nappes (within the Aenos Mountain) and small foreland basins (Argostoli gulf), all within the margins (APM). In Lefkas Island, the lack of space, very close to KFT, lead to the movement of the Ionian basin over the margins, attempting to overthrust the Apulian platform. Because the obstacle between basin and platform was very large, the moving part of Ionian Basin strongly deformed producing nappes and anticlines in the external part of the Ionian basin, and a very narrow foreland basin (Ionian Thrust foreland basin).

This research project aimed to address the growing concern about methane emissions from seaweed by developing a Convolutional Neural Network (CNN) model capable of accurately predicting these emissions. The study used PANDAS to read and analyze the dataset, incorporating statistical measures like mean, median, and standard deviation to understand the dataset. The CNN model was trained using the ReLU activation function and mean absolute error as the loss function. Model performance was evaluated through MAPE graphs, comparing the mean absolute percentage error (MAPE) between training and validation sets and between true and predicted emissions, and analyzing trends in yearly greenhouse gas emissions. The results demonstrated that the CNN model achieved a high level of accuracy in predicting methane emissions, with a low MAPE between the expected and actual values. This approach should enhance our understanding of methane emissions from Sargassum, contributing to more accurate environmental impact assessments and effective mitigation strategies.

In the context of rapid urbanization, the spatiotemporal patterns of socio-economic exposed to high seismic hazard in large cities lacks quantitative assessment, thus, it is difficult to understand the evolution of earthquake catastrophe risk there. In this paper, exposure change rate, and absolute and relatively exposure indices were proposed to quantitatively study the changes of spatiotemporal exposure to high seismic hazard in urban areas of large cities (i.e., permanent residents in urban areas more than 1 million) in Chinese mainland, using a set of multi-temporal population, GDP, and built-up datasets and a seismic hazard zoning map. The results show that, 64 out of 78 large cities are entirely or partially located in high seismically hazardous zones. Although the urban areas of large cities in high seismically hazardous zones (HSHUAs) cover only 1.73% (167177 km²) of mainland China, their share of population, GDP, and built-up land amounted to 18.14%, 30.24% and 24.55%, respectively, in 2015. Unprecedented urbanization has led to a dramatic exposure growth in HSHUAs between 1990 and 2015. The population, GDP, and built-up land in HSHUAs increased by 110 million people (with an average annual growth rate of 2.37%), 273.71 trillion USD(average annual growth rate of 11.15%), and 10593 km2 (average annual growth rate of 2.02%), respectively. HSHUAs experienced much faster population and GDP growth than the whole country, while relatively slower growth in built-up land. Exposure growth in HSHUAs also was varied for different types of large cities. Megacities had a higher proportion of increased GDP and population in HSHUAs, induced by industry and population agglomeration. Whereas, Type II large cities had a higher proportion of increased built-up land in HSHUAs, driven mainly by urban sprawl. Our analysis indicates that, for large cities under rapid urbanization, it is an urgent need to strengthen resilient urban planning, renewal and construction.

Cambodia is a predominantly agrarian society, with a majority of the population residing in rural areas and relying on agriculture for food and income. The primary sources of food for the Khmer society are rice and fish. However, the country faces vulnerabilities due to climate change, natural disasters, impacts of hydropower and infrastructure development, and land grabs, which disrupt food sources and the livelihoods of local communities. Since 2015, the Royal Government of Cambodia (RGC) has been actively promoting rice production for export, resulting in increased rice farming seasons and annual rice production. Despite these efforts, a significant portion of the population still experiences food insecurity. Therefore, this study aims to explore the reasons why food security issues persist despite the government program to increase rice production. The study involves a review of existing literature and an examination of food security in three provinces in the Cambodian Mekong Delta. It concludes that, on the one hand, the increased rice production has increased food availability, but access to and utilization of food have been challenged by indebtedness, increased cost of production and migration, and on the other hand, the rights to foods have been challenged by land crabs, water conflicts, and lack of sectoral integrations of food systems; and compounded by climate change and environmental degradation, which all contribute to food security.

The advancement of mechanization in forestry has increased productivity in the forestry sector, bringing positive and negative impacts that require a deeper understanding for sustainable forest management. This study aimed to apply a simplified instrument for assessing damage and environmental impacts in forest harvesting of commercial eucalyptus plantations, using a combination of methodologies. The methodology used combined interaction networks and impact assessment matrices, carrying out field surveys, transposing them to interaction networks and weighting them through assessment matrices, resulting in environmental indices (ES) for prioritizing actions. The study was conducted on a commercial eucalyptus plantation in the municipality of São Pedro, São Paulo, Brazil. The mechanized harvesting of the area consists of the structure of a module with a mobile unit consisting of a harvester and forwarder. The results indicated that wood transport presented the highest ES, both positive and negative. The most significant negative impacts (ES) were the depletion of water resources and erosion, while the positive impacts included regional development and job creation. The most notable changes, positive and negative, were observed in the physical and anthropic environment, with a lesser impact on the biotic environment.

Carbon monoxide (CO) is a colorless, odorless gas emitted from carbon fuel combustion. In this study we monitored indoor carbon monoxide (CO) levels for 120 homes over three seasons in the North Denver metropolitan region as part of an environmental justice initiative to quantify health and social well-being impacts from a major freeway construction upgrade nearby. Urban outdoor CO levels are typically very low (less than 1 ppm in Denver) due to air pollution control strategies and technologies implemented over the past several decades. However, people can still be exposed to higher than outdoor levels of CO in their homes due to the operation of indoor appliances that use carbon fuels such as natural gas. Our data show that ~10% of the homes had consistent daily average levels of CO above 3.5 ppm and 24-57% of the homes showed peaks greater than 9 ppm. While much higher levels can result in CO poisoning and fatalities, these lower levels of CO have been associated with adverse health impacts, especially pregnant women, and sensitive populations. Our results highlight the need for increasing awareness regarding CO exposures in homes with gas appliances and motivate the transition from non-electrified homes toward electrification.

The purpose of this experiment was to assess the morphological parameters and dry matter yield of Brachiaria decumbens ILRI-10871 grown for two years under four fertilizer rates (0,100, 300kg N and manure). The field experiment was carried out at Robit Bata Kebele in the Bahir Dar Zuria district of Amhara region, Ethiopia. Each 9-m2 plot in the treatments was arranged in a 4x2 factorial configuration in a randomized complete block design with three replications. Morphological data were collected from 10 randomly selected plants grown in the middle rows of each plot. All recorded datasets were subjected to a general linear model procedure of SAS (9.0) at a significance level of alpha

By using a two-stage physiologically based extraction test (PBET) and (W-PBET), the authors of this paper have estimated the bioaccessibility of metals (Pb and Fe) and their compounds in the GI tract of waterfowl and mammals. It has been shown that the metals (Pb and Fe) have low bioaccessibility; combined with the short time of shot exposition at the GI tract, this eliminates the risk of toxic effects in the case of shot ingestion by waterfowl. It has also been discovered that there is a significant difference in the bioaccessibility of metals and their compounds. A model was proposed and tested to predict the toxic effects of lead on biological objects depending on the threshold mass of consumption. This model takes into account data on the bioavailability of lead and regulatory values indicating dangerous concentrations of lead.

The morphology, internal architecture, and emplacement mechanisms of the Central Atlantic Magmatic Province (CAMP) lava flows of the Hartford and Deerfield basins (USA) are presented. The Talcott, Holyoke, and Hampden formations within the Hartford basin constitute distinct basaltic units, each exhibiting chemical, mineralogical, and structural differences corresponding to flow fields. Each flow field was the result of several sustained eruptions that produced both inflated pahoehoe flows and subaquatic extrusions: 1–5 eruptions in the Talcott formation and 1-2 in Holyoke and Hampden basalts, where simple flows are dominant. The Deerfield basin displays the Deerfield basalt unit, characterized by pillow lavas and sheet lobes, aligning chemically and mineralogically with the Holyoke basalt unit. Overall, the studied flow fields are composed of thick, simple pahoehoe flows that display the entire range of pahoehoe morphology, including inflated lobes. The three-partite structure of sheet lobes, vertical distribution of vesicles, and segregation structures are typical. The characteristics of the volcanic pile suggest slow emplacement during sustained eruptive episodes and are compatible with a continental basaltic succession facies model. The studied CAMP basalts of the eastern United States are correlated with the well-exposed examples on both sides of the Atlantic Ocean (Canada, Portugal, and Morocco).

The role that aquatic aerosols might play in inter-ecosystem exchange in freshwater riparian environments has largely been understudied. In these environments, where freshwater streams are used both as drinking water and for treated waste disposal, water features like waterfalls, downed trees, and increased streamflow can serve as bioaerosol producers. Such water features could have an important role in the bacterial colonization of surrounding surfaces, including the riparian phyllosphere. In this study, we explore the influence of a freshwater stream’s bacterial community composition and micropollution on riparian maple leaves exposed to bioaerosols produced from the stream. Using culture-based and non-culture-based techniques, we compared phylloplane microbial communities in riparian zones, adjacent non-riparian forested zones, and the surface waters of the stream. In this system, riparian zone maple leaf surfaces had higher bacterial counts than non-riparian zone trees. Using metagenomic profiling of the 16S rRNA gene, we found that, while microbial communities on leaves in both riparian zone and forested sites were diverse, riparian zone bacterial communities were significantly more diverse. In addition, we found that riparian leaf bacterial communities shared more amplicon sequence variants (ASVs) with stream bacterial communities than forest leaves, indicating that the riparian zone phyllosphere is likely influenced by bioaerosols produced from water surfaces.

Oil spills upset the delicate balance of the environment. Remediation methods are employed to recover areas affected by contaminants. Green surfactants have considerable potential with regards to enhancing environmental remediation methods. The aim of the present study was to formulate a green natural detergent containing the biosurfactant produced by Starmerella bombicola ATCC 22214 grown in mineral medium containing 1.2% canola oil, 10% sucrose, and 0.5% corn steep liquor. The biosurfactant reduced surface tension to 31.84 mN/m and was produced at a yield of 22 g/L. Twelve formulations were initially proposed using cottonseed oil as the natural solvent and three different stabilisers (vegetable wax, hydroxyethyl cellulose, and sodium alginate). The natural detergent was assessed with regards to emulsifying capacity and stability over a 10-day period. Ecotoxicity of the formulated detergent was investigated using the marine recruitment test on metal plates covered with paint into which the biosurfactant was incorporated as well as tests with the microcrustacean Artemia salina and vegetable seeds. Dispersing capacity and the potential for removing oil from rock surfaces were also investigated. The formulation designated H, which was composed of 1% biosurfactant, 40% cottonseed oil and 2% hydroxyethyl cellulose, achieved the best results. The formulation exhibited both stability and emulsifying capacity (100% of petroleum). The ecotoxicity tests revealed no significant toxicity, demonstrating the safety of the natural detergent. The detergent achieved satisfactory oil dispersion and solubilised 98% of oil impregnated on rock. The results indicate the potential application of the natural detergent formulated in this study for the efficient remediation of environmental compartments contaminated with oil and petroleum derivatives.

The benthic matrix acts as a key natural archive where the memory of long-term timescale environmental changes is recorded. Some ecological and chemical features of fjord sediments were explored during the AREX cruise carried out in the Svalbard archipelago in summer 2021. The activity rates of the enzymes leucine aminopeptidase (LAP), beta-glucosidase (GLU) and alkaline phosphatase (AP) and community-level physiological profiles (CLPP) were studied with the aim of determining the functional diversity of the benthic microbial community, while bacterial isolates were screened for their susceptibility to antibiotic molecules in order to explore the role of these extreme environments as potential reservoirs of antibiotic resistance. Enzyme activity rates were obtained by fluorogenic substrates, CLPP by Biolog Ecoplates; antibiotic susceptibility assays were performed through the standard disk diffusion method. Spatial trends observed in the functional profiles of the microbial community suggested the variability in the microbial community composition, presumably related to the patchy distribution of organic substrates. Complex Carbon sources, carbohydrates and amino acids were the organic polymers preferentially metabolized by the microbial community. Multiple resistance to ampicillin, clindamycin and gentamycin was detected in all the sampled sediments, excepting in the southern Hornsund area, stressing the role of sediments as a potential reservoir of chemical wastes ascribable to antibiotic residuals. This study provides new insights on the health status of fjord sediments of West Spitsbergen applying a dual ecological and biochemical approach. Microbial communities in the fjord sediments showed globally a good functional diversity, suggesting their versatility to rapidly react to changing conditions.

Unmanned Aerial Vehicles (UAVs) equipped with hyperspectral imagers have emerged as an essential technology for the characterization of inland water bodies. The high spectral and spatial resolutions of these systems enable the retrieval of a plethora of optically-active water quality parameters via band ratio algorithms and machine learning methods. However, fitting and validating these models requires access to sufficient quantities of in situ reference data which are time-consuming and expensive to obtain. In this study, we demonstrate how the Generative Topographic Mapping (GTM), a Bayesian realization of the Self-organizing Map, can be used to visualize high-dimensional hyperspectral imagery and extract spectral signatures corresponding to unique endmembers present in the water. Using data collected across a North Texas pond, we first apply the GTM to visualize the distribution of captured reflectance spectra revealing small-scale spatial variability of water composition. Next, we demonstrate how the nodes of the fitted GTM can be interpreted as unique spectral endmembers. Using extracted endmembers together with the normalized spectral similarity score, we are able to efficiently map the abundance of near shore algae as well as the evolution of a rhodamine tracer dye used to simulate water contamination by a localized source.

Recently, environmental degradation has become an international issue due to the extensive economic activities around the globe. This aspect demands the policymakers' and new researchers’ emphasis. Hence, the present article examines the impact of corporate social responsibilities (CSR) to community and environment on the environmental performance (ENP) of the manufacturing industry in China. The article also investigates the mediating role of green innovation and environmental strategy among CSR to community, CSR to environment and ENP of manufacturing industry in China. The article gets the primary data from the selected employees of the manufacturing industry using questionnaires. The article also tests the data's validity and reliability, and association among variables using smart-PLS. The outcomes indicated that CSR to environment has a positive association with ENP. The outcomes also revealed that green innovation and environmental strategy significantly mediate among CSR to community, CSR to environment and ENP. The article guides the policymakers in making policies related to improve ENP using CSR to environment and green innovation.

In this study, we develop a stochastic partial differential equation (SPDE) model to assess the regional severity of temperature increases due to global warming. The model incorporates various stochastic processes to account for uncertainties such as solar explosions, economic upheavals, rising emissions, and irreversible changes in the climate system. Our base temperature model, influenced by latitude, is enhanced by these random factors to simulate realistic and diverse outcomes of climate change. Numerical simulations on a global grid provide a heatmap representing potential temperature increase severity across different regions. The results highlight the significant impact on tropical and polar regions, demonstrating the utility of SPDE models in understanding and predicting the complex dynamics of climate change. This approach offers valuable insights for policymakers and researchers aiming to develop adaptive strategies for mitigating the adverse effects of global warming.

Smallholder farmers in Ethiopia face increasing challenges from climate change and variability, which threaten their food security and livelihoods. This study examines how adopting single and combined climate change adaptation practices affects their vulnerability to food insecurity in Bench Maji Zone, southwest Ethiopia. Through multistage sampling, data was gathered from 390 rural households in four climate-prone districts. The study examines the impacts resulting from both individual and combined implementations of adaptation techniques. These techniques encompass crop management practices, soil and water conservation measures, and livelihood portfolio diversification strategies. The study employed the multinomial endogenous treatment effect regression model to address selection bias and endogeneity resulting from various sources of heterogeneity, whether observed or unobserved. The results show that farmers who adopted adaptation practices were less vulnerable to food insecurity than those who did not. The study also finds that adopting multiple practices has a more significant impact than adopting single practices. Our findings suggest that implementing climate change adaptation strategies can increase the resilience of smallholder farmers in the study area and decrease their vulnerability to food insecurity. The study recommends supporting farmers in adopting these strategies through research and development, information dissemination, and collaborations among farmers, researchers, and extension services.

Using the limits of a specific watershed (river basin) to establish boundaries of precise rural and urban intervention strategies, can conduce to a better understanding of the dynamics between natural hydro-morphology of a hydrological region, water infrastructures (damns, canals, reservoirs) and urban and rural fabric. To perform watershed-based planning approaches with valuable indicators is necessary to generate hybrid cartographies combining urban, architectural, agricultural and hydrological boundaries. In some countries, the necessary information to produce these cartographies is not available; however, is possible to create fundamental layers using GIS software and national geospatial information and subsequently perform algorithmic calculations in the same software. Once these cartographies are developed and analyzed for a determined basin is possible to observe scenarios where rural and urban planning are better suited for precise hydric-urban restoration. In the following article a series of hybrid cartographies are presented. These types of maps are useful for interpretation of water usage flow in rural communities and their agricultural productive surfaces, and ultimately for analytical purposes in dealing with hydrological alterations of the water cycle. The diagnostic results can be used to develop specific rural interventions for fluvial restoration in territorial contexts, and improvement on hydrological infrastructure and the hydrological region water network.

The advancement of mechanization in forestry has bolstered productivity within the sector while simultaneously precipitating impacts necessitating deeper comprehension for the attainment of heightened levels of environmental sustainability in forestry management. The aim of this study was to apply an instrument for assessing the environmental damage and impacts of forest harvesting in commercial Eucalyptus plantations, based on a combination of methodologies. The environmental impact assessment methodology for forest harvesting was applied by combining interaction network approaches and impact assessment matrices. This methodology was then applied to a commercial Eucalyptus plantation in the municipality of São Pedro, state of São Paulo, Brazil. The results show that timber transportation activities had the highest positive and negative environmental indices. The most significant negative impacts refer to the depletion of water resources and erosion, while the positive impacts are regional development and job creation. The most significant changes, both positive and negative, were observed in a greater number of environmental impacts for the physical and anthropic environment, with fewer for the biotic environment. The combination of methodologies has potential as an expedient tool for planning forestry operations, providing practical results for decision-making, making production more sustainable and applicable to different crops and production systems.

Environmental chemicals, including PFAS (per- and polyfluoroalkyl substances), pesticides, industrial chemicals, and consumer products, commonly exist as mixtures. These substances are frequently exposed or co-exposed in varying concentrations, leading to potentially hazardous health effects such as cancer in humans. Thus, understanding the dose-dependent toxicity of chemical mixtures is important for assessing health risks. In this context, comprehensive methods for assessing the toxicity and identifying the mechanisms of harmful chemical mixtures are currently lacking. Here, the dose-dependent toxicity assessments of chemical mixtures are performed in three methodologically distinct phases. In the first phase, we evaluated our machine learning method (AI-HNN) and pathophysiology method (CPTM) for predicting toxicity. In the second phase, we integrated AI-HNN and CPTM to establish a comprehensive new approach method (NAM) framework called AI-CPTM, targeted at refining prediction accuracy and providing a comprehensive understanding of toxicity mechanisms. The third phase involved experimental validations of the AI-CPTM predictions. Initially, we developed binary, multiclass classification, and regression models to predict binary, categorical toxicity, and toxic potencies, using nearly a thousand experimental mixtures. This empirical dataset was expanded with virtual mixtures compensating the lack of experimental data and broadening the scope of the dataset. For comparison, we also developed additional machine learning models based on RF, Bagging, AdaBoost, SVR, GB, KR, DT, KN, and Consensus methods. The models achieved overall accuracies of over 80% with AUC values exceeding 90%. The regression models achieved an R2 >0.88. In the second phase, we innovatively integrated HNN-derived toxicity predictions with Z-scores from CPTM, resulting method called AI-CPTM. In the final phase, we demonstrated the superior performance of AI-CPTM through rigorous literature and statistical performance validations. Additionally, the predictive capability of AI-CPTM, including for PFAS mixtures and their interaction effects, was demonstrated by experimental validations using dose-response zebrafish embryo toxicity assays. Overall, the AI-CPTM approach significantly improves upon the limitations of standalone models and has shown extensive enrichments in the identification of toxic chemicals and mixtures. Further experimental studies involving human cell models, patient-derived xenografts, and investigations into the toxicity of multiple mixtures are currently underway.

Heavy metals represent a class of chemical elements that includes metalloids, bases and transition metals, lanthanides and actinides. They are distinguished for their toxicity in small concentrations and for their negative effects on the environment and human health. They are present in various samples, mainly in water, industrial waste and food. The determination of heavy metals is carried out mainly by analytical methods, using spectroscopy, spectrometry and electroanalysis, while studies are being carried out for the development of new and faster methodologies and techniques for their analysis, with particular emphasis on voltammetry. This review deals with the determination of heavy metals mainly in environmental samples (water) using voltammetry. In particular, the methods of their determination are evaluated in terms of sensitivity, selectivity and applicability.

Amazon tropical forest is actually subject to strong deforestation, generally originated from illegal logging, resulting in ecological, environmental and economic problems. Aiming stop deforestation and timber commercialization of illegal logging of tropical forest, new laws has been introduced in many countries. Here we investigated the utility of DNA fingerprinting of nuclear and cytoplasmatic SNPs to timber tracking the intensive logged and commercialized of the Amazonian Neotropical tree Jacaranda copaia. Samples of 832 individuals from 43 populations from Bolivia, Brazil, French Guiana, and Peru were used to investigate the power of 113 nuclear SNPs, 11 CpSNPs, and four MtSNP loci to determine the country and population origin. The genetic differentiation among all populations and contries was high (0.233–0.942), specialy for CpMtSNP (generally>0.6) loci, and there is a strong isolation by distance pathern among populations, favoring the group or individual samples tracking to correct site. For self-assignment tests, we were able to 100% correct determine country and population origin of all samples using all SNPs. Our results show that the use of 128 SNP markers is suitable to correct determination of country and population site of J. copaia timber origin and very useful tool for customs and local and international policies.

Air pollution knows no boundaries, which means for a city or a region to attain clean air standards, must not only look at the emission sources within its own administrative boundary, but also at sources in the immediate vicinity and those originating from long-range transport. And there is a limit to how much area can be explored to evaluate, govern, and manage as designated airsheds for cities and larger regions. This paper discusses the need from an official airshed framework for India’s air quality management, urban airsheds designated for India’s 131 non-attainment cities under the national clean air programme, and proposes climatically and geographically appropriate regional airsheds to support long-term planning. Between 28 states, eight union territories, 36 meteorological sub-regional divisions, and six regional meteorological departments, establishing the proposed 15 regional airsheds for integrated and collaborative air quality management across India is a unique opportunity.

physicochemical methods was effective for the degradation of organics, but was highly hampered by the salt coexist in the complex wastewater matrix, resulting in low degradation dynamics. In this study, ZnO loaded carbon nitride (Zn-CNx) was synthesized and exhibited an excellent performance for 2,4-dichlorophenol (2,4-DCP) degradation (0.63 mg/L/min) in photcatalysis system. The doping of Zn into CNx contributed to the increased light absorption of the catalyst and the optimized electron transport pathways. The quenching experiment results proved that the superoxide radicals (·O2-) played a dominant role and hydroxyl radical (·OH) played a secondary role. Notably, the 2,4-DCP removal increased slightly with increasing salt content. As the initial pH increased from 3 to 11, the first-order degradation kinetic constants increased significantly, and the final pH was equilibrized in the range of 6.01-6.59. This study provided a high performance catalyst for photcatalysis and the mechanism for the effective degradation of 2,4-DCP under high salinity condition.

Deploying onshore wind energy as a cornerstone of future global energy systems challenges societies and decision-makers worldwide. Expanding wind energy should contribute to a more sustainable electricity generation without harnessing humans and their environment. Opponents often highlight the negative environmental impacts of wind energy to impede its expansion. This study reviews 152 studies to synthesize, summarize, and discuss critically the current knowledge, research gaps, and mitigation strategies on the environmental impacts of onshore wind energy. The investigated effects comprise impacts on the abiotic and biotic environment, with birds and bats in particular, noise and visual impacts. Effects are discussed in the context of social acceptance, other energy technologies, and wind energy expansion in forests. The review illustrates that many effects are highly case-specific and must be more generalizable. Studies are biased regarding the research focus and areas, needing more standardized research methods and long-term measurements. Most studies focus on the direct mortality of birds and bats at wind farms and are concentrated in Europe and North America. Knowledge gaps persist for many impact categories, and the efficacy of mitigation strategies has yet to be proven. More targeted, unbiased research is required that allows for an objective evaluation of the environmental impacts of wind energy and strategies to mitigate them. Impacts, such as those on biodiversity, need to be addressed in the context of other anthropogenic influences and the benefits of wind energy. This forms the basis for a socially acceptable, efficient, and sustainable expansion of wind energy.

The increasing prevalence of species that are detrimental to biodiversity is a major concern, particularly for managers of National Parks. To develop effective programs for controlling weeds, it is essential to have a thorough understanding of the extent and severity of infestations, as well as the contributing factors such as temperature, rainfall, and disturbance. Predicting these factors on a regional scale requires models that can incorporate a wide range of variables in a quantifiable manner, while also assisting with on-ground operations. In this study, we present two Bayesian Network models specifically designed for six significant weed species found along the southern coast of Australia. Our models are based on empirical data collected during a coastal weed survey conducted in 2015 and repeated in 2016. We applied these models to the coastal national parks in the isolated and pristine East Gippsland region. Importantly, the prediction models were developed at two different spatial scales that directly corresponded to the scale of the observations. Our findings indicate that coastal habitats, with their vulnerable environments and prevalence of open dune systems, are particularly susceptible to weed infestations. Moreover, adjacent regions also have the potential for colonization if these infestations are not effectively controlled. Climate-related factors play a role in moderating the potential for colonization, which is a significant concern for weed control efforts in the context of global climate change.

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.

In light of growing concerns over water contamination, particularly in regions like Sindh, Pakistan, this research aimed to evaluate and map the groundwater quality in Taluka Larkana for both drinking and irrigation applications, addressing the expressed worries of the local community. A total of forty groundwater samples were collected from various sources such as hand pumps, taps, and tube wells. These samples underwent comprehensive analysis encompassing parameters including color, odor, taste, turbidity, pH, total hardness (TH), electrical conductivity (EC), and total dissolved solids (TDS), with comparisons drawn against WHO guidelines.Results indicated that taste, color, odor, and turbidity of the groundwater samples generally fell within acceptable ranges. However, EC levels varied from moderately elevated to excessively high. Notably, a significant proportion of samples (84% EC, 21% Cl, 30% Ca, 37% Mg, 22% TH, and 84% TDS) exceeded WHO-recommended thresholds.Assessment via the SPI model classified approximately 16% of samples as moderately contaminated, while 65% were deemed highly contaminated, and 19% were found unsuitable for drinking purposes. These findings underscore the pressing need for concerted efforts to address water quality issues in the region.

A new approach based on input-output (IO) analysis has emerged to estimate the carbon footprints of companies and their products from cradle to gate. While they rely on the same principles as the GHG Protocol, they use a distributed iterative framework to improve the footprint estimations and reduce their uncertainty. While optimal estimations would result if all the world’s companies would enter such a system, this paper shows how such a distributed system could apply to the real world where many enterprises would stay out of the system. We show how it would increase the quality of the estimations with respect the GHG Protocol by integrating scope 1 and scope 2 data of the value chains in the footprint estimations and reducing the part of remaining scope 3 data. To help analyzing uncertainty, we show how to use the scope 1/2/3 decomposition to estimate the biases and the standard deviations of the computed production intensities. We illustrate the model on macroeconomic data for 44 sectors and two regions (Europe and Rest of World), using the Inter-Country Input-Output database (ICIO). Such a system would necessarily rely on Information and Communication Technology since the companies would be permanently interconnected in a large-scale meshed network, using an application protocol for data exchange.

The quality of waste activated sludge produced in urban wastewater treatment systems varies according to the efficiency of the operation of treatment units along the content of microflora and organic carbon. However, these represent a biogas-energy alternative through anaerobic co-digestion, contributing to reducing the environmental impacts caused by their inadequate disposal. Biogas production by the Two-stage production method in batch digesters was evaluated by two qualities of waste activated sludge (SLB50 y SLB90) and with a mixture of two co-substrates: cattle manure (CEV50 y CEV90) and residual edible oil with mixing, pH and temperature control. Bacteria in good quality sludge (SLB90) showed a faster adaptation of 2 days than those in low quality (SLB50) with 25 days lag phase. The highest CH4 production was for SLB90 (303.99cm3 d-1) compared to SLB50 (4.33 cm3 d-1); while cow manure sludge mixture (CEV90) contributed to increasing production of CH4 (42 422.8 cm3 d-1) compared to CEV50 (12 881.45 cm3 CH4 d-1), while in residual edible oil mixture they were 767.32 cm3 d-1 and 211.42 cm3 d-1 for CAV90 y CAV50, respectively. The addition of sludge co-substrates improves the nutrient balance, C/N rate and micro flora diversity; consequently methane production improves too; this methodology could be integrated into concepts of Circular economy.

During the last decade, Bangladesh has been experienced a significant climatic anomalies which lead to an increase in magnitude and frequency of various climate relate extreme events. Climate scientists substantiate that global temperature and precipitation pattern is expected to change, which may result in consequential impact on agriculture, livelihood, and ecosystem. Bangladesh is therefore likely to face substantial challenges in the coming decades. In order to adequately understand this complex, dynamic phenomena, Analyzing historical Climate change scenarios as well as projecting its future trends is a great concern for researcher. This study aims to analyzes/ historical climatic data from (1901-2020), and predict future temperature and precipitation patterns in Bangladesh using CMIP6 data. Data used in this study (Observed data is from CRU TS 4.05 and future data is from CMIP6) have been acquired from WorldClim v2.1. Various methods including correlation, regression, standard deviation, correlation matrix, percentiles, cell statistics, and IDW interpolation were performed to analyze the trends, variability and spatial patterns of temperature and rainfall. This study revealed that Over the historical study period (1901-2020) Bangladesh has been experienced a significant warming trend with an average increase in temperature 2°C and with annual decline of the total precipitation 607.26 mm along with a shift towards drier conditions despite weak correlation with hotter years. Projected climate models represents that Bangladesh minimum temperature is expected to increase from 1°C to 4.4°C as well as maximum temperatures from 1°C to 4.1°C by 2100. Moreover, projected precipitation is expected to increase by 480.38 mm, with the biggest rises during monsoon months. Regional variations in temperature and precipitation are again expected, with the Southeast (SE) likely experiencing the most significant warming and the Northeast (NE) seeing the most substantial increase in precipitation.

Water is a fundamental resource for ecosystems, humans, and the development of all economic sectors; it is necessary to identify and evaluate its environmental pressures or impacts. The water footprint (WF) is an appropriate indicator for the consumption of water used to produce a product. The present study uses this tool to evaluate the green and blue water requirements and the sustainability of irrigation water use for agroindustrial avocado production in Ziracuaretiro, Michoacán (2012-2021). Our analysis was based on aggregating weather and soil data at the municipal level and official government databases of avocado cultivated surface, fruit production, and water rights concessions. The analysis considers the homogeneity of information throughout the study area. We estimated that rainfed plantations require 839.03 m³/ton and irrigated plantations require 2355.80 m³/ton, with an average of 1597.47 m³/ton. In addition, we determined that avocado cultivation can demand up to 124.3% of agricultural water concessions in this municipality. In addition to the WF estimates, the analysis indicates that such studies are fundamental for decision-makers to develop and implement water use-efficiency strategies and shows the need for further research related to water consumption of avocado as a crop at more detailed scales to reduce uncertainty.

Introduction: Agricultural practices significantly influence soil microbial populations and physicochemical properties, which are crucial for crop growth and quality. This study aims to investigate the impact of different agrochemical applications on soil microbial dynamics, soil physicochemical properties, as well as yield and proximate properties of maize. Methods: Carefully gathered topsoil samples at depths ranging from 1 to 15 cm, were transported to Jimma University to cultivate maize. Over a period of up to 120 days, soil and maize samples were collected at specified days to analyze various parameters, including soil pH, microbial populations, as well as nutrient content both in soil and plants. The collected data was statistically analyzed using one-way ANOVA, with a significance level of p < 0.05. Results: The soil bacterial and fungal populations were measured on days 5, 10, 20, 40, 80, and 120. The highest total mesophilic bacterial count (TMBC) was measured in the pots containing compost (G) and the lowest in pots that received macronutrient fertilizers and glyphosates (B) (i.e. 91.8 x 105 and 13.13 x 105 cfu/g of soil, respectively). The highest total mesophilic fungal count (TMFC) was observed in pots containing glyphosates and compost (F) (i.e. 67.25 x 104 cfu/g soil) and again the lowest in pot treated with macronutrient fertilizers and glyphosate (B) (i.e. 3.23 x 104 cfu/g soil). Moreover, the pots treated with macronutrient fertilizers and glyphosate (B), macronutrient fertilizers (A), and micronutrient fertilizers (C) exhibited the lowest levels of Fe and Zn. Furthermore, the pots receiving macronutrient fertilizer combined with glyphosate (B), as well as those receiving macronutrient fertilizers (A) alone had the lowest concentrations of Mn and Cu micronutrients. Finally, in maize the lowest protein, fats, and carbohydrates (g/100g) were found in the pots treated with macronutrient fertilizer combined with glyphosate (B, 2.21 ± 0.2), micronutrient fertilizer (C, 8.57 ± 0.25), and glyphosates only (D, 57.34 ± 0.1). Maize treated with compost (G) showed the highest levels of Fe, Cu, and Zn, while macronutrient fertilizer combined with glyphosate (B) resulted in the lowest content of these micronutrients. Additionally, maize receiving micronutrient fertilizer (C) had the highest concentration of Mn, whereas those treated with glyphosates (D) had the lowest. Conclusions: Significant variations in soil’s mesophilic bacterial and fungal populations, micronutrient levels, and nutritional composition were observed, indicating treatment-related changes. Generally, treatment with micromineral fertilizer combined with glyphosate (B) seemed to deplete the soil while compost treatment improved. Compost-treated soils exhibited the highest mesophilic bacterial and fungal count, as well as Fe and Zn micronutrient concentrations. The use of agrochemicals also had a negative effect on maize yield quality. The fluctuations in the soil parameters underscore the multifaceted effects of agrochemical treatments.

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants of emerging concern, recognized for their toxicity and potential carcinogenic properties. PFAS chemicals are reported to act as endocrine disruptors through their interactions with various nuclear receptors (NRs). Despite their significant impact, comprehensive screenings and detailed analyses of PFAS binding strengths at both the orthosteric and allosteric sites of NRs are currently lacking in the literature. Our study addresses this gap by focusing on the binding interaction analysis of both common and uncommon PFAS with key nuclear receptors such as the vitamin D receptor (VDR), peroxisome proliferator-activated receptor gamma (PPARγ), pregnane X receptor (PXR), and estrogen receptor alpha (ERα). We used advanced docking simulations to screen 9,507 PFAS chemicals at the orthosteric and allosteric sites of the PPARγ, PXR, VDR, and ERα. We verified the accuracy of our docking protocol through multiple docking procedures and validations. The python code used for PFAS chemical screening is deposited in the supplementary file. Among the PFAS assessed at the orthosteric site of the VDR, 21 demonstrated similar binding affinities compared to the calcitriol, while 130 PFAS, exhibited stronger binding affinities than calcitriol. At the VDR allosteric site, where lithocholic acid (LCA) natively binds, 412 PFAS matched the binding energies of LCA, and 2,229 showed even greater binding energies. Similar testing on the PXR, PPARγ, and ERα revealed that the orthosteric site of PPARγ had 1,863 PFAS binding with a higher affinity than native ligand ET1 and 693 PFAS binding at the allosteric site with greater affinity than T35 native ligand. At the PXR orthosteric site, 650 PFAS bound with a greater affinity than native ligand 4WH, while at the allosteric site, 9,148 PFAS demonstrated a greater binding affinity than the known allosetric ligand glycerol. At the orthosteric site of ERα, 40 PFAS displayed binding with a greater affinity than the native ligand estradiol and at the allosteric site, only 8 PFAS exhibited greater binding affinity than coactivator ligand SRC-1. Further, our mixture modeling analysis indicates that PFAS can bind in various combinations with themselves and with endogenous or native ligands simultaneously, to disrupt the endocrine system and cause carcinogenic responses. These findings reveal that PFAS can interfere with nuclear receptor activity by displacing endogenous or native ligands by binding to the orthosteric and allosteric sites. This study elucidates the mechanisms through which PFAS exert their endocrine-disrupting effects, potentially leading to more targeted environmental regulations and therapeutic strategies. Importantly, this study is the first to explore the binding of PFAS at allosteric sites and to model PFAS mixtures at nuclear receptors. Given the high concentration and persistence of PFAS in humans, this study called for the urgent need for further research into the carcinogenic mechanisms of PFAS and the development of intervention strategies that target nuclear receptors. Our ongoing studies extend these findings by further investigating the interactions of PFAS and co-exposed chemicals with nuclear receptors. These investigations are supported by experimental verification, which will enhance our understanding of PFAS broad effects and aid in the design of effective mitigation strategies.

Drought and arsenic contamination pose a serious threat to global rice crop yield. Existing solutions focus on either heavy metal or drought remediation, but not both. Examination of the Oryza sativa metagenome via the National Center for Biotechnology Information (NCBI) database revealed promising candidates within the aquaporin gene family capable of efficiently mitigating both arsenic toxicity and drought stress. Rice cotyledons were genetically augmented with arsenic-resistant OsNIP2;1 and OsNIP3;2 genes, and drought-resistant OsPIP2;2 genes. In moderate drought conditions and 25 ppm arsenic-contaminated soil, transgenic plants showed drought tolerance and reduced translocation of arsenic from root to shoot. Soil arsenic levels plummeted from 25 ppm to 5 ppm, demonstrating the strategy's efficacy. Statistical significance was confirmed using T tests. Thus, aquaporin-augmented Oryza sativa offers a promising solution to mitigate both arsenic and drought stress in rice plants improving crop yield and facilitating soil decontamination.

Marine finfish landings in Cuba have decreased during the last 30 years. However, in Cuba's most productive fishing region, certain species, including rays, herrings, and snappers, have increased landings over the past decade. Despite these anomalies, no comprehensive analysis of the interactions between multispecies landing dynamics, environmental factors, and fishing effort has been carried out. This study estimates the dynamics of multispecies finfish landings between 1981 and 2017 on the southeastern coast of Cuba. Dynamic factor analyses (DFA) were performed to identify common landing trends across multiple species and their relationship with fishing effort and environmental variables. During the period analyzed, finfish landings and fishing effort decreased by 46% and over 80%, respectively. Despite concerns about overfishing, landings per unit of effort (LPUE) increased by 2.8 times, suggesting the decline in landings was closely linked to decreasing fishing effort and Atlantic Multidecadal Oscillation cycles, with delays of 2 and 3 years. The study highlights the changing relationship between landings and fishing effort, suggesting that LPUE may not accurately reflect true stock abundance. The findings of this study will assist in integrating the dynamics of finfish species, ecosystem status, and management actions for Cuba’s most productive fishing zone.

The objective of this study is to investigate the correlation between the advancement of flood research and the utilization of Geographic Information Systems (GIS) and multi-criteria evaluation techniques, both from a theoretical and practical standpoint. Additionally, this research seeks to identify potential ways to address the aforementioned relationship. The present study employs a thorough literature review methodology. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, a total of 28 papers were identified and included in the analysis, as they fulfilled the predetermined criteria. The findings of the study indicate that current research pertaining to the utilization of Geographic Information Systems (GIS) and multicriteria evaluation in flood control mostly centers around five key areas, namely natural factors, technical considerations, institutional factors, socio-economic factors, and financial factors. However, the aforementioned studies have identified specific areas of focus, including natural factors pertaining to climate, technical factors related to infrastructure, institutional factors concerning flood management strategies, socio-economic factors associated with demographics, and financial factors pertaining to financial obligations. However, there is a limited amount of existing research that specifically addresses flood management in developing nations. Therefore, it is anticipated that this study can serve as a valuable resource for future research endeavors, particularly in informing decision-making processes pertaining to the establishment of priorities in flood control plans. The primary subject of this study pertains to flood management occurrences within developing nations.

Water quality assessment stands as a fundamental step in water resource management. In addition to substances and organisms present in the water, land use and land cover are two factors affecting also water quality. This study analyzed the correlation and influence between water quality and land use and land cover in the Miranda River Basin (MRB) and the natural wetlands in the Pantanal Biome. Using a watershed-wide approach, results suggested that water quality management policies can be considered in terms of sub-basins (smaller planning units). The Water Quality Index (WQI) was considered GOOD or EXCELLENT throughout the MRB. It was observed that the natural wetlands have the capacity to contribute to improve WQI, with reductions in thermotolerant coliforms and turbidity; however, high values were found for thermotolerant coliforms, a temporal increasing trend of biochemical oxygen demand (BOD), and a reduction in dissolved oxygen and total phosphorus. Conversely, it was found in these flooded areas a trend of decrease in dissolved oxygen and an increase in BOD concentrations. Natural wetlands play important hydrological and ecological roles in water quality, storing, removing, and cycling nutrients. They are highly relevant areas for defining watershed management and conservation strategies, environmental protection, and providing ecosystem services.

The present work reports the effective method for removal of inorganic and organic pollutants using membranes based on different carbonaceous materials. The membranes were prepared based on cellulose acetate (18 wt. %), polyvinylpyrrolidone as a pore generating agent (2 wt. %) and activated carbon (1 wt.%). Activated carbons were developed from residues after extraction of mushroom Inonotus obliguus using microwave radiation. It has been shown that addition of activated carbon the physical (porosity, equilibrium water content and permeability) and chemical (content of the surface oxygen group) properties of the membranes. The addition of carbon material has a positive effect on the removal of copper ions from their aqueous solutions by the cellulose-carbon composites obtained. Moreover, the membranes were proved to be more effective in removal of copper ions than iron ones and phenol. The membranes were found to show higher effectiveness in copper removal from a solution of the initial concentration 800 mg/L. The most efficient in copper ions removal was the membrane containing urea-enriched activated carbon.

Ultramafic rocks become promising candidates for carbon sequestration by enhanced carbon dioxide (CO2) mineralization strategies due to their highly CO2-reactive mineral composition and its abundant availability. This study reports a mineralogy and microtextures of a representative ultramafic rock from the Ma-Hin Creek in northern Thailand and observes evidence of CO2 mineralization occurring through the interaction between CO2 and the rock with the existence of water under ambient conditions. After sample collection, rock description was determined by optical petrographic analysis. The rock petrography reveals a cumulated wehrlite comprising over 50% olivine and minor amounts of clinopyroxene, plagioclase, and chromian spinel. Approximately 25% of the wehrlite has altered to serpentine and chlorite. A series of CO2 batch experiments were conducted on six different rock sizes at a temperature of 40°C and pressure of 1 atm over five consecutive days. The post-experimental products were dried, weighed, and geochemically analyzed to detect changes in mineral species. Experimental results showed that product weight and the presence of calcite increased with reducing grain size. Additionally, the modal mineralogy of the wehrlite theoretically suggests a potential CO2 uptake of up to 53%, which is higher than the average uptake values of mafic rocks. These findings support the suitable rock investigation approach and the preliminary assessment of carbon mineralization potential, contributing to enhanced rock weathering techniques for CO2 removal that could be adopted by mining and rock supplier industries.

Keywords: standing water bodies, glacial lakes, freshwater biodiversity, eutrophication; nature conservation network

High Education Institutions (HEI) play a key role in fostering sustainability since students will be future active society members. By providing them with the knowledge, skills, and mindset needed to address environmental challenges, they can contribute to increase sustainability in a long-term approach. With the effects of climate change strongly affecting water availability across planet, it is increasingly relevant to understand if higher education students are aware of this situation, to develop adequate measures to promote sustainable behaviors regarding water uses. This study aimed to assess students’ perceptions regarding water efficiency through a questionnaire submitted in 7 HEI in Portugal. Students recognized the importance of water with older students, women and science students demonstrating a greater awareness. Inspite of this 27% students do not know what the average water consumption in Portugal is and only 18% accurately reported the consumption range in Portugal. There is also a lack of knowledge (&gt;50% students) if common water efficiency measures are applied in their HEI. The main information sources identified by the students were “social communication” and “internet/social media”, revealing that water efficiency knowledge transfer in high education can be improved.

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes financial damage to the environment. In the case of air pollution, harmful and foreign substances in the air reach an amount and density above normal values. Air pollution also causes climate change, which affects global warming. Particulate matter is a harmful substance that harms the health of humans and other living things, causes air pollution, increases radiation, and negatively affects cloud formation. Particulate matter is extremely small solid particles and liquid droplets suspended in the air. PM10, which is less than 10 microns in diameter, is defined as small particles that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. Many criteria affect PM10 density and changes in density. The main criteria are vehicle traffic and fuel consumption, industrialization, coal, fuel oil and wood-burning heaters, greenhouse gas impact, and unregulated urbanization. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data between 2019 and 2023 obtained from the Air Monitoring Station in Kocaeli, Türkiye are used. After determining the criteria affecting PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking expert decision-maker opinions. The proposed decision-making model aims to guide obtaining the important causes of PM10 emission in terms of danger and focusing on these causes. Additionally, PM10 data is analyzed in the context of Covid-19 and a statistical analysis is made. One-way ANOVA is used to evaluate whether there is a significant difference in the average monthly data over the years. Games-Howell test, one of the post-hoc tests, is used for differences between groups (years). The study is important in that it provides a focus on the criteria affecting PM10 with an intuitive fuzzy perspective, along with statistical analysis.

During an interdisciplinary study of the mire “Pod Małym Śnieżnikiem”, a very old specimen of the Norway spruce (Picea abies L.) was encountered. The aim of the present work was to perform a detailed examination of this tree, to compare it to other spruce trees on the mire, and to provide support for establishing protection for this tree stand. Tree-ring cores were sampled at 1.3 m above ground using Pressler borer, in two field campaigns: in June and July 2023, the latter campaign aiming to find the oldest trees. A total of 46 trees were sampled, yielding 84 measuring radii. Tree ring widths were measured down to 0.01 mm under a stereomicroscope. The oldest sampled tree yielded a total of 370 tree rings in the two radii, representing the period 1653–2022. The average tree ring width for TM15 equals 0.33 mm/year, and shows low values (on average 0.19 mm/year) for the period 1742–1943, i.e., during the Little Ice Age cooling. TM15 does not stand out from other trees from the population with respect to height or trunk diameter. A comparison of the age of this tree to the oldest spruce trees in Poland indicates that it is one of the longest living specimens of this species. Considering the natural character of the stand, the remaining flora and the peat-forming processes taking place within the mire “Pod Małym Śnieżnikiem”, we argue that the mire should become protected by the law as soon as possible in order to preserve this valuable high-mountain habitat.

River estuaries are dynamic and complex ecosystems influenced by various natural processes, including climatic fluctuations and anthropogenic activities. The Pearl River estuary (PRE), one of the largest in China, receives significant land-based pollutants due to its proximity to densely populated areas and urban development. This study aimed to characterize the composition, diversity, and distribution patterns of sediment microbial communities (Bacteria, Archaea, and Eukaryotes) and investigated the connection with environmental parameters within the PRE and adjacent shelf. Physicochemical conditions, such as oxygen levels, nitrogen compounds, and carbon content, were analyzed. The study found that the microbial community structure was mainly influenced by site location and core depth, which together explained approximately 67% of the variation in each kingdom. Sites and core depths varied in sediment properties such as organic matter content and redox conditions, leading to distinct microbial groups associated with specific chemical properties of the sediment, notably C/N ratio and NH4+ concentration. Despite these differences, certain dominant taxonomic groups were consistently present across all sites: Gammaproteobacteria in Bacteria; Bathyarchaeia, Nitrososphaeria, and Thermoplasmata in Archaea; and SAR in Eukaryota. The community diversity index was the highest in the bacteria kingdom, while the lowest values were observed at site P03 across the three kingdoms and were significantly different from all other sites. Overall, this study underscores the critical role of microbial communities in shaping biogeochemical processes in estuarine environments and their sensitivity to environmental changes, providing valuable information for managing and preserving the health of estuaries and coastal ecosystems.

Phosphorus (P) concentration in rivers and lakes receives greater attention due to its significance in contributing to eutrophication. This study aimed at profiling phosphorus species in Vembanad lake (Ramsar site) and its adjoining rivers. Four phosphorus fractions (total reactive phosphorus (TRP), total acid hydrolysable phosphorus (TAHP), total organic phosphorus (TOP) and total phosphorus (TP)) were monitored according to premonsoon and postmonsoon seasons. Meenachil river mouth is a hotspot for eutrophication with high values of most of the phosphorus fractions. Among the four fractions TRP, TOP and TP were recorded maximum concentration during the premonsoon and postmonsoon seasons. Each fraction of TRP, TAHP, TOP, and TP had an average concentration of more than 300 µgL-1 P throughout two seasons, which is highly eutrophic. The result reveals that the surface water of Vembanad lake is highly polluted with phosphorus input and it may trigger algal growth and consequent destruction of the biodiversity rich wetland system.

We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting existing terrestrial fiber infrastructure. Employing a Waveplate model, we integrate real ground displacement data from seven earthquakes, magnitudes ranging from four to six, to simulate the strains within fiber cables and collect large set of light’s polarization evolution data. These simulations help to enhance a Machine-Learning model that is trained and validated to detect Primary waves arrivals that precede earthquakes’ destructive Surface waves. The validation results show that the model achieves over 95% accuracy. The Machine-Learning model is then tested against an M4.3 earthquake, exploiting three interconnected mesh networks as a smart sensing grid. Each network is equipped with a sensing fiber placed to correspond with three distinct seismic stations. The objective is to confirm earthquake detection across the interconnected networks, localize the epicenter coordinates by a triangulation method and calculate fibers to epicenter distance. This setup allows early warning generation to municipalities close to epicenter location, and progressing to those further away. The model testing shows 98% of accuracy in detecting primary wave and one-second of detection time, affording nearby areas 21-seconds to take countermeasures, and an extended 57-seconds in more distant areas.

Membrane gas absorption technology has been considered as a promising approach to mitigate CO2 emissions from power plants. The aim of this study is to evaluate the environmental impacts of CO2 absorption and desorption processes by hollow fiber membrane contactors using life cycle assessment methodology. On the basis of ReCipe 2016 Midpoint and ReCipe 2016 Endpoint methods, the research results show that, membrane gas absorption system exhibits the lowest environmental impacts across the majority assessed categories in comparison with chemical absorption and membrane gas separation systems. The CO2 capture process via membrane gas absorption has the most significant impact on METP category, with heat consumption as the primary contributing factor accounting for 55%, followed by electricity consumption accounting for 43.1%. According to the sensitivity analysis, heating by natural gas shows a better performance than other heat supply sources in improving overall environmental impacts. In addition, the increasing utilization of renewable energy in electricity supply reduces the global warming potential, fossil resource consumption and ozone formation.

(1) Agricultural production is one of the most important, fundamental and resilient sectors. The excessive and incorrect use of agricultural pesticides has caused environmental pollution, with final destination in aquatic environments. Once in the aquatic environment, the decontamination process aimed at removing the pesticide is not always a simple task. There are expensive and low-efficiency procedures in the literature. In this sense, it is necessary to develop low-cost, sustainable procedures with high remediation capacity. Among the widely used agricultural pesticides, glyphosate stands out for weed control, which according to the World Health Organization (WHO) is potentially carcinogenic in humans. (2) In this context, a nanocellulose-based biopolymer was developed to recover glyphosate from aquatic environments. Different methodologies have been developed, the most interesting being membrane immersion in aquatic systems. The analytical technique for quantifying glyphosate was molecular spectrophotometry in the ultraviolet – visible range (UV-VIS); (3) Nanocellulose showed a value of 4.7 mg of Glyphosate per g of nanocellulose, and organomodified nanocellulose showed the removal of 6.1 mg of Glyphosate per g of nanocellulose, evaluated in pseudo-first order kinetic models; (4) The biomaterial has a sustainable and renewable origin and has potential for contaminant removal and can be applied to contaminated aquatic systems.

This comparative study aims to investigate environmental awareness, knowledge, and safety among students in Montenegro and North Macedonia, considering the unique socio-cultural and environmental contexts of both countries. A mixed-methods approach involving surveys and interviews was employed to gather data from students in educational institutions across Montenegro and North Macedonia. The study assessed various factors, including students' awareness of environmental issues, their perceived level of knowledge, and their attitudes towards safety measures. A comprehensive series of 400 face-to-face interviews was carried out and these interviews encompassed 200 students from Montenegro and an equal number from North Macedonia, taking place at two esteemed academic institutions: The University of Montenegro in Podgorica and The University of St. Clement of Ohrid, Bitola, Republic of North Macedonia. Our hypothetical conceptual framework proposes that a combination of variables, including gender (H1), age (H2), year of study (H3), and rate of study (H4), significantly influences the attitudes of students from Montenegro and North Macedonia towards environmental awareness, safety, and knowledge. Research findings indicate significant variations in environmental awareness and knowledge perception among students in the two countries. While both Montenegro and North Macedonia face environmental challenges, differences in educational systems and socio-economic factors contribute to distinct attitudes and behaviors towards environmental issues and safety practices. This study sheds light on the importance of understanding regional differences in environmental awareness and knowledge perception among students. By identifying areas of strength and areas needing improvement, policymakers and educators can develop targeted interventions to enhance environmental education and foster a culture of sustainability in both Montenegro and North Macedonia.